USMCA 2010
USMCA
2011

New Technologies for
ICUS
UrbanReport
Safety 2011-02
of Mega(serial
Cities No.56
in Asia)
the 10th International
Symposium
October 13-15, 2010
on New
Technologies
Kobe International
ConferenceCenter, Kobe, Japanfor Urban SafetyEditedof Mega
Cities in Asia
by
Michael W. Henry

October 12-14,
2011&
Eiko Yoshimoto
The Empress Hotel
Chiang Mai, Thailand
OrganizedbyEdited byInternational Center for Urban Safety Engineering (ICUS),
AkiyukiKawasakiInstituteof Industrial
Science (IIS),The University&of Tokyo, Japan

Eiko Yoshimoto
Sponsored by
Global Center of Excellence
for Sustainable
Organized
by Urban Regeneration,
The University of Tokyo, Japan
International
Centerfor Urban
SafetyScience,
Engineering,
The Foundation for
the Promotionof Industrial
Japan,
Institute of Industrial Science,and
The University of Tokyo, Japan
Meet in21, Japan Thailand
Asian InstituteofKobeTechnology,

Chiang Mai University, Thailand
Cooperated byUnited Nations Internationaland
Strategy for Disaster Reduction,
Chulalongkorn
ThailandAsian DisasterUniversity,
Reduction Center,
Disaster Reduction and Human Renovation Institution,
Graduate School of Global Environmental Studies, Kyoto University,
Sponsored
Research Center for Urban
Safety andby
Security, Kobe University,
Nations Center
Regional Development,
Global CenterUnitedof Excellence
forforSustainable
Urban Regeneration,
andThe University of Tokyo, Japan
United Nations University Institute for Sustainability and Peace

andThe Foundation for the Promotion of Industrial Science, Japan,

Cooperated by
Asian Disaster Preparedness Center, Thailand
Department of Disaster Prevention and Mitigation, Ministry of Interior,
ThailandGeo-Informatics and Space Technology Development Agency, Thailand
Japan Society for the Promotion of Science, Bangkok Office, Thailand
andUnited Nations University Institute for Sustainability and Peace (UNU-ISP)SYMPOSIUM ORGANISERSSTEERING COMMITTEEBoonsom Lerdhirunwong, Chulalongkorn University, Thailand
Ekasit Limsuwan, Chulalongkorn University, Thailand
Jin Young Kim, KDPA, Korea
Katsumi Mushiake, Foundation of River & Watershed Environment Management, Japan
Kazuhiko Takeuchi, United Nations University, Japan
Mahesh C Tandon, ICI, India
Mehedi Ahmed Ansary, BUET, Bangladesh
Pong-in Rakariyatham, Chiang Mai University, Thailand
Rajib Shaw, Kyoto University, Japan
Shunji Murai, Japan Association of Surveyors, Japan
Sudhir Misra, IIT Kanpur, India
Surachai Ratanasermpong, GISTDA, Thailand
Taketo Uomoto, Public Works Research Institute, Japan
Tomonari Yashiro, IIS, The University of Tokyo, Japan
Tran Thuc, VIMHE, Vietnam
Tso-Chien, Pan, Nanyang Technological University, Singapore
Tsuneo Katayama, Tokyo Denki University, Japan
Waon-Ho Yi, NIDP, Korea
Wei Cheng Fan, CPSR, Tsinghua University, China
Worsak Kanok-Nukulchai, AIT, Thailand
Yoshifumi Yasuoka, CRDS, JST, JapanTECHNICAL COMMITTEE
Chang-Yong Kim, KICT, Korea
Chayanon Hansapinyo, Chiang Mai University, Thailand
Haruo Sawada, ICUS, IIS, The University of Tokyo, Japan
Hiroshi Yokota, Hokkaido University, Japan
Jeffrey C.L. Chiang, Monash University, Malaysia
Kiang Hwee Tan, National University of Singapore, Singapore
Kimiro Meguro, ICUS, IIS, The University of Tokyo, Japan
Lal Samarakoon, AIT, Thailand
Munaz Ahmed Noor, BUET, Bangladesh
Tien Dich, IBST, Vietnam
Nitin Kumar Tripathi, AIT, Thailand
Pennung Warnitchai, AIT, Thailand
Somnuk Tangtermsirikul, Thammasat University, Thailand
Srikantha Herath, United Nations University, Japan
Sucharit Koontanakulvong, Chulalongkorn University, Thailand
Taikan Oki, IIS, The University of Tokyo, Japan
Tai-Ping Chang, NKFUST, Taiwan
Yozo Fujino, G-COE, The University of Tokyo, JapanORGANIZING COMMITTEE

Akiyuki Kawasaki, ICUS, IIS, The University of Tokyo, Japan
Anat Ruangrassamee, Chulalongkorn University, Thailand
Arisara Charoenpanyanet, Chiang Mai University, Thailand
Kyung- Ho Park, AIT, Thailand
Michael W. Henry, ICUS, IIS, The University of Tokyo, Japan
Pakawat Sancharoen, Thammasat University, Thailand
Raktipong Sahamitmongkol, Thammasat University, Thailand
Shinya Kondo, ICUS, IIS, The University of Tokyo, Japan

PREFACE
On behalf of the Organizing Institutes of the 10th International Symposium on
New Technologies for Urban Safety of Mega Cites in Asia (USMCA2011), I expressed
our sincere welcome to all symposium participants and distinguished keynote speakers.
In the Asia and Pacific-Rim regions, rapid economic development andpopulation growth and concentration is fast accelerating the pace of urbanization.
Unfortunately, the rapid expansion of infrastructure for urbanization is not adequatelybalanced with appropriate measures for their maintenance and management, and urban
disasters have resulted. During the last few years, there were several big disasters inAsia and the Pacific Rim regions, such as killer cyclones Sidr in Bangladesh (2007),
Nargis in Myanmar (2008), and Aila in Bangladesh and India (2009), and Typhoon
Ketsna in Philippines (2009), flooding in Mongolia (2009) and Pakistan (2010), thedevastating earthquakes in Sichuan, China (2008), Sumatra (2009), Samoa (2009) andJapan (2011), and heat waves in Russia and Japan (2010). The number of fatalities andmissing reported due to these disasters was well over 200,000. These unprecedented
events show us the importance of urban safety.
The International Center for Urban Safety Engineering (ICUS) was establishedin 2001 at the Institute of Industrial Science (IIS), the University of Tokyo, with theobjectives of carrying out researches on urban safety and implementing them towards
the realization of safer cities in the 21st century. ICUS has been actively tackling
advanced researches, networking and information collection and dissemination for 10
years. Based on ICUS’s past 10-year activities, new ICUS started since April 1, 2011.
The purpose of the “new” ICUS is to identify, investigate, and resolve issues towards
the realization of sustainable urban systems for the prosperity and safety of society
considering challenging socio-economic problems such as depopulation and aging
society, shrinking economic resources, advanced technology, environmental awarenessand climate change, dense and decentralized urbanization, and so forth. Specifically,
three research divisions – “Urban safety and disaster mitigation division,”“Environment informatics division,” and “Social infrastructure management division”– will form the core of the “new” ICUS, and activities in these fields are intended tofulfill the objectives of “promotion of advanced research,” “construction of networks,”and “information collection and dissemination” considering the above-mentioned
socio-economic problems.
At 14:46:18 (local time) on March 11, 2011, a gigantic earthquake (called"The 2011 Tohoku region Off-Pacific Ocean earthquake") with moment magnitude(Mw) 9.0 occurred in the Tohoku (North-East) region of Japan. This earthquake ishistorically the largest event ever recorded in Japan. A killer tsunami induced by thisearthquake killed approximately 20,000 people and injured 5,700 people. Manybuildings and infrastructures, including nuclear power plants, were damaged. Totallycollapsed, burnt, and/or washed away structures due to the tsunami, fires, and groundmotion was numbered 112 thousand, heavily damaged structures numbered over 140
thousand, and partially damaged structures numbered over 500 thousand. Due to lossof power, including emergency back-up power, at the Fukushima I nuclear power plant,
the cooling systems in the nuclear reactor failed, resulting in a severe accident whichleaked large amounts of radiation. Due to this accident, people living around the power
plant were forced to evacuate and live in refugee camps for long time. The totalmonetary loss due to the earthquake was officially estimated by the national government
at 16.9 trillion yen, but indirect losses and damage due to the nuclear power accident
were not included.
Issues with the response, recovery and reconstruction of the affected areas are
typical of the purposes of “new” ICUS. In order to fully realize ICUS’s vision for safer

cities in Asia and the Pacific Rim regions, ICUS has been annually co-organizing
USMCA since 2002 with its partners in the Asian region. In 2011, ICUS jointly
organized the 10th USMCA in in Chiang Mai, Thailand, with the Asian Institute ofTechnology, Chiang Mai University, and Chulalongkorn University. The objectives ofthe symposium was to bring together decision makers, practitioners and researchers
involved in the field of urban safety to share their expertise, knowledge and experiencein tackling the critical issues for safer cities in Asia and the Pacific Rim regions. It also
provided an environment to create and reinforce collaborative networks among experts
in the fields relevant to urban safety.
During this two-day symposium, 54 papers in twelve parallel sessions and 23
posters in poster session were presented with five papers by keynote speakers. Total
participants were 149 from 13 countries such as Thailand, Australia, Cambodia, China,
Costa Rica, Bangladesh, Japan, Korea, Mongolia, India, Indonesia, Singapore andUSA. The symposium focused on disaster response and recovery; risk assessment,
prediction, and early-warning; decision-making technologies; planning anddevelopment of urban infrastructure systems; life-cycle management of infrastructure
systems; climate change mitigation and adaptation; development and application ofsustainable technologies; and application of geospatial technologies. Also, a speciallythemed session on “Earthquake and Tsunami in Sumatra and Indian Ocean and Tohoku,
Japan” was included.
I would like to thank all the members of the Steering, Technical and Organizing
Committees as well as the Symposium Secretariat for their hard work, time and effort inputting this symposium together. I would also like to thank all our sponsors for theirgenerous support and contribution. Thanks are also due to those who have contributed
towards making this symposium successful.

Kimiro MEGURO
Director of ICUS, IIS, The University of Tokyo(Co-Chairman of Organizing Committee, USMCA2011)

Copyright and Reprint Permission:
Photocopy of an article is permitted for authors and other researchers for their own reading
and research. Abstracting and indexing of the papers are permitted but acknowledgement
should be given to “The 10th International Symposium on New Technologies for Urban Safetyof Mega Cities in Asia” and the authors of each specific paper. Written permission should beobtained from the publishers prior to any other type of reproduction. Please contact:

International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Science (IIS),The University of Tokyo, Japan
Tel: +81-3-5452-6472
Fax: +81-3-5452-6476

ISBN: 4-903661-51-2

2011 Program Overview
Time
1600-1800

Tuesday, 11 October
Pre-Registration (Reception Hall of The Empress Hotel)

Time

Wednesday, 12 October

0745-0830

Registration (2F Exhibition Area)

Inauguration Ceremony
0830-0850

Mr. Kazuo Shibata, Consul General of the Consulate-General of Japan in Chiang Mai.
Prof. Kimiro Meguro, Director of ICUS
Moderator: Prof. Sawada

Keynote Speech (2F Chiangmai 3-5)
Dr. Shunichi Koshimura, Tohoku University
The 2011 Tohoku Earthquake Tsunami Disaster: Its Impact, lessons of renovation

0850-1020

Dr. Ir. Muhammad Dirhamsyah, Syiah Kuala University
An Application of Geographic Information System for Aceh Multi-Hazard DisasterDr. Sidthinat Prabudhanitisarn, Chiang Mai University
Environmental Management
Moderator: Dr. Kuwano

1020-1050
1050-1200
1200-1330

Group photo and Tea-break (2F Exhibition Area)
Special poster session (2F Exhibition Area)
Lunch (2F Exhibition Area)
2F Chiangmai 1

Session 1：Vulnerability and risk
1330-1510 assessment for seismic hazard

1510-1540

2F Chiangmai 2

Session 2：Flood risk assessmentand management

Special Presentation: Prof. Uomoto

Special Presentation: Dr. Herath

Session Chairs: Prof. Ansary and Prof. Meguro

Session Chairs: Dr. Dutta and Dr. Kato (T)Tea-break (2F Exhibition Area)

Session 3：Durability of construction Session 4：Urban Environmental
planning and assessment
1540-1705 materials
Special Presentation: Prof. Fan (Prof.Huang) Special Presentation: Dr. Nitin
Session Chairs: Prof. Uomoto and Dr. Nagai

1800-2200

Session Chair: Prof. Rogers and Prof. Sawada

Symposium dinner at Khum Kan Toke Restaurant(Meeting at the reception hall of The Empress Hotel at 1800)

Time

Thursday, 13 October
2F Chiangmai 1

0840-1005

1005-1035
1035-1200

1200-1330

2F Chiangmai 2

Session 5：Properties andperformance of construction
materials

Session 6：Disaster reponse andrecoverySpecial Presentation: Prof. Misra

Special Presentation: Prof. Mansor

Session Chairs: Dr.Kato(Y) and Dr. Koshihara

Session Chairs: Dr. Tanaka and Dr. Dirhamsyah

Tea-break (2F Exhibition Area)

Session 7：Evaluation of
infrastructure health andperformance

Session 8：Earthquake and Tsunami
in Sumatra and Indian Ocean andTohoku, Japan

Special Presentation: Prof. Tan

Special Presentation: Mr. Ho

Session Chairs: Dr. Chayanon and Dr. Nagai

Session Chairs: Dr. Koshimura and Dr. Herath

Lunch (2F Exhibition Area)
Session 9：Seismic vulnerability
Session 10：Environmental
and performance of structures
management: air quality, forest, water
resources1330-1455

Session Chairs: Prof. Msira and Dr.Nishida

Session Chairs: Dr. Mansor and Prof. Ichihashi

Tea-break (2F Exhibition Area)

1455-1525
1525-1635

Special Presentation: Dr. Dutta and
Mr. Kimkong

Session 11：Structuralvulnerability and safety

Session 12：Vulnerability and risk
assessment for urban safety

Special Presentation: Prof. AnsarySpecial Presentation: Dr. Jargalsaikhan

Session Chairs: Prof. Tan and Dr. Kuwano

1635-1645

Session Chairs: Dr. Nitin and Dr. Tanaka

BreakKeynote Speech (2F Chiangmai 3-5)

1645-1745

Prof. Peter Rogers, Harvard University
Energy, Food, and Water Security: Implications for Asian Megacities
Prof. Haruo Sawada, ICUS, The University of Tokyo
Satellite information for large natural hazard
Moderator: Dr. Kuwano

Closing Ceremony (2F Chiangmai 3-5)
1730-1800

Dr. Chayanon Hansapinyo (Award presentation and comment to USMCA2011)
Dr. Yondonsuren Jargalsaikhan (Announcement of USMCA2012)
Prof. Kimiro Meguro (closing speech)
Moderator: Dr. Kuwano

Time0850-1530

Short tour

Friday, 14 October

Contents
Keynote Session

page

The 2011 Tohoku Earthquake Tsunami Disaster:Its impact, lessons for renovation

1

Energy, food, and water security: implications for Asian megacities

11

Satellite information for large natural hazard

25

Shunichi KOSHIMURAPeter ROGERS

Haruo SAWADA

Poster Session
Mainstreaming climate change adaptation in urban planning in Africa

35

Disaster information gathering behavior after the Tohoku earthquake
part 1: Results of Japanese respondents

45

An experimental study on strengthening lap splice by ferrocement jacket

57

Correlation analysis of a reinforced-concrete building under tsunami
loads and effect of masonry infill walls in tsunami resistance67

Area suitability modeling for rice cultivation in Saraburi Provinceof Thailand

79

Bridge deck condition assessment by ground penetrating radar-A case study in Bangladesh

93

Urban high speed rail link tunnel projects (GTX) in Korea

101

Geospatial technologies in wetland dynamics of Deepor Beel, India

109

Estimation of building stories for HAZUS using light detection
and raging (LiDAR)

119Long and deep underground road tunnel projects of the mega-city in Korea
Chang-Yong KIM, Seong-Won LEE, Xiu-Mei ZHENG, Ho-Keun KIM

127

Abbadi GIRMAY REDA and Nitin K. TRIPATHI

Akiyuki KAWASAKI, Michael HENRY and Kimiro MEGURO
Amorn PIMANMAS and Rakriangkrai PAOLENG

Anat RUANGRASSAMEE and Piyawat FOYTONG

Bharambe K. P., Tripathi N. K. and A. R. Phalke

Bushra ISLAM, Raquib AHSAN and Mehedi Ahmed ANSARY
Chang-YONG KIM, Seong-WON LEE and Ho-GEUN KIM

Chitrni MOZUMDER, Taravudh TIPDECHO and Nitin K. TRIPATHI

Chomchanok LIANGWANNAPHORM and Kiyoshi HONDA

and Kyung-Ho PARKDevelopment of early warning system in Maldives

137

Disaster information gathering behavior after the Tohoku earthquake part 2:
Results of foreign respondents

149

Survey on people’s awareness of Earthquake Early Warning
before and after the 2011 off the Pacific Coast of Tohoku earthquake

163

Seismic risk evaluation on existing RC frame buildings for northernpart of Sylhet city, Bangladesh

173

Geospatial analysis of groundwater quality using Geographical Information
System: A case study from Maharashtra State of India

187

Flood risk modeling in Bangkok Province, Thailand

199

Geophysical investigation at Meghna Dhonagoda Irrigation Project (MDIP)
using ground penetrating radar method

213

Review of nuclear energy demand in urbanareas of India; VIS-À-VIS
seismic disturbances

225

Basic study on restoration capability of bio-cemented sandy soil

235

Transformation of hybrid color space for road extraction using highresolution image

241

Future plan for the world longest undersea tunnel projects in Korea

253

Assessment of community fire hazard vulnerability:
A case study of ward 65 in Dhaka city261

A study on the preferable urban structure of provincial small town
in the depopulation age

271

Microscopic risk analysis of rear-end collisions on Tokyo
Metropolitan Expressway

283

Mahmood RIYAZ, Dugkeun PARK, Chang-Yong KIM, Sung-Wook KIM
and Kyung-Ho PARK

Michael HENRY, Akiyuki KAWASAKI and Kimiro MEGURO

Miho OHARA, Kimiro MEGURO and Atsushi TANAKA

Ram Krishna MAZUMDER, Mushtaq AHMED and Mehedi Ahmed ANSARY

Parmeshwar UDMALE and Sangam SHRESTHA

Phalke APARNA, Tripathi NITIN and Bharambe KHAGENDRA

Ram Krishna MAZUMDER and Mehedi Ahmed ANSARY

T.Sai Sumanth REDDY and Ramancharla Pradeep KUMAR
Reiko KUWANO and Makoto HOSOO

Sanit ARUNPOLD

Chang-Yong KIM, Seong-Won LEE and Ho-Geun KIM

Sharmin ARA and Mehedi Ahmed ANSARY

Shimpei IWAMOTO, Takahiro TANAKA and Daisaku NISHINA

Shinji TANAKA and Hisashi MIURA

Development of Geospatial Disaster Management Information Service (GDMS)
as a Social System

293

Comparison of neural network learning algorithms; BR and LM
for flood forecasting, upper ping catchment

303

Building back right learning from Tohoku

313

Takaaki KATO, Mitsuaki KOBAYASHI, Katsuyuki YOSHIDA
and Jin NAKAMURA

Tawee CHAIPIMONPLIN, Linda SEE and Pauline KNEALE
Tomoko MATSUSHITA and Kimiro MEGURO

Oral Sessions
Session 1:
Vulnerability and risk assessment for seismic hazard
Importance of engineering judgment against unexpected hazards

319

Seismic functional vulnerability of the road network of the metropolitan
area of San Jose, Costa Rica

325

Earthquake hazard in Ulaanbaatar city and its surrounding area

335

Seismic risk analysis for intercity railway system in the Tokyo metropolitan area

343

SSI effect on seismic response of high-rise building in Jakarta, Indonesia

353

A fundamental study on social vulnerability for public safety in China

363

Special Presentation: Taketo UOMOTOGrettel MOLINA, William VARGA and German VALVERDE
Ulziibat MUNKHUU, Yasuyoshi ICHIHASHI
and Demberel SODNOMSAMBUUYoshimasa MAEDA, Hisamichi HATTORI, Toshiro SHIZUMA
and Hiromichi YOSHIKAWA
Kullachai TANTAYOPIN, James FRANK, Seong-Won LEE
and Kyung-Ho PARKNan ZHANG and Hong HUANG

Session 2:
Flood risk assessment and management
Flood and debris flow disaster management of Mae-Ngon basin Fang District
Chiangmai Province

373

Development of 3D viewer of flood disaster risk to enhance evacuation
capacity of residents

389

Januwat LEARDSILJALEARN and Chatchai PEDUGSORN

Kohei MAKINODAN, Miho OHARA and Kimiro MEGURO

Sukhothai flood analysis and its response under climate changes

399

Preparing water supply master plan for a newly declared city lacking
land use guidelines and demographic information

411

Patinya HANITTINAN, Anurak SRIARIYAWAT
and Sucharit KOONTANAKULVONG

Mustafa T. HASAN and Mahmud R. AMIN

Session 3:
Durability of construction materials
The major research plan ‘study on unconventional emergency
management’ in China
Special Presentation: Weicheng FAN, Wenguo WENG and Hong HUANG

421

Effects of environmental condition on corrosion of structural steel
in marine environment of Thailand

431

Influence of temperature on deterioration process due to chloride attack443

Durability evaluation of marine structure based on continuous
microstructure of concrete

455

Defect detection and crack classification in cementitious materials
by ultrasonic testing with ANN

465

Prasong PERMSUWAN, Pakawat SANCHAROEN,
Somnuk TANGTERMSIRIKUL, Paiboon SREEARUNATHAI,
Ekkarut VIYANIT and Wanida PONGSAKSAWAD

Takahiro NISHID, Nobuaki OTSUKI and Hiroshi MINAGAWA

Hitoshi AKIYAMA, Tomoya SAGAWA, Shafiqul Md. ISLAM
and Toshiharu KISHI

Saowanee SAECHAI, Pansaran SARANROM, Raktipong SAHAMITMONGKOL,
Waree KONGPRAWECHNON and Somnuk TANGTERMSIRIKUL

Session 4:
Urban environmental planning and assessment
A study on the proper land use of the hillside urban area in depopulation
tendency-evaluating future scenarios from the view of disaster mitigationand environmental conservation-

477

Urban heat island creating a design tool for adaptation
Maria B. K. DEWI

489

Study on urban air quality risk using spatial technology and public perception:a case study of Vientiane Capital city, Laos

499

Iyo YONEMASU , Takahiro TANAKA and Daisaku NISHINA

Soutthanome KEOLA, Edsel SAJOR and Vivarad PHONEKEO

Potential greenhouse gas reduction in Samui towards becoming
carbon neutral island

511

Poon THIENGBURANATHUM, Pongtip THIENGBURANATHUM and
Chaya VADDHANAPHUTI

Session 5:
Properties and performance of construction materials
Using copper slang in cement concrete

519

Role of coarse aggregate in a cement-based material with strain-hardening
subjected to stress-field rotation

527

Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete537

2nd dosage of superplasticizer and slump recovery of concrete using
naphthalene based superplasticizer

547

Evaluation of induced strain in concrete due to ASR expansion
by digital image correlation

557

Special Presentation: Sudhir MISRA and Kunwar Krishna BAJPAI

Kohei NAGAI, Benny SURYANTO and Koichi MAEKAWA

Kinaanath HUSSAIN, Pongsak CHOKTAWEEKARN,
Warangkana SAENGSOY and Somnuk TANGTERMSIRIKUL

Chalermchai WANICHLAMLERT and Somnuk TANGTERMSIRIKUL

Yuichiro KAWABATA, Hiroki GODA, Ema KATO and Mitsuyasu IWANAMI

Session 6:
Disaster response and recovery
Development of remote system for supporting building damage assessment
during large-scale earthquake disaster

567

Basin water management under land use and climate changes-Nan Basin as case study-

577

Relationship among response, recovery and development from the view
point of financial resource allocation

589

Development and application of triage system (TRACY)

597

Makoto FUJIU, Miho OHARA and Kimiro MEGURO

Sucharit KOONTANAKULVONG and Kwanchai PAKOKSUNG

Yasuhito JIBIKI

Muneyoshi NUMADA, Yasunori HADA, Miho OHARA
and Kimiro MEGURO

Session 7:
Evaluation of infrastructure health and performance
Alkali-silica reaction in cement mortar with waste glass as fine aggregatesSpecial Presentation: Kiang Hwee TAN and Hongjian DU

609

Health survey of concrete in urban infrastructure by non-contact acoustic
imaging method

619

Service life cycle assessment of chloride attacked concrete structureswith silane treatment considering environmental impacts

629

Development of probabilistic structural performance evaluation method
for port RC structure

641

Calibration of roughness prediction for asphalt pavement case study:
Thailand’s department of highways’ roads

653

Noriyuki UTAGAWA, Ryo AKAMATSU and Tsuneyoshi SUGIMOTO

Aruz PETCHERDCHOOEma KATO, Yuichiro KAWABATA, Mitsuyasu IWANAMI
and Hiroshi YOKOTA

Siwarak UNSIWILAI and Boonchai SANGPETNGAM

Session 8:
Earthquake and Tsunami in Sumatra and Indian Ocean
and Tohoku, Japan
Application on spatial information for the reaction of the huge earthquake-supporting recovering activities for the 2011 off the pacific coastof Tohoku earthquake-

663

Challenges in preparedness, response and relief for people with special needsin times of disasters followings the great East Japan earthquake

671

Simple and inexpensive tsunami disaster mitigation system for Indian Ocean
Rim Regions by combining multi-purpose ocean observation buoys
and properly arranged evacuation centers using religious facilities

683

Study on recovery curves for housing reconstruction in Sri Lanka, Thailand, andIndonesia after the 2004 Indian Ocean Tsunami Disaster

691

March 11, 2011, Tsunami Earthquake of Japan –Nine epistles to friends
and colleagues
Tsuneo KATAYAMA

699

Hirotoshi KISHI, Ryotaro TAKEDA, Dai YAMAZAKI, Kanya TOKUNAGA,
Yoshito SAWADA, Shiro OCHI, Takahiro ENDO and Haruo SAWADA

Shigeo TATSUKI

Kimiro MEGURO, Shunichi KOSHIMURA and Muneyoshi NUMADA

Osamu MURAO, Kazuya SUGIYASU and Hideaki NAKAZATO

Session 9:
Seismic vulnerability and performance of structures
Seismic vulnerability of low-rise, single long span reinforced concrete buildings711

A simple and effective seismic retrofit scheme for masonry-infilled non-ductile
reinforced concrete frames

721

Evaluation model of the five story horizontally-mixed hybrid timber structure729

A study on seismic performance and reinforcement method of rammed
earth wall, ‘HANCHIKU’739

A study on the effect of wall stiffness on the vibration characteristicsof traditional timber frames including Kumimono

751

Chayanon HANSAPINYO

Panitan LUKKUNAPRASIT and Jarun SRECHAI
Mengting TSAI and Mikio KOSHIHARA

Mikio KOSHIHARA and Akiko TAKADACHI

Iuko TSUWA and Mikio KOSHIHARA

Session 10:
Environmental management: air quality, forest, water resources
A new generation software for regulated river system operations
Special Presentation: Dushmanta DUTTA, Wendy D. WELSH,

761

Environmental management in Cambodia case study: Community forest
governance at local context
Special Presentation: Ham KIMKONG

771

Potential bioavailability of pops in lake sediment: A case studyof Mae Thang reservoir, Northern Thailand785

The effect of moisture on the ground surface for LiDAR DEM generation

797

Multi-temporal study on PM10 distribution for urban air quality
in upper Northern of Thailand using spatial technology

803

David NICHOLLS and Shaun KIM

Pannawee MEKWICHAI, Preeda PARKPIAN and Nguyen Thi KIM OANH
Takahiro ENDO, Yoshito SAWADA and Haruo SAWADA

Nion SIRIMONGKALERKAL, Vivarad PHONEKEO
and NGUYEN Luong Bach

Session 11:
Structural vulnerability and safety
Site characteristics estimation of BUET campus by microtremor H/V technique
Special Presentation: Mehedi Ahmed Ansary and Md. Saidur Rahman

815

Passporting of buildings, its safety and quality in Ulaanbaatar city, Mongolia

827

Influence of underground structures on cavity formation due to repetitionof water penetration

835

Application of elastic wave measurement to model tests using bender elements

845

Enebish NINJGARAV, Mendbayar OYUNCHIMEG, Yasuoshi ICHIHASHI
and Danzan DAMIRAN

Mari SATO and Reiko KUWANOSho OH and Reiko KUWANO

Session 12:
Vulnerability and risk assessment of urban safety
City development safety and improvement of urban planning of Ulaanbaatar city
Special Presentation: Yondonsuren JARGALSAIKHAN

855

Evaluation of tsunami strengths of houses subjected to a Tsunami wave load

861

Integrated climate adaptation and disaster resilience - a landscapecooperatives paradigm

873‘Urban environment climate maps (UECM)’ for supporting ‘Urban planningwith urban climate’: trial for mitigating urban heat island in Shanghai, China

885

and Yasuoshi ICHIHASHI

Gaku SHOJI and Hirofumi SHIMIZU

Alfredo ANCENO, Nitin TRIPATHI and Oleg SHIPIN

Kaoru MATSUO and Takahiro TANAKAPhotographs

ICUSReport
Report 56
56
ICUS

Welcome boards

Registration

Inauguration ceremony

Mr. Kazuo Shibata, Consul General of the ConsulateGeneral of Japan in Chiang Mai

New Technologies for Urban Safety of Mega Cities in Asia

Prof. Kimiro Meguro, Director of ICUSi i

October 2011,
October
2011, Chiang
ChiangMai,
Mai,Thailand
ThailandInvited speakers (Keynote)

Dr. Ir. Muhammad Dirhamsyah,
Syiah Kuala University, Malaysia

Dr. Shunich Koshimura,Tohoku University, Japan

Dr. Sidthinat Prabudhanitisarn,
Chiang Mai University, Thailand

Prof. Peter Rogers,
Harvard University, USA

Special poster session at Exhibition areaii

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October 2011,
October
2011, Chiang
ChiangMai,
Mai,Thailand
ThailandInvited Speakers

Dr. Taketo Uomoto, Chief Executive,
Public Works Research Institute, Japan

Prof. Srikantha Herath,
United Nations University Institutefor Sustainability and Peace, Japan

Prof. Hong Huang,
Tsinghua University, Beijing, China

Dr. Nitin Kumar Tripathi,
Asian Institute of Technology, Thailand

Prof. Sudhir Misra,
Indian Institute of Technology Kanpur,
India

Prof. Kiang Hwee Tan,National University of Singapore, Singapore

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Mr. Bill Ho,
Asian Disaster Preparedness Center(ADPC), Thailand

Dr. Dushmanta Dutta,
CSIRO Water for a Healthy Country National
Research Flagship, CSIRO Land and Water, Australia

Mr. Ham Kimkong,Royal University of Phnom Penh, Cambodia

Prof. Mehedi Ahmed Ansary,
Bangladesh University of Engineering andTechnology, Bangladesh

Mr. Yondonsuren Jargalsaikhan,
National Security Council, Mongolia,

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October 2011, Chiang Mai, Thailand

Group photo of participantsClosing Ceremony

Prof. Haruo Sawada, ICUS

Young-researcher-award awardees
with Dr. Chayanon HansapinyoviviComment of Dr. Chayanon Hansapinyo,
Chiang Mai University

Thank you to the Thai staffs of conference

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Panel presentation awardees: Mr. Mahmood Riyaz,
Asian Institute of Technology, Thailand (left) and
Ms. Tomoko Matsushita, The Univ. of Tokyo, Japan (right)

Oral presentation awardees:
Ms. Sho Oh, The Univ. of Tokyo, Japan (left) andMr. Hirotoshi Kishi, The Univ. of Tokyo, Japan (right)

Closing speech of Prof. Kimiro Meguro, Director of ICUS

BanquetMs. Aphisorn Suwannasuk (MC),RNUS secretary

Dr. Nat Vorayos, Vice president for Research and Academic
Services (left) and Prof. Kimiro Meguro, ICUS (right)

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Lunch and break timeTour

Phuping Palace

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Suthep Temple

Group photo at Meo Hilltribe Village, Doi Pui with Hmong

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The 2011 Tohoku Earthquake Tsunami Disaster: Its impact, lessons for renovation
Shunichi KOSHIMURA
Associate Professor, Disaster Control Research Center, Tohoku University, Japan
koshimura@tsunami2.civil.tohoku.ac.jp
ABSTRACTThe author reports a comprehensive study to identify the impact of the 2011
Tohoku tsunami disaster and to understand the lessons towards renovation of
Tohoku coastal communities. Our team conducted an integrated investigation by
field measurement of tsunami heights (flow depths, inundation and run-up
heights), optical satellite image analysis, aerial photo inspection based on spatial
information sciences. The preliminary findings, combined with numericalmodeling technologies, lead to a new understanding of structural vulnerability
against tsunami and a guide for land use management and relocation planning toreconstruct resilient coastal communities.
Keywords: The 2011 Tohoku earthquake tsunami disaster, remote sensing, fieldsurvey, tsunami fragility curve, GIS
1. INTRODUCTION
On 11 March, 2011, a devastating tsunami accompanied with M9.0 earthquake
attacked the northern Pacific coast of Japan, and the coastal communities
especially in Iwate, Miyagi, and Fukushima prefectures were totally swept away.
The total affected area by the tsunami was estimated as 561 km2 along the Pacificcoast of Japan (Geospatial Information Authority of Japan, 2011). The tsunami
run-up height reached up to 40 m (The 2011 Tohoku Earthquake Tsunami Joint
Survey Group, 2011). As of 10 September, six months after the event occurred,
National Police Agency reported 15,781 dead (4,656 in Iwate, 9,456 in Miyagi,
and 1,603 in Fukushima, 66 in other prefectures) and 4,086 still missing, 115,151
buildings/houses were collapsed or washed-away. The economic impacts were
estimated as 16 to 25 trillion yen (Cabinet Office, 24 June, 2011), while FY2010
national budget of Japan was 92 trillion yen (Ministry of Finance, February, 2010).
Having passed six months since the event occurred, the devastated areas havestarted moving forward to recover and reconstruct, or in other words, renovate
their communities. Approximately 82,000 residents who lost houses moved fromshelters to temporary houses (supplied 52000 units) and rental housing (Ministryof Land, Infrastructure, Transport and Tourism, 2011), 89 % of 23 million tons oftsunami debris have been removed (Ministry of Environment, 2011). Though therecovery process is still underway, local governments completed the draft ofreconstruction plan including infrastructure design, transportation, land use
management, urban design, relocation, and economic and industrial outlooks.

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Every decision has been made quite fast compared to this wide extent ofdevastation.
This paper aims to comprehend the impact of the Tohoku tsunami disaster, tounderstand the lessons for renovation of Tohoku coastal communities. To identify
the tsunami impact, our team conducted an integrated investigation by fieldmeasurement of tsunami heights (flow depths, inundation and run-up heights),
optical satellite image analysis, aerial photo inspection with approach of spatial
information sciences. The preliminary findings are combined with numericalmodeling technologies to find out structural vulnerability against tsunami and toprovide a guidance for land use management and relocation planning toreconstruct resilient coastal communities.
2. MAPPING TSUNAMI INUNDATION ZONE
2.1 Field survey
Mapping tsunami inundation extent was conducted through the analysis of opticalsatellite image with the ground truth calibration from the field survey. The
significant feature of the 2011 tsunami was the wide extent of inundation zone. In
fact, on the Sendai plain, the tsunami inundated more than 5 km inland. Since theevent occurred, many Japanese groups have conducted emergency field surveys tomeasure the tsunami inundation and run-up heights, flow depths. Our groupfocused on mapping the inundation limit of the coast of Tohoku region. We
conducted high-resolution surveys of the inundation limit and height in the fewcentimeter accuracy by using GPS measurement system (Promark3) in Miyagi,
Iwate, and Aomori prefectures. The horizontal measurement interval is ranging
from approximately 500 m to several kilometers and we measured nearly 300 sites
until the end of April. To draw the inundation line, we applied a remote sensing
technology using satellite and aerial photographs acquired after the tsunami.
2.2 Satellite image analysis
Here, the author introduces the analysis of ALOS AVNIR2 image acquired on 14
March, 2011. Figure 1 shows the ALOS AVNIR-2 image with the plot of the fieldmeasurement of tsunami inundation limit. To evaluate the inland limit of tsunami
inundation, a threshold using normalized difference water index (NDWI) is
determined. NDWI is calculated by following formula,

NDWI =DN BLUE − DN NIR
DN BLUE + DN NIR(1)where DNBLUE and DNNIR indicate the digital number of blue band and nearinfrared band, respectively. We preliminarily confirmed that the inundation limit
estimated from the satellite image is well consistent with the field measurement
results at most places, when threshold value of NDWI is 0.4, although there aresome exceptions that might have not been interpreted from the satellite images.

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Figure 1 : (a) ALOS AVNIR-2 image acquired on 14 March 2011 with the pointof measurement of tsunami inundation limit. (b) NDWI for mapping tsunami
inundation extent. Black dots are the survey points used for thresholding.
3. MAPPING STRUCTURAL DAMAGE AND VULNERABILITY
3.1 Visual inspection of aerial photos
Mapping structural damage was conducted through visual interpretation of aerial
photos to identify the structural vulnerability against the 2011 tsunami. For visualinspection, we used the aerial photo archives of Geospatial Information Authorityof Japan acquired in the devastated area. The ortho photos of 80 cm/pixel
resolution were composited with mosaic image processing. Combined with theZENRIN building data (building shape files), the inspection was conducted foreach building, by comparing pre and post tsunami aerial photos focusing on theexistence of houses’ roofs to add an attribution of classification “washed-away” or“surviving” as the damage status. Figure 2 shows an example of the classificationin Ishinomaki city that suffered 3273 fatalities. By mapping the structural damage
and overlooking its spatial distribution, not only the impact of tsunami, but theeffect of coastal protection and vegetation can be seen. Complete mapping ofstructural damage in Miyagi Prefecture is on our web site<www.tsunami.civil.tohoku.ac.jp> to be used for field survey, land use
management to understand vulnerable areas and reconstruction planning.

The 2011 Tohoku
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Figure 2 : Mapping structural damage by inspection of post-event aerial photos.
3.2 Structural vulnerability and tsunami fragility curves
Integrating structural damage mapping with field survey data, such as flow depths,
lead to a new measure of identifying structural vulnerability against tsunami, as aform of tsunami fragility curve or tsunami fragility function. Tsunami fragility
curve is defined as the structural damage probability or fatality ratio with

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particular regard to the hydrodynamic features of tsunami inundation flow, suchas flow depth, current velocity and hydrodynamic force.
Figure 3 shows a spatial distribution of flow depths measured in tsunami
inundation zone. Spatial interpolation of measurement data (point data) to obtainraster data is combined with the structural damage mapping (e.g. Figure 2). The
procedure of developing tsunami fragility curves is as follows.
1. Damage data acquisition: obtaining damage data from aerial photointerpretation (e.g. Figure 2).
2. Tsunami hazard estimation: estimating the hydrodynamic features of tsunami
by field measurement (e.g. Figure 3).
3. Data integration between the damage data and tsunami hazard information:correlating the damage data and the hydrodynamic features of tsunami throughthe GIS analysis.
4. Calculating damage probability: determining the damage probabilities bycounting the number of damaged or survived structures, for each range of flow
depths.
5. Regression analysis: developing the fragility curves by regression analysis ofdiscrete sets of damage probability and hydrodynamic features of tsunami.

Figure 3 : Mapping the tsunami flow depth measured by Miyagi Prefecture andour survey team.

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Taking above procedure, the tsunami fragility curve is preliminary obtained
as shown in Figure 4. Fragility curve shown in the figure indicates the damage
probabilities of structural destruction equivalent to the flow depth. Structures in
Miyagi Prefecture were especially vulnerable when the local flow depth exceeded
2 m, and 6 m flow depth would totally cause washed away. This fact leads to alesson to determine the land use plan (zoning) which considers the effect of
coastal protection.

Figure 4 : Tsunami fragility curve for structural destruction (washed-away). The
solid line is obtained from Miyagi Prefecture (2011 event) and the dashed one isfrom Banda Aceh, Indonesia (2004 Indian Ocean tsunami).
4. TSUNAMI FLOW VELOCITY AND HYDRODYNAMIC FORCE ON
BUILDINGS INTERPRETED FROM THE SURVIVOR VIDEO
When a tsunami reaches the coast, its characteristics change significantly fromwater wave to strong water flow. And this strong inundation flow causes damage
on infrastructures, buildings and humans. Measuring flow velocities of tsunami
inundation on land was quite rare and it was difficult to understand what really
happened in the devastated area and to identify the cause and mechanisms ofstructural destruction by tsunami inundation flow. But in recent years, owing to
the handy video cameras and mobile phones, many of tsunami survivors
attempted to capture the moment of tsunami attack to their communities anduploaded to the Internet. Applying a video analysis technique, the tsunami flow
velocity can be determined.
Here, the author represents one example from Onagawa town, Miyagi
Prefecture (10,014 population before the earthquake), which is one of thedevastated towns by the 2011 Tohoku earthquake tsunami. The tsunami attacked
to the town of Onagawa (Figure 5) at 15:20 (35 minutes after the earthquake
occurred) and caused 816 fatalities and 125 still missing. As the author
investigated, at least 6 reinforced concrete or steel construction buildings were
found overturned or washed away. The video was taken by a resident from the topof the reinforced concrete building in Onagawa harbor (see Figure 5). Figure 6

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indicates a snapshot from the video capturing the moment of the houses being
washed away. Using this video, the author analyzed the time series of flow depth
by measuring the height of the water level on withstanding buildings in the video.
Also focusing on the movement of drifting objects, the flow velocity wasestimated at the moment when the houses were washed away. As a result, flow
velocity of the tsunami inundation was estimated as 6.3 m/s at the flow depth ofapproximately 5 m. Using this hydrodynamic features, the tsunami force wasroughly estimated as 100 kN/m, which is the drag force acting on a house’s wall
per unit width.

Figure 5 : An overview of Onagawa town, Miyagi Prefecture. Photo taken by
PASCO Corporation. The red arrow indicates the point where the survivor video
was taken.
5. TOWARDS RESILIENT COASTAL COMMUNITIESIn April 2011, one month after the event occurred, the central government
established the reconstruction policy council to develop a national recovery andreconstruction outlook for tsunami-resilient community. Besides, the central
government decided the policy of coastal protection such as seawall and breakwater, which would be designed to ensure their performance to potential tsunami
level of 150 year recurrence interval. In this sense, the government policy ofdesigning coastal protection is for 150-year tsunami level (this is called“Prevention Level”) which ensures to protect lives and properties. And for thetsunami level more than 150-year recurrence interval, so-called extreme event, thegovernment calls “Preparedness/Mitigation Level” to reduce the losses anddamage by all of the efforts of coastal protection, urban planning, evacuation, andpublic education.
Under the limitations and uncertain conditions of funding, prefectural andlocal governments have developed their own recovery and reconstruction plans,
which assume 10 years to be completed. These plans consist of the combination of
structural prevention/mitigation, urban planning, preparedness, and suggest theirland use management, relocation, housing reconstruction and tsunami disaster
The 2011 Tohoku
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mitigation plans. The key role of academia, in engineering point of view, is toverify and evaluate if these plans really work for future disaster reduction.
When the proposed reconstruction plan should be verified, numericalmodeling is a powerful tool. Figure 7 shows an example of evaluating Sendai
city’s reconstruction plan that includes 6.2 m levee and 6 m elevated road. As
shown in the figure, through the comparison of the 2011 tsunami simulated under
the pre-tsunami condition in coastal protection and land use, potential
reconstruction plans can be evaluated with regard to tsunami inundation area andflow depth, exposed population and buildings, and reducing risks.

Figure 6 : (a) A snapshot of the survivor video (Yomiuri Shinbun, 2011) capturing
the moment that the houses were washed away. (b) Time series of tsunami flow
depth and current velocities interpreted by the video.
ACKNOWLEDGEMENTS
The post tsunami field survey was conducted by a group of 20 scientists andengineers. All the data of our measurements can be viewed on the web page<http://www.tohoku-tsunami.jp/>. This research was funded Ministry of
Education, Culture, Sports, Science & Technology (MEXT), New Energy andIndustrial Technology Development Organization (NEDO), and Japan Society for
Promotion of Science (JSPS).

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Figure 7 : Preliminary results of tsunami numerical modeling to evaluate theeffect of proposed reconstruction plan in Sendai city. Sendai city is now planningcoastal levees and elevated roads to minimize tsunami risks. Upper panel: The
2011 tsunami flow depth in Sendai simulated under the pre-tsunami condition incoastal protection and land use. Lower panel: Evaluation of reconstruction planwith 6.2 m levee and 6 m elevated road.

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REFERENCES
Geospatial Information Authority of Japan (GSI), 2011, aerial photo archives,<http://portal.cyberjapan.jp/denshi/index3_tohoku.html>
Geospatial Information Authority of Japan (GSI), 2011, oblique aerial photoarchives, <http://zgate.gsi.go.jp/SaigaiShuyaku/20110525/index2.htm>
National Police Agency, 2011,<http://www.npa.go.jp/archive/keibi/biki/index.htm>
The 2011 Tohoku Earthquake Tsunami Joint Survey Group, 2011,<http://www.coastal.jp/tsunami2011/>
Cabinet Office, <http://www.bousai.go.jp/oshirase/h23/110624-1kisya.pdf>
Ministry of Land, Infrastructure, Transport and Tourism, 2011,<http://www.mlit.go.jp/common/000140307.pdf>
Ministry of Environment, 2011, <http://www.env.go.jp/jishin/shori111004.pdf>
Gokon, H. and S. Koshimura, 2011, Mapping of building damage of the 2011
Tohoku earthquake tsunami, Proceedings of the 9th International Workshop
on Remote Sensing for Disaster Management.
Koshimura, S., Y. Namegaya and H. Yanagisawa, 2009, Tsunami Fragility, A new
measure to assess tsunami damage, Journal of Disaster Research, Vol. 4, No.
6, pp.479-488.

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Energy, food, and water security:
implications for Asian megacities
Peter Rogers
Harvard University
ABSTRACTWith the rapid rise in incomes and alarming rates of urbanization, Asia isalready experiencing major crises in its fundamental urban resource bases:
land and water. The demands for energy and food have skyrocketed as has
the water needed to keep expanding the resource base and keep cities
functioning. The rate of increase in urban populations is large because of
the already high population densities in the rural areas and the increasing
population has no place to go but to the cities. Conflict over access to water
is increasing in the urban areas, and also in the rural areas as the pressure
on food supplies intensifies.
Many of the cities are already badly served with unsafe drinking water andinadequate sanitation. Not only do the cities typically suffer inadequate
supplies of potable water but they will have to find rapidly expanding
supplies for their future growth. Not an easy task given the industrial andagricultural demands already being placed on the same resource base.
Generally there is a poor understanding of the relationship between urban
water and wastewater treatment and their impact on the amounts of energy
and types of energy infrastructure needed to meet these growing demands.
Moreover, megacities exert broad spatial geographical impacts on theirregions and hinterlands, often taking the best available water andagricultural lands out of food production.
Urban water has high embedded energy content. Meeting new water
demands could increase the total urban energy demands considerably. In
the US, for example, as much as one-quarter to one-half of the electricity
used in many cities is consumed at municipal water and wastewater
treatment facilities. Unfortunately many of the modern ways of increasingwater availability greatly increase the embedded energy demanded. This
paper analyses technical options for resolving the urban water-food-energy
nexus and explores how they could fit into the resource policy andmanagement of these increasingly large urban agglomerations
1. INTRODUCTION
The theme of this symposium is “Urban Safety” and this usually is applied
to the mitigation of intermittent shock disasters such as earthquakes, floods,
and terrorism. This paper attempts to identify and cope with potential“Silent Disasters” which happen slowly and gather their strength over many

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years. Examples of such disasters are the growing demands placed on theurban infrastructure. For example, the need to provide the urban population
access to food for nourishment and water for sanitation and commercial use
is well understood. On the other hand, the interaction of both the need forfood and for water−which directly connect to energy for the system tofunction−is not well understood. In the literature this is increasingly called
the urban “food, water, and energy nexus.” Often the word “sustainability”
is applied to studies of resource use in cities; however, there is nothing thatis inherently self-sustaining in modern cities. The word “viability” is abetter description of what can be achieved in the long-run. Of course there isa long list of desirable properties associated with the concepts ofsustainability and viability when applied to cities; however, the concept ofefficient resource use is the fundamental property.
Currently of the 20 cities in the world with more than 10 million1
people, nine are in Asia, and based on UN projections (UN|DESA, World
Urbanization Prospects: The 2009 Revision, 2009) by 2050, seven of the 10
largest cities in the world will be in Asia. Over the same period thepercentage of urban population in Asia will rise from 42% to 65%. These
numbers are unprecedented, but for one country, China, its urban population
is predicted to rise to one billion by 2030 (McKinsey, 2009). The UN reportforecasts that by 2025 the following Asian cities will be megacities (seeFig.1): Tokyo (37 million), Delhi (29), Mumbai (26), Dhaka (21), Kolkata(20), Shanghai (20), Karachi (19), Beijing (15), Manila (15), Osaka-Kobe(11), Shenzhen (11), Chongqing (11), Guangzhou, Guangdong (11), Jakarta(11), and Lahore (10). London which was the 30th largest city in 2010 with
8.6 million does not make it onto the list of top 30 cities by 2025.
2. HOW PERCEPTIONS OF URBAN METABOLISM HAVECHANGED OVER TIME
Urban sustainability and viability are strongly related to, and have theirroots in, urban metabolism and urban ecology. For most people the era of“urban metabolism” was ushered in by Abel Wolman’s 1965 Scientific
American article entitled “The Metabolism of Cities.” Wolman’s emphasis
on water and wastewater may be understandable because as a leading
sanitary engineer he had worked on these issues for his whole career.
Nevertheless, Wolman spotted an anomaly in the metabolism of the citywhen he compared the city to biological organisms which metabolize food,water, and energy to survive and in turn produce waste products which must
be excreted. Using a simple materials balance he demonstrated that in termsof materials, water and wastewater were the overwhelming input andoutputs to cities in terms of their sheer magnitudes. Wolman’s figure (1965)
1

It is only recently that the UN (2002) was referring to megacities as those cities of 5
million or more people. Currently the UN (2011) uses 10 million and above. This change isan indication of just how rapidly urbanization has been occurring.

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Figure 1

shown here in Fig. 1,
shows the material
inputs of water, food,and energy for atypical US city of themid 1950s. Water at
625,000 tons per day
dwarfs the food andenergy inputs by 2
orders of magnitude.
And on the output
sidesewageat
500,000
tons
predominates, again
by two orders ofmagnitude, over the
metabolized
foodand energy outputs.

Given the clarity of Wolman’s exegesis, it is surprising to move theclock forward to 2002 when London was the subject of a comprehensive
study on its resources flow and the urban footprint (City Limits, 2002).
Despite Wolman’s clear signal, the study on the ecological footprint ofGreater London ignored the 866,000,000 tons of water input into Greater
London and concludes that water with 866,000,000 tons of consumption
accounts for only 0.3% of its footprint, while food with only 6,900 tons of
input accounts for 14% of the footprint. Part of the problem here ismethodology of converting tons of material flow to equivalent global
hectares of space on the planet. Nevertheless, the London study is a mine ofuseful comparative data and methodology for assessing the footprint ofmany other cities which have not benefited from the meticulous data
generation and analysis that London has through this study. As mentioned
above the one major problem of the London study is its handling of water as
an input and output of urban metabolism, some of which may be due to thepossible double counting of water and land for food production in any
footprint study.
For the year 2000, with a population of 7.4 million, Londoners
consumed 154,400 gwh of energy (13.26 million tons of oil equivalent and85,494 gwh as actual electricity use), 49 million tons of materials (of which
27.8 million tons were used in the construction sector), generated 27.8
million tons of waste, consumed 6.9 million tons of food, and 876 million
cubic meters of water. Figure 2 (City Limits, 2002, p. 17) shows the inputs
and outputs graphically. These physical flows were translated into an
ecological footprint of 49 million global hectares (the equivalent size of
Spain) comprised of 44% for materials and waste, 41% for food, 10% forenergy, and only 0.3% for water.
Comparing the development of urban metabolism between the
Scientific American’s 1965 issue on “Cities,” and the 2011 issue of theEnergy, food,
food, andand water
implications forfor Asian
Asian megacities
megacities
Energy,water security:
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Scientific American devoted to “Cities: Smarter, Greener, Better,” we cansee the early arc of shock and disbelief that the massive urbanization was
actually happening and how unprepared for it we were then, evolving to thecurrent positive embracing of the city as engines of innovation for economic
and social life. In the recent issue there is little technical pessimism: we cansolve all of the resource and environmental problems that cities create withexisting and emerging technologies for wealthy cities in the developed
world.
3. URBAN WATER, FOOD, AND ENERGY
In the US of the total 123.45 thousand gwh ofelectricity used in 2000, fully 3.4% were used bywater supply and wastewater treatment (EPRI,
2009). This places the water sector in third place
below the chemical and the primary metals
industries in energy use. Of this amount morethan 50% was used in public and private
wastewater treatment and 25% in public watersupply and a further 19% were used for supplying
irrigation water. The average energy intensity for
public water supply was 1,900 kwh/mg (0.5kwh/cm). Based on Wolman (1965), Decker et al.
(2000) delineated the historical energy andmaterial flows through urban ecosystems (Fig. 3)
from an estimated 6 tons per year for a human in
Neolithic times, through rural individuals ca 1800
mobilizing 25 tons per person per year, up tomodern urban individuals ca 1990 mobilizing 100
tons per year, such as in Sydney and London.
The prospects of water shortages in Asia,
alone, would be a serious resource-allocation
problem, but it will be confounded by climatechange and its attendant effects on the hydrology
of continents, regions, and nations.
Water and energy issues havetraditionally been researched as single
issues, not as an integrated web ofopportunities
andlimitations,particularly in urban regions. The
uncertainties
ofclimatechangecomplicate the resource-management
challenges. Studies need to go beyond
traditional views of a stationary world inwhich not only is climate known, butalso the future economic and social
developments are viewed in similarly
narrow terms.

Figure 2

Decker et al, Energy and Material Flow through the Urban Ecosystem, Ann. Rev. Energy Environ, 2000, 25:685-740

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Becoming aware of these complex interactions, many countries havespent huge amounts of financial resources to improve their water security.
Modern examples of such concerns include Israel’s National Water Carrier,
the Central Valley Project in California, the PRC’s current work on theSouth-North Water Diversions, and India’s attempts to interlink some river
basins to bring water to water-scarce regions.
Less well known is the competition for water that exists between the
demands for food and energy. For example in the PRC, 76% of the water
withdrawn for industrial use was used in the generation of electricity; coalpowered generation is the number one consumer of water in the PRC’s
industrial sector. Thus, as rapid economic growth leads to large increases inthe demand for energy and increased food consumption, countries like the
PRC and India find themselves in a serious bind: already their existingwater resources are almost fully committed to agriculture and foodproduction, leaving little available for meeting increasing urban andindustrial demands. The case of the PRC is particularly severe and theGovernment is taking it very seriously, not only with massive water
diversions (over $60 billion) but also by beginning to implement watersaving technologies in both the water sector and the energy sector.
According to Goklany (2007) and Brown (2011), access to water andenergy will be the major constraints on moving toward a sustainable planetby 2050. The big consumer of water is agriculture and its ability to feed theglobal populations is in doubt without major improvement in water-use
efficiency in agriculture. This paper focuses more on water access in urban
areas and its energy implications than on the conflicts over water for
agricultural uses. Many of the destination cities of rural-urban migrants,
however, are already badly served, having unsafe drinking water andinadequate sanitation. Not only do the cities typically suffer inadequate
supplies of potable water but also they will have to find rapidly expanding
supplies for their future growth—not an easy task given the industrial andagricultural demands being placed on the same resource base.
Generally, the relationships among urban water and wastewater
treatment and their impact on the amounts of energy and types of energy
infrastructure needed to meet these growing demands are poorly understood.
Urban water uses as much as 1.65 kilowatt-hours per cubic meter supplied(NRDC, 2004). Depending on the nature of the water supply options and thelocation of the resources, meeting the new water demands could increase thetotal urban energy demands by 10%–15% and electrical energy by as muchas 30%. Unfortunately, many of the modern ways of increasing water
availability to relieve urban water stress, such as by recycling anddesalination, greatly increase the embedded energy demanded. It is
commonly accepted that 40% of the cost of desalination and water recovery
using reverse osmosis are due to energy. This paper assesses the current
energy demanded by urban water, predicts how large the future demands
could be, and reviews technical options for resolving the urban waterenergy-food nexus for Asian megacities.
Energy, food,
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4. ENERGY USEMANAGEMENT

FOR

WATER

AND

WASTEWATER

The amounts and types of energy used in the provision of urban watersupply and wastewater disposal depend to a large extent on the current
water-use behavior of the populations and the nature of the technologies for
supply and disposal. For low-income areas, the per capita water use could
be as low as 50 liters per day (lpcd), with only 70% of the population being
covered by the water systems and as low as 20% with access to sanitation
systems. Working toward attaining the Millennium Development Goals(MDGs) could increase the urban coverage into the 90% range and increase
the demand to 100 lpcd or above. Thus, even without any population
increase, the total water demands placed on the megacities’ systems could
increase greatly. Rapid population growth will greatly exacerbate theproblem.
The most recent summary of progress toward meeting the MDG goals,
UN-ESCAP (2010) reported on data from 2008 and projected these forward
to the 2015 deadline. Of the major countries with megacities the Philippines
and China appear to be on target to meet the 2015 goals, Bangladesh may beon the way, but Pakistan and India lag far behind.
5. FUTURE URBAN WATER-BASED DEMANDS FOR ENERGYAND FOODTABLE 1ASIAN MEGACITIES IN 2025 (UN World Urbanization Prospects, 2010)
POPULATION IN 2010 AND PROJECTED TO 2025 (Millions)

Table 1 reports the 15 Asian megacities
projected by the UN Population Division(2011) to be individually at least 10 million
in population by 2025. The 15 cities had a
combined population in 2010 of 218
million, or 12.39% of the total Asian urban
population and the population in thesemegacities only rose to 267 million by2025. The total Asian urban population
over the same period is projected to growby over 35%. This indicates a belief thatthe bulk of the future urbanization will
occur in cities smaller than the 10 million
plus megacities, probably in the 1 to 5
million-sized cities as the UN predicts.
This should give some solace to the mayors
and city government of the megacities that
their rates of growth will slow down overthe next 15 years.

CITY
Pop in 2010
36.67
1 Tokyo*+
22.16
2 Delhi+
3 Mumbai*+
20.04
4 Dhaka*
14.65
5 Kolkata+
15.55
6 Shanghai*+
16.58
7 Karachi*+
13.12
8 Beijing+
12.39
9 Manila+
11.63
10 Osaka‐Kobe+
11.34
11 Shenzhen
9.01
12 Chongqing
9.4
13 Guangzhou*+
8.8
14 Jakarta*+
9.21
15 Lahore
7.13
TOTAL
217.68TOTAL ASIA
1757.31% in Megacities
12.39* = on World Bank ESMAP study list
+ = on Green Cities Index

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Pop in 2025
37
29
26
21
20
20
19
15
15
11
11
11
11
11
10
267
2383.27
11.20

ICUS Report 56

6. MODELING THE FUTURE URBAN WATER-FOOD-ENERGY
NEXUS
In order to assess the magnitudes of potential conflict among urban wateruse, urban energy use and the urban food supply, I constructed a simple
simulation for the food, water and energy resources needed by 2025 for the
projected 15 Asian megacities. Results are given in Table 2. The projectionsof potential urban water and wastewater supply and treatment by country are
made from a 2010 base year until 2025. The table reflects the increasing
population sizes based on the UN World Urbanization Prospects, 2010, andon estimates of current water consumption, and on estimates of percentage
coverage of the population by municipal water supply and sewerage, and on
estimates of water footprints of the food imports to the cities. For futuredates, I assumed that the megacities are on a path toward meeting the MDGs
in terms of coverage and increasing per capita use. Table 2 shows the joint
effect of increasing urban populations, increasing coverage by water
systems, increasing water for food demands, and increasing per capita water
use for each of the megacities. For all of the megacities taken together overthe 15-year interval there is a 22% increase in the demand for water services
for an 11% increase in population. In the cases of Dhaka and Karachi theincreased water demand would be more than 50%, whereas in Tokyo theincremental effects are negligible due to the fact that its water and foodintakes are so high that they probably not increase, and of course thepopulation is expected to increase very slightly over the 15 year period.
Table 3 simulates the incremental demand for electricity just for thewater and wastewater sectors of the cities. While the cities of Delhi andDhaka will expect around 10% incremental growth in demand for the WSS
sector, the overall energy demand of the WSS sector will remain at a modest
3-5% of total urban electricity use—which is what we experience in thedeveloped countries.
TABLE 2
INCREMENTAL WATER NEEDED TO MEET WSS AND FOOD DEMANDS 2010‐25 mcm
food increment
WSS increment
Domestic
Food#
2010‐25%
2010‐25%
CITY
Water lpcd
Water lpcd
mcm
mcm
1 Tokyo*+330
5500
665.47
0.90
39.93
0.9
2 Delhi+
250
4000
9991.06
30.89
1471.24
72.8
3 Mumbai*+
250
4000
8701.6029.74
1303.05
71.3
4 Dhaka*
115
4000
9271.00
43.34
1914.52311.3
5 Kolkata+138
4000
6497.00
28.62
1625.75
207.6
6 Shanghai*+
411
4500
5617.35
20.63‐78.25‐3.1
7 Karachi*+
164
4000
8584.8044.82
1503.19191.4
8 Beijing+
218
4500
4286.9321.07
820.8883.3
9 Manila+
155
4000
4920.2028.98
1148.78174.6
10 Osaka‐Kobe+
418
5500‐682.55‐3.00‐405.19‐23.4
11 Shenzhen
350
4500
3268.5822.09
173.92
15.1
12 Chongqing
350
4500
2628.00
17.02
124.10
10.3
13 Guangzhou*+
527
4500
3613.50
25.00‐367.77‐21.7
14 Jakarta*+
77
4000
2613.40
19.44
1066.10411.9
15 Lahore
350
4000
4190.2040.25
293.6432.2
TOTAL
74166.52
10633.88* = on World Bank ESMAP study list
+ = on Green Cities Index

Total water increment
2010‐25%mcm
705.390.9011462.30
33.35
10004.65
32.18
11185.52
50.83
8122.7534.59
5539.1018.6410087.99
50.59
5107.8023.94
6068.98
34.41‐1087.74‐4.443442.50
21.58
2752.1016.54
3245.7320.10
3679.5026.85
4483.8439.61
84800.40
22.56

Hunger Free World, Special issue, No. 26, Jan 24, 2011. Cites japanese government sources that average Japanese consumes 3 cm

of water per day for drinking and food.
Olli Varis, WRD, vol 22, no. 2, pp. 199‐225, June 2006, gives figures that high or high‐middle income countries consume 5.5 cm
per person per day, and lower‐middle, or low income countries' city dwellers may consume 4.0 to 4.5 cm per day.

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TABLE 3ASIAN MEGACITIES IN 2025 (UN World Urbanization Prospects, 2010)
ENERGY FOR WSS
Current
AssumedEnergy2025
CITY
kwhe/ckwhe/c1 Tokyo*+6638
6000
2 Delhi+
5000
5000
3 Mumbai*+
5000
5000
4 Dhaka*
144
3000
5 Kolkata+
5000
4000
6 Shanghai*+
6666
6000
7 Karachi*+
475
4000
8 Beijing+
6000
5000
9 Manila+
5000
5000
10 Osaka-Kobe+
6638
6000
11 Shenzhen
6000
6000
12 Chongqing
5000
5000
13 Guangzhou*+
6000
5000
14 Jakarta*+
564
5000
15 Lahore
3000
5000

Gwh/yr# Gwh/yr Gwh/yr
WSS
WSS
2010-25 %2010
2025 increment
73.6
74.3
0.7
32.3
42.3
10.0
29.3
38.0
8.7
21.4
30.7
9.3
22.7
29.2
6.5
27.2
32.9
5.6
19.2
27.7
8.6
20.4
24.6
4.3
17.0
21.9
4.9
22.8
22.1
-0.7
14.8
18.1
3.3
15.4
18.1
2.6
14.5
18.1
3.6
13.4
16.1
2.6
10.4
14.6
4.2

% of 2025
total city use
0.9
30.9
29.7
43.3
28.6
20.6
44.8
21.1
29.0
-3.0
22.1
17.0
25.0
19.4
40.3

3.3
2.9
2.9
4.9
3.7
2.7
3.7
3.3
2.9
3.2
2.7
3.3
3.3
2.9
2.9

* = on World Bank ESMAP study list
+ = on Green Cities Index# = assumes 1 kWh per cubic meter processed

7. IMPROVING THE EFFICIENCY OF URBAN WATER AND
ENERGY AND FOOD SUPPLIES
When dealing with the approaches to solving the problems of sustainable
water resources for urban areas, the type of problem addressed and the scaleof the potential solutions must be defined clearly. There is a large andgrowing literature and databases on the concepts of sustainable cities. Muchof the literature (Hao et al., 2010), however, focuses on smart buildings
rather than entire cities. Moreover, the discussion tends to focus on newbuildings rather than retrofit of the existing building stock of old traditional
infrastructure. The literature also bifurcates into those specializing in actual
here-and-now cases and those promoting future potential developments.
Unfortunately, many of the cases reported are still largely hypothetical.
Hard data on actual cases are difficult to find. For example, hypotheticalcases like Qingdao and Dongtan, near Shanghai, are widely discussed (Haoet al., 2010) and promoted because of their widespread integrated energywater-transport systems approaches, but cases like The Solaire in Battery
Park City, New York, or Dockside Green in Victoria, Canada, which havesuccessfully integrated buildings, or multiple buildings with new
construction and the rehabilitation of existing cities, receive little attention.
The examples of Solaire and Qingdao are illustrative of the wide
discrepancy between the empirically based data and the hypothetical data
used in future-oriented studies. The Solaire has consistently achieved a 48%
water-consumption reduction in comparison with comparable residentialbuildings in New York City and a 56% reduction in wastewater discharge.
This water and wastewater reduction is achieved by a combination ofwastewater reuse and water conservation where non-potable water isdistributed in closed-loop systems for uses that include toilet flushing,

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cooling tower make-up, laundry, and irrigation. Each building in The
Solaire development is unique and the exact components vary somewhat,
but the overall program of wastewater and rainwater reuse remains the same.
The Qingdao Eco-city is repeatedly cited as an excellent approach to
making cities more sustainable with 85% water savings and 100% energy
savings. Unfortunately, like most of the future-oriented cases, the basis forthe calculations is often optimistic or unrealistic. Wherever possible, I
recommend that actual performance of integrated water and waste-recycling
data be used instead of the hypothetical data.
Hao et al. (2010) provide a critical review of city-scale developments
aimed at improving the actual water and energy nexus. Hammarby Sjöstad
(Sweden) actually has been developed; Dongtan, planned near Shanghai(PRC), is apparently one of the first comprehensive conceptual eco-city
developments. The final population was planned to be 500,000 around 2050.
However, its construction is currently on hold. For Qingdao (PRC), ecoblocks are the foundational units in Fraker’s (2008) concept of the eco-city.
A super block is a typical high-rise residential development in the PRC,
usually 100–200 ha with 2,000–10,000 residential units housing 6,000–
30,000 people. The PRC is now building 10–15 super blocks per day withconventional infrastructure, but the innovative Qingdao project is on hold.
Two well-funded projects underway are in Tianjin (PRC) with $9.7 billion
invested and Masdar (United Arab Emirates), with an expected funding of$22 billion. Two projects already developed in the United States are
Treasure Island and Sonoma Mountain Village, both in California.
Table 4, from Hao et al. (2010), pulls together some of the salient
facts about water and energy conservation in these projects. Note the huge
differences between the water savings claimed for the three projects actuallydeveloped (Hammarby, Treasure Island, and Sonoma Valley) and those inplanning stages. The energy savings reported for the developed projects are
remarkably close to those predicted for the remaining projects, implying thatenergy conservation is inherently easier to accomplish than water
conservation at the household and project level. The last column reports thecosts or the expected costs for typical units in the projects. The costs for thecompleted or underway projects are much higher than the predicted costs forthe not yet constructed projects. This reveals a bias in favor of lower costsby the planners rather than what the project developers actually see. There isalmost a factor of 10 underestimate on the not yet constructed projects.
CONCLUSIONSThe simple simulation models used in this paper do not show unexpected
results. First despite the relatively low rates of total population growth in theregion, urban populations are likely to increase substantially by 2025 (from1.75 billion in 2010 to 2.38 billion, a 35% increase), but the large megacities
cities in the region will experience a more modest increase of less than 25%.
This implies that there will be large population increases in the smaller
cities and towns in the region.
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For the current large cities in Asia, the electricity demands for theurban water sector would likely stay well within the 3%-5% range of total
city use—well within the range in the industrialized countries. Moreover,each city and country is currently embarked on extensive expansion of theirelectricity supply capacity, such that electricity capacity will grow alongwith the demands and does not foresee major crises as long as fossil fuels
will be readily available. Unfortunately, this is not the case with watersupply. There are some serious limits on water availability, hence the needto conserve water in this sector. This may be quite difficult given thepressures to expand the actual quantities of water supplied and broaden the
coverage of the systems and meet the increasing demands for food.
The analysis presented in this paper has two major problems. First andforemost is the absence of reliable comparative data on urban water, food,and electricity use. Secondly, we only consider the water-food-energy nexus
for urban water supply and wastewater treatment, the energy and water toproduce the food for the cities, and the energy required to keep thisintegrated system thriving. Third, other important water uses related toflooding and urban drainage are not incorporated. Finally, and equallyimportant, is that the model does not really reflect the dynamic economic
behavior of the consumers who ultimately drive the systems. Nevertheless,this simple model does provide some confidence that there can be asustainable urban future in the megacities without resort to the fancy
integrated water and energy solutions promoted in Hao et al. (2010),
provided that careful attention is paid to the water management in the cities.
One major concern, however, is the potential reduction in water available
for agriculture in all the countries of Asia and its repercussions on food,sanitation, health and urban energy use; this needs careful study
Notes

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20

1

A discussion of the unreliability of the generally available databases is worth including here. Kallidaikurichi and Rao (2010) review
the data on the adequacy of drinking water in 23 Asian countries.
They spent a great deal of effort on developing the best available
database for the region, but were critical of the quality of available
national and local data for serious policy analysis. Their bookdeveloped an index of drinking water adequacy, which could be used
for ranking countries from the point of view of access to safe
drinking water; they did not include the associated food and energy
inputs. McIntosh (1993) and McIntosh and Yñiguez (1997) assessedwater management in 50 utilities in Asia for the Asian Development
Bank (ADB). Their compilation of economic data reveals that the
majority of the utilities were unable to cover their operational costs
from tariffs alone. Ten of our projected megacities were on the 1993
list of 38 cities surveyed and 10 of 49 in the 1997 list. Later ADB(2004) surveyed 18 Asian cities of which 6 were in our set of future
megacities. These data were from 2001 or earlier, and showed only
marginal improvement over the situation in 1997. Two sources ofenergy data for Asian cities are The World Bank’s ESMAP Study
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ICUS Report 56(2010) and the Asian Green City Index (2011) which provide somespotty data for 7 and 11 of our cities and 11 respectively. Obvious
sources, such as AQUASTAT of the United Nations Food andAgriculture Organization (FAO), the World Bank’s rapid assessment
framework (ESMAP, 2010), ADB-UNEP (2004), the International
Energy Association’s energy data (IEA, 2008), and the Pacific
Institute’s global water data (Gleick, 2009) were all utilized toassemble a workable database for initial estimations. The Southeast
Asian Water Utilities Network’s (SEAWUN, 2005, 2007) databaseson energy use in water and wastewater utilities in Southeast Asia
were a very helpful, but outdated, source. It should be understood,
however, that the combination of data from different sources andslightly different dates can be misleading. In the end the simulation
model is really a “thought model” based on the variety of collected
data bolstered by what appear to be reasonable assumptions where
the data coverage fails.
Tonnes are metric tons, or 1000 kg.
Gha global hectare is a measure of biocapacity.
Cheng (2011) calculates on p. 19 the electrical energy requirement
for providing 35 mgd of 0.22kwh/m3 for water supply alone.
The World Bank (ESMAP, 2010) gives a range of 0.1-0.59
kwhe/m3 for potable water and 0.21–0.59 kwhe/m3 forwastewater.
The Pacific Institute (Gleick, 2009) reports 0.77 kwhe/m3 for potable
and waste treatment, and distribution.
The New York State Energy and Research Development Authority(2008) reports a national average of 0.36 kwhe/m3 for potablewater supply, and 1.25 kwhe/m3 for secondary treatment and1.78 kwhe/m3 for tertiary.
For simplicity we have chosen to use 1.0 kwhe/m3 for combined
water and waste supply and treatment.
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24

New Technologies for Urban Safety of Mega Cities in Asia

Satellite information
for large natural hazard
Haruo SAWADA
Professor, ICUS, IIS, The University of Tokyo, Japan
sawada@iis.u-tokyo.ac.jp
ABSTRACT
Remote sensing images are used as an important information source at
preparedness, response and recovery stages in hazard and disastermanagement. Aerial photos are commonly used for many disaster events inJapan because of their high resolution and quick acquisition. A normal
aerial photo, however, covers only about 4 km2 in average and a large
number of aerial photos are required for a large hazard. Although it is noteasy to control observation modes of satellite systems, there are many
ongoing earth observation satellites and we have chances to get these data.
This paper focuses on showing ways to use earth observation satellite
systems for a large hazard and to mitigate disasters caused by earthquake
including tsunami, flooding, and wildfire. Although manual interpretation
technique is useful to identify land covers and land uses on satellite images,
speedy reproduction by automatic classification is better solution for large
event. As for earthquake, high resolution images are requested to identify
conditions of housing and infrastructure. SAR is used to identify geologicalmovement of the surface because the movement of one-fourth of SAR
wavelength can be detected. Remote sensing image is the only tool toidentify heavily damaged area by tsunami because it destroys all theinfrastructures including communication systems and no information comesout from the damaged area. As for flooding, high frequent observation
system is useful for monitoring and SAR easily allows us distinguish water
coverage and inundated areas. Wildfire issue also requires a large
observation area for warning and detecting fires. The International Disaster
Charter (IDC) was started in 2000 for mitigating these disasters in theworld. Many satellite observation systems have been involved in the IDC
through the ten space agencies in the world and the charter was activatedmore than 300 times. The IDC is a passive action for affected developing
countries and more active action might be effective even in developed
countries.
Keywords: remote sensing, image collection, International Disaster Charter
1. INTRODUCTION
Number of large hazard and disaster has been reported in the world and theimpact to human beings is very high in Asia because of their occurrencesand dens populations. For large natural hazards and disasters, collecting up-

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to-date information safely and efficiently is quite important not only foradministrative persons but also for citizens. Satellite remote sensing as wellas airborne survey systems are introduced and progressed for that purpose.
However, few systems are in operation for large hazards and disasters in theworld. Because advanced technologies related to remote sensing and GIS
are required for that purpose in affected countries, international
collaborations, such as the Disaster Charter and the Sentinel Asia, have beenstrengthened in the world.
2. CURRENT REMOTE SENSING
With the rapid development of space platform and sensors, remote sensing
data have been broadly utilized to natural hazard investigation andmanagement.
Remote sensing data are classified in several ways: ex. airborne vs.
satellite, passive vs. active, optical vs. microwave, high-resolution vs. low
resolution from the platform and sensor systems. At the data interpretation
stage, the technologies are divided into visual (manual) interpretation andautomatic classification.
Satellite remote sensing has become an advanced tool for the natural
disaster management because of the increasing availability of satellite
images with high resolution and decreasing costs. Satellite images show asynoptic overview and provide useful environmental information related to
the natural hazard.
Each sensor system is characterized its capabilities mostly on spectral
bands, ground resolution, observation width and observation cycle.
Although MODIS on Terra and Aqua satellite shows the whole damaged
area two times every day, high-spatial resolution satellite images (ex.
GeoEye, FORMSAT, IKONOS) could be an efficient and useful resourcefor decision-makers to prepare rescue and recovery operation, especially forsome disaster areas where damage distribution and levels are uneven andhard to reach in time (Table 1).
Imaging RADAR (Radio Detection and Ranging) provides us allweather, day and night imaging capability. As the microwave energy strikes
ground features, the radar antenna receives and measures the strength of theenergy that is scattered back towards the system. Therefore worldwide
comparison is meaningful for RADAR data, although optical sensors areaffected by sun altitude and cloud and have no meaningful data for directcomparison. Remote sensing techniques are summarized in Table 2
There are kinds of LiDAR (Light Detection and Ranging) systems
currently. The primary differences among them involve laser wavelength,
pulse duration and repetition rate, beam size and divergence angle (which incombination with altitude dictates the ground footprint size), the model of2
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scanning
scanning
scanningmechanismmechanismmechanism
andandandthetheechoes
theechoesechoesrecordedrecordedrecordedforforeachforeacheachlaser
laserlaser
pulse.
pulse.
pulse.
LiDAR
LiDAR
LiDAR
providesprovidesprovidesthethehighest
thehighesthighestresolution
resolution
resolution
DEM
DEM
DEM
available
available
available
forforfault
fault
for fault
interpretation.
interpretation.
interpretation.
Table
Table
Table
1:1:Characteristics
Characteristics
1: Characteristics
ofofmainmainof mainremoteremoteremotesensingsensingsensingsensors
sensors
sensors
Satellite
Satellite
Satellite Sensor
SensorSensor
LiDAR
LiDAR
LiDAR
Airborne
Airborne
Airborne
CASI
CASI
CASI
sensors
sensors
sensors
Hymap
Hymap
Hymap
Panchromatic
Panchromatic
PanchromaticWorldview
Worldview
Worldview
Multispectral
Multispectral
Multispectral
Panchromatic
Panchromatic
Panchromatic
Quickbird
Quickbird
Quickbird
Multispectral
Multispectral
Multispectral
Panchromatic
Panchromatic
Panchromatic
IkonosIkonosIkonosMultispectral
Multispectral
Multispectral
RapidEye
RapidEye Multispectral
Multispectral
RapidEyeMultispectral
ALI
ALIALI
EO-1
EO-1EO-1
Hyperion
Hyperion
Hyperion
Terra
ASTER
ASTER
TerraTerra
ASTER
Terra
/ /Aqua/ AquaMODIS
MODIS
TerraTerra
Aqua
MODIS

Nadir
Nadir
Nadir
spatialspatialspatialSwath(km)Swath(km)Swath(km)Revisit
Revisit
Revisitcapability
capability
capability
resolution
resolution
resolution
variablevariablevariable
Mobilized
order
Mobilized
Mobilized
totoorder
to ordervariable
1–2 1–2
variablevariable 1–2
100–225
2–102–10
100–225
100–225 2–10
16.416.4
0.460.46
16.4
0.46
1.1daysdays
1.1
1.1 days
16.416.4
1.851.85
16.4
1.85
16.5
0.6
16.516.5
0.6 0.6
1.5–3
1.5–3
days
1.5–3
daysdays
16.5
2.4
16.516.5
2.4 2.4
11
11 1
11 11
1.5–3
1.5–3
days
1.5–3
daysdays
11
44 4
11 11
77
77
x 15006.5
11day
77xx1500
1500
6.5 6.5
day1 day
60
30
60 60
30 30
Every
Every
16
16 daysEvery
16daysdays
7.530
7.5 7.530 30
60
15,30,90
15,30,90 4–16
days
60 60
15,30,90
4–164–16
daysdays
250,
250,
At twice
least
250,500,
500,500, At
Atleastleast
twicetwice
2300
23002300
1000
daily
for
for each
10001000
dailydaily
foreach
each

PRISM
PRISM
35
44 4
PRISM
35 35
AVNIR
AVNIR
70
10
AVNIR
70 70
10 10
ALOS
ALOS
ALOS
PALSARPALSAR(Fine)(Fine)
40–70
40–70 10PALSAR(Fine)
40–70
10 10
PALSARPALSAR(ScanSAR)(ScanSAR)250–350
250–350 100
PALSAR(ScanSAR)
250–350
100 100
Panchromatic
Panchromatic
60–80
60–80 55 5
Panchromatic
60–80
SPOT-5SPOT-5SPOT-5Multispectra
Multispectra
60–80
60–80 10Multispectra
60–80
10 10
ETM+
ETM+
Panchromatic
Panchromatic 185
15
ETM+
Panchromatic
185 185
15 15
Landsat-7
Landsat-7 ETM+Multispectral
Landsat-7
ETM+Multispectral 185
30
ETM+Multispectral
185 185
30 30
ETM+Thermal
ETM+Thermal
185
60
ETM+Thermal
185 185
60 60
NOAA
NOAA
NOAA

AVHRR
AVHRR
AVHRR

2399
23992399

1100
11001100

EnvisatEnvisat MERISMERISEnvisat
MERIS
Radarsat-2
Radarsat-2Ultra-fine
Ultra-fine
Radarsat-2
Ultra-fine

575
575 575
20
20 20

300
300 300
33 3

Spotlight
Spotlight
Spotlight
TerraSAR-X
TerraSAR-X
TerraSAR-X
Stripmap
Stripmap
Stripmap

10
10 10

11

1

30
30 30

33

3

ScanSAR
ScanSAR
ScanSAR100
100 10018
18 18

SeveralSeveraltimes
perSeveraltimestimes
per per
year
year
asJAXAper JAXA
yearas
asper
per
JAXA
acquisitionacquisitionplan
acquisition
planplan11
11 times
every
every
26
11times
times
every
26 26
days
daysdays
Every
Every
16
16 daysEvery
16daysdays
SeveralSeveraltimes
perSeveraltimestimes
per perday
day day
2-3
2-3 days
2-3days
days
Every
Every
few
few
Every
fewdays
daysdays
11-day11-dayrepeatrepeat11-dayrepeatcycle
cyclecycle
2.5-day
2.5-day
revisitrevisit
2.5-day
revisitcapability
capability
capability

Table
Table
Table
2:2:Comparison
Comparison
2: Comparison
ofofremoteremoteof remotesensingsensingsensingtechniques
techniques
techniques
Data
DataData
Type
TypeTypeTechniqueTechniqueTechnique

Advantages
Advantages
Advantages

Manualinterpretation
Benefitsfromanalyst’s
knowledge
ofoftheMultispectral
Multispectral
ManualManualinterpretationinterpretation
Benefits
Benefits
fromfrom
analyst’s
analyst’s
knowledgeknowledge
theofareaarea
the inarea
in inMultispectral
addition
totootherinterpretation
cues
hightohigh
to toaddition
additionotherto otherinterpretationinterpretation
cuessuchcues
suchassuch
ascontext,
context,
as context,
high
site,
shape,
size;
moderate
moderate
site,association,site,
association,
association,
shape,
shape,
size;size;
moderate
resolution:
resolution: Spectral
resolution:
SpectralSpectralclassification
classification
Relatively
Relatively
rapidrapid
apply
to apply
overaoveralargelarge
a largearea areaclassification
Relatively
rapid
totoapply
overarea
Ikonos,Ikonos,Ikonos,thresholding
Image
Image
thresholding
thresholding Simple
andtotoapply,
band
ratiosreduceSimpleSimpleandrapid
rapid
and rapid
apply,
to apply,
bandbandratiosratiosreducereduceQuickbird,
Quickbird, Image
Quickbird,(including
band(including(including
bandband illumination
variability,canappliedwithillumination
illumination
variability,
variability,
canbe
be
can
appliedbe applied
withwith
SPOT,
SPOT,
SPOT,
ratios)ratios)panchromaticdata
panchromatic
panchromatic
datadata
ASTER,
ASTER, ratios)
ASTER,
ALOS
ALOS
ALOS
Postclassification
Postclassification Does
DoesDoes
notrequire
requirenot requireradiometricradiometriccalibration
calibration
betweenbetweenPostclassification
notradiometriccalibration
betweenchangechangedetection
detection multiple
multiple
multiple
imagesimageschangedetection
imagesSatellite
Satellite
information
information
forforlarge
large
naturalnaturalhazardhazardSatellite
informationfornaturalhazardSatellite
information
for large
large
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3. NATURAL HAZARDS AND DISASTER
Every year, disasters related to meteorological, hydrological and climate
hazards cause significant loss of life, and set back economic and social
development. Between 1980 and 2005, nearly 7500 natural disasters
worldwide took the lives of over 2 million people and produced economic
losses estimated at over 1.2 trillion US dollars (WMO, 2011). Of this, 90 per
cent of the natural disasters, 72.5 per cent of casualties and 75 per cent of
economic losses were caused by weather-, climate- water-related hazards
such as droughts, floods, windstorms, tropical cyclones, storm surges,
extreme temperatures, landslides and wildfires, or by health epidemics andinsect infestations directly linked to meteorological and hydrologicalconditions.
Natural disasters could be classified into 3 groups;(1)Hydro-meteorological disasters: flooding, typhoon, hurricane anddrought, including wildfire and landslide caused by heavy rain
(2)Geophysical disasters: earthquake, tsunami and volcanic
eruptions(3)Biological disasters: epidemics and insect infestations
Here, we consider the first two types of disasters, Hydrometeorological disasters and Geophysical disasters. Disaster management ofan event like cyclone, flood or earthquake etc. requires some ingredients,
such as, detection, response, mapping, establishing priorities, developing
action plans and implementing the plan to protect human lives, property andthe environment. Early detection of large disaster is one of the mostimportant roles of remote sensing. Remote sensing provides cost effective
and safe methodology to collect information of a large disaster.
The impacts of natural hazards are increasing as a result of socialchanges like urbanization and population increase. And there are four stages
in disaster management; Reduction (mitigation), Readiness (Preparedness),
Response, and Recovery.
3.1 Heavy rain
Weather satellite observes the entire movement of meteorologicalhazard sources with a short time cycle, 30 minutes to 1 hour, and anothersatellite observes the affected areas with higher ground resolution but lower
repeat cycle. GIS in combination with remote sensing, can be used very
effectively to identify hazards and risk for cyclone (Rana et al., 2010).
For meteorological hazard, prediction is the most important for
mitigating disaster. The TRMM has very interesting capability to monitor
the rainfall in 3D while the cyclones are yet on the sea. The information forpredicting the severity is useful for early evacuation. Integrating local
knowledge with GIS and remote sensing techniques to develop map and428

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assess the hazard prone areas is an excellent tool for cyclone disastermanagement and regional planning development (Rana et al 2010).
SAR (Synthetic Aperture Radar) data would be most useful in theevent of storm-induced hazard. For example, SAR has good capability todetect flooding even under heavy cloud. By combining SAR with DEMs, it
is also possible to estimate the depth of water in flooded regions. One of theunique features of SAR is the ability to detect flooding under closed-canopy
vegetation by the corner-reflector effect formed from the vegetation andwater, which is well observed in Amazon.
Information management is the key to make effective the remotesensing data. For example, there is a flood control system to save Bangkok
at the sacrifice of agricultural land in northern Thailand to reserve water. In
this case, administrative persons decide to control the flood gates according
to the meteorological information observed by meteorological satellite andnational network of authorities.
3.2 Drought and wildfire
Drought, extreme opposite to the heavy rain, is the most common
natural disaster in the world, and the soil moisture content is one of the mainindicators of drought monitoring. Remote sensing quantitative retrieval ofsoil moisture content was scientifically available in semi-arid regions(Yichang, 2010).
Present technology and knowledge is limited to prevent such natural
disasters and such events still continue to make an increasing threat tohuman life and urban development. Avoidance or mitigation of the impactof the disaster could be achieved with effective disaster management
strategies along with proper utilization of remote sensing technology (Liouet al., 2010).
Although wildfire is a normal event of dry season in some area,abnormal drought causes severe forest fires. Because many country use fire
for agriculture, prediction of drought, especially the abnormality of thedrought, must be informed to fire managers as well as farmers for keeping
away of using fire. Even though the El Nino influences forest fire inIndonesia and Asian countries, most of the fire ignitions are responsible topeople who use fire in severe dry weather. TERRA and AQUA-MODIS andNOAA-AVHRR are commonly used for fire management to predict droughtand detect fires because of their capabilities in frequent monitoring andlarge area coverage.
Early warning and early detection are the keys to mitigate forest fire.
Together with these early detections, other meteorological parameter, suchas wind speed and dry index, should be monitored in short interval.
Geosynchronous satellite is considered the most important satellite to
mitigate wildfire because of its high repeated time of observation.

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There are many factors which influence wildfire, such as fuels on the
ground (types, amount and dryness), meteorological factors (wind direction,wind speed, humidity and sunshine), and terrain condition. It must benecessary to introduce these factors into the system to enhance accuracies.
Fires occur in a large area and a nationwide observation and reporting
system is required to mitigate wildfire and the system should be appropriate
to the situations for fire management in each country. Our experience for 5
years showed that it is difficult to detect forest fire before human eye inJapan and early warning is effective for forest management to prevent fireuses by introducing the prediction map derived from the dryness index.
3.3 Earthquake
Earthquake causes various damages to buildings, roads, bridges, fueltanks (gas), dams, traffic systems and other infrastructures in urban cities.
Liquefaction, ground sinkage, land slide are also caused by earthquake.
The damage and disaster monitoring require high resolution remotesensing data which covers a large area and requires huge amount of dataprocessing facilities as well as remote sensing data. The International
Disaster Charter well supports these demands for earthquake and otherdisasters.
Manual interpretation technique on optical remote sensing image has
been used to detect fault lines. High resolution SAR (Synthetic Aperture
Radar) data is also used for mapping changes and damages by analyzing
difference between multi-temporal images. ALOS-PALSAR, TerraSAR-X
and Radarsat-2 provide polarization data. It is possible to achieve accuracy
better than one quarter of SAR wavelength. Phase shift and intensity
difference between images of polarizations depend on land cover and arethus used for its classification.
Airborne LiDAR is also useful for mapping fault lines because of its
high vertical and horizontal resolution. However, this technique is notsuitable for providing information in an emergency situation due to the time
for processing the data.
3.4 Tsunami
Earthquakes commonly occur along the plate boundaries. The earthquakethat triggered the tsunami occurred at a convergent plate boundary. The
2011 Tohoku-Pacific Earthquake caused tsunami across a very wide area,
along the Pacific coastline from Hokkaido to Kanto area. Tsunami, whose
wave heights were more than 1m, were observed not only in Tohoku but
also Hokkaido and Kanto regions, even in Tokai and Kyushu. Especially in
Iwate prefecture and the northern area of Miyagi prefecture, the inundation
height and the run-up height of tsunami exceeded 10m.

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Figure 1: Tsunami inundation line on the orthophoto map (1/10,000)
The Tsunami caused various huge damages along the Tohoku
coastal line. A large number of people were washed away to the ocean withfloating matters.
4 . RAPID RESPONSE SYSTEMS
A number of different satellite systems are currently providing informationon hazards and disasters. Some of these systems are operational and someare experimental, some of the data processing methods are well developedand some are in the research and development phase. The integration is oneof the most important matters to develop operational system for disastermanagement using remote sensing and GIS.
4.1 International Disaster Charter
The International Charter started their activities in 2000 and aims at
providing a unified system of space data acquisition and delivery to thoseaffected by natural or man-made disasters through Authorized Users. 20
member agency has committed resources to support the provisions of theCharter and thus is helping to mitigate the effects of disasters on human lifeand property.
4.2 Sentinel Asia
“Sentinel Asia” is a voluntary basis initiative led by the APRSAF(Asia-Pacific Regional Space Agency Forum) to support disaster
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management activity in the Asia-Pacific region by applying the WEB-GIS
technology and space based technology, such as earth observation satellites
data.
Sentinel Asia was originally proposed in November 2004 when it was
realized that maximum benefit from rapid technological advances in theregion would occur, and this data could be delivered more quickly via theinternet as easy-to-interpret disaster-related information. Sentinel Asia aims
to expand efforts of each country and make such data available to all
countries and many more people in the region, particularly in countries that
do not have their own satellite reception facilities. Through such a backbone,
information about disasters could begin to be delivered more efficiently
through the 'world-wide-web', even outside national borders, in 'real-time' or'near real-time', and used as early-warning, or as post-disaster information
by various countries and relevant end-user agencies (Sentinel Asia, 2011).
4.3 International activity for forest fire:
Information on fire danger, active fires, burned area, fire emissions
and post-fire recovery are required for wildfire management. Although anumber of countries are collecting ground-based information, theinformation that is needed on fire is often missing and a system formonitoring effectively the long-term trends in global fire distributions andcharacteristics has yet to be supported (GOFC, 2000).
GOFC/GOLD (Global Observations of Forest and Land Cover
Dynamics) is a project of the Global Terrestrial Observing System (GTOS)
program, which is sponsored by the Integrated Global Observing Strategy(IGOS). The main goal of GOFC/GOLD is to provide a forum forinternational information exchange, observation and data coordination, anda framework for establishing the necessary long-term monitoring systems.
The GOFC/GOLD-Fire Mapping and Monitoring Theme wasestablished in 2000 aiming at refining the international observation
requirements and making the best possible use of fire products from theexisting and future satellite observing systems, for fire management, policy
decision-making and global change research.
5. CONCLUSIONS
Remote sensing is the only source for severely damaged area because no
information comes out from such an area, although the first priority of
rescue activities should be considered to that area. The detection of floating
materials is also an important to save lives in the sea. Unfortunately, we
have to conclude that information integration is not sufficiently operational
for a large hazard and disasters. We need to proceed to integrate theobservation systems, information technologies, related officers, policy
makers, and local people’s knowledge and behavior.

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REFERENCE
GOFC, 2000, http://gofc-fire.umd.edu/
Joyce, K. E., Belliss, S. E., Samsonov, S. V., McNeill, S. J., &Glassey, P. J. (2009) A review of the status of satellite remote sensing andimage processing techniques for mapping natural hazards and disasters.
Progress in Physical Geography, 33(2), 183-207.
Liou, Y.-A., Kar, S. K., & Chang, L. (2010) Use of high-resolution
FORMOSAT-2 satellite images for post-earthquake disaster assessment: astudy following the 12 May 2008 Wenchuan Earthquake. International
Journal of Remote Sensing, 31(13), 3355-3368.
Rana, M. S., Gunasekara, K., Hazarika, M. K., Samarakoon, L., &Siddiquee, M. (2010) Application of remote sensing and GIS fro cyclone
disaster management in coastal area?: A case study at Barguna district.
International Archives of the Photogrammetry Remote Sensing and Spatial
Information Science, XXXVIII(8), 122-126.
Sentinel Asia, 2011, http://dmss.tksc.jaxa.jp/
Van Westen, C. J., & Westen, C. J. V. (2002) Remote sensing andgeographic information systems for natural disaster management. In A. K.
Skidmore (Ed.), Information Systems Journal (pp. 1-27). DSIR.
WMO, 2011, WMO Disaster Risk Reduction Programme
http://www.wmo.int/pages/prog/drr/
Yichang, W., Fang, Z., Liping, Z., Lingling, K., & Xiaoqiang, L.
(2010) Estimating Soil Moisture in Semi-arid Region by Remote Sensing
Based on TM Data. International Conference on Multimedia Technology
ICMT 2010 (pp. 1-5). IEEE

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34

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Poster Session

Mainstreaming climate change adaptationin urban planning in Africa
Abbadi GIRMAY REDA1 and Nitin K. TRIPATHI2
Tigray Agri. Research Institute, NRM Research Directorate, Ethiopia andRS and GIS Field of Study, AIT, Thailand (Abbadigirmayreda@gmail.com)
2
Asian Institute of Technology (AIT), Remote Sensing and Geographic Info.
Systems Field of Study, Thailand
1

ABSTRACT
Climate change, coupled with unprecedented rates of rapid urbanization,
makes the potential impacts of disasters much worse. The frequency andintensity of climate-related disasters has quadrupled in the past two decades.
Small and medium-sized cities are currently rapidly emerging with higheconomic and political importance. Vector-borne diseases such as malaria
are expanding to new habitats of higher altitudes where these habitats had
been formerly unsuitable and urban adaptation is crucial. Persistentpoverty, lack of governance and high rate of population growth have left
African countries with scant capacity to manage. Africa will have to combat
adverse effects of climate change. The impacts of climate change will fall
disproportionately on the urban poor. Vulnerability to climate change canbe exacerbated by other stresses, especially in developing country cities.
Climate change impacts on urbanization has negative implications on urban
infrastructure, health, water availability, economy and high risk of natural
disasters such as flooding. International, national and local governments
should have to raise the challenges of climate change on urbanization tosave millions of urban residents to have a livable continent with better
urbanization prospect in the era of globalization. Given the rapid rates ofurbanization in Africa, particular attention must be paid to city-level
policies and actions. Cities can reduce climate and disaster risks throughbreaking the nexus between urban poverty, informal settlements anddisaster risk reduction through community driven development programs;
promoting sound land-use supported by robust local risk assessments;
investing in Early Warning Systems and making risk information widely
available so communities and businesses can prepare for disasters.
Responding to this challenge starts with improving our disaster risk
reduction capacity. This will require new models of cooperation andcoordinated policy responses across multiple sectors, agencies andministries; mainstreaming and institutionalizing climate change insustainable urban planning and a new set of policy instruments for decisionmaking under deep uncertainty. Neither adaptation nor mitigation alone
can avoid all climate change impacts; however, they can complement eachother and together can significantly reduce the risks of climate change.
Keywords: climate change, urbanization, urban adaptation, mainstreaming,
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1. INTRODUCTION
Africa has a population of 1 billion million people and a land area of 30.3
million km2. It is bounded in the north by the Mediterranean Sea, theAtlantic Ocean to the west, and Indian Ocean towards the central and south
east of the continent, and the Red Sea to the northeast, Connecting to theMediterranean via the Suez Canal. The impacts of climate change are
already evident. According to the latest Intergovernmental Panel on Climate
Change (IPCC) report, the average global temperature has increased by
0.76°C and sea level has risen by 17 cm since the 19th century (IPCC 2007).
Climate change is a major threat to sustainable growth and development in
Africa, and the achievement of the Millennium Development Goals. Africa
is particularly vulnerable to climate change because of its overdependence
on rain-fed agriculture, compounded by factors such as widespread poverty
and weak capacity. The main longer-term impacts include: changing rainfall
patterns affecting agriculture and reducing food security; worsening water
security; decreasing fish resources in large lakes due to rising temperature;
shifting vector-borne diseases; rising sea level affecting low-lying coastal
areas with large populations; and rising water stress. The United Nations
Framework Convention on Climate Change (UNFCCC) provides that
all Parties must formulate and implement national or regional
programmes containing measures to facilitate adequate adaptation toclimate change (Art.4.1.b). The developing world already contends withchronic food problems. Climate change presents yet another significant
challenge to be met. While overall food production may not bethreatened, those least able to cope will likely bear additional
adverse impacts (WRI, 2000). Climate change and variability are among
the most important challenges facing Least Developed Countries becauseof their strong economic reliance on natural resources and r a i n -fed
agriculture. These can significantly reverse the progress towards poverty
reduction and food security in Africa. Climate change will affect poorer
African countries disproportionately. The poorest people in those countries
will suffer the greatest consequences. Those least able to cope will be hit thehardest. Hence, climate adaptation strategies should reflect suchcircumstances in terms of the speed of the response and the choice ofoptions (Easterling, 1996 and FAO, 2010).
Urban population in Africa is growing at an alarming rate. African
society is rapidly changing from rural to urban, with cities and towns
expanding, not only in terms of population growth, but also spatially. They
are taking up more space and encroaching on rural and agriculturally
productive land. Rural-urban migration results from landlessness resulting
from privatization of property, commercialization and mechanization ofagriculture, failing agricultural productivity and increase rural population.
One-third of the African population lives in drought-prone areas. Six of theten largest cities in Africa are located on the coast. Many large population
centres are built in coastal zones, which are vulnerable to the loss of land
from sea-level rises and to increased storm occurrence. Cities, particularly
in developing countries, are especially vulnerable to climate change due tothe large concentration of populations and their role as national economic

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hubs. In addition, many urban areas are located on the coast, making themsusceptible to rising sea levels. Within cities, the urban poor are among themost vulnerable. On the other hand, the concentration of resources in urban
areas means cities can be key players in adapting to climate change andmitigating its impact (E.O. Akrofi, 2006).
While the majority (62.1 per cent) of the African population is still
rural, urban growth rates at nearly 4 per cent a year are the most rapid in theworld, and nearly twice the global average (United Nations Population
Division 2001). Growth rates are predicted to average 3.5 per cent per year
over the next 15 years, meaning that Africa's share of the world's urban
population will increase from 10 to 17 per cent between 2000 and 2015
(United Nations Population Division 2001). North Africa is the mosturbanized sub-region with an average urban population of 54 per cent,followed by West Africa (40 per cent), Southern Africa (39 per cent. There
are now 43 cities in Africa with populations of more than one million
inhabitants, a figure which is expected to increase to almost 70 by 2015
(United Nations Population Division 2001).
Rates of urbanization in Africa are the highest in the world. By 2025,
more than half of the African population will be urban, and during the next
quarter century the urban population will be growing almost twice as fast as
the general population, increasing by more than half a billion from 1990
levels. Over a third of Africa's 1 billion inhabitants currently live in urban
areas, but by 2030 that proportion will have risen to a half. According to a
recent report from UN-HABITAT, the United Nations agency for humansettlements, the population of some cities is set to swell by up to 85% in thenext 15 years. Despite the negative attributes of urbanization, these new andgrowing areas, which are located in coastal areas and the hinterland, havealso become vibrant centers of education, culture, commerce and industry
and technological innovation, providing opportunities for various
manufacturing and service industries (UNEP, 2008).
Table 1: Sub-Saharan Urban Population Growth to 2025 (millions)
Year

1990

2010

2025

%Growth(‘90-’25)

Sub-Saharan Africa

527

937

1362

258

Urban Population

149

387

705

473

Urban % of Total

28

41

52

Source: J.L. Venard, Urban Planning and Environment in Sub-Saharan Africa, UNCED ,1995

Rapid growth in urban populations necessarily entails rapid growthboth in the size and number of urban places. By 2020, Africa will have 11
mega-cities (5 million inhabitants or more) and almost 3000 cities withpopulations of more than 20,000, an increase of almost 300% from 1990
(UNCED, 1995)

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Urban populations (millions) by sub-region

Urbanization level (%):

Figure 1: African urban population and urbanization level (United Nations
Population Division
3. CLIMATE CHANGE VULNERSBILITY AND IMPACTS IN
URBAN AFRICA
Climate change is a major threat to sustainable growth and development in
Africa, and the achievement of the Millennium Development Goals. Africa
is particularly vulnerable to climate change because of its overdependence
on rain-fed agriculture, compounded by factors such as widespread poverty
and weak capacity. The main longer-term impacts include: changing rainfall
patterns affecting agriculture and reducing food security; worsening water
security; decreasing fish resources in large lakes due to rising temperature;
shifting vector-borne diseases; rising sea level affecting low-lying coastal
areas with large populations; and rising water stress. Climate change,
coupled with unprecedented rates of rapid urbanization, makes the potential
impacts of disasters much worse. The frequency and intensity of climaterelated disasters has quadrupled in the past two decades. Small and mediumsized cities are currently rapidly emerging with high economic and politicalimportance. Vector-borne diseases such as malaria are expanding to new

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habitats of higher altitudes where these habitats had been formerly
unsuitable. Malaria not only remains a leading cause of morbidity andmortality, but it also impedes socioeconomic development, particularly in
sub-Saharan Africa. Rapid and unprecedented urbanization, going hand-inhand with often declining economies, might have profound implications forthe epidemiology and control of malaria, as the relative disease burden
increases among urban dwellers. A study by The American Society ofTropical Medicine and Hygien using a modeling approach found out thatentomologic inoculation rates in cities range from 0 to 54 per year,
depending on the degree of urbanization, the spatial location within a city,and overall living conditions. The study further indicated that 200 million
people (24.6% of the total African population) currently live in urban
settings are at risk of contracting the disease. Considering different plausible
scenarios, it was estimated that an annual incidence of 24.8-103.2 million
cases of clinical malaria attacks occurred among urban dwellers in Africa.
As cities in the developing world grow, unmanaged urbanization can
outpace infrastructure and environmental safeguards, leading to highpollution and carbon dioxide emissions and to increasing vulnerability forresidents (Jennifer Kaiser, 2004). Climate change has implications inphysical infrastructure, economy, and social welfare and exposes society todisease epidemics and poverty (WHO, 2010).
Sea Level Rise (SLR) in Coastal Zones of Africa
Africa has a large and growing coastal population, including a numberof important coastal cities. With sea-level rise, flooding and inundation ofcoastal areas would be expected creating problems for infrastructure,transportation, agriculture and water resources within the coastal zone.
While risks are not well understood, with 320 coastal cities (with more than
100,000 people) and nearly 56 million people (2005 estimate) living in low
elevation (<10-m) coastal zones, indicating the potential magnitude of
impacts and identifies to countries which have a high absolute risk. It is also
important to note that sea-level rise will not be the only factor shaping
Africa’s coast in the 21st Century. Other climate change impacts such asincreased storminess, higher temperatures and reduced precipitation also
have immediate or secondary impacts of the coast. Sea-level rise as an
impact of human-induced climate change has significant implications to
low-lying coastal areas and beyond. The coastal zone contains valuableecosystems and typically has higher population densities than inland areas(B. Sally et’al, 2011). Studies indicate that most African coastal countries
are highly vulnerable to climate change and sea-level rise, leading toincreased rates of coastal erosion and flooding of low-lying coasts (Ibe andAwosika, 1991). A study was undertaken by B. Sally et’al (2011) to assesssea level rise in African coastal zones to predict changes for the period 2000
to 2100 based on DIVA model. The DIVA (Dynamic Interactive
Vulnerability Assessment) model is an integrated model of coastal systems
that assesses biophysical and socio-economic impacts of sea-level rise andsocio-economic. DIVA downscales the sea-level rise scenarios by
combining global sea-level rise scenarios due to global warming with local
vertical land movement. In this study, four sea-level scenarios (A1FI, A1B,

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B1 and Rahmstorf) have been analysed coupled with three socio-economic
scenarios describing population density and GDP (A1FI, A1B, and B1).
Results of these scenario analysis showed that without adaptation, thephysical and economic impacts of sea-level rise tend to increase with time
under all sea-level rise scenarios (although in the A1 and B1 socioeconomic scenarios used here the population declines after 2050 (Arnell etal., 2004).

Figure 2: People affected by flooding with no adaptation

Figure 3: People affected by flooding with adaptation measures(2000- 2100).
CLIMATE CHANGE IMPACTS
The Impacts of Climate Change on African cities include:• Extreme weather events damage buildings and urban
infrastructure• Coastal cities and small island states affected by sea level rise;
Coastal erosion• Water resources stress: floods and droughts• Human Health – malaria; waterborne diseases; polluted water

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Food Security – Livelihoods – Tourism
Climate refugees move to urban slums

Figure 4: Climate Change Vulnerability in Africa (UN- HABITAT, 2011)
4. MAINSTREAMING CLIMATE CHANGE ADAPTATION IN
URBAN DEVELOPMENT
Building cities that are green, inclusive and sustainable should be thefoundation of any local and national climate change agenda. This requires
better management of cities, mobilization of a global array of stakeholders,
additional financing, and strengthened partnerships, as well as specificsector policy reforms such as urban transport policies, sustainable city
planning, and enhancing city resilience and energy efficiency. The focus ison approaches and issues on African cities coping with climate change andan integrated perspective on cities and climate change, focusing on
mitigation, adaptation and sustainable development. Climate change impacts
upon particular social groups and locations differently, both within andbeyond urban areas. Building resilience in a city requires a systems, or
integrated approach. Cities need an integrated approach that considers
mitigation, adaptation and urban development. The improvement of city
services is related to the ability of cities to adapt to climate change andreduce their greenhouse gas emissions. Cities with excellent services are
generally resilient cities (WRD, 2010). The focus should be on
mainstreaming and formulating urban planning and land use strategies in
response to current and future climate risks and vulnerability - building on
an understanding of underlying socio-economic and environmental trends.
Important adaptation potentials for cities are connected to improved land
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use and the localisation and standards of urban structures and criticalinfrastructure (Wilbanks et. al 2007). Urban planning and land management
are essential (but obviously not the only) tools for policymakers to develop
urban structures resilient towards climate change and build capacity at local
level for sustainable city development, linking adaptation and mitigation
measures and improving livelihoods and quality of life for the urban
population. Attention is should shift to integrated development planning,and housing policies that support environmentally sustainable housing. Key
environmental issues in urban areas in Africa are related to the provision ofservices for waste, water and sanitation, and urban air pollution. In the longterm, climate change adaptation needs to be supported by an integrated,cross-cutting policy approach. Local action plans (amended every three tofive years) are important entry points for change in local governance toaccommodate policies that would increase resilience to climate change.
Local and international institutions have a great role to play in strengthening
local responses to climate change
Responding to this challenge starts with improving our disaster risk
reduction capacity. This will require new models of cooperation andcoordinated policy responses across multiple sectors, agencies andministries; and a new set of policy instruments for decision-making underdeep uncertainty. Given the rapid rates of urbanization in Africa, particularattention must be paid to city-level policies and actions. Cities can reduceclimate and disaster risks by:• Breaking the nexus between urban poverty, informal settlements anddisaster risk reduction through community driven development
programs• Promoting sound land-use supported by robust local risk
assessments• Investing in Early Warning Systems• Making risk information widely available so communities andbusinesses can prepare for disasters
From a local government perspective, the extent to which an issue
such as climate change becomes successfully institutionalized in day-to-day
operations, planning and decision making can be evaluated by using
institutional markers similar to the ones outlined below:• Emergence of an identifiable political/administrative champion(s)for climate change issues;• Appearance of climate change as a significant issue in mainstream
municipal plans;• Allocation of dedicated resources (human and financial) to climatechange issues; and• Incorporation of climate change considerations into political andadministrative decision making.

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5. KEY ADAPTATION AND MITIGATION STRATEGIES FORAFRICAN CITIES
Africa contributes only about 4% to global emissions but will suffer
increasingly severe impacts of climate change. Local action plans areimportant entry points for change in local governance to accommodate
policies that would increase resilience to climate change. Local andinternational institutions have a great role to play in strengthening local
responses to climate change. Africa has the lowest GHG emissions, yet ishit hardest by climate change. Adaptation to the unavoidable impacts ofclimate change will need strong support by the international community andinvolve all stakeholders (World Bank, 2010). It is necessary to have accessto a diverse array of adaptation technologies and practices that areappropriate and affordable in various contexts. Hence, urban adaptation is
crucial in Africa. Adaptation and mitigation are interconnected and closely
related to the overall development and poverty alleviation agenda. Key
adaptation and mitigation strategies include the following options (Elliot
et’al, 2011).
Adaptation Options• Climate proofing of urban infrastructure, e.g. seawalls and storm
surge barriers• Investing in storm water drainage• Early warning systems• Enhance community resilience• Upgrading of slums; Relocation of extremely vulnerable
settlements and infrastructure• Access financing mechanisms such as the UNFCCC Adaptation
Fund
Mitigation Options• Energy efficiency in local government facilities, e.g. street
lighting and water pumps• Foresighted transport and infrastructure planning• Compact and dense urban patterns to reduce travel distances andinfrastructure networks• Promote energy efficient building materials• Landfill methane recovery• Finance: Clean Development Mechanism (CDM)
6. CONCLUSION
Africa is subject to the interaction of ‘multiple stresses’, occurring at
various levels, leading to a reduced adaptive capacity. This vulnerability is
exacerbated by existing developmental challenges such as poverty, complex
governance issues, weak institutions, limited access to capital and markets,
infrastructure and technology, ecosystem degradation, disasters, andconflicts. Africa’s weak adaptive capacity increases the continent’svulnerability to projections of climate change. Africa has the lowest GHG
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emissions, yet is hit hardest by climate change. Adaptation to theunavoidable impacts of climate change will need strong support by theinternational community and involve all stakeholders. Urban adaptation is
crucial. Urbanization affects climate change, resulting in severe impacts to
African cities and livelihoods. The severest burden will be borne by theurban poor in African slums. Climate change actions by African cities need
to be expanded and capacities strengthened. City initiatives need to be
integrated in national action plans and global reporting. Key environmental
issues in urban areas in Africa are related to the provision of services for
waste, water and sanitation, and urban air pollution. Climate change impacts
on urbanization have negative implications on urban infrastructure, health,water availability, economy and high risk of natural disasters such as
flooding. International, national and local governments should have to raise
the challenges of climate change on urbanization to save millions of urban
residents to have a livable continent with better urbanization prospect in theera of globalization. This deserves cooperation and coordinated policy
responses across multiple sectors, agencies and ministries; mainstreaming
and institutionalizing climate change in sustainable urban planning and a
new set of policy instruments for decision-making under deep uncertainty.
Neither adaptation nor mitigation alone can avoid all climate change
impacts; however, they can complement each other and together cansignificantly reduce the risks of climate change.
REFERENCES
Arnell et’al. 2004. Climate and socioeconomic scenarios for climatechange impacts assessment. Global Environmental Change, 14 (1): 3-20.
B. Sally et’al. 2011. Sea level Rise (SLR) and impacts in Africa 20002100.
E.O. Akrofi. 2006. Urbanization and the urban poor in Africa.
Elliot. M. eta’al. 2011. Technologies for climate change adaptation.
ISBN: 978-87-550-3902-5. New Delhi.
FAO. 2010. Climate change threat to Africa: Adaptation a priority.
L.A. Farrell. 2010. Mainstreaming climate change adaptation in urban
development in South Africa. MSc Thesis, MIT, USA.
Rahmstorf, S. 2007. A semi- empirical approach to projecting future
sea level rise. Science, 315: 368-370.
UN- HABITAT. 2008. Climate change resilience in urbanizing West
Africa.
UNCED. 1995. Urban planning and environment in Sub-SaharanAfrica (SSA). Paper No. 5.
UNEP. 2008. Urbanization in Africa.
WHO. 2010. Essential public health package to enhance climatechange resilience in developing countries.
World Bank. 2010. Cities and climate change. Volume 10.
WRI, UNDP, UNEP and World Bank, 2000. World Resources 20002001: People and Ecosystems - the Fraying Web of Life. World Resources
Institute, Washington D.C

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after the Tohoku earthquake part 1:
Results of Japanese respondents
Akiyuki KAWASAKI1, Michael HENRY2, and Kimiro MEGURO3
1
Project associate professor,
International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japanakiyuki@iis.u-tokyo.ac.jp
2
Project researcher, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japan
3
Professor and Director, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japan
ABSTRACTThe magnitude 9.0 Tohoku Earthquake, subsequent tsunami along the
Pacific seaboard of Japan, and ensuing crisis related to the nuclear
reactors at the Fukushima Daiichi power plant have reinforced theimportance of clear and timely communication of disaster-related
information for mitigating long-term negative impacts and working towards
recovery. For people living in Japan, however, this disaster has been one ofconfusing and conflicting messages from differing information sources, andthe atmosphere of uncertainty in the immediate wake of the earthquake led
many people, Japanese and foreigners alike, to relocate to western Japan orleave the country entirely. In order to improve the dissemination of
information after future disasters, a survey investigation was conducted tounderstand how people in the Kanto region – the most populous area ofJapan and bordering the Tohoku region – received their disaster-related
information and how it affected their decisions in the aftermath of thedisaster. This paper presents an overview of the responses of Japanesenationals to the survey and discusses some initial impressions of theirdisaster information gathering behavior.
Keywords: Tohoku earthquake, disaster information, Japanese, social
media, traditional media
1. INTRODUCTION
At 14:46 Japan Standard Time (05:46 UTC) on March 11, 2011, amagnitude 9.0 earthquake occurred off the Pacific coast of the Sanriku areain the Tohoku region of Japan. This earthquake, the largest ever recorded inJapanese history, not only caused strong ground motion which lasted forminutes but also triggered a massive tsunami which inundated the easternseaboard of Japan and caused widespread destruction. The earthquake and451

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tsunami also knocked out the cooling systems at the Fukushima Daiichi
nuclear power plant in Fukushima Prefecture, sparking a nuclear-related
crisis which culminated with the confirmation of nuclear meltdown in threeof the reactors.
In the wake of this triple disaster, people living in Japan began to seek
disaster-related information in order to make decisions regarding their postdisaster actions. The primary source of information after environmental or
man-made disasters is generally the mass media (Greenberg et al., 2002),
and although this information was traditionally accessed via television,
radio or printed media, Internet-based media are becoming the predominantmeans for people to access and communicate disaster-related information(Boyle et al., 2004). After a disaster, during the “response” and “recovery”
phases, the information transmitted by the mass media is generally focusedon affected areas in order to assist with recovery, but in the long-term“mitigation” phase the mass media help provide information to raiseawareness and improve preparation (Quarantelli, 1996).
After the Tohoku Earthquake and during the unfolding of the nuclear
crisis in Fukushima, however, there emerged a growing disparity between
the information given by domestic Japanese sources and overseas sources(Sanchanta, 2011). Conflicting information and differing approaches
between domestic and overseas sources may have contributed to the widelydifferent responses between Japanese and foreigners in Japan; while
Japanese people in general continued life as usual, foreign communities
reacted much differently, with a large number of people relocating to otherparts of the country or leaving Japan entirely – thus spawning the term “flyjin,” a play on “gaijin,” the Japanese word for foreigner. In order to improvedisaster response and recovery, it is necessary to understand what effectthese information-related issues may have had on people’s post-disasteractions and how to improve information dissemination in the future.
The objective of this investigation is therefore to examine and clarify
people’s information gathering behavior after the Tohoku Earthquake, tounderstand the relationship between information and people’s actions, andcontribute to improving information dissemination in the future, particularly
for reducing miscommunication and misunderstanding for foreign nationals
residing in Japan. This paper – part one of two – presents the results of asurvey developed for this investigation and focuses on the responses ofJapanese people. As domestic media sources and information are almost
wholly in the Japanese language, the responses of Japanese people can serve
as a control sample for comparison to the responses of foreigners, which
will be discussed in the second part.
2. SURVEY METHODOLOGYThis study focused just on the behavior of people living in the Kanto regionof Japan. The Kanto region lies to the south of the Tohoku region andincludes Tokyo – the capitol and political, financial, and entertainment

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center of Japan – along with seven surrounding prefectures with apopulation of approximately 42 million Japanese and 1 million foreigners asof 2009. Tokyo itself lies roughly 370 kilometers southwest of the epicenterof the Tohoku Earthquake and 250 kilometers southwest of the Fukushima
Daiichi nuclear power plant.
Data on disaster information gathering behavior were collected using
an online survey. This survey was provided in nine different languages(Japanese, English, Chinese, Korean, Portuguese, Nepalese, French, Thai,
Vietnamese), and the contents were separated into three sections as shownin Table 1. The first section asked respondents about their information
gathering activities, the second section asked respondents about their postdisaster actions and the effect of information, and the third section collected
demographic information.
Section1:
Information
gathering activities

2:
Post-disaster actionand effect of
information

3:
Demographic
information
1
2

Table 1: Survey contents

Questions
What information sources did you trust the most / the least during
the two weeks following the earthquake?
During the two weeks following the earthquake, which media did
you use to acquire information and in what language?
In the case of this earthquake and tsunami disaster, by which media
would you have preferred to receive disaster-related information?
What types of information were most important for you during thefirst day, first week, and second week after the earthquake?
What types of information were unavailable, unclear, or difficult foryou to understand during the first day, first week, and second week
after the earthquake?
In general, what were the reasons why the above information was
unclear or difficult to understand?
When faced with unclear or difficult to understand information,
what media did you utilize in order to clarify or better understandthat information?
At the time of the disaster were you familiar with the Japanese
Earthquake Early Warning System? 1
Were you able to properly receive information regarding the rotating
blackouts?*
Within the first two weeks after the earthquake, did you choose toremain in the Kanto area, relocate to another area of Japan, or leave
Japan? 1
What was the reason for your choice?
At that time when you made your choice, how useful, if at all, wasdisaster-related information in making that choice? 1
If you chose to relocate to another area of Japan or leave Japan,
within which time period after the earthquake did you make yourchoice? 1
What is your nationality?1
Which prefecture were you residing in at the time of the earthquake?
1

What is your occupation?1,2
How old are you? 1,2
What is your yearly income level? 1,2

Questions were restricted to a single response; other questions allowed multiple responses
Response was optional

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The online survey was distributed via two methods: first, through thesocial and professional contacts of the authors; and second, through direct
requests for cooperation with various entities such as business communities,
universities, embassies, and so forth. People who were contacted toparticipate in the survey were also asked to distribute it to their social andprofessional networks.
3. SAMPLE CHARACTERISTICS
The survey received 497 responses from Japanese people, making up 36%of the total number of responses. The distribution of Japanese respondents
by their location and occupation is shown in Figure 1. The majority werefrom Tokyo, followed by Kanagawa, Chiba, and Saitama Prefectures.
Japanese company employees, Japanese educational institution employees,
and students were the top occupations and made up more than three-quartersof the Japanese respondents.
Yamanashi Gunma
0.6%
2.4%
Ibaraki
7.4%

Tochigi
0.4%

Saitama
8.2%
Chiba
10.3%

Tokyo
57.1%

Kanagawa
13.5%Japanesegovernment
employee
4%

Others15%

Japanesecompany
employee29%

No response
4%

Student
23%

Japanese
educational
institution
employee
25%

Figure 1: Distribution of respondents by location (left)
and top occupations (right)
The age and income distribution of respondents are shown in Figure 2.
The most responses were received from people in the 20-29 and 30-39 years
old range, with the number of responses decreasing as age increases. The
annual income of respondents fell mostly in the less than 1.95 million yen(approx. US$24,900) range or in the 3.3 to 6.95 million yen (approx.
US$42,130 to US$88,730) ranges.

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10-19
20-29
30-39
40-49
50-59
60-69
70-79
80 or higher
0

50

100

150

200

Number of responses
Less than 1.95 million yen
1.95 to 3.3 million yen
3.3 to 6.95 million yen
6.95 to 9 million yen
9 to 18 million yen
More than 18 million yen
0

50

100

150

200

Number of responses

Figure 2: Distribution of respondents by age (left) and annual income(right)4. SURVEY RESULTS
4.1 Information sources
Figures 3 and 4 show the top five most-trusted and least-trusted
information sources, respectively, for Japanese respondents. It can be seenthat Japanese news sources were rated as the most trusted, followed by
Japanese research and academic institutions; the national Japanese
government; family, friends colleagues, etc.; and overseas news sources.
However, it can also be seen that the national Japanese government,
Japanese news sources, and overseas news sources were also ranked among
the top-five least trusted sources of information. Tokyo Electric Power
Company was the least-trusted of any information source.
4.2 Media & language for information acquisition
Figure 5 shows the media and language which people used for
acquiring disaster information. Japanese television was the most-used means,followed by Japanese traditional internet media (as in websites, information
portals, and so forth). As may be expected, Japanese respondents did not
utilize media in other languages very much, except for English traditional
internet media.

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Japanese news source
Japanese research/academic institution
National Japanese government
Family, f riends, colleagues, etc.
Overseas news source
0

100

200

300

400

Number of responses

Figure 3: Top five most-trusted information sourcesTokyo Electric Power Company (Tepco)
National Japanese government
Japanese news source
Overseas news source
Third party other than f amily, f riends, colleagues, etc.
0

100

200

300

400

Number of responses

Figure 4: Top five least-trusted information sources
Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

500

Number of responses

Figure 5: Utilized media and language for disaster information acquisition
Figure 6 shows by what media and language people would prefer toreceive the disaster information. Japanese television and traditional internet
media are again the highest-rated. The preference for radio can also be seen
to be higher relative to other media than it was actually utilized.
Understandably, non-Japanese language media were not preferred by theJapanese respondents.

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Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

500

Number of responses

Figure 6: Preferred media and language for disaster informationacquisition
4.3 Importance of information
Figure 7 shows the importance of information types as it changed overtime from the first day to the first and second weeks. On the first day, thesafety of family and friends was by far the most important information,
followed by concerns about the transportation systems and earthquake andtsunami damage. By the first week, however, radiation level and risk was
the most important type of information, followed by continuing concerns
about transportation systems and earthquake and tsunami damage. By thesecond week, the importance of most information continued to decrease
except for radiation level and risk, which actually increased slightly. Also,
government response became the second-most important information type.
4.4 Problems related to information
The importance of information needs to be considered in terms ofwhether that information can actually be obtained or understood. Figure 8
shows what information people found to be unavailable, unclear, or hard tounderstand over the same two-week period.
For the first day, information related to the safety of family andfriends, radiation level and risk, and transportation systems, and earthquake
and tsunami damage were the hardest to find or understand. By the first
week, these had decreased except for radiation level and risk andgovernment response, which increased. By the second week, the unavailable
or difficult to understand information decreased slightly, but radiation level
and risk and government response were still highly viewed as unavailable,
unclear, or hard to understand.

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Results of Japanese respondents

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During the f irst day
During the f irst week
During the second week
Saf ety of f amily, friends, etc.
Earthquake & tsunami characteristics
Earthquake & tsunami damage
Radiation level & risk
Government response
Evacuation & shelters
Food & water supply
Electricity & other utilities
Transportation systems
School & business continuity
0

100

200

300

400

500

Number of responses

Figure 7: Importance of information types over time
During the f irst day
During the f irst week
During the second week
Saf ety of f amily, friends, etc.
Earthquake & tsunami characteristics
Earthquake & tsunami damage
Radiation level & risk
Government response
Evacuation & shelters
Food & water supply
Electricity & other utilities
Transportation systems
School & business continuity
0

100

200

300

400

500

Number of responses

Figure 8: Unavailable, unclear, or hard to understand information overtime
The reasons why the previously-discussed information was unclear or
hard to understand are shown in Figure 9. The biggest reason appeared to bethat people were confused by conflicting or differing information, followed
closely by being unable to access information due to problems such as

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mobile congestion or power outages. The other reasons were ranked much
lower.
Was conf used by conf licting or differing inf ormation
Unable to access inf ormation due to mobile congestion,
power outage, etc.
Couldn’t understand inf ormation due to dif f icult or
unf amiliar terminology
Unable to f ind the inf ormation due to dif f iculty insearching or locating it
Other
Couldn’t understand inf ormation due to lack of language
comprehension
0

100

200

300

400

Number of responses

Figure 9: Reasons information was unclear or hard to understandFigure 10 shows what media and language people turned to in order toclarify problems they had with information. Traditional Japanese internet
media was the most-used means, followed by Japanese television. Among
non-Japanese language media, traditional English internet media was thehighest rated.
Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

Number of responses

Figure 10: Media and language for clarifying information problems
4.5 Early warning system and rotating blackouts
Figure 11 shows the distribution of respondents who were familiar
with the Japanese Earthquake Early Warning System and whether
respondents could properly receive information regarding the rotating
blackouts. It can be seen that a large majority of Japanese respondents werealready familiar with the warning system. Only slightly more than half ofthe respondents, however, said that they could receive information on therotating blackouts, with one-third responding that they were unable toreceive blackout information. Being unable to access information due tomobile congestion, power outage, etc. was cited as one reason why
Disaster information gathering behavior after the Tohoku Earthquake Part 1: Results of Japanese
Disaster information gathering behavior after the Tohoku earthquake part 1:
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Results of Japanese respondents539

October 2011, Chiang
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information was unclear or hard to understand, which may have contributed
to difficulties in accessing rotating blackout information.
Notapplicable
14.9%

No
15.9
%

Yes
50.7%

No
34.4%

Yes
84.1
%

Figure 11: Distributions of whether respondents were familiar with theearly warning system before the earthquake (left)
and whether they could receive information on the rotating blackouts (right)
4.6 Post-disaster relocation & usefulness of information
The survey also asked people whether they remained in the Kanto area,
relocated to another area of Japan, or left Japan within two weeks after theearthquake. As shown in Figure 12, an overwhelming majority of the survey
respondents did not relocate – they remained in the Kanto area. Among thevery few number of people who relocated or left, it can be seen in Figure 13
that the number increased from within one day up to within one week, andthen decreased again.
Remained in the Kanto area
Relocated to another area of Japan
Lef t Japan
0

100

200

300

400

500

600

Number of responses

Figure 12: Distribution of whether respondents stayed, relocated, or left
Within 1 day
Within 3 days
Within 1 week
Within 2 weeks
Af ter more than 2 weeks
0

10

20

30

Number of responses

Figure 13: Timing of relocation or leaving
The primary reason people cited for whether they stayed, relocated orleft was that it was a personal decision, as shown in Figure 14. This reason
by far outranks other reasons such as unable to leave, job obligation, orothers. Overall, it appeared that disaster-related information was somewhat
useful for people’s decision making, as shown in Figure 15. These results,
however, are going to require more analysis to look at which reasonscorresponded to which actions.

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Personal decision
Unable to leave
Job obligation
Other
Family request
Concern f or babies or children
Government directive
0

100

200

300

400

500

Number of responses

Figure 14: Reasons for staying in Kanto, relocating, or leaving Japan
Very usef ul
Somewhat usef ul
Slightly usef ul
Not usef ul
0

100

200

300

400

Number of responses

Figure 15: Usefulness of disaster-related information for decision making
5. INITIAL IMPRESSIONS
When considering the information gathering behavior of Japanese
respondents, it could be seen that several of the information sources whichwere among the top five most-trusted sources were also among the top five
least-trusted sources. This illustrates one of the difficulties in disseminating
disaster information, in that what may be a highly trusted source for one
person may be another person’s highly distrusted source. Japanese
research/academic institutions were the highest trusted source which did not
fall within the top five least-trusted sources, indicating that these institutions
may be a good, neutral source for disseminating information in the future.
To collect their disaster information, Japanese respondents primarily utilized
television and traditional internet; as the situation after the disaster wasconstantly in flux, these media were very useful as they can provide
frequent updates with accompanying visual and discussions. The results ofthis survey, however, may be biased towards people who regularly utilize
the internet, as the survey was distributed online.
The importance of and unavailability or difficulty in understanding
information was also seen to change over time, which reflects the constantly
changing situation as concern shifted from the earthquake to the tsunami
and the nuclear situation. These two followed a similar trend, suggestingthat as people became more concerned with a certain type of information

Disaster information gathering behavior after the Tohoku Earthquake Part 1: Results of Japanese
Disaster information gathering behavior after the Tohoku earthquake part 1:
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Results of Japanese respondents

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they wanted to know it in more detail, thus highlighting issues related tofinding or understanding that information.
The majority of the Japanese respondents did not relocate or leave
Japan, citing personal decision as their reasoning. It is difficult at this levelof analysis to clarify what effect disaster information may have had on thisdecision, if any.
The results and discussion in this paper (part one of two), however,
only represent some initial impressions focusing on the Japanese
respondents. Part two continues introducing the survey results by focusing
on the responses of foreign nationals and comparing them to those ofJapanese respondents.
REFERENCES
Boyle, M., Schierbach, M., Armstrong, C.L., Mcleod, D.M., Shah,
D.V., Pan, Z., 2004. Information seeking and emotional reactions to the
September 11 terrorist attacks. Journalism and Mass Communication
Quarterly 181, 155-167.
Greenberg, B.S., Hofschire, L., Lachlan, K., 2002. Diffusion, media
use and interpersonal communication behaviors. Communication andterrorism: public and media responses to 9/11, Hampton Press, Cresskill, 316.
Quarantelli, E.L., 1996. The future is not the past repeated: projecting
disasters in the 21st century from current trends. Journal of Contingencies
and Crisis Management 4(4), 220-240.
Sanchanta, M., 2011. Japanese, foreign media diverge. The WallStreet Journal. Available from:http://online.wsj.com/article/SB1000142405274870351240457620904
3550725356.html (27 September 2011)

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NewAn experimental study on strengthening
lap splice by ferrocement jacket
Ratkriangkrai PAOLENG
Sirindhorn International Institute of Technology,
Thammasat University, Pathumthani, Thailand
joe.kriangkrai_civil@hotmail.com
Amorn PIMANMAS
Associate Professor, Sirindhorn International Institute of Technology,
Thammasat University, Pathumthani, Thailand
amorn@siit.tu.ac.th
ABSTRACTThis paper presents the experimental program on strengthening substandard lap splice of reinforcement using ferrocement jacket. The
strengthening technique employed the skeleton steel of 9 mm diameter for
confining the lap splice zone. The test program consisted of 7 specimens.
One is the control specimen with continuous bar (no lap splice). The other 6
specimens contained lap splice of longitudinal bars. Two of them were unstrengthened and the remaining 4 specimens were strengthened byferrocement jacket. The main study variables were lap splice length, theratio of concrete cover to bar diameter, concrete compressive strength andthe volume of confining skeleton steel. The ferrocement was made with 50
MPa mortar and reinforced by two layers of hexagonal wire meshes. The
thickness of ferrocement jacket was 20 mm. Based on experimental results,
the un-strengthened specimens showed a substantial drop in load bearing
capacity. The failure was characterized by a horizontal splitting crack along
the lap splice. Strengthening by ferrocement jacket could significantly
increase the strength by as high as 50% and could develop the yieldstrength of the bars. The ferrocement jacket could also increase the ductilityof the strengthened specimens.
Keywords: strengthening, lap splice, ferrocement, bond strength
1. INTRODUCTION
In reinforced concrete construction, lap splice of reinforcing bars is common
in many locations of the structures, for example, the lap splice of column
longitudinal bars and beam longitudinal bars. If the splice length isinadequate for the bond development, the strength and ductility of the bars
can be degraded (Thai, 2010). The premature failure of lap splice isnormally caused by the splitting of longitudinal bars leading to the loss ofbond and sudden drop in load carrying capacity.

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The main factors that affect the bond between concrete and steel bars
are (1) lap splice length, concrete compressive strength and the concrete
cover-to-bar diameter ratio (Thai, 2010; Harajli, 2006; Harajli, 2009). In
existing structures, there is an urgent need to retrofit the substandard lap
splice to meet the new requirements (Bournas and Triantafillou, 2010;
Jumaat and Alam). There are several methods to retrofit inadequate lap
splice such as fiber-reinforced polymer (FRP) wrapping (Thai, 2010; Harajli,
2006; Harajli, 2009), concrete jacketing (Bournas, and Triantafillou, 2010;
Jumaat and Alam; Joyklad et al.; Bousias et al., 2006), steel plate jacketing(Lin et al., 2010), ferrocement jacketing (Kumar et al., 2007; Al-Kubaisy
and Jumaat, 2000). When considering the cost of retrofitting old structures,
ferrocement is a competitive method (Juntanalikit et al.,2009; Bansal et al.).
Ferrocement is a thin reinforced material with thickness not more than 25
mm. It is made from closely spaced wire mesh and plastered with highcement mortar (Joyklad et al.; Juntanalikit et al., 2009; ACI549R-97, 2009).
The strength can be enhanced by adding skeleton steels made from ordinary
plain steel bars. In this research, the authors apply ferrocement to strengthen
lap splice zone.
2. EXPERIMENTAL PROGRAM
2.1 Specimen details
The experiment aims to study the effect of strengthening lap splice byferrocement. The factors to be considered are lap splice length, concrete
compressive strength, technique of ferrocement reinforcement and the ratioof concrete cover-to-bar diameter. The experiment consisted of 7 specimens.
One of them employed continuous bars without lap splice and served as thecontrol specimen. The rest of specimens were divided into two groups,
25db group with 300 mm splice length and 20db group with 250 mm splicelength as shown in Table 1. The specimens are beam type with crosssection size 150x300 mm and the span length of 2140 mm. They are tested
under a static point load applied at the center of the beam. The
reinforcements in the specimens are 3-DB12 (diameter = 12 mm) top bars
and 2-DB12 bottom bars. The nominal yield strength of the bar is 400 MPa.
The specimens also contain stirrup of 6 mm diameter spaced at 150 mm
throughout the length of the specimen. The nominal yield strength of stirrup
is 240 MPa. The detail of specimen with lap splice is shown in Fig. 1.

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CL

6@150mm

3DB12Strengthening
zone
50

2DB12
Lap splice length
2140
2340

(a) Specimen’s detail

Unit: mm(b) control specimen (continuous bar) (c) specimen with lap splice
Figure 1: Detail of specimens and lap splice
2.2 Strengthened specimens(a) Strengthening of specimen by(b) plastering step
ferrocement
Figure 2: Application of ferrocement(a) Skeleton steel(b) Hexagonal Wire mesh
Figure 3: Skeleton steel and hexagonal wire mesh

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strengthening lap
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Chiang
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October
2011,
Chiangmai,
Chiangmai,
Thailand

The
The
2020
mm
mm
thick
thick
ferrocement
ferrocement
is isjacketedjacketedaroundaroundthethespecimen
specimen
in inthethelaplapsplicesplice
zone.
zone.
The
The
mortarmortarplasterplaster
was
was
high
high
cementcementcontent.
content.
It is
It reinforced
is reinforced
with
with
2 layers
2 layersof ofhexagonal
hexagonal
wire
wire
mesh
mesh
as as
shown
shown
in in
FigureFigure2 (a).
2 (a).
The
The
skeletonskeleton
steel
steel
areare
plain
plain
round
round
barbar
RB9
RB9
(9 (9
mm
mm
diameter)diameter)withwiththethespacing
spacing
of of
2020
mm
mm
as as
shown
shown
in in
(Figure(Figure2 (b)).
2 (b)).TheThe
skeletonskeletonsteelssteelsarearefabricatedfabricatedin in
2 C-shaped
2 C-shaped
piecespiecesandandassembled
assembled
to to
form
form
a loopa loopbyby
welding
welding
as as
shown
shown
in in
FigureFigure3. 3.
2.32.3Specimen
Specimen
designations
designations
Table
Table
1: 1:
Specimens
Specimens
SeriesSeries

25db
25db

20db
20db
without
without
laplapsplicespliceBeam
Beam

Skeletal
Skeletal
steel
steel
Lap
Lap
splicesplicef'c f'ccover/barcover/barlengthlength member
member diameter
diameter Diameter
Diameter Spacing
Spacing, mm)(Lsp(L(Mpa)(c/d(c/d
sp, mm) (Mpa)
b) b)
(mm)
(mm)
(mm)
(mm)

25F0
25F0

30030041 41

1.71.7

- -

- -

25FP
25FP

30030041 41

1.71.7

- -

- -

25F5
25F5

30030041 41

1.71.7

9 9

50 50

20F0
20F0

25025041 41

1.71.7

- -

- -

20FP
20FP

25025041 41

1.71.7

- -

- -

20F5
20F5

25025041 41

1.71.7

9 9

50 50

00C1
00C1

- -

41 41

1.71.7

- -

- -

From
From
Table
Table
1, 1,
thethespecimens
specimens
withwithlaplapsplicesplicearearedivideddividedinto
into
2 groups,
2 groups,
25db
25db
andand
20db.
20db.
The
The
numbernumberin inthethegroup’sgroup’s
name
nameindicates
indicates
thethelengthlengthof oflaplapsplicesplice(L(L) which
is is
equal
equal
to to
thethemultiple
multipleof ofbarbardiameterdiameter
(db(d
=12
mm)
mm)
forforsp)spwhichb=12
example,example,25db
25dbwill
willhave
havethethesplicesplicelength
lengthequal
equalto to300
300mm.
mm.TheThesplice
splicelengthlengthis isindicatedindicatedin incolumncolumn
3 of
3 of
Table
Table
1. 1.
The
The
specimen
specimen
designation
designationis iscomposedcomposed
of of
three
three
parts.
parts.
The
The
numbernumberindicates
indicates
thetheseriesseries
(20db
(20db
or or
25db).
25db).
The
The
letterletterF indicates
F indicatesspecimens
specimens
withwithlaplapsplice.
splice.
The
The
lastlast
letterletteror or
numbernumberindicates
indicates
thethe
type
type
of of
retrofit,
retrofit,
i.e.,
i.e.,
“0”“0”
indicates
indicates
nono
retrofit,
retrofit,“P”“P”
indicates
indicates
thetheretrofit
retrofitbyby
hexagonal
hexagonal
wire
wire
mesh
mesh
only
only
and
and
“5”“5”
indicates
indicates
thetheretrofit
retrofit
byby
9 mm
9 mm
skeletonskeleton
steel
steel
spacedspaced
at at
5050
mm.
mm.
The
The
control
control
specimen
specimenwithwithcontinuous
continuous
barbaris isdesignateddesignatedbyby“00C1”.
“00C1”.
2.42.4
Material
Material
properties
properties(a)(a)
specimens
specimens
coveredcoveredbyby
wetwet(b)(b)
Lap
Lap
splicesplicezone
zone
burlapsburlaps
Figure4: 4:Curingof ofspecimen
FigureCuringspecimen

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2.4.1 Concrete
The specimens were cast by ready mixed concrete. They were left 24hours before curing by wet burlaps as shown in Figure 4 (a). The tested
compressive strength of standard cylindrical specimen at 28 days is 41 MPa.
2.4.2 Reinforcement
The tested yield strength of main bars (DB12) is 474 MPa and thetensile strength is 782 MPa. The tested yield strength of stirrups (RB6) is
380 MPa and the tensile strength is 457 MPa. The tested yield strength ofskeleton steel (RB9) is 346 MPa and the tensile strength is 427 MPa.
2.4.3 Ferrocement
The plastering mortar was mixed at the water:cement:sand ratio =1:2:4. The target compressive strength at 7 days is 50 MPa. After plastering
mortar to the lap splice area, it is left 24 hours and then covered by wet
burlaps as shown in Figure 4 (b).
2.5 Instrumentations
The deflection of specimens is measured by 7 transducers as shown in
Figure 5. The transducers at position 1 and 2 are to measure support verticalmovement. The transducers at position 3 and 4 are to measure verticaldeflection at ¼ span length. The midspan deflection is measured bytransducer 6.
1

2

3

5

6

4

Figure 5: Position of transducers
2.6 Applied load
The point load is statically applied at midspan through hydraulicactuator. The load cell with 100 kN capacity is used to measure the load.
The load is applied incrementally at 2.5 kN. At each load increment, thedeflection and the cracks are recorded.
3. THE RESULTS
3.1 Load-Displacement
The deflection at mid-span ( Δ ) is obtained by subtracting measured
support deflections (position 1 and 2) from measured mid-span deflection(position 6) as shown in equation (1).

An experimentalAnexperimental study
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strengthening lap
lap splicespliceby
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ferrocementjacket
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October 2011, Chiang
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Chiangmai,

Δ = (6) −(1)(1) + (2)2100Load (kN)

80
60
40
20
0

0

10

20

30

40

Displacement (mm)

00C1

20F0

20FP

50

60

20F5

Figure 6: load versus displacement of series 20DB and 00C2
100

Load (kN)

80
60
40
20
0

0

10
00C1

20

30

40

Displacement (mm)
25F0

25FP

50

60

25F5

Figure 7: load versus displacement of series 25DB and 00C2
The test results are shown in Figure 6 and 7. In each figure, the control
specimen 00C1 is shown as dash line. From Figure 6, when comparing
specimen 20F0 with 00C1, it can be seen that specimen 20F0 can resist the
maximum load of 40 kN at deflection of 5.1 mm. After that, the graph drops
suddenly. As for specimen 20FP, the maximum load is 56 kN at 5.10 mm
deflection. The load drops suddenly after reaching the peak load. It can beseen that the use of ferrocement without skeleton steel cannot develop theyield strength of steel bar. As for specimen 20F5, the maximum load is80.93 kN at 22.75 mm deflection. It can be seen that this specimen candevelop yield strength of steel bar. The strengthening by ferrocement jacket
with skeleton steel is shown to increase both load and deformation capacity.
The strength increase is higher than that of 00C1.
Figure 7 shows the comparison between specimens in series 25db withthe lap length of 300 mm. In this figure, specimen 25F0 without any retrofit
can resist the maximum load of 59.06 kN at 6.02 mm deflection. The load
drops sudden after reaching the peak. The tendency is similar to series 20db.
For retrofitted specimens 25FP and 25F5, both of them can reach yield load,
but the strength of specimen 25FP drops suddenly when reaching the peak.
The highest load that specimen 25FP can reach is 64.89 kN. However,specimen 25F5 can reach the highest load up to 95.65 kN and can deform as

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much as 41.4 mm. When compared with specimen 25F0, it can be seen thatstrengthening by ferrocement jacket with skeleton steel is very effective toincrease both strength and deformation capacity of the specimen.
3.2 Crack pattern
The crack patterns are recorded during the tests. The photos of thespecimens after the test are shown in Figure 8-12. Figure 8 shows the crack
pattern of specimen 00C1. Most of vertical cracks occur in the midspanregion of the beam. On the other hand, the failure of specimen 20F0
without retrofitting shows less vertical cracks than observed in 00C1. A
large horizontal crack along the lap splice can be clearly observed. It isobserved that once this horizontal crack forms, the load drops suddenly.
This horizontal crack is thought to be caused by bond splitting failure.

Figure 8: Crack pattern of specimen 00C1 at failure

Figure 9: Crack pattern of specimen 20F0 at failure
The crack pattern of specimens 25F5 retrofitted by ferrocement jacket
with skeleton steels is shown in Figure 10. When ferrocement jacket isremoved from the main beam, the cracks are revealed as shown in Figure11-12. Figure 11 shows the crack pattern of specimen retrofitted byferrocement jacket without skeleton steels. A large horizontal splitting crack
can be clearly observed. However, when skeleton steels are added toferrocement jacket, it can be seen that the crack pattern at failure is similar
to specimen 00C1 with continuous bars (Figure 8). From this observation, it
can be clearly seen that ferrocement jacket with skeleton steel are effective
to retrofit the lap splice in reinforced concrete beam.

25F5

Figure 10: Crack pattern of specimens retrofitted by ferrocement jacket

An experimentalAnexperimental study
study onon strengthening
strengthening lap
lap splicespliceby
byferrocement
ferrocementjacket
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October 2011, Chiang
Mai,Thailand
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Chiangmai,

Figure 11: Crack pattern of specimens retrofitted by ferrocement jacket
without skeleton steel (observed on main beam)

Figure 12: Crack pattern of specimen retrofitted by ferrocement jacket withskeleton steel (observed on main beams)
4. CONCLUSIONS
From the experimental study of retrofitting lap splice by ferrocement jacket.
Two experimental series are performed, that is 20db (splice length = 250mm) and 25 db series (splice length = 300 mm). A total of 7 specimens havebeen tested under static load applied at the midspan of the beam. From thetest results, the following conclusions can be drawn.
•••

The specimens with lap splice length of 20 and 25 times bar
diameter cannot develop yield strength of steel bars. The failure isbrittle and caused by the horizontal splitting crack occurring the lap
splice zone.
Retrofitting specimens by ferrocement jacket without skeleton steel
can increase the strength of the specimens a little but does notenhance the deformation capacity.
Retrofitting specimens by ferrocement jacket with skeleton steel can
substantially increase both the strength and deformation capacity ofthe specimens. This retrofit method is also effective to develop theyield strength of steel bars.

ACKNOWLEDGEMENT
The authors are grateful to Thailand Research Fund for providing the
research grant RSA 5280034.

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REFERENCES
ACI549R-97, 2009. Report on Ferrocement, ACI committee report,
ACI committee 549.
Al-Kubaisy, M.A., Jumaat, M.Z., 2000. Flexural behaviour ofreinforced concrete slabs with ferrocement tension zone cover, Construction
and Building Materials 14, 245-252.
Bansal, P.P., Kumar, M., and Kaushik, S.K., Effect of Wire Mesh
Orientation on Strength of Beams Retrofitted using Ferrocement Jackets,
International Journal of Engineering, Vol.2 , issue 1, 8-19.
Bournas, D.A., and Triantafillou, T.C., 2010. Bond strength of Lap
Spliced Bars in Concrete Confined with Composite Jackets, ASCE Journalof Composites for Construction, 40pp.
Bousias, S., Spathis, A.L., and Fardis, M.N., 2006. Concrete or FRP
Jacketing of Column with Lap Splices for Seismic Rehabilitation, Journal ofAdvanced Concrete Technology, Japan, Vol.4, No.3, 431-444.
Harajli, M.H., 2006. Effect of confinement using steel, FRC, or FRP
on the bond stress-slip response of steel bars under cyclic loading,Materials and Structures, 39, 621-634.
Harajli, M.H., 2009. Bond Stress–Slip Model for Steel Bars in
Unconfined or Steel, FRC, or FRP Confined Concrete under Cyclic Loading,
Journal of Structural Engineering, 509-518.
Joyklad, P., Jantanalilit, P., and Pimanmas, A., Shear Strengthening of
RC beams using web steel and Ferrocement cover, Annual Concrete
Conference 5, Thailand, STR.41-46.
Jumaat, M.Z., and Alam, M.A., Strengthening of reinforced concrete
structures” Department of Civil Engineering, University of Malaya, Kuala
Lumpur.
Juntanalikit, P., Joyklad, P., and Pimanmas, P., 2009. Shear
Strengthening of Reinforced Concrete Beams using Ferrocement, New
Technologies for Urban Safety of Mega Cities in Asia, 301-312.
Kumar, P.R., Oshima, T., Mikami S., and Yamazaki, T., 2007. Studies
on RC and Ferrocement Jacketed Columns Subjected to Simulated Seismic
Loading, Asian journal of civil engineering (Building and Housing), VOL 8,
No.2, 215-225.
Lin, M.L., Chen, P.C., Tsai, K.C., Yu, Y.J., and Lui, J.G., 2010.
Seismic steel jacketing of rectangular RC bridge columns for the mitigationof lap-splice failures, Earthquake engineering and structural dynamics.
Thai, D.X., 2010. Strengthening Lap Splice in Sub-standard
Reinforced Concrete Column by Frp Wrapping, M.sc. Thesis, Sirindorn
International Institute of Technology, Thammasat University, Thailand

An experimentalAnexperimental study
study onon strengthening
strengthening lap
lap splicespliceby
byferrocement
ferrocementjacket
jacket659

October 2011, Chiang Mai, Thailand

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Correlation analysis of a reinforcedconcrete building under tsunami loads
and effect of masonry infill walls
in tsunami resistanceAnat RUANGRASSAMEE1 and Piyawat FOYTONG2
1
Assistant Professor, Department of Civil Engineering,
Chulalongkorn University, Thailand
anat.r@chula.ac.th2
Ph.D. Candidate, Department of Civil Engineering,
Chulalongkorn University, Thailand
piyawat_pwf@yahoo.com
ABSTRACTThe December 26th, 2004 Indian Ocean tsunami caused damage to manybuildings in the southern provinces of Thailand. Reinforced-concretebuildings in the area are mainly designed for gravity loads. One-story
building which was the former office of Thai Meteorological Department
located in Phang-Nga province was tested under tsunami load patterns. In
this research, the reinforced-concrete building model is investigated by 3dimensional non-linear static pushover analysis. In the building model,
masonry infill walls are considered and idealized as the diagonal stud. The
results of the building model agree well with the test results. To analyze theeffect of masonry infill walls, the patterns of the wall are rearranged. The
masonry infill walls with the appropriate arrangement can significantly
improve the load resisting capacity of the building.
Keywords: tsunami, tsunami load, reinforced concrete, building, nonlinear
analysis
1. INTRODUCTION
The December 26th, 2004 Indian Ocean tsunami caused damage to several
buildings in southern provinces of Thailand. Reinforced-concrete buildingsin the area are mainly designed for gravity loads. One-story building whichis the former office of Thai Meteorological Department located in PhangNga province was tested under tsunami load patterns. This research focuseson correlation analysis of the reinforced-concrete building with in-filled
masonry walls under tsunami loading by using 3-dimensional nonlinear
pushover analysis. Then the model is used to study the effect of masonry
infill walls in a tsunami load resisting capacity.

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2. DAMAGE OF BUILDING DUE TO 2004 INDIAN OCEANTSUNAMIThe December 26th, 2004 Indian Ocean tsunami caused damage tobuildings in Indian Ocean countries. The damage of buildings were reported
and analyzed by several researchers (Ruangrassmee et al., 2006). Damage toreinforced-concrete buildings ranged from no damage to collapse. To
understand behavior of a reinforced-concrete building, the former office ofThai Meteorological Department located in Phang-Nga province was tested
by Lukkunaprasit et al. (2010). As shown in Figure 1, this building was
exposed to the tsunami inundation height of 4.4 m and damaged in nonstructural members. In the test, the lateral pushover force was applied torepresent the hydrodynamic force due to the tsunami. Figure 2(a) depicts the
pushover test setup and Figure 2(b) shows the relationship of lateral force
and displacement of each frame.

Figure 1: The former office of Thai Meteorological Department inPhang-Nga (Lukkunaprasit et al., 2008)(a) Test setup
450
400

Load (kN)

350
300
250
200
150

Frame_A

100

Frame_B

50

Frame_C

0
0

2

4

6

8

10

12

Displacement (mm): Reference at base

1416(b) lateral force vs displacement relation
Figure 2: Pushover test setup and results (Lukkunaprasit et al., 2008)

2
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3. ANALYTICAL MODEL
In this study, the building is analyzed using a non-linear static pushover
analysis by the TDAPIII program. The reinforced-concrete frames andmasonry infill walls are the main structural components that need tovalidation with existing results from tests of structural components.
3.1 Reinforced-concrete frames
3.1.1 Analytical modelA 3-dimensional fiber model is used in the plastic region at the end of
beams and columns to predict the behavior of reinforced-concrete frames.
The plastic lengths of beams and columns are evaluated by using theequation proposed by Pauley and Priestley (1992). The fiber model consistsof the unconfined concrete model, confined concrete model, longitudinal
reinforcement model. The stress-strain relationship of unconfined concrete
is modeled using the equation proposed by Kent and Park (1971). The
stress-strain relationship of confined concrete is modeled using the equation
proposed by Hoshikuma et al. (1997). The stress-strain relationship byMenegotto-Pinto (1973) is used for longitudinal reinforcement. The shear
failure is considered using a non-linear spring as proposed by Sezen andMohele (2004).
3.1.2 Comparison with test results
To validate the structural model, the experimental results by Wehbe(1999) and Anil and Altin (2007) are considered. From the study by Wehbe(1999), the rectangular reinforced-concrete column with 308 mm x 610 mm
section was tested under cyclic loading and subjected to the axial force of
615 kN. The column height was 2.050 m. The analytical column model
consists of the zero length shear spring, the fiber section element, and theelastic element. The calculated plastic length of the column is 0.352 m. The
comparison between analytical result and experimental result of this column
is shown in Figure 3.
Lateral Load (kN)

500
300
100

-100
-300
-500
-200

Analytical
Experimental
-100
0
100
Lateral displacement (mm)200

Figure 3: Comparison of experimental results by Wehbe (1999)
and analytical results
From the study by Anil and Altin (2007), the reinforced-concrete
frame with the 100 mm x 150 mm column section and 150 mm x 300 mm
beam section was tested under cyclic loading without axial force. The frame
Correlation analysis of a reinforced-concrete building under tsunami loads and effect of masonry infill walls
Correlation analysis of a reinforced-concrete building under tsunami loads
in tsunami resistance693
and effect of masonry infill walls in tsunami resistanceOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

had columns with a height of 750 mm and and a 1,500 mm long beam. The
analytical model of the frame consists of the zero length shear springs at theend of columns, the fiber section elements at the end of the columns and thebeam, and elastic elements as shown in Figure 4. The plastic lengths are
0.174 m and 0.150 m for the columns and beam, respectively. The
comparison between analytical result and experimental result of this column
are shown in Figure 5. From Figures 3 and 5, it is found that the reinforced
concrete models can capture the actual behaviors satisfactorily.

40

Shear Force (kN)

30
20
10
0

-10
-20

Analytical
Experimental

-30
-40
-60

-40

-20
0
20
40
Lateral displacement (mm)60

Figure 4: Analytical model of bare frame Figure 5: Comparison ofexperimental results by Anil and Altin (2007) and analytical results
3.2 Masonry infill wall
3.2.1 Analytical model
There are several models to idealize masonry infill walls. The
diagonal stud was used in this research. For the lateral resisting force
capacity of infill wall, the formulas proposed by FEMA 306 (1998) andMostafaei and Kabeyasawa (2004) are considered. The experimental resultsof Mehrabi et al. (1996) are used to validate the masonry infill wall model.
Four specimens were tested under monotonic loadings with the same RC
frames, but they were different in the masonry types and the distribution of
axial loads. The frame consisted of columns with a height of 1.537 m and a
2.312 m long beam. Table 1 shows the comparison of the lateral resisting
forces with calculated forces by equations by FEMA 306 (1998) andMostafaei and Kabeyasawa (2004). The resisting forces calculated fromequations by Mostafaei and Kabeyasawa (2004) agree well with theexperimental results, thus the equation by Mostafaei and Kabeyasawa(2004) was used to calculate the wall resisting force.

4
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Specimen
No.
2
3
8
9

Table 1: Comparison of lateral resisting forces

Experiment(1)14515.1
28304.5
19368.629846.7

Mostafaei andKabeyasawa (2)14215.1
23845.1
14975.921898.6

FEMA 306 (3)(2)/(1)(3)(1)

8884.414017.8
9178.313059.8

0.98
0.84
0.77
0.73

0.61
0.50
0.47
0.44

3.2.2 Comparison with test results
The masonry infill wall and frame was modeled as shown in Figure 6.
The masonry infill wall is modeled as a diagonal stud. The fiber sections areused in the plastic region at the end of beams and columns. The plastic
lengths are 0.174 m for columns and 0.237 m for a beam. Shear springs areused to capture shear behaviors of columns and beam-column joints are
assumed to be rigid. The comparison of the lateral load and lateraldisplacement relationship between the experimental results and analyticalresults for all four specimens are shown in Figure 7. It is found that themodel can capture the maximum load satisfactorily.

Figure 6: The analytical model of bare frame with masonry infill wall model
Lateral Load (kN)

300
250
200
150
100

Analytical
Experimental

50
0
0

10

20
30
40
Lateral displacement (mm)50(a) Specimen No.2
Lateral Load (kN)

300
250
200
150
100

Analytical
Experimental

50
0
0

10

20
30
40
Lateral displacement (mm)50(b) Specimen No.3

Correlation analysis of a reinforced-concrete building under tsunami loads and effect of masonry infill walls
Correlation analysis of a reinforced-concrete building under tsunami loads
in tsunami resistance715
and effect of masonry infill walls in tsunami resistanceOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Lateral Load (kN)

300
250
200
150
100

Analytical
Experimental

50
0
0

10

20
30
40
Lateral displacement (mm)50(c) Specimen No.8
Lateral Load (kN)

300
250
200
150
100

Analytical
Experimental

50
0
0

10

20
30
40
Lateral displacement (mm)50(d) Specimen No.9
Figure 7: Comparison of experimental and analytical results
4. CORRELATION ANALYSIS OF RC BUILDING SUBJECTED TOTSUNAMI LOADSThe reinforced-concrete building which was the former office of Thai
Meteorological Department in Phang-Nga Province was tested as mentioned
in the previous section. The correlation analysis is conducted to understandthe behavior of the building and investigate the effect of masonry infill wall.
This building is a one-story reinforced-concrete building. The building planis illustrated in Figure 8. Figure 9 shows the positions of the masonry infill
walls. There is no masonry infill wall in the frame A. For the frame B, thereis the masonry in filled wall at the front span. For the frame C, there arewalls under window panels. The percentage of masonry infill walls is 21.8%
in the plane parallel to direction of tsunami flows. The compressive strengthof concrete obtained from in-situ coring was 12 MPa, and the yield strengthof reinforcement was 240 MPa. The span to depth ratio of the column is7.625. The axial load ratio is 0.128. The longitudinal reinforcement ratio
and volumetric ratio of transverse reinforcement are 0.0113 and 0.0038,
respectively. Due to the large shear span ratio, the column is governed by
the flexural failure. The analytical models validated in the previous section
are used in the correlation study. The building model is analyzed by using 3dimensional non-linear pushover analysis under force control as shown in
Figure 10. Six point loads consisting of three point loads at the roof level
and another three point load at the floor level are applied to the building at
the same locations as the field load test. These point loads representshydrodynamic forces acting on tributary areas. The fiber sections are used in
the plastic region at the end of beams and columns. The masonry wall is

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modeled as a diagonal springs. The ground and roof slabs are modeled as
rigid diaphragms.

(b) 1st and roof floor plan(a) Ground plan

Figure 8: Plan of the former office of Thai Meteorological Department(a) Frame A(b) Frame B(c) Frame C

Figure 9: The location of masonry infill wall of each frame
A

B

3
Rigid link

C
R

2
F

1

G

PRA

PRB

PRC

PFA

PFB

PFC

Figure 10: 3-dimensional model of the building
Correlation analysis of a reinforced-concrete building under tsunami loads and effect of masonry infill walls
Correlation analysis of a reinforced-concrete building under tsunami loads
in tsunami resistance737
and effect of masonry infill walls in tsunami resistanceOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

The lateral load and displacement relationships from the experimentand analysis are compared in Figure 11. The load is applied until the totalload reaches that in the experiment. It is seen that the analytical model cancapture the initial stiffness well however the lateral displacement from theanalysis is slightly larger. The masonry infill wall in the frame B reaches the
maximum resisting capacity. This result agreed well with the field load test
that cracks on the masonry infill wall in the frame B significantly widened
at the end of the test.
450
400
Shear Force (kN)

350
300
250
200
150
100
50
0
0

0.005

0.01
Displacement (m)

0.015

0.02

0.015

0.02

(a) Frame A
450
400
Shear Force (kN)

350
300
250
200
150
100
50
0
0

0.005

0.01
Displacement (m)(b) Frame B
450
400
Shear Force (kN)

350
300
250
200
150
100
50
0
0

0.005

0.01
Displacement (m)

0.015

0.02

(C) Frame C
Figure 11: The force and displacement relationship of building model
5. EFFECT OF MASONRY INFILL WALL ON TSUNAMIRESISTING CAPACITY
The effect of masonry infill wall is investigated by arranging patterns ofwalls. The building model is analyzed with the same load pattern as thefield load test. The names of each masonry infill wall are denoted as in

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Figure 12. A, B, and C denotes the infill wall in both front and back spans in
the frames A, B, and C, respectively.

A2

B2

C2

A1

B1

C1

Figure 12: Definition of masonry infill walls
Table 2: Results of rearranged masonry infill wallNo

Description

1
2
3
4
5
6

Without wall
A
B
A-C
A-B-C
A1-B1-C1

Percentage Max Loadof Infill Wall
(kN)
0.0
33.3
33.3
66.7
100.0
50.0

138.8
162.1
694.1
704.6
706.2
685.4

FailureAll Columns
Columns in Frame C
Shear in Short Columns
Shear in Short Columns
Shear in Short Columns
Shear in Short Columns

Latteral Resisting Force (kN)

800
700
600
500
400

Eccentric w/o frame B wall
Eccentric w/ frame B wall
Concentric
Existing building

300
200
100
0
0

20

40
60
80
Percentage of Masonry Infilled Wall

100

Figure 13: Relationship of lateral resisting force and percentage of infill
wall
Table 2 summarizes the cases and results from the analysis. Several
arrangement patterns of walls are considered and it is found that if there is
no wall in the building the load resistance of the building is limited to only
138 kN which is governed by flexural failure of columns. If walls areprovided in the frame A, torsional effect will result in the flexural failure ofcolumns in the frame C. The wall in the frame B will significantly increase
the lateral load capacity of the building to about 700 kN. If walls are
Correlation analysis of a reinforced-concrete building under tsunami loads and effect of masonry infill walls
Correlation analysis of a reinforced-concrete building under tsunami loads
in tsunami resistance759
and effect of masonry infill walls in tsunami resistanceOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

provided in all frames, the load resistance is about 700 kN which is limitedby shear failure of short columns. Figure 13 illustrates the relation of lateralload resisting capacity vs percentage of walls. It is obvious that providing
the wall in the frame B (33% of walls) is the most effective pattern to get alarge tsunami resisting capacity. The building is subjected to shear failure ofshort columns under the floor slab.
6. CONCLUSIONSThis research focuses on correlation analysis of a reinforced-concretebuilding with in-filled masonry walls under tsunami loading and the effectof masonry infill walls in a tsunami load resisting capacity. The study canbe concluded as follows:
1) The former office of Thai Meteorological Department located inPhang-Nga province is used for the 3-dimensional nonlinear
pushover analysis. Material models are selected and compared withtest results before applying to the building. Then the 3-dimensionalmodels are developed and subjected to the load pattern similar to thefield test. The good agreement is obtained between the test andanalysis.
2) It is found that masonry infill walls play a major role in the tsunami
load resisting capacity of the building. Hence the effect of infill
walls is investigated by varying the arrangement pattern to find theeffective pattern of walls. If there is no wall in the building the load
resistance of the building is limited to only 138 kN which isgoverned by flexural failure of columns. The wall in the middle
frame significantly increases the lateral load capacity of the building
to about 700 kN. If walls are provided in all frames, the load
resistance is about 700 kN which is limited by shear failure of shortcolumns. It is obvious that providing the wall in the middle frame is
the most effective pattern to get a large lateral load resisting capacity.
However, the building is subjected to shear failure of short columns
under the floor slab. Enhancement of the shear capacity of the shortcolumns will improve the performance of this building.
REFERENCES
Anil, O., and Altin, S., 2007. An experimental study on reinforced
concrete partially infilled frames. Engineering Structures, 29, 449-460.
FEMA 306., 1998. Evaluation of earthquake damaged concrete andmasonry wall buildings - Basic procedures manual. Federal Emergency
Management Agency, Washington, DC.
Hoshikuma, J., Kawashima, K., Nagaya, K., and Taylor, A. W., 1997.
Stress-strain model for confined reinforced concrete in bridge piers. Journalof the Structural Engineering, ASCE, 123(5), 624-633.
Kent, D. C., and Park, R., 1971. Flexural members with confinedconcrete. Journal of Structural Engineering, ASCE, 97(7), 1969-1990.

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Lukkunaprasit, P., Ruanrassamee, A., Stitmannaithum, B.,
Chintanapakdee, C., and Thanasisathit, N., 2010. Calibration of tsunami
loading on a damaged building, Journal of Earthquake and Tsunami, 4(2),105-114.
Mehrabi, A. B., Shing, P. B., Schuller, M. P., and Noland, J.L., 1996.
Experimental evaluation of masonry-infilled RC frames. Journal of
Structural Engineering, 122, 228-237.
Mostafaei, H., and Kabeyasawa, T., 2004. Effect of infill masonrywalls on the seismic response of reinforced concrete buildings subjected to
the 2003 Bam Earthquake strong motion: A case study of Bam telephone
center. Bulletin Earthquake Research Institute Univ. Tokyo, 79, 133-156.
Paulay, T., and Priestley, M. J. N., 1992. Seismic design of reinforced
concrete and masonry structures. John Wiley and Sons, Inc.
Ruangrassamee, A., Yanagisawa, H., Foytong, P., Lukkunaprasit, P.,
Koshimura, S., and Imamura, F., 2006. Investigation of tsunami-induced
damage and fragility of buildings in Thailand after the December 2004
Indian Ocean tsunami. Earthquake Spectra, 22, S377–S401.
Sezen, H., and Moehle, J. P., 2004. Shear strength model for lightly
reinforced concrete columns. Journal of Structural Engineering, ASCE. 130,
1692-1703.
Wehbe, N. I., Saiidi, M. S., and Sanders, D. H., 1999. Seismic
performance of rectangular bridge columns with moderate confinement. ACIStructural Journal, 96(S27), 248-259

Correlation analysis of a reinforced-concrete building under tsunami loads and effect of masonry infill walls
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Area suitability modeling for rice cultivationin Saraburi Province of Thailand
Bharambe K. P1., Tripathi N. K2 and A. R. Phalke3
1
Research Associate, RSGIS FoS, Asian Institute of Technology, Thailand
khagendra007@gmail.com
2
Coordinator, RSGIS FoS, Asian Institute of Technology, Thailand
3
Master Student School of Eng., RSGIS FoS, Asian Institute of Technology,
Thailand
ABSTRACT
Thailand is the rice bowl of rice in the world. It has the fifth-largest amountof land under rice cultivation in the world and is largest exporter of rice.
The world population is increasing at a higher rate which is affecting
environment and putting hard stress on available agricultural land forhuman settlement and food security.
Agricultural land is the most crucial factor that can enhance the possibility
for development of rice production. It is necessary first to assess the land
suitability for rice growing areas in order to develop a good land
management system. This study examines the area suitability classification
for rice production in Saraburi Province of Thailand. Relevant data in theform of different layers such as land use, soil pH, annual rainfall, stream
network, and slope at 1:250000 scale physical database formats were used
and analyzed. Suitability maps were generated applying the suitability
criteria for all the respective parameters. Final suitability map was
obtained by multi-criteria analysis using Analytical Hierarchy Process(AHP).
The outcomes of the study showed that only 21.21 percent land had beenfound to be highly suitable for rice cultivation under all suitability criteria.
Around 21 percent land from remaining land obtained was found to bemoderately suitable where further possibility of conversion exist byadopting some irrigation and management practices. Rest of the areas has
under gone in marginally suitable land and least or not suitable land forrice cultivation in Saraburi Province of Thailand.
Keywords: Agricultural land, Land suitability, Rice cultivation, AHP,
Saraburi
1. INTRODUCTION
Rice is one of the most important crops of Thailand as Thailand is the major
exporter of rice in the world. To meet the increasing demand for domestic
consumption and to maintain the position in export it is required to bring the791

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

more suitable areas under rice cultivation. Rice is a high water consuming
crop. Rice production varies from area to area due to different topographic
conditions, soil conditions, weather conditions and agricultural practices
within a target-area. Generally in plain region rice production is higher
because of high probability of getting more water than hilly region.
Rice is the economic crop and the significant expert product ofThailand. Farmer can grow rice in every region, particularly the cultivation
are in the central plain. The rice cultivation areas and the rice product havebeen changed and declined regarding the development and changes of land
use from paddy fields to the industrial areas, urban areas, mines and others.
From the statistical report of agriculture of Thailand found that the ricecultivation areas of the country have been declined from past to the present.
The agricultural areas and rice cultivation are limited in some areas, whichlead to the increasing of the invasion for cultivated areas in the forest.
Furthermore, there are non suited land use, regarding the rice cultivation, forother forms, which cause the extravagant expensed for land development insome areas and lead to the high demand of chemical fertilizer for theincreasing productivity.
Four seasons were recognized in Thailand: the southwest monsoon
from May to September; a transition period from the southwest to thenortheast monsoon during October; the cool, dry northeast monsoon from
November to February; and a pre-monsoon hot, dry season from March to
April.
Table 1.1: Rice production seasons in Thailand
Production seasons

Planting

Harvesting

North and Central,
Major season
North and Central,
Minor season
South, major season

May-July

Nov-Dec

Dec-Jan

May-Jun

Sep-Nov

Mar-MaySouth, minor season

Apr-May

Aug-Sep(Source:-IRRI, 2009)

During the wet season, rice was planted nearly everywhere across thecentral region which covered 21% of the country’s total cultivated rice landand produced 30% of the total rice. About 450,000 ha of land in the central
region were planted to irrigate dry-season rice.
The various climatic events such as more intense and more frequent
droughts, cyclones, flood and heat waves caused incalculable threats oncrop production. Crop yield is a function of numerous factors. Most
important factors for rice production are favorable temperature, a constant
supply of water for irrigation and suitable soils. Apart from the management
and cultural practices yield determination factors could be broadly
categorized in to three types, as crop factors, climatic factors and soil factors

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ICUS Report 56(Stansel,1980)
he revealed
thatgrowthcrop growththeareyield
are highly(Stansel,1980) andhe andrevealed
that cropand theandyield
highlysensitive
toclimaticchanges.
Temperaturechangesmodifygrowingsensitive to climatic changes. Temperature changes modify growing season season
constraints
and influenceplant development.
A difference
constraints
and influence
the ratetheof rateplantofdevelopment.
A differenceof one of one
centigradeinmean
temperature
could
resultinachangeof117
to 25indays incentigrade in mean temperature could result in a change of 117 to 25 days
effective
And finally
had estimatedrice production
effective
growinggrowing
season.season.
And finallyhe had heestimatedthat ricethat
production
could
be decreased
the combination
a 2 Celsius
temperature
could bedecreased
19% by19%
the bycombinationof a 2 ofCelsiustemperature
reduction
and15% precipitation
reduction(Stansel,
reductionand 15%precipitation
reduction(Stansel,1980). 1980).
As mentioned
above several
are affecting
ultimately
As mentioned
above several
climaticclimatic
events events
are affecting
ultimately
crop production
onlyto due
to changes
land
on croponproduction
which whichcaused caused
only duechangesin landinuse
anduse andvariables.
climaticclimatic
variables.
had ofdone
arealand)(or suitabilityland) suitability
for crop
SeveralSeveral
studies studies
had done
areaof (orfor crop
production
under different
conditions
is affecting
production
under different
variablevariable
natural natural
conditions
which whichis affecting
different
mentionedaremainly mainly
different
natural natural
hazardshazards
mentioned
above. above.
FactorsFactors
which whichareforcultivation
rice cultivationvary placefrom toplace
to place.
suitablesuitable
for ricevary fromplace.
Tyagi Tyagi(2003) (2003)
categorized
suitabilityof physicalrice cultivation
in Southern
categorized
suitabilityof physicalfactors factors
for riceforcultivation
in Southern
Goa,and
India
and Ratanakhom
et al, categorized
suitability
rice cultivation
Goa, India
Ratanakhom
et al, categorized
suitability
for ricefor
cultivationin Chinagmai
Province,
Thailandinto
four categories
as follows
in Chinagmai
Province,
Thailandinto four
categories
as follows
Table
1.2: Criteria
and ofratingland qualities
for inpaddy
in southern
Table 1.2:
Criteria
and rating
landofqualities
for paddy
southern
Goa, Goa,
India
India

Suitability
Suitability
Class ClassLand
Highly Suitable
Moderately Marginally
Marginally
Not Suitable
Land
Highly Suitable
Moderately
Not Suitable
Quality Quality
SuitableSuitable
SuitableSuitable
Clay, clay,
Silty Sandy
clay, Sandy
clay, Loamy
silty sandLoamy sandandTexture TextureClay, Silty
clay, silty
Sandy Sandy andclay loam.
loam, clay
sandy clay
fragmental
Silty claySilty
loam.
loam, sandy
fragmental
loam loam
loam loam
Imperfectly
anddrained
Well drained Excessively
Excessively
Excessively
andDrainageDrainage
Imperfectly
and Well
Excessively
andmoderately
wellverypoorly poorly
moderately
welldrained drained verydrained drained
drained drained
Soil depth
to very Moderately
deep Moderately
deep
Very shallow
Soil depth
Deepy toDeepy
very deep
deep
Shallow Shallow Very shallow
Gravelliness/
Low
Very highGravelliness/
Low
ModerateModerate
High HighVery highStoninessStoniness
Low
Inherent InherentHigh High
MediumMedium
Low
Very lowVery low
fertility fertility
Subnormal ConcaveConcave Excessive
Excessive
Relief Relief Normal Normal
Subnormal
Slope
Nearly
level
to
very
Gentlyslopping
Undulating
Moderate
Slope
Nearly level to very Gently slopping
Undulating
Moderate to very to very
gently sloping
gently sloping
steep steep
Erosion ErosionNone to Noneslight to slight ModerateModerate
hazards hazards
Risk
Risk
of Lowof Low
ModerateModerate
floodingflooding

Very severe
Severe Severe Very severeHigh

Area suitability
suitability
modeling
rice
inProvince
ofofThailand
Area suitability
modeling
for rice forcultivationin Saraburi
Provinceof Thailand
Area
modeling
forrice cultivation
cultivation
inSaraburi
SaraburiProvince
ThailandHigh

Very highVery high3813

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table 1.3: Criteria and rating of land qualities for paddy in Chiangmai,
ThailandCrop Requirement

Factor Rating

Land Quality

Unit

Highly Suitable

Moderately
Suitable

Marginally
Suitable

Not
Suitable

AverageRainfall

mm

>1500

1100-1500

500-1000

500

Nutrient
Availability
Index(NAI)
-N

%

>0.2

0.1-0.2

<0.1

-

-P

ppm

>25

10-25

<10

-

-K

ppm

>60

30-60

<30

-

-pH

-

5.6-7.3

7.4-7.8

7.9-8.4>8.4

5.1-5.5

4.0-5.0<4.0

Soil Depth

-

>50

25-50

15-25

<15

Drainage

-

1,2,3

4

5

6

Slope

-

0-2

2-5

>5

This project has studied the land evaluation of rice cultivation inSaraburi province in order to plan for the uses the use of rice cultivation inSaraburi province to be suitable. The use of Geographic Information System(GIS) can be managed and analyzed with the data based in the form of map,
all of which are the basic information for planning. The ability of data
access and improving descriptions can be studied for the suitability for thephysical characteristics and the general uses at present so that there can beplanning for the sustainable rice cultivation. The results of the study will be
useful for planning the rice planting area in Saraburi province.
The main objective of this exercise is to develop a GIS based model
for land suitability assessment for rice production in Saraburi province.
However, specific objectives are to classify the area in terms of land
suitability for rice cultivation and to prepare the model for favorable land
for good yield of rice for Saraburi Province of Thailand.
1.2 Study Area
Geographically Thailand has four regions: Central Thailand(Including Bangkok), Southern Thailand, Northern Thailand, Northeastern
Thailand. Saraburi is located in central part of the Thailand east side of the
Chao Phraya river valley. The co-ordinates of the study area is ........N
latitude and .......E to .......E longitude. Saraburi Province is covering
approximately 357650 ha Administratively Saraburi is divided into 13
districts (amphoe), 111 communes (tambon) and 965 villages (muban).

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Figure1 - Map of Central Thailand and Saraburi province
2. MATERIALS AND METHODOLOGY
Required data such as land use data, soil pH, soil texture, slope,
rainfall, water body had been gathered from Remote Sensing andGeoinformatic Department of Asian Institute of Technology, Thailand.
2.1 Methodology
Overall process involved in GIS- based area suitability assessment forrice cultivation in Saraburi province can be divided into four major steps:
data acquisition, data manipulation, data analysis, and output generation.
Figure 2.1 is explains the overall methodology for area suitability modelingfor rice cultivation.

Area suitability
suitability modelingArea
modeling forfor rice
rice cultivation
cultivationin
inSaraburi
SaraburiProvince
ProvinceofofThailand
Thailand835

October
2011,
Chiang
Mai,Thailand
Thailand
October
2011,
Chiangmai,
Chiangmai,
Thailand

Data
Acquisition
Data
Acquisition

Data
UpdateData
UpdateGISGIS
Database
Database

Data
Extraction
Data
Extraction

Area
andand
Area
Slope
Slope

Area
andand Area
andand Area
andand Area
andand
Rice
Area
Area
Area
Area
Rice Water
Water
Land
useuse Rainfall
pHpH Production
Availability
Land
Rainfall SoilSoil
Production
Availability

GISGIS
datadata
manipulation
andandAnalysismanipulation
Analysis
(ARC
VIEW)
(ARC
VIEW)

Reclassification,
WeightingandandReclassification,
Weighting
Score
Score

Generationof Map(Suitability
areaarea
Generationof Map(Suitability
for for
Rice
Production)
Rice
Production)

Final
ReportFinal
ReportFigureFigure2.1:2.1:
Flowchart
Flowchart
for forArea
Area
Suitability
Suitability
Modeling
Modeling
for for
Rice
Rice
Cultivation
Cultivation
Relevant
Relevant
datadata
waswasobtained
obtainedfromfrom
ThailandThailandGISGIS
database
databaseprovidedprovidedby byRemoteRemoteSensing
Sensing
andandGeographic
Geographic
Information
Information
SystemSystem
Department
Departmentof Asianof Asian
Institute
Instituteof ofTechnology
Technology
which
which
waswasin in
1:250,000
1:250,000
scale
scale
physical
physicaldatabase
database
format.
format.
Required
Required
process
process
waswas
done
done
by by
using
using
GISGIS
softwaresoftware
ArcArcView
View
v. 3.2a.
v. 3.2a.
TheTheareaareaof Saraburiof Saraburiprovince
province
waswasseparated
separatedfromfromthethemapmapof theof thecentralcentralregionregionof Thailandof Thailand
as shown
as shown
in figurein figure
1. Various
1. Various
processes
processes
likelike
table
table
joining,joining,
extracting
extracting
required
requiredfeaturesfeaturesfromfromdatadata
layerslayershashas
been
been
done
done
with
with
thethehelphelpof ofdifferent
different
tools
tools
in arcin arcview.
view.
Similarly
Similarly
thethelandlanduse,use,soilsoil
pH,pH,
streamstreamnetwork,
network,annualannualrainfallrainfallandandricerice
production
production
themesthemeswere
wereclippedclippedandandstoredstoredfor forSaraburi
Saraburiin ainseparate
a separate
database
databasecreatedcreatedfor forthisthisproject.
project.
These
These
shape
shape
filesfiles
were
were
thenthenconvertedconverted
to to

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grid for classification as per the required parameter out of all theinformation given for that class in the database. Then these grid files werereclassified into four categories defining the following suitability criteria as
mentioned in the table.
Table 2.1: Ranking criteria and weighing criteria for various suitability
factors
Factors

Weight1

HighlySuitable(S1=6)
Paddy
Fields0-500

Suitability
Moderately Marginally
Suitable
Suitable(S2=3)(S3=1)
Agriculture Forest andlandgrass cover
501-1000
1001-1500

Land use

1

Distance from Stream(m)Annual rainfall (mm)
Soil pH
Slope
Rice production(kg/household)

1
1
1
1

>1800
6.0-8.00 – 7%>3000

1200-1800
5.5-7.0
8 – 15%
2000-3000

900-1200
4.5-5.5
16 – 24%
1000-2000

Not suitable(N=0)
Urban andIndustrial
>1500
<900
4.0-5.0>25%<1000

After giving the suitability criteria as per the level three in AHP,
following suitability maps of each factor were obtained.
3. RESULTS AND DISCUSSIONSExisting data layers of Saraburi province was categorized into many
categories which were reclassified into four main categories. These
categories were then ranked and weigh, as per their suitability ricecultivation assigned to them are presented in table 2.1
Paddy field was assumed to be most suitable for rice cultivation with all
requirements needs for growing whereas water body and urban considered
as not suitable for rice cultivation as shown in the table 3.1
Table 3.1: Suitability criteria for Land use

Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

Suitability Criteria[Plu_e] = “Paddy Field”[Plu_e] = “Agriculture Field”[Plu_e] = “Forest”[Plu_e] = “Miscelleneous”[Plu_e] = “Urban area”

Weight6
3
1
0

Suitability
S1
S2
S3
N

The Soil pH theme had been grouped in to different range startingfrom 4.0–8.0 which was then reclassified into four groups as shown infigure 3.2. The suitability criteria and weights assigned to them arepresented in table 3.2. The areas with pH in the range of 6.0-8.0 wereconsidered as most suitable and the areas with pH 4.0-5.5 were considered
as unsuitable.

Area suitability
suitability modelingArea
modeling forfor rice
rice cultivation
cultivationin
inSaraburi
SaraburiProvince
ProvinceofofThailand
Thailand857

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table 3.2: Suitability criteria for soil pH

Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

Suitability Criteria[pH_upper] = “6.0-8.0”[pH_upper] = “5.5-7.0”[pH_upper] = “4.5-5.5”[pH_upper] = “4.0-5.0”

Weight6
3
1
0

Suitability
S1
S2
S3
N

Figure 3.2: Soil pH of Saraburi Province

Figure 3.1: Land Use map of Saraburi

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The land slope was provided in to four groups starting from <7% to>24% which was then analyzed as shown in figure 3.3. The suitability
criteria and weights assigned to them are presented in table 3.3. The areas
with slope less than 7% were considered as most suitable and the areas withslope more than 24% were considered as unsuitable.
Table 3.3: Suitability criteria for land slope

Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

Suitability Criteria[Slope] < 7%
[Slope] > 7 and <=16%[Slope] >16 and <=24%[Slope] >24%

Weight6
3
1
0

Suitability
S1
S2
S3
N

The information about various types of streams located in Saraburi
was provided. To analyze the suitability the buffer distance around thestreams created using “Create Buffer” feature of Arc View. The area within
the range of 500 m around the stream was considered as most suitable while
the area which is farther than 1500 m was considered as unsuitable. The
suitability assessment of the area is as presented in table 3.4.
Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

Table 3.4: Suitability criteria on Stream
Suitability Criteria[BuffDis] <= 500[BuffDis] > 500 and <=1000[BuffDis] > 1000 and <=1500[BuffDis] > 1500

Weight6
3
1
0

Suitability
S1
S2
S3
N

Figure 3.3: Land slope in Saraburi

Area suitability
suitability modelingArea
modeling forfor rice
rice cultivation
cultivationin
inSaraburi
SaraburiProvince
ProvinceofofThailand
Thailand879

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 3.4: Streams of Saraburi with buffers
Annual rainfall data of Saraburi was re-categorized into four levels asshown in Figure 3.5 Since rice crop consumes lot of water so the areas
having high rainfall i.e. more than 1800 mm per annum were considered as
most suitable while the areas receiving less than 900 mm were consideredunsuitable for rice production. The suitability assessment is as presented intable 3.5.
Table 3.5: Suitability criteria for Rainfall

Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

Suitability Criteria[Annual] > 1800
[Annual] > 1200 and <=1800[Annual] >900 and <=1200[Annual] < 900

Weight6
3
1
0

Suitability
S1
S2
S3
N

The rice production data was provided in terms of kg per household. It
was reclassified into four groups as shown in figure 3.6. The areas
producing more than 3000 kg per household were considered as mostsuitable and the areas producing less than 1000 kg per household wereconsidered as unsuitable. The suitability assessment is as present in table 3.6.
Table 3.6: Suitability criteria on Rice Production

Suitability Class
Highly Suitable
Moderately Suitable
Marginally Suitable
Not Suitable

1088

Suitability Criteria[Rice_production] > 3000
[Rice_production] > 3000 and <= 2000
[Rice_production] > 2000 and <= 1000
[Rice_production] < 1000

Weight6
3
1
0

Suitability
S1
S2
S3
N

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Figure 3.5: Rainfall of Saraburi Province

Figure 3.6: Rice production of Saraburi
The following criteria were used to carry out the final land suitability
assessment for rice production with considering all the parameters
mentioned above
Land suitability = land use + slope + soil pH + stream buffer + rainfall+ rice production

Area suitability
suitability modelingArea
modeling forfor rice
rice cultivation
cultivationin
inSaraburi
SaraburiProvince
ProvinceofofThailand
Thailand1189

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 3.7: Final Land Suitability map and area in KM2 as per theirsuitability for ricecultivation
It was found that the area under highly suitable, moderately suitable,
marginally suitable and not suitable derived as about 747 km2 (21%), 738
km2 (20%), 589 km2 (17%) and 1448 km2 (41%) respectively.
CONCLUSIONSLand suitability map showed that southern and western parts of theprovince are suitable for rice cultivation because the geography of theseareas and high fertile soil suited for rice cultivation. On the other hand, northeast part of the province is cover by high plains, high slope and nationalparks, thus this area is classified as not suitable for rice cultivation because
rice cannot grow on high plains.
Management practices such as irrigation development, fertilizer
application are the crucial parameters which can change marginally suitablearea to moderately suitable and moderately suitable to highly suitable area.
However, irrigation development is an important issue to rice cultivation in
the future due to huge requirement of water for rice cultivation.
REFERENCES
De Datta, S. K. (1981). In J. W. Sons, Principles and practices of riceproduction. Canada.
Mikkelsen et al. (1980).,"Rice Culture". In Rice-Production andUtilization. pp. 103-186. Edited by Bor. S. Luh. U.S.A.: Van Nostrand
Reinhold.
Perera, L.K., Kajiwara, K. and Tateishi, K. (2007). Land Suitability
Assessment by GIS for Paddy Cultivation in Sri Lanka. With a concern on
environmental conservation. Remote Sensing and Image Research Center,
Chiba University, Yayoi-Cho, 1-33. Inage-Ku, Chiba Ciiy 263, JAPAN.

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Ratanakhom, Ravi, Ruamkaew, Siriwan, Nongbundit and Sarawut(2008). Land Evaluation for rice in Chiangmai Province.
http://geoinformatics.sut.ac.th/sut Retrieved on 10 November 2010.
Saaty, T. L. (1980). The Analytic Hierarchy Process. New York:
McGraw-Hill.
Saraburi Province. http://en.wikipedia.org/wiki/Saraburi_Province.
Retrieved on 18November 2010.
Stansel, J. (1980). Impact of world weather changes on riceproduction, Proceeding of a symposium on the agrometeorology of the ricecrop. International Rice Research Institute.
Thus-songchun, Akarawuth (1983)., Rice Story. Kasetsart University.
Tyagi, S. (2003). Agricultural land use planning using remote sensing
techniques in part of south Goa (India)

Area suitability
suitability modelingArea
modeling forfor rice
rice cultivation
cultivationin
inSaraburi
SaraburiProvince
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Thailand13
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Bridge deck condition assessment
by ground penetrating radar -A case study
in Bangladesh
Bushra ISLAM1, Raquib AHSAN2 and Mehedi Ahmed ANSARY2
1
Research Assistant, JMBSIP, BUET
2
Professor, Department of Civil Engg., BUET, Dhaka, Bangladesh
ansary@ce.buet.ac.bd
ABSTRACT
Bridge condition assessment is necessary to evaluate the serviceability andsafety of the existing bridge structures. At present a significant number ofbridges are functioning in Bangladesh at poor state and require proper
maintenance. The bridges which are functioning properly also need regularmonitoring. In this study the current condition of an existing bridge deck
was evaluated by non-destructive test method using Ground Penetrating
Radar (GPR) with high frequency (1.6 GHz) ground coupled antenna.
Bridge deterioration mapping and reinforcement layout of bridge deck were
produced from the collected data. This information will facilitate effective
decision making regarding future maintenance of the bridge.
Keywords: Ground Penetrating Radar, bridge deck assessment,
deterioration mapping, reinforcement corrosion, concrete degradation
1. INTRODUCTION
In Bangladesh both roads and waterways provides support as major meansof travel due to its location on an alluvial plain formed by large rivers. In
case of roadways, one of the factors that have essentially influenced theexisting transportation system is the presence of large rivers in this country.
As a result of the numerous rivers and regular flooding in rural areas mostroads are built on embankments with a large number of bridges, culverts andferries. Approximately over ten thousand bridges and culverts are present inthis country. Regular assessment of these bridges is necessary to takeappropriate measures for maintenance work and keep them functioning
properly for a smooth traffic flow.
The conventional bridge deck evaluation requires time and destructive
operations like removal of asphalt layers to acquire feedback regarding thebridge deck condition and accuracy of the collected data mostly depends on
the performance and experience of the operator. On the other hand Ground
Penetrating Radar (GPR) provides an easier operation and reliable dataacquisition resulting into an accurate assessment of the deck condition. It isan established electromagnetic evaluation technique used in diverse area of931

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

applications including concrete structure inspection, utility detection, roadquality assessment or quality control, bridge deck evaluation, geological andarcheological investigation, forensic research and military applications. A
recognized application of GPR is the accurate condition assessment ofbridge decks as well as other reinforced concrete structures (Parrillo et. al,
2005; Romero et. al, 2000; Romero, 2003; Schongar, 2004). The conditionof a bridge deck can be assessed with higher degree of accuracy with highfrequency (1.6 GHz) ground-coupled antenna. It is effective in indentifying
rebar location by using reflections from reinforcement. From this reflection
it is also possible to produce deterioration maps presenting the condition ofbridge deck. The GSSI’s instrument setup for Bridgescan consists of a SIR3000 portable GPR data collection system with 1.6 GHz ground-coupledantenna which allows maximum 18 inches depth of penetration in concrete.
A 3 wheeled curt and a small hand cart is available to carry the antenna for
application.
In this study, the second Buriganga Bridge was inspected using theBridgeScan GPR system on April 28th, 2011 to evaluate the condition of theexisting bridge deck. The bridge is located in Dhaka and also known as
Babubajar Bridge. It is a Reinforce Concrete Deck Girder bridge with total
11 girders, constructed in early 1980. The bridge deck is asphalt overlaid.
Current condition of bridge deck and the location of bridge are shown in
Figure 1 and Figure 2 respectively.

Buriganga Bridge No.

Figure1: Location of bridge

2
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Figure 2: Bridge Deck
2. DATA ACQUISITION AND PROCESSING
2.1 Data Collection
In the present study GPR data was collected to attain rebar layout andbridge deck condition assessment. At first to identify the orientation of top
layer reinforcement sample GPR data was collected in both directions andthen the arrival time of rebar reflection was compared. It was found that therebar in transverse direction reflect wave in less time than in longitudinal
direction. So it was confirmed that the top layer reinforcement is intransverse direction. Thus the data for deterioration assessment wascollected in the perpendicular direction which is along the longitudinal
direction or along the traffic movement.
Since the overall condition of the location was not in favor ofcollecting data of the whole bridge, only data was collected along two
profile lines each 50 ft long, in the mid span of bridge deck. Also the data
was collected by preparing a 10ft X 10ft grid near the curb of bridge withgrid spacing of 1 ft. Data collection using GPR is shown in Figure 3.

Figure 3: GPR data collection
Bridge deck
Bridgedeck condition
condition assessment
assessment by
by groundground penetrating
penetratingradar-A
radar -Acasecasestudy
studyininBangladesh
Bangladesh953

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Reinforcements are observed in GPR as form of hyperbolas. The
theory of detecting reinforcement is related to its energy transmission andreceiving principle. The reflection pattern will vary in case of deterioration.
Weak reflection is an indication of bridge deck deterioration. Thisattenuation of wave signal may occur due to concrete degradation,
reinforcement corrosion or other reasons. Unprocessed GPR data is shownin Figure 4. From this data weaker signal reflection can be observed whichis indicating the presence of deterioration. Also the bottom of asphalt layer
can be identified from the observation of the reflection pattern. The asphalt
bottom and rebar reflections have been shown in Figure 4.

Figure 4: Unprocessed GPR data
2.2 Data Processing
After the data collection all the unprocessed data files were transferredfrom SIR-3000 to computer and processing operations were performed
using Bridge Assessment Module of RADAN. The processing steps include
time-zero correction, migration, rebar reflection mapping and interactive
interpretation. Finally from this processed data, using a plotting software
contour map presenting deterioration can be produced.
2.2.1 Time-Zero correction
At first time-zero correction was applied to the unprocessed data to
shift all data scans so that the offset is removed and the top of the scans startfrom the beginning of the deck surface.
2.2.2 Migration
During data collection process hyperbolic diffraction occurs for
specific rebar location. Migration which is a hyperbolic summation process
is performed to collapse these diffractions in the point of rebar location. The
processed GPR data and 3D view of reinforcement layout is shown in
Figure 5 and Figure 6 respectively.

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FigureFigure5: 5:Processed
Processed
GPR
GPR
data
data

FigureFigure
6: 6:
3D3D
view
view
of of
Reinforcement
Reinforcement
LayoutLayout
2.2.3
2.2.3
Rebar
Rebar
Reflection
Reflection
Mapping
Mapping
The
The
optionoptionavailable
available
in in
BridgeBridgeAssessment
Assessment
ModuleModuleforfordeterioration
deterioration
mapping
mapping
locates
locates
allallrebar
rebar
reflections
reflections
andandamplitudes
amplitudes
andand
save
save
these
these
data
data
into
into
an an
ASCII
ASCII
comma-separated
comma-separated
value
value
(CSV)
(CSV)
file.
file.
2.2.4
2.2.4
Interactive
Interactive
Interpretation
Interpretation
If Ifthethebridgebridgeis isdeteriorated
deteriorated
andandreflections
reflections
areare
weak
weak
then
then
thetherebar
rebar
reflection
reflection
peaks
peaks
in in
thatthatlocationslocations
need
need
to to
be be
edited.
edited.
In In
FigureFigure
7 the
7 the
rebar
rebar
reflections
reflections
locatedlocatedin ininteractive
interactive
interpretationinterpretation
process
process
areare
shown
shown
byby
yellowyellow
circlescirclesonon
thethetoptop
data
data
pane.
pane.
In In
thethebottombottom
data
data
pane
pane
thetherebar
rebar
locationslocationscancanbe beseen
seenwith
withvarying
varyingslab
slabthickness.
thickness.It Itcancanbe beseen
seenthatthatthethetoptoplayer
layer
reinforcement
reinforcement
is locatedis locatedapproximately
approximately
at 40
at 40
to to
6060
mm
mm
depth.
depth.

BridgeBridgedeck
deck
condition
conditionassessment
assessment
by bygroundpenetrating
penetratingradar-A
radar-A
study
study
in Bangladesh
ininBangladesh
Bridgedeck
conditionassessment
by groundgroundpenetratingradarcase-Acasecase
study
Bangladesh

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Mai,Thailand
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Chiangmai,

Figure 7: Interactive interpretation process
2.3 Deterioration Mapping
To prepare the deterioration mapping, rebar location X, Y, andreflection amplitude data were imported from the saved ASCII file. Then
using a contour mapping tool DPLOT, a color-coded contour map of thebridge deck deterioration was produced. Lower amplitude value
representing weaker rebar reflections were presented with reddish colors toindicate the areas of the bridge deck suspected to be more deteriorated. The
deterioration map prepared for the inspected part of bridge deck is presented
in Figure 8.

Figure 8: Deterioration map

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3. CONCLUSION
In the deterioration map a higher deterioration compared to other places ofdeck can be observed from the weaker rebar reflections indicated by thereddish colors in Figure 8, which is in a portion near the curb. Different
reasons may lie behind this deterioration. Some of these factors might beconcrete degradation, corrosion of the reinforcement due to penetration ofwater, which will attenuate the radar signal. One important factor in case ofinterpretation is to understand that it is not possible to identify the amount ofdeterioration quantitatively only by observing color contour. It is aqualitative measure only.
The whole process of bridge quality assessment using Ground
Penetrating Radar (GPR) is performed in a non-destructive manner withconsiderable accuracy which is the most important advantage of theevaluation process. The aim of the present study was to evaluate present
deck condition of the Second Buriganga Bridge by Ground Penetrating
Radar (GPR). No destructive phenomena were required during the entire
performance and the whole data collection and processing steps were done
approximately within two hours with a savings of huge amount of time.
Moreover due to the benefits of getting deterioration information without
any opening up of the deck, this GPR data can be used to locate the places
which require repair and maintenance in an economical and effective
manner. It is also possible to determine the appropriate repair methodology
by observing the deterioration condition. So deterioration map developed inthis study using GPR data can be used to locate deteriorated places in theexisting deck and proper measures can be taken for condition improvement
accordingly.
REFERENCES
Parrillo, R., Roberts, R.L., and Haggan, A., 2005, Bridge Deck
Condition Assessment Using Ground Penetrating Radar, International
Bridge Conference, June 13-15, 2005, Pittsburgh, PA.
Romero, F.A., Roberts, G.E., and Roberts, R.L., 2000, Evaluation of
GPR bridge deck survey results used for delineation ofremoval/maintenance quantity boundaries on asphalt-overlaid, reinforced
concrete deck, Structural Material Technology IV, February 28-March 3,
2000, Technomic Publishing Co, p. 23-30.
Romero, F.A., 2003, New York State Department of Transportation
Ground Penetrating Radar Demonstration on Route 378 Bridge over D&H
Railroad and Route 66 Bridge over Kinderhook Creek.
Schongar, G., 2004, GPR Demonstration Project on Two Steel
Reinforced Concrete Bridge Decks, Client Report 87, Transportation
Research and Development Bureau, NYSDOT, 27 p

Bridge deck
Bridgedeck condition
condition assessment
assessment by
by groundground penetrating
penetratingradar-A
radar -Acasecasestudy
studyininBangladesh
Bangladesh997

October 2011, Chiang Mai, Thailand

100

New Technologies for Urban Safety of Mega Cities in Asia

Urban high speed rail link tunnel projects(GTX) in Korea
Chang-Yong Kim1, Seong-Won Lee1, Ho-Geun Kim1
1
Korea Institute of Construction Technology,
Daehwa-dong 283, Goyangdae-ro, Ilsanseo-gu, Goyang-si,
Gyeonggi-do, 411-712, Korea
cykim@kict.re.kr

ABSTRACT
Urban high speed rail link tunnel projects, namely GTX(Great Train
Express), is suggested by Gyeonggi-province and Ministry of Construction,
Transportation and Marine time Affairs by this year and start the design byseveral consortium in Korea. Basically, this project has four lanes withalmost 150km long. West-Center line and South-Center line and NorthCenter line and Southwest-Centerline are planned. And almost below 40m,
the tunnel is located, so deep construction will be needed. Average speed of
the rail is designed by 100 km/h, and the maximum speed reach 200km/h.
Normally, Seoul Subway average speed is about 30km/h. The GTX has very
fast connections in between Seoul and other satellite cities, namely Great
Mega City. Basically, this kind of mega project has a precedent project suchas Seoul Metropolitan Subway projects, but, Seoul metro experiences very
shallow tunnel and low speed rail. So there need new approaches for thehigh speed rail link and deep tunnel conditions.
This kind of project is for the first time in the world, but we have theexperiences in Subway construction.
In this paper, the concept of underground transportation infrastructures
specially in high speed rail link tunnels that is suitable for Korean
circumstances was established and the core base technologies to constructeconomical and safe underground space was deduced to consider practicaluse in the future.
In this paper, we emphasis on the needs of consideration of the technicalrequirements of this kind of projects in high speed rail link and deep urban
tunnel conditions
In this paper, we will present the detailed plan of this project and thetechnical weakness and challenging factors are also discussed.
Keywords: High speed rail link tunnel, GTX (Great Train Express), Great
depth tunnel

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1. INTRODUCTION
Urban high speed rail link tunnel projects, namely GTX(Great Train
Express), is suggested by Gyeonggi-province and Ministry of Construction,
Transportation and Marine time Affairs by this year and start the design byseveral consortium in Korea. Basically, this project has four lanes withalmost 150km long. West-Center line and South-Center line and NorthCenter line and Southwest-Centerline are planned. And almost below 40m,
the tunnel is located, so deep construction will be needed. Average speed of
the rail is designed by 100 km/h, and the maximum speed reach 200km/h.
Normally, Seoul Subway average speed is about 30km/h. The GTX has very
fast connections in between Seoul and other satellite cities, namely Great
Mega City. Basically, this kind of mega project has a precedent project suchas Seoul Metropolitan Subway projects, but, Seoul metro experiences very
shallow tunnel and low speed rail. So there need new approaches for thehigh speed rail link and deep tunnel conditions.
‘G’ in GTX, the acronym of ‘Great Train eXpress’, ambiguously
refers to the meanings of ‘Great, Green, Global and Governance’, so themetropolitan train express contains a meaning of Gyeonggi-do’s traffic
alternative to solve the Seoul area’s traffic problems, to minimize theenvironment pollution and to enhance the Seoul area’s competitiveness.
The land owners can straighten the lines and build the rail
infrastructure to make the running time reduced through using the space of
40m underground which is not usually used. It makes reach the Seoul
downtown at 2-3 times quickly compared to any road traffic, so it can build
the network of 30-minute living zone from Seoul area to Seoul downtown.

Figure 1. Usage of GTX at the underground of 40m or more

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Its scheduled speed, the average passage speed considering stoppage
time, was designed as over 100km/h. The scheduled speed of the existing
metropolitan rails was about 30-50km/h, but it’s expected to be improved
through minimizing the number of stations (the required maintenance ofinterval among stations), arranging the time of getting quickly on and off
and building the high-speed rails (Table 1).
Table 1. Characteristics of the GTX
SectionCharacteristics

Hierarchical characteristics

Absorption of long-distance wide area traffic
The influential area and running speed remaining at
middle level of the existing metropolitan rails andgeneral/high-speed rail

Operation characteristics

Reduced passage time up to 30 minutes among key
points
The scheduled speed over 100km/h at least
Running time interval less than 10 minutes
Quick getting on and off, sufficient capacity secured

Route characteristics

The maintenance of the distance between stations of atleast 10km at Seoul’s neighbored areas
Selection of station at the points available for theuse/construction of linkage traffic modes

2. NECESSITY
While the living zones are expanded and the metropolitan traffic zones areextended thanks to the quick growth of Seoul area and the development of
new towns, the total passengers and long-distance passage at the Seoul areas
are gradually increasing. As a result, the traffic at the major roads in Seoul
areas and the flow-in and –out roads at the Seoul boundary is continuously
increasing, but because of deficient traffic infrastructure, the traffic
congestion is emerging as one of the key social problems in Seoul areas(Korea Traffic Academy, 2009).
The traffic between Gyeonggi-do and Seoul is continuously
increasing; mostly the over-30km long-distance flow-in and –out passage at
Seoul boundary. The commuting traffic into Seoul increased by 14%;especially, increased by 37% in 2006 from 2002. Accordingly, the traffic
speed among Seoul areas has been reduced. The average commuting time isaround 43 minutes; longer compared to the other developed nations.
The facility investment has been continuously conducted throughestablishing the measures to improve the metropolitan traffic in order tomitigate the increased traffic and travel time caused by the expansion of
metropolitan traffic zones, but the measures promoted based on road traffic
is resulting in new traffic congestion.

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linkrailtunnel(GTX) in
Korea
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in Korea1033

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It’s needed to introduce a new-concept metropolitan traffic mode forthe environment-friendly, energy-efficient metropolitan traffic in order topromote the sustainable development and green growth. In terms of traffic,
the concept means the introduction of high-speed public traffic mode forcommon persons’ metropolitan passage and the introduction of high-speed
public traffic mode to absorb cars’ traffic.
In terms of social economy, it’s needed to introduce the environmentfriendly, energy-efficient transportation mode. In the domestic environment
and energy sector, the transportation accounts for around 21% of the totalenergy consumption. Furthermore, Korea ranks the world-7th in the
consumption of energy (imported by 97%). It’s found that it’s critical tosecure an eco-friendly, energy-efficient traffic mode under the condition of
the increased environment pollution and energy crisis.
Especially, the increased car traffic leads to the severe air pollution.
As for the traffic mode-specific energy consumption, the road accounts forabout 79% as the most proportion, and the marine transportation, airline andrail, 11, 9 and 1%, respectively. As for the traffic mode-specific CO2
emissions, cars account for about 8.4 times more than rail and subway andvans about 3.5 times more (Figure 2).

(b) Transportation mode-specific CO2
emissionsFigure 2. Traffic sector-specific energy consumption and CO2 emissions(a) Energy consumption in traffic sector

3. CONSTRUCTION PLAN
This project sets the Seoul-linking metropolitan traffic axis as a key
influential zone and the whole Seoul areas, including Seoul, Incheon-si and
Gyeonggi-do, as the indirect influential zones. As for the project period, theyear of 2016 was set as the short-term target year and the year of 30 years
after opening was set as the final target year.

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Figure 3. Expected GTX routeThe number of routes is 4 (A, B, C and D) as seen at Figure 3, thetotal length 160km and the operation length including KTX common
sections about 188km. The number of stations is scheduled to be totally 25
including 4 transfer stations of metropolitan express rail and the common 3
stations with KTX. The train base stations are scheduled to be 5. According
to the planned standard, the design speed is expected to be about 200km/h
and the minimum curve radius about 1,200m (R=600m in unavoidable
circumstances). The average distance between stations is designed to beabout 9km at Seoul areas and about 6km at Seoul.
As for the funding, 7 trillion 200 billion won, about 60% of the total
project cost of 12 trillion won, is planned to be raised through private capitaland the other 4 trillion 800 billion won, about 40% of the total project cost,through public financial support. The public financial support is composedof the development charge of 50% and the government support of 50%.
As seen at Figure 4, as for the station construction plan, the general
stations are planned to apply the excavation + tunnel type and the tunnel
type. The excavation + tunnel type is expected to be applied to 12 stations
including Daegok Station, only to the excavation-possible sections. The
tunnel-type general stations are applied to the GTX sections, namely 3 ones
including Singal Station, to minimize the complaints during construction.
The transfer stations are divided into “+” shape and “T” one. “+”shape transfer station is applied to Samsung Station and Cheongyangri
Station available for direct intersect and “T” shape station to SindorimHigh speed
linkrailtunnel(GTX) in
Korea
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in Korea1055

October
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Station and Yongsan Station transferred separately due to the difference ofvertical alignment.

(a) Common station(excavation + tunnel type)(b) Common station (tunnel type)(c) Transfer station (“+” shape)(d) Transfer station (“T” shape)
Figure 4. Representative Station plan
The plan for preventing disasters was largely divided into main line
section and station section. In case of main line section, the interval ofventilation devices was designed to be 2.5km through the safety analysis
and a quick-exhaust ventilation-linking system is expected to be applied
depending on the fire-occurring location and a pressure differential system
is expected to be installed to a refuge room. The fire control section isplanned to be installed to a quick escape-possible location from a fireoccurring point, a special step will be made for a direct escape to outsidefrom the fire-occurring point and it is expected to control the inflow ofsmoke into platform through changing air supply into exhaust gas.
As seen at Table 2, the vehicle system is composed of the design
speed of 200km/h and the highest speed of 180km/h and the vehicles to beable to run from Seoul surrounding areas to Seoul downtown in 20-30
minutes are expected to be selected. The domestically developed vehicles
are preferred to be applied but the foreign vehicles in case of unavoidable
situation.

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Table
Table
2. Suggested
2. Suggested
HighHigh
Speed
Speed
Train
Train
TypeType
SectionSection

KoreaKorea
Railroad
Railroad
ResearchResearch
Institute
Institute

Hitachi
Hitachi(Class(Class395) 395)

VehicleVehicleorganizat
organizat
One train
One trainwith with
6 vehicles
6 vehicles
One train
One trainwith with
6 vehicles
6 vehicles
ion ionMaximuMaximuDesign:Design:200km/h,
200km/h,operation:
operation:
180km/h
180km/h Design:
Design:225km/h,
225km/h,operation:
operation:
200km/h
200km/hm speedm speedNumberNumber278 seats
278 seats/ 6 vehicles/ 6 vehicles
348 seats
348 seats/ 6 vehicles/ 6 vehicles
of seatsof seats

4. EFFECTS
4. EFFECTS
GTXGTX
can cancreatecreatethe expected
the expected
effecteffecton theon increased
the increasedtransportationtransportation
sector’s
sector’s
efficiency,
efficiency,
green
green
growth
growthand andeconomic
economic
viewpoint
viewpoint
and andthe solution
the solutionof Seoulof Seoul
areas’
areas’
problems.
problems.
It canIt canannually
annually
savesave
584.6
584.6
billionbillionwonwonthroughthrough
reducing
reducing
the theenergyenergyconsumption
consumptionof roadof roadsectorsectorby about
by about
450 450thousandthousandtonstons
and andemissions.
In addition,
In addition,
the cost
the cost
to treatto treat
reducereduce1,490
1,490
thousandthousandtonstonsof CO
of 2CO
2 emissions.
CO2CO
can2 becanannually
be annually
reducedreducedby 59.5
by 59.5billionbillionwon.won.
In terms
In terms
of economy,of economy,
the construction
the construction
projects
projects
are expected
are expected
to createdto createdjobsjobs
by about
by about
260 260
thousandthousandand andthe theproduction
production
inducement
inducement
effecteffectin localin localeconomyeconomyis expected
is expected
to betoabout
be about
30 trillion
30 trillion
won.won.
In addition,
In addition,
it is itjudged
is judged
to tocontributecontributeto solving
to solving
the housing
the housing
problems
problems
throughthroughthe real
the real
expansion
expansionof ofdailydailylivinglivingzonezoneboundaryboundary
withinwithinSeoul
Seoul
areasareas
and andto reinforce
to reinforce
the thecompetitivenesscompetitivenessin thein theSeoul
Seoul
areasareas
throughthrough
expanding
expandingthe theeconomic
economic
activities
activities
basis.
basis.
5. CONCLUSIONS
5. CONCLUSIONS
Including
IncludingIncheon,Incheon,Ilsan,
Ilsan,
Bundang,
Bundang,
and andthe neighboring
the neighboringsatellite
satellite
towns
towns
are areveryverymuchmuchpresent,
present,
and andthe population
the populationof theseof these
satellite
satellite
citiescities
is booming,is booming,
traffic
traffic
on on
handling
handling
the theproblemproblem
is mostis mosturgenturgentproblems.
problems.
PublicPublictransportationtransportationis inis thein themidst
midst
of thisof thisproposal
proposalis very
is very
encouraging
encouraging
phenomenon
phenomenonof GTX,of GTX,and andthe future
the futureof thisof thisareaareais thoughtis thought
to betopositioned
be positioned
as anasalternative
an alternative
to transportation.
to transportation.
In particular,
In particular,
the deepthe deeptunneltunnelconstructions
constructions
using
using
TBM
TBM
machinemachineare arethought
thought
to betostill
be stillin thein future,
the future,
withwithplansplans
to Seoul's
to Seoul's
U-SMARTWAY.
U-SMARTWAY.
Urban
Urban
transportationtransportationin thein future
the future
increasingly
increasingly
will will
go downgo down
to deep
to deep

HighUrban
speedspeed
rail linktunnelprojects(GTX)
in KoreaHigh
rail
linkrailtunnel
(GTX)
in
Korea
high
speed
link projects
tunnelprojects(GTX)
in Korea

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underground. Tunneling technology advances and demand for public
transport will take place this.
The first evidence, GTX is the first construction worldwide success ofthe deep underground tunnel, and a lot of technical back-up and technicalassistance is considered to be needed near the future.

REFERENCES
Korea Railway Research Institute, 2010, The Master Plan of the GTX
in Mega-City in Gyeonggi Province, Reports of KRRI.
C. Y. Kim, 2010, A Study on Present Status of Deep Underground
Tunnel and Future Technologies, the 21st KICT-JICE Joint Workshop

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Safety ofof Mega
Mega Cities
Cities inin Asia
Asia
NewGeospatial technologies
in wetland dynamics of Deepor Beel, India
Chitrini MOZUMDER1, Taravudh TIPDECHO2 and Nitin K TRIPATHI3
1
PhD Student
chitrini.mozumder@ait.asia
2
Adjunct Faculty
taravudh@ait.asia
3
Associate Professor and Coordinatornitinkt@ait.asia
Remote Sensing and GIS
Asian Institute of Technology Thailand
ABSTRACT
Geospatial technologies offer cost effective methods for identifying andmonitoring wetlands and their uplands. However due to mixed pixel
problems it is difficult to directly delineate the wetland from its
surroundings. In this study, topographic maps, Landsat (MSS, TM andETM) and SRTM DEM have been used for identification and detection of
spatio-temporal changes in the Deepor Beel, a Ramsar convention wetland
in North East India. A water index (Normalized Difference Water Index,
NDWI) derived from the LANDSAT was found effective in differentiating thewetland boundary from its upland. A multilayer classification technique forthe wetland and its upland was adopted for the preparation of the LULC
(Land Use Land Cover) maps. Deepor Beel is mainly rain fed and one or
two narrow direct links exist between the wetland and the major river
Brahmaputra in North East India. A few possible underground links
between the Deepor beel and the river Brahmaputra were identified in thisstudy. Approximately 57% downfall in the wetland water area wasestimated over the last 38 years (from 1972 to 2010). However, in contrast
to the wetland water area downfall, the area of marshy land increment up to
150% was observed beyond the wetland during the same time frame. This
study is an initiative for assessing different issues associated with changes
in the wetland and its upland for several factors like anthropogenic, climatechange or many more.
Keywords: Remote Sensing, NDWI, Wetland, Flow accumulation, LULC
change1. INTRODUCTION
Wetlands, which are considered as the world’s most productive
environments are endangered and degraded by anthropogenic influences(urban, industrial and agricultural activities, increasing consumption ofwater resources) as well as natural processes (changes in precipitation inputs,

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erosion and weathering of crustal materials). Deepor beel is a Ramsar
convention wetland, which is the largest storm water basin in North East
India. The entire beel was highly contaminated due to the inflow ofenormous quantity (50%) of the untreated Guwahati city sewage and otherinorganic/industrial effluents, and agriculture wastes (O'Hara, 2002; Bera etal, 2008; Planning, 2008). Also, there are number of dwelling units andconcrete structures inside the beel which are increasing with a due pace oftime. The wetland, once spread with 41 sq km of area, is now barely covers
5 sq km (Planning, 2008).
This study aims in accounting the change in extent and areal
dimension of Deepor Beel and its upland areas in last 50 years or more. This
demanded the use of multi temporal remote sensing data and techniquessuitable for wetlands. There have been a number of satellite images whichhave been used in wetland studies such as Landsat (TM, ETM), IRS (LISS),
Envisat, Radar, Lidar etc (De Roeck et al., 2008; O'Hara, 2002; Ozesmi andBauer, 2002). But, it is really difficult to identify and map wetlands fromsatellite imageries since their reflectance confuse with other land areas.
Hence there are several innovative approaches for identification, delineationand classification of the wetland systems (Grenier et al., 2008, Baker et al.,2006, DeAlwis et al., 2007).
Deepor Beel, located about 10 km southwest of Guwahati city, Assam,
India is considered as one of the large and important riverine wetlands in the
Brahmaputra valley of lower Assam (figure 1). It is surrounded by the
Bharalu basin in the east, the Kalamani in the west, Jalukbari in the northand Rani and Garbhanga reserve forests in the south. It lies between 91º35′
to 91 º 43′ E longitudes and 26º05′ to 26º11′N latitude. It is recognized as
one of the most significant wetland systems (10,000 acres) in the world
under the Ramsar International Convention on Wetlands.

Figure 1: Overview Deepor Beel, India with its surrounding locations

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2.
2.

DATA AND
AND METHODSMETHODSDATA

2.1 Data
2.1
Data
The
Landsat (MSS,
1972 toto
The Landsat(MSS, TM,
TM, ETM+)
ETM+) multi
multi temporal
temporal data
data fromfrom 19722010 were2010
were thethe spectral
spectral data
data sources
sources used
used forfor thethe study.
study. Landsat
Landsat MSS
MSS (Multi(MultiSpecral Scanner)
Scanner) sensor
sensor records
records spectral
bands ofof visible,
visible, infrared
Specralspectral data
data inin 55 bands
infraredand Thermalof Electromagnetic
Electromagnetic spectrum
spectrum with
with aa spatial
spatialandThermal wavelengths
wavelengths ofresolution ofm forresolution
of 79
79 m
m (240(240 mfor thermal).
thermal). The
The Landsat
Landsat TM
TM (Thermal(Thermal Mapper)
Mapper)and ETM+andETM+ (Enhanced(Enhanced Thermal
Thermal Mapper)
Mapper) senses
senses earth
earth observation
observation data
data inin 77
bands ofofbands
of visible,
visible, infra
infra red
red andand thermal
thermal regions.
regions. The
The spatial
spatial resolution
resolution ofthese two(120 min Thermalband in
inthese
two sensors
sensors is
is 30
30 m
m (120m in
Thermal band
in TM
TM andand 6060 m
m inETM+) resulting
resulting inminimum mapping
mapping unit.
unit. InIn addition
addition toto 77 bands,
bands,
ETM+)
in aa 900
900 m
m22 minimum
ETM+ also
band withm resolution
resolution which
which cancan bebeETM+also carries
carries aa panchromatic
panchromatic bandwith 15
15 m
used tosensor. Multi
Multi seasonalseasonal
usedto prepare
prepare 15
15 m
m resolution
resolution images
images fromfrom ETM+
ETM+ sensor.
imageries werefor easy
easy identification
identification ofof thethe wetland.
imageries
were used
used forof thethe extent
extent ofwetland.
Other
Other data
data used
used forfor this
this study
study includes
includes thethe 9090 m
m SRTM
SRTM DEM
DEM (Digital(Digital
Elevation Model)
for topographic
topographic information
delineation. Also,
Also,
Elevation
Model) for
information delineation.
topographical map
from Texas
Texas Library
Library (1940’s)(1940’s) arebase maps.
topographicalmap from
are used
used asas thethe basemaps.
2.2 ImagePre processing
processing
2.2
Image PreThe
and images
georeferenced toto thethe samesame
The topographicaltopographical maps
maps andimages areare georeferenced
coordinate systemprojection (UTM).
coordinate
system andand projection(UTM). This
This waswas donedone byby image
image toto image
image
rectification method
rectification
method toto avoid
avoid mismatchingmismatching ofof features.
features. The
The DEM
DEM whichwhich waswas
initially ingeographic projection
projection isis transformed
transformed toto UTM.
UTM. TheThe satellite
satellite
initiallyin geographic
images are
digitally toimagesare processed
processed digitallyto prepare
prepare them
them forfor visualvisual andand digital
digitalinterpretation. The
depends oninterpretation.
The extent
extent ofof image
image enhancement
enhancement depends
on thethe quality
quality ofofthe images.
images. However,emphasis was
was givengiven tothe
However, emphasis
to enhanceenhance thethe waterwater andand moist
moist
lands tolands
to detectdetect thethe wetland
wetland boundary.
boundary. For
For this
this purpose,
purpose, Normalised
Normalised
Difference Vegetation
Difference
Vegetation Index
Index (NDVI)(NDVI) images
images andand Normalised
Normalised Difference
Difference
Water Index
Index (NDWI)
were preparedprepared (figure
Water(NDWI) images
images were
(figure 2).
2). These
These cancan bebeobtained byratioing asas follows:
follows:
obtainedby aa simple
simple band
band ratioing
(1)
(1)
(2)
(2)
The
step was
was toto classify
classify thethe wetland
wetland asas wellwell asas itsits uplandupland using
using aa
The next
next step
hybrid classification
hybridclassification technique
technique which
which isis aa combination
combination ofof supervised
supervised andandunsupervised classification
classification technique.
technique. The
unsupervised
The principal
principal component
component analysis
analysis(PCA) wasimages priorprior to(PCA)
was applied
applied toto thethe images
to classification.
classification. However
However it
it waswasdifficult toto differentiate
differentiate between
between thegrasslands ofdifficult
the wetland
wetland andand grasslandsof thethe uplanduplanddue todueto thickthick vegetation
vegetation cover
cover ofof thethe wetland
wetland (figure(figure 3).
3). Hence,
Hence, aa layerwise
layerwiseclassification techniqueclassification
technique waswas adopted
adopted where
where thethe wetland
wetland waswas digitizeddigitized from
from
using
the
NDWI
image
and
subset.
This
subsetwasseparately
classified
using the NDWI image and subset. This subset was separately classified andandsuperimposed onon thethe previous
previous layer
layer forsuperimposed
for thethe final
final classification
classification map.
map.

Geospatial
Geospatial technologies
technologies
inwetlanddynamicsofdeeporbeel,
India
Geospatial
technologies inin wetland
wetland dynamics
dynamics ofof deepor
Deeporbeel,
Beel,India
India

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Figure 2: NDVI (left) and NDWI images of the study area

Figure 3: Classified image of the study area
Flow accumulation layer was prepared from the SRTM DEM to know
the low elevated paths which are possible passage of water connecting
different areas of the study area. The output of Flow Accumulation would
then represent the amount of rain that would flow through each cell,
assuming that all rain became runoff and there was no interception, evapo
transpiration, or loss to groundwater. The results can be used to create a
stream network by applying a threshold value to select cells with a highaccumulated flow.
2.3 Change Detection Procedure
The change detection has been done in both qualitative andquantitative manner. For quantitative analysis, a model has been prepared in
ERDAS which was used to detect the changes in the NDWI images of the
input images. The thresholds of NDWI for each image are determined on a
trial and error basis. For example, if in the NDWI image, the DN values
greater than 0.1 are observed to be water, then in the model, the water areas
are separated. Similar has been done for the second time series data, and4112

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finally in the output layer, only 3 values are kept where (a) there is nochange, (b) water changed to land and (c) land changed to water in thewetland area. The stepwise algorithms are as follows:[1] EITHER 255 IF ( $n1_deepor_ndwi01 >= 0.1 ) OR 0 OTHERWISE[2] EITHER 255 IF ( $n4_deepor_ndwi10 >= 0.1 ) OR 0 OTHERWISE[3] CONDITIONAL { ($n3_memory == $n6_memory) 0 ,($n3_memory > $n6_memory) 70 , ($n3_memory < $n6_memory)
255}
Another way of quantifying the change was to use GIS techniques toobtain the areal extents of the wetland classes from the time series classified
images. These were then compared and analyzed in tabular and graphical
form.
3.

RESULTS AND DISCUSSION

3.1 Historical Trends
Figure 4 (a) to (d) shows the toposheet and the NDWI images of 4
different years from 1940 to 2010 with the digitized wetland boundary. All
the images are of pre-monsoon season. It has been observed from thescenario in 1940’s that there were two separate wetlands (lakes) (figure4(a)). The bigger one was Deepor beel with adjacent Berhala beel in its rightside. The NDWI images show the water in a bright tone than the otherfeatures of the image. Hence, as observed from figure 4 (b), in 1972 theBerhala beel was shrinking and continued to move towards Deepor beel.
Also, as observed from the toposheet, there was a well defined linkage
between the Brahmaputra river and Deepor Beel which was not muchvisible from the image. Since, the 1972 image (figure 4(b)) is of 60 m
resolution, this linkage may have been nullified by the sensor. Now, in 2001
(figure 4 (c)), the scenario was completely different where the extent of the
moist land obtained in NDWI image was spread out and Berhala beel has
been connected to the Deepor beel. As observed in figure 4 (d), the wetland
has not much changed from 2001 except in the tail portion in the right handbottom corner of the image. These all areas have been captured byagricultural fields due to the fertile land. A field photograph of some
agricultural fields in the tail of the Deepor beel taken in January 2011 has
been shown in figure 5. However, the linkage between the river and the
Deepor beel has not been observed also in these two images of 2001 and2010 of 30 m resolution.
Figure 5 shows the graphical representation of the change observed in
the wetland from 1972 to 2010. Using the threshold of NDWI, the total areaof the wetland in 1972 was found to be 5.2 sq km (2.4 % of the whole studyarea) changed to 12.4 sq km (5.5% of study area). This makes an increase of
138% in the wetland. However, if individual classes are noticed, the area ofwater has tremendously decreased from 1972 to 2010 (figure 5(a)). In 1972,
the area of water was 3.4 sq km which decreased to 1.4 sq km in 2010 bydecreasing an amount of approximately 57%. In 1972 the wetland with
Geospatial technologies
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vegetation was very less as compare to 2001 and 2010. This vegetation is
supposed to be mostly the agricultural fields which are the activities of thelocal people due to fertile nature of the wetland. Hence, it is critical to say
whether the wetland has expanded or due to anthropogenic activities the real
wetland is shrinking.
Twenty one random locations were selected within the wetland
boundary of 2010 to see the changes of NDVI from 1972 (figure 5 (b)).
These points fall in both water and vegetated areas. Although there is no
definite trend in the NDVI values, for different years, same season NDVI
data shows drastic difference in their values. The pre monsoon (Feb-Apr)plot infers a gradual increase in NDVI from 2001 to 2003. However, there isno much difference in the average NDVI of 2003 and 2010 for all points,
although there are some changes in each location. For post monsoon plot
(Oct-Nov), there are few locations (1 to 8), where the NDVI was less in1972 which increased in 2009, however in June 2000 the NDVI of these 8
locations are observed to be the highest. For the rest of the locations of theplot in this season, the pattern is random. But, in June 2000 the average of
all the points can be assumed to be a constant horizontal line.

(a)

(b)

(c)

(d)

Figure 4: (a) Topographic map (1946) (b) NDWI image of Landsat (1972)(c) NDWI image of Landsat (2001) (d) NDWI image of Landsat(2010) of the study area

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Figure 5: (a) Change in the area of the LULC classes (b) NDVI variation at
21 random locations within the Deepor Beela. Linkages between Deepor beel and river Brahmaputra
To determine the existence of the linkage between the Brahmaputra
river and the Deepor beel, the SRTM DEM has been used to find thedifference in elevations around the area (figure 6). Originally the Deepor
beel had its natural linkage with the river Brahmaputra through the Borholabeel and the swampy areas of Pandu, lying to the Northeast. But owing to
the construction of NH-37 and civil works like residential buildings theearlier link has already been severed (Saikia, 2005). The flow accumulation
map derived from the DEM shows a number of possible linkages between
the river and the wetland. However, the linkage observed in the toposheet of
1940’s still exists with some disconnections in the middle. The disconnected
portion of the linkage may have occurred due to some true elevated area inGeospatial technologies
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Chiang
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Thailand
October
2011,
Chiangmai,
Chiangmai,
Thailandthethetopography
topography
or dueor dueto existence
to existenceof bridge.
of bridge.
This
This
waswasconfirmed
confirmed
withwiththethehighhighresolution
resolution
imagesimagesof of
GoogleGoogleEarth
Earth(2005).
(2005).
TheTheGoogleGoogle
Earth
Earth
image
image
showedshowedthethecontinuous
continuous
linkagelinkagewithwitha smalla smallbridgebridgeover
overit. it.
Two
Two
more
more
linkagelinkage
betweenbetweenthetheriver
river
andandthethewetlandwetlandwaswasdiscovered
discovered
which
which
waswasnotnotvisiblevisiblefromfromthethegooglegoogleearth
earth
imageries.
imageries.
These
These
arearethetheundergroundundergroundchannelschannels
which
which
feed
feed
thethewetlandwetlandfromfromthetheriver
river
Brahmaputra.
Brahmaputra.

(a)(a)(b)(b)

FigureFigure6: (a)
6: (a)
SRTM
SRTM
DEM
DEM
(b)(b)
Flow
Flow
Accumulation
Accumulation
map
map
derivedderivedfromfromthethe
DEM
DEM
Table
Table
1 shows
1 shows
thetheareas
areasaroundaroundthetheDeepor
Deeporbeelbeel
which
which
have
have
changedchanged
from
from
water
water
to to
land
land
or or
viceviceversa.
versa.
These
These
have
have
been
been
obtained
obtained
from
from
NDWI
NDWI
imagesimagesby byrunningrunninga modela modelin ERDAS.
in ERDAS.
Hence,
Hence,
fourfourscenarios
scenarios
were
were
obtained
obtained
on on
pixel
pixel
to pixel
to pixel
basis
basis
where
where
thethechangeschanges
from
from
water
water
to water
to waterandand
land
land
to to
land
land
have
have
been
been
considered
considered
as no
as no
change.
change.
TheTheother
other
twotwoscenarios
scenarios
arearechangechange
from
from
water
water
to landto landandandviceviceversa.
versa.
Table
Table
1: Changes
1: Changes
in landin landandandwater
water
obtained
obtained
from
from
NDWI
NDWI
imagesimagesChangeChangeWater
Water
to water/Land
to water/Land
to tolandland
Water
Water
to landto landLandLand
to water
to water

count
count

areaarea(sq (sqkm)km)

1972-2001
1972-2001

2001-2010
2001-2010

1972-2001
1972-2001

2001-2010
2001-2010

48854
48854

49723
49723

1.46562
1.46562

1.49169
1.49169

1831
1831

1993
1993

0.054930.054930.05979
0.05979

2529
2529

1645
1645

0.07587
0.07587

0.04935
0.04935

4. CONCLUSION
4. CONCLUSION
TheThepresent
present
study
study
is is
an an
attempt
attemptto touseusethethetechniques
techniquesof ofremoteremotesensingsensing
andandGISGIS
to delineate
to delineate
thethechangeschangesin ainwetland
a wetlandof Ramsarof Ramsar
convention
convention
in Northin North
East
East
India
India
in lastin last7 decades.
7 decades.
TheThe
NDWI
NDWI
image
image
waswasfound
foundeffective
effectivein indeciding
deciding
thetheboundaryboundary
of ofthethewetland.
wetland.
A A
layer
layer
wise
wise
classification
classification
techniquetechniqueon onprincipal
principal
component
component
imagesimagesof ofLandsat
Landsatwaswasadoptedadoptedto toimprove
improvethetheclassification
classificationof theof thewetland.
wetland.

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The wetland “Deepor Beel” has shrank in its water covered area asfound in the study but, interestingly, the coverage of the moist land has been
increased. The wetland has been spread out in its surrounding areas andmost of these lands have been used for agricultural purpose due to theirfertility. There is a narrow linkage between the river and the wetland andseveral other possible linkages around the wetland. The flow accumulation
map shows some definite surface or underground linkages between thewetland and the surrounding areas which improves the fertility of the land.
The area covered by water in the Deepor beel has decreased by 57%
whereas, the moist land has increased by almost 150% from 1972 to 2010.
Most of the wetland is covered by water hyacinth and other aquatic plants.
Interestingly, area changed from land to water is more than the area changed
from land to water from 1972 to 2001. However this was calculated on a
pixel to pixel basis from NDWI image by considering a threshold value
different for each image by considering the actual conditions from theimages.
REFERENCES
Baker, C., Lawrence, R., Montagne, C. and Patten, D., 2006. Mapping
Wetlands and Riparian using Landsat ETM+ Imagery and Decision Tree
Based Models. Wetlands 26(2), 465-474.
Bera, S. K., Dixit, S., Basumatary, S. K. and Gogoi, R., 2008.
Evidence of biological degradation in sediments of Deepor Beel Ramsar
Site, Assam as inferred by degraded palynomorphs and fungal remains.
Current Science 95(2), 3.
De Roeck, E., Verhoest, N., Miya, M., Lievens, H., Batelaan, O.,
Thomas, A. and Brendonck, L., 2008. Remote Sensing and Wetland
Ecology: a South African Case Study. Sensors 8(5), 3542-3556.
DeAlwis, Da., Easton, Z. M., Dahlke, H. E., Philpot, W. D. andSteenhuis, T. S., 2007. Unsupervised classification of saturated areas using
a time series of remotely sensed images. Hydrology and Earth System
Sciences Discussions 4(3):1663-1696.
Grenier, M., Labrecque, S., Benoit, M. and Allard, M., Accuracy
Assessment Method for Wetland Object Based Classification. In: Geoffrey J.
Hay TBaDM, editor; 2008; Calgary, Alberta, Canada. University of Calgary.
O'Hara, C. G., 2002. Remote Sensing and Geospatial Application for
Wetland Mapping Assessment and Mitigation. Integrating Remote Sensing
at the Global, Regional and Local Scale Pecora 15/Land Satellite
Information IV Conference. Denver, Colorado.
Ozesmi, S. L. and Bauer M. E., 2002. Satellite remote sensing of
wetlands. Wetlands Ecology and Management 10(5):381-402.
Planning CGoI. 2008. Report on Visit to Deepor Beel in Assam - awetland included under National Wetland Conservation and Management
Programme of the Ministry of Environment & Forests. Guwahati, Assam,
13-14 Aug, 2008.
Saikia PK. Qualitative and Quantitative Study Of Lower And Higher
Guwahati; 2005. Available at:
http://www.ndsu.edu/pubweb/~bezbarua/em/Documents/DeeporReport-PrasantaSaikia.pdf.

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technologies inin wetland
wetland dynamics
dynamics ofof deepor
Deeporbeel,
Beel,India
India

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Estimation of building stories for HAZUS
using light detection and raging (LiDAR)
Chomchanok LIANGWANNAPHORN and Kiyoshi HONDA
Remote Sensing and GIS, School of Engineering and Technology
Asian Institute of Technology (AIT), Thailand
Chomchanok.L@gmail.com
ABSTRACTIn this decade, Thailand was affected by a lot of disaster especially in
Tsunami disaster triggered by an earthquake. HAZUS Loss Estimation
methodology involves many parameters for damage estimation. One of themost critical parameter in estimating Hazard Loss is floor area. Floor area
refers to the total of floor area of building which can derived from building
stories multiplied by footprint area. Therefore building stories is importance.
LiDAR provides high resolution spatial point data used in the numbers ofapplications especially in urban mapping. The capability of LiDAR, rapid
data acquisition, eliminates the time consuming and costly problem which ismain problem from traditional survey. The point cloud LiDAR be
determined to be ground point data and non-ground point data. LiDAR isgenerated to digital surface model (DSM), the ground point from LiDAR is
become a digital terrain model (DTM), afterwards normalize digital surface
model (nDSM) which is a technique for eliminating the terrain affect in dataset, created by subtracting DTM from DSM. Building’s height is extracted
by building footprint database, As the result, the numbers of building stories
will be extracted using the relationship between building height and numberof story of building.
Keywords: LiDAR, HAZUS, earthquake loss estimation, building stories
extraction
1. INTRODUCTION
In this decade, Thailand was affected by a lot of disaster especially in
Tsunami disaster triggered by an earthquake. Therefore, disastermanagement became the top priority concerned by the Thailand government
and private sectors. Since 2006, Thai Meteorological Department (TMD) isdeveloping a database for disaster management named as Thailand National
Database for Earthquake and Tsunami Relief and Prevention. The
mentioned database is based on HAZUS-MH program requirements.
HAZUS-MH program was selected as the loss estimation methodology for
Thailand.
HAZUS methodology, an inventory database contains various data
which affected by hazard. The database consists of various databases such

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as hazard database, boundary and infrastructure database and building
database. During, hazard database initiation of the hazard scenario in loss
estimation, building damage estimation is calculated by building databasewhich provides the main calculating parameters, for instance; building
location, structure type, footprint area, age of building, building occupancy
type, numbers of building stories, etc.
1.1

Statement of the Problem

Thailand National Database is collecting from various sources, which
results in different accuracy, scaling and reliability. The number of building
stories in existing database is not much accurate when comparing with theupdating data from surveying, which found in 25 percentages of nonmatching in databases. Cross checking and modification of the existingdataset will take time and costly. Moreover the accuracy of building stories
is directly contributing to floor area in building damage estimation using
HAZUS-MH. The capability of LiDAR in automatic three dimension
reconstruction is play an important role in extracting building stories. The
result of LiDAR associated with building footprint is precise accuracy andreliability in building stories extraction.
1.2

Objective

The main priority of this research is extracting building stories from
LiDAR image using building footprint from existing database.
• Overlay building’s height from LiDAR and building footprint.
• Analyze Relationship between building height and building stories.
• Estimate building stories and validate the result.
2. BACKGROUND
2.1 HAZUS Method
HAZUS stands for HAZard United States which is a nationallyapplicable methodology and software program for estimation of loss fromearthquake, floods and hurricane. HAZUS is being developed by the Federal
Emergency Management Agency (FEMA) which uses geographic
information system software to calculate, map, and display earthquake
hazards and damage and loss estimation. The earthquake model provided by
HAZUS was released in early 2003 as part of a multi-hazard version of
HAZUS. The model allows users to forecast damage and loss to buildings,
infrastructure and population that may result from potential earthquakes.
Loss estimates produced by HAZUS are based on current scientific andengineering knowledge of the effects of earthquakes. (FEMA, 2008)
2.2 Building Dataset
Thai Meteorological Department (TMD) is developing a database fordisaster management known as “Thailand National Database for Earthquake

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and Tsunami Relief and Prevention”. The database is combined fromexisting database and data from ongoing surveys. Existing database in
Bangkok area is provided by the Department of city planning, Bangkok
Metropolitan Administration (BMA) which consists of building data setssuch as building location, structure type, footprint area, age of building,building occupancy type, numbers of building stories, etc. Existing data isbased on the data in 2003, therefore, is out of date and unorganized
regarding existing building database. It may be caused by missing records,
not-matching data, missing information and human error. Existing data
modification is time consuming and accuracy improvement is notguaranteed because improvement depends on surveyor quality, time
limitation of project, budget, etc. Furthermore, existing database is notcompatible with HAZUS requirement. Existing database needs re-coding inbuilding occupancy type according to HAZUS methodology.
2.3 Related work
There have been several related works on building detection using
LiDAR data. Guoqing Zhou, C.Song, J. Simmers and P.Cheng used LiDAR
and digital aerial images for generating urban 3D GIS. For ground point
extraction; M.A. Brovelli and M. Cannata (2004) proposed filtering methodfor LiDAR data, called region growing algorithm and also mentioned in
Claus Brenner’s research (2005). Another filter is the morphological filter
that was used by Wolfgang Schickler in 2001, used for application of
surface estimation based on LiDAR. Moreover, LiDAR data have thecapability of acquisition of 3D features models for virtual reality application.
Numerous application of LiDAR for 3D modeling, building extraction and3D city modeling has been introduced by many researchers. Norbert Haala
and Claus Brenner introduced two methods for data collection in urban
environment in 1999. The first method combined multi-spectral imagery
and laser altimeter data for the extraction of buildings in urban area. The
second method used laser data and 2D ground plan information to obtain 3D
reconstruction of buildings. In addition, building footprint extraction fromaerial LiDAR data has been done by Oliver Wang, Suresh K. Lodha andDavid P. Helmbold. They presented a novel Bayesian technique for
automatically constructing building footprint form a pre-classified LiDAR
point cloud. Scott Orford and Jonathan Radcliffe presented a method forderiving living space estimated by using LiDAR associated with OS
Mastermap for Cardiff which provides topographic and address layers to
extracts the number of stories. Building heights were then calculated foreach polygon within a building outline using a weighted average of the
LiDAR data and then this was converted into a measure of the number ofstories.
3. METHODOLOGY
The general methodology of the research and the procedures that relevant toanalysis dataset for number of building stories is consists of three mainprocedures; (1) Derived Digital Terrain Model (DTM) for LiDAR data ; (2)Estimation of
using
light
detectionandranging
Estimationof buildingbuilding stories
stories forfor Hazus
HAZUS
using
light
detectionandraging(LIDAR)(LiDAR)

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Normalized Digital Surface Model, also called nDSM. This techniquereduces topographical affect from the objects on terrain in other words; theabsolute height value of protruding objects is extracted; (3) Building dataand number of building stories are extraction.
3.1 Ground point selection
Elevation derived from LiDAR dataset is normally stand on earth’s
surface, height is based on the sphere which is still having the terrain affect.
The terrain affect is terminated by subtracting Digital Terrain Model (DTM)from Digital Surface Model (DSM). A digital surface model (DSM) on theother hand includes buildings, vegetation, and roads, as well as natural
terrain features. Hence, features on surface have to eliminate the terrain
affect before calculate net height.Points represented as ground point isgenerated a digital terrain model (DTM). Digital terrain model, also called
DTM, is derives from ground point using interpolation technique. Bilinear
interpolation is selected in this research because this interpolation isappropriate to for continuous data.
Bilinear interpolation is a one extension of linear interpolation whichfunctions of interpolating two variables on a regular grid. The interpolation
starting with interpolate in one direction, then again in another direction.
Suppose, interpolate in x – direction first, and then interpolate in y –direction as equation 1 , equation 2 and equation 3 respectively. First, dolinear interpolation in the x-direction with following equation.
(1)

(2)

Then again, do interpolating in the y-direction.
(3)
3.2 Normalize Digital Surface Model (nDSM)
The concept of Normalize DSM is calculates the difference between
DSM and DTM as demonstrate in Figure1.

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Figure1. Normalized Digital Surface Model Concept
DTM is derived from DSM afterwards; simply subtracted DSM by
DTM data which results in all objects stands on elevation height zero.
3.3 Building and Building Stories Extraction
The aim of this work is extract number of building stories using lightdetection and ranging (LiDAR) and building footprint dataset. Additional,
the result form this research can contribute on increasing accuracy ofbuilding database in case of earthquake loss estimation using HAZUS
program. The requesting dataset to finish this research are building footprint
and height of building which derived from building database and LiDAR
dataset respectively.
Data combination between building footprint and nDSM dataset,zonal analyst technique was chosen. Zonal analyst calculated nDSM foreach cell using the value for each belonging the zone which defined bybuilding footprint in another word, a statistic is calculated for each zone
defined by a building dataset, based on values from nDSM dataset
Result of combined dataset between building information and nDSM,
building occupancy type and building’s height can reach for building stories
extraction. Aforementioned, floor’s height of building is limited by building
occupancy type. Standard floor’s height of building base on Bangkok
Legislation act 2001: Building control regulation which defined floor heightas Table 1
Table1: Standard of Floor height(Bangkok Legislation act 2001: Building control regulation)
Occupancy Type

Vertical High
(Standard Height)

1.

Residential, Town house

3.00 m.

2.

Commercial and School

3.25 m.

3.

Warehouse, Hall

3.50 m.

Estimation of
using
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Building data from nDSM is firstly extracted, afterwards; zonal
analysis is applied for average-height calculation in each building according
to footprint data, result of calculated value which appeared in the tabular
data. The tabular data from zonal analyst is joined with tabular data inbuilding database. Finalize, all information both from LiDAR data andbuilding information became unique dataset.
3.4 Error Assessment
Examined data should be reliability and up to date, so survey data is
acquired in this research. Survey data is separated in two levels, first level isexisting database verification and second level is building stories extraction
validation.
Sampling data is differencing in existing database verification andbuilding stories by LiDAR verification. For existing database verification is
focusing on building stories and building occupancy type. Because building
occupancy type is directly affects the standard of building floor’s height.
Therefore, error assessment is beginning with verify building occupancy
type and building stories in existing database.
Since existing database verification is collected by visual survey,
massive sampling is allowance. On the contrary, building stories by LiDAR
verification is required more than visual survey. Building’s height ismeasured using laser measurement which one set of measurement had tomeasured three time in each building; then average for the height of one
building. Because laser instrument and building is not on the same elevation,
triangle measurement technique is required in this section (1) measure the
top of building (2) measure on middle in height and (3) measure the lowestof the building, mentioned steps is counted in one set of measurement.
An error over existing database found error data varies increasingly base on
number of building stories. Major error is found in number of building
stories is three and four as show in Table 2
Table 2: Error in Existing Building Database
Number of Building Stories

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Error
Percentage (%)

1 Story-0.75

2 Stories

0.60

3 Stories

6.51

4 Stories

6.08

5 Stories

0.70

Total Error

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In contrast, a total error of building stories which derived from LiDAR
dataset is decreasing seven times comparing with existing building database.
Most decreasing of error founds in building with three stories and fourstories as Table 3
Table3: Error in Number Stories derived from LiDAR
Number of Building Stories

4.

Error
Percentage (%)

1 Story-0.23

2 Stories

0.09

3 Stories

0.33

4 Stories

0.05

5 Stories

0.14

Total Error

0.37

CONCLUSION

The aim of this work is extract number of building stories using lightdetection and ranging (LiDAR) and building footprint dataset. Additional,
the result form this research can contribute on increasing accuracy ofbuilding database in case of earthquake loss estimation using HAZUS
program. The requesting dataset to finish this research are building footprint
and height of building which derived from building database and LiDAR
dataset respectively.
LiDAR dataset providing efficient result in number of building stories
extraction which derived seven times increasing of accuracy. As mentioned
reason, number of building stories is key factor in floor area calculation
which directly affects to loss estimation by HAZUS program. Number ofbuilding stories is extracted and contributed in building database. The result
from LiDAR is more accuracy than existing database which directly
contributes more accuracy in loss estimation. Consequently, number ofbuilding stories derived from LiDAR is more efficiency in term of moreaccuracy, time-consuming and reliability data than traditional processes.
In conclusion, LiDAR is effective in number of building stories
extraction which shows in correction of data is increasing approximated75.54%.
REFERENCES
Claus Brenner., 2005, Building reconstruction from images and laser
scanning. International Journal of Applied Earth Observation andGeoinformation,6, p 187-198.
Estimation of
using
light
detectionandranging
Estimationof buildingbuilding stories
stories forfor Hazus
HAZUS
using
light
detectionandraging(LIDAR)(LiDAR)

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Derek McNamara. Extracting Building Footprints from LiDAR and
Aerial Imagery in the Wildland Urban Interface (WUI). available online
http://gis.cdatribe-nsn.gov/projects/images/BuildingExtractionFin.ppt
F.Rottensteiner, J.Trinder, S.Clode and K.Kubik., 2005, Automatic
Delineation of roof planes from LiDAR data. ISPRS Workshop "Laser
scanning 2005", Enschede, the Netherlands
F.Rottensteiner, J.Trinder, S.Clode and K.Kubik. Detecting building
and roof segments by combining LiDAR data and Multispectral images.
available
onlinehttp://espace.library.uq.edu.au/eserv/UQ:9764/ICVNZ_submitted.pdf
Friedrich Ackermann., 1999, Airborne laser scanning—present status
and future expectations. Journal of Photogrammetry & Remote Sensing, 54,
p.64–67.
G.Priestnall, J.Jaafar and A.Duncan., 2000, Extracting Urban
Features from LiDAR digital Surface Models. Computers. Environment and
Urban Systems, 24, p.65-78
George Miliaresis and Nikolaos Kokkas., 2007, Segmantation andobject-based classification for the extraction of the building class from
LiDAR DEMs. Computers& Geosciences, 33, p. 1076-1087.
Gunho Sohn and Ian Dowman., 2007, Data Fusion of High-resolution
Satellite Imagery and LiDAR Data for Automatic Building Extraction.
ISPRS Journal of
Photogrammetry&Remote Sensing, 62 , p.43-63
M.A.Brovelli and M.Cannata., 2004, Digital terrain modelreconstruction in urban areas from airborne laser scanning data: the method
and example for Pavia (northern Italy). Computers& Geosciences, 30, 325331
Norbert Haala and Claus Brenner., 1999, Extraction of buildings andtrees in urban environments. ISPRS Journal of Photogrammetry&Remote
Sensing, 54, p. 130-137
Phisan Santitamnont. , 2007, Feasibility study of LiDAR Technology
for Engineering Surveys. Lecture note online of Chulalongkorn University
available
onlinewww.subweb2.dpt.go.th/orw/udti/data/training_online/TrainingProgram_Ch
ula.pdf.
Phisan Santitamnont., 2008, Introduction of LiDAR. Lecture note of
LiDAR Training at GISTDA on 2nd June 2008.
Ronald A. Bauer and Craig M. dePolo., 2006, Loss-Estimation
Modeling of Earthquake Scenarios for Each County in Nevada Using
HAZUS-MH. NEVADA BUREAU OF MINES AND GEOLOGY, Nevada,
United State.
Scott Orford and Jonathan Radcliffe. Modelling residential living
space for individual properties using digital infrastructure and remotesensing data: a Cardiff case study. School of City and Regional Planning,
University of Cardiff
Wolfgang Schickler and Anthony Thorpe., 2001, Surface estimation
based on LIDAR. ASPRS Annual Conference. St. Louis, Missouri.

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NewLong and deep underground road tunnel
projects of the mega-city in Korea
Chang-Yong KIM 1, Seong-Won LEE1, Xiu-Mei ZHENG1,
Ho-Keun KIM1 and Kyung-Ho PARK2
1
Korea Institute of Construction Technology, Daehwa-dong, Goyangdae-ro,Ilsanseo-gu, Goyang-si, Gyeonggi-do, Korea,
cykim@kict.re.kr
2
Asian Institute of Technology, P.O. Box 4, Klong Luang,
Pathumthani 12120, Thailand
ABSTRACT
Recently, the developed countries such as Europe and USA are promoting
to construct traffic facilities using the underground spaces of downtown
area to develop the new sustainable space for Green Growth, securinggreen zone on the ground and solving traffic congestion. Expanding groundtraffic facilities in a metropolis has gone as high as it can go due to landcompensation and civil appeals during construction and especially, a traffic
tie-up and concentration in Seoul and the Metropolitan area cause severesocial/economical loss so it is necessary to construct deeply undergroundtraffic facilities to solve traffic congestion fundamentally. Accordingly, thecity of Seoul announced the U-Smartway project based on 6 undergroundroads and 4 circular road networks that extend to 149km. This project is thefirst challenge of urban deep road and longest tunnels in Mega City such as
Seoul and Busan etc. Already, there are several lanes of Subway line
number 1-9. But, this kind of the huge project in road tunnel in urban area
is first in Korea.
However, compared with the developed countries experiences, Korea has
been inexperienced in constructing underground roads of the downtown
area with insufficient consideration on the related core technologies andaccumulated knowledge. Then, if the project is promoted, we cannot help
depending on overseas technologies. Accordingly, in this study, the concept
of underground transportation infrastructures specially in road tunnels thatis suitable for Korean circumstances was established and the core basetechnologies to construct economical and safe underground space wasdeduced to consider practical use in the future.
In this paper, we emphasis on the needs of consideration of the technicalrequirements of this kind of projects in long and deep urban road andrailway tunnels
Keywords: Urban Road Tunnel, Deep and Long Tunnel, U-Smartway

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1. INTRODUCTION
Approximately 70% of Korean peninsula consists of mountainous area andSeoul, in the capital of Korea also located in very hard rock condition(Figure 1). As shown in Figure1, Gneiss, Granite and Schist are the main
formations of Korean peninsula. The percentage of these kinds of hard rockformation is almost over 64%. So, there are very good conditions for thedevelopment of underground infrastructures in Seoul, namely Mega-Cityof Korea.

Gneiss Granite

Meta
Igneous morphic Sedimentary

Schist

Etc.

Tertiary
ShinraNackdong
Bansong
Carboniferous
SilurianOrdovician
SangwonGranitiic Gneiss
GneissBasaltAndesite,Rhyollite
GraniteFelsic RockFigure 1: Geological Formations in Korean Peninsula
At present, the construction of transportation facilities utilizing urban
deep underground to promote sustainable development, secure green zone
above the ground and relieve traffic congestion has been briskly proceed inadvanced nations. Even in Korea, the need for construction of urban deep
underground transportation infrastructure came to the fore as a way of2128

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relieving traffic congestion as economic loss of 21.5 trillion won a year was
estimated as a result of traffic jam and traffic concentration on Seoul
metropolitan area, and the expansion of traffic facilities above the groundwas no longer available due to various problems related to civil affairs
during construction and compensation for land required.
On this, Seoul metropolitan government presented its plan of USMARTWAY, which is designed to construct 2 belt highway and 6
underground road(total of 149km), and the Ministry of Land, Transport andMaritime Affairs and Gyeonggi provincial government presented the projectof deep tunnel express line for metropolitan area (GTX). Currently, the needfor underground expressway project of partial section in Gyeongbu[SeoulBusan] Expressway and Gyeongin[Seoul-Incheon] Expressway is under the
study, which is suggested by Seoul Policy Development Institute.
Government is performing a study on the utilization, maintenance anddevelopment of underground space to activate construction of urban deep
underground transportation infrastructure, and based on this, the Ministry ofLand, Transport and Maritime Affairs is making systematic basis likeenactment of ‘Basic Regulations on underground space’.
However, since Korea doesn't have many construction experiences ofurban deep underground transportation infrastructure, compared toadvanced nations, and the review on core technologies and accumulation oftechnologies are lacked, we have no choice but to depend on foreigntechnologies in case the projects proceed. In addition, most projects which
are suggested and reviewed until now are designed to cut and cover tunnel
and NATM tunnel by blasting in spite the fact that tunnels pass through thelower part of existing road or crowded downtown area. Above all, in-depth
reviews as well as technological and political alternatives are required since
many people are concerned about the safety and disaster prevention of urban
deep underground transportation infrastructure, and the specialists
concerned have conflicting ideas on this kind of issue. Accordingly, it issaid that now is the time that we have to establish the technologies ofdesign/engineering for construction of safe and economical undergroundtransportation infrastructure, and correct concept of undergroundtransportation facilities suitable for domestic environment.
In this study, the direction of technology development is presented bydeducing core technology items for construction of urban deep undergroundtransportation infrastructure, reviewing the present status of major projects
related to transportation facilities utilizing urban deep underground of Korea.
2. URBAN DEEP INFRASTRUCTURE
Urban deep underground infrastructure is defined as underground roaddesigned to pass through the lower part of downtown areas for the purposeof controlling traffic volume and reorganizing the overcrowded city, andcurrently there is increasing demand for this because of awareness onimportance of beautiful urban landscape and environment, alternative ofLong andLong
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civil affairs during construction and compensation for land required, andproblem of overcrowded downtown area.
Deep underground is defined as the point which is more than 40m,
where there is no construction of subway in general, or more than 10m fromthe upper part of the support ground, where there is no use for foundation
installation for structure.
For the underground transportation facilities in downtown area whichis planning in Korea, the method utilizing urban deep underground which ismore than 40m in depth is being reviewed. Table 1. shows that the generaladvantages of utilizing urban deep underground as transportation
infrastructure and requirements precedent for construction of undergroundtransportation facilities.
Table 1: The advantages of urban deep underground transportation
infrastructure and technical requirements.
The advantagesof urban deep
undergroundtransportation
infrastructure

Technical
requirementsy Possible to reduce construction expenses of urban deep
undergroundy Reducing construction periody Curtailing expenses by rational tunnel alignmenty Cutting down noise and quake and preserving urban environment
y Avoiding large-scaled civil engineering work above the ground incrowded downtown area
y Little damage from earthquakey Environmental countermeasures of tunnel(ventilation tower,
underground water)y Countermeasure for disaster prevention of tunnel
y Ventilation method of tunnely Structure of tunnel and method of construction
y Increase of management and construction costy Restriction of the entrance and difficulty of expansion in the future

3. U-SMARTWAY PROJECT
Seoul metropolitan government established the basic plan for undergroundroad in 2006 and last year, the government came to present the plan for USMARTWAY underground road, which is total of 149km and has 9 lines insouth/north and east/west axes to solve serious traffic problems throughreview for several years. U-SMARTWAY is new conceptual undergroundroad, which is safer and more pleasant than space above the ground since
not only driver but also system can control the vehicle, sending andreceiving information through the cutting-edge communication system inurban deep underground of 40 to 60m. Estimated working expense amounts
to 11.2 trillion won.
3.1 ROUTE
The composition in lines of U-SMARTWAY is designed to improveaccessibility between Seoul and Incheon by reflecting regional
characteristics like harbours and airports, which shows in Figure 2. In

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addition, the traffic which passes through downtown area can be made to
take a roundabout by connecting metropolitan area with subcenter ofmetropolis. In particular, the traffic volume which passes through downtown
area can be effectively reduced by connecting 2 recurring lines which is tobe constructed underground with internal circulating line and Gangnam
circulating line above the ground. For additional method of restricting
vehicles incoming downtown area, 4 access roads are to be installed in
downtown area so that the vehicles can go into outskirts of the city rapidly.

Figure 2: Scheme Drawing of U-SMARTWAY
3.2 DESIGN CONCEPTS
The disaster prevention plan which is considered as the mostimportant factor in U-SMARTWAY is designed and operated, connectingwith the entire systems constructing underground road such astransportation management plan, ventilation plan and central control centers,
including the prevention and extinction of fires. By all transportation
measures, emergency road of 2.0m is installed in entire section of USMARTWAY to secure safety zone each, and water atomizing facilities andautomatic fire sensing devices are installed to prevent from fire spreading.
In addition, the 24-hour management on entire section is expected to bemade through radio, VMS and CCTV in the central control center.

Figure 3 Cross Sectional Diagram for Main Tunnels

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Looking at the sectional diagram of underground road, the rest 5 axes
except for south/north 3 axes are planned as duplex structure for compact
car exclusive like Figure 3, considering economical efficiency and easinessin construction of circulating lines. In addition, JCT is installed in thesection at which south/north axis and east/west axis intersect so that vehicles
can change direction without entering into the road above the ground in thecenter of the city and the secondary center of the city sections (Figure 4).

Figure 4 Connecting System with the Road above the Ground of USMARTWAY (a) JCT, (b) Underground Parking rot, (c) Connection withTransportation above the Ground
3.3 EMERGENCY EVACUATION SYSTEM
For ventilation plan, overflow-typed ventilation plan by exhaust ductis reviewed, targeting entire sections to realize stable evacuation efficiency
after careful consideration of the fact that it is ultra long tunnel in which one
axis is more than 20km, and the plan is connected with disaster prevention
plan in coordinated way(Figure 5). In addition, the introduction of such
purifying systems as electric precipitator and ventilation facilities will makeit possible to filter out pollutant from vehicles in underground road anddischarge clean air into the atmosphere.
Considering transportation aspect, the construction of undergroundroad makes it possible to move the entire area of Seoul metropolitan city
within 30 minutes, and promote space for environment-friendly public
transportation since cycletrack(more than 492km) and green tract ofland(615,000m2) can be secured in city spatial aspect. In addition, reduction
in social expenditure of 2.4 trillion won a year is expected through reduction
cost of traffic congestion and environmental pollution in economic aspect

Figure 5 Ventilation method and emergency evacuation facility

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4. TECHNICAL REQUIREMENTS
Looking into such cases of transportation facilities utilizing urban deep
underground as A86 underground road in France, central underground roadin Tokyo, Japan, M30 project in Madrid, Spain, SMART project in Malaysia
and Alaska Way project in Seattle, the United States, those projects
commonly adopted Shield TBM method, environment-friendly tunnel
method of construction to prevent obstruction of traffic flows and damage ofsurrounding environment during construction work, and construct duplex
tunnel for compact car exclusive to achieve efficiency of sectional diagram.
In addition to point of sameness in the technological method, those projects
had powerful driving force for operation of the projects in common, while
promoting harmonious communication with local residents.
The technological realization of urban deep undergroundtransportation infrastructure is said to be completed in 2005 worldwide.
However, 2016 is estimated for completion of the technologicalachievement in case of Korea since core technology related isn't prepared
for the project, not to mention research on marketability and economical
efficiency. Since the construction of urban deep underground transportation
infrastructure in downtown area is aimed at solution of traffic problem in a
metropolis, the core technologies required are ultra large sectioned Shield
TBM technology, designing and engineering technology of ultra large
sectioned duplex tunnel and safety management technology of undergroundpassage. For this, research and development must be made. Considering
foreign cases of commercialization, it seems that the technology connectingwith existing transportation network is not systematically defined, so it isestimated that the technology connecting with existing transportation
network can be utilized as major technology item as core technology
development item.
It is said that Korea has large cross sectional and urban deep
underground shaft technology for connection of underground tunnel withroad above the ground and construction technology of excavation tunnel atpresent, but as interest and demand for protection of surrounding
environment, minimization in obstruction of traffic flows during
construction work and maintenance of pleasant city life increases,
economical and environment-friendly shaft construction technology andtechnological development of excavation tunnel construction will be
constantly required. In addition, securing ventilation and disaster prevention
technology to guarantee safety in urban deep underground passage has to be
put the first, and the cutting-edge technology to minimize damage ofexisting structures and surrounding environment has to be developed as well.
Above all, to cope with the era of environment-friendly green growth, thestudy on technology of green space development and Net-zero energy tunnel
technology producing energy on its own required for operation of tunnel has
to be put the first, and space utilization technology for sustainable
development of new space have to be also developed. Table 2 shows thesummary of core technology development items for construction of urban
deep underground infrastructure in downtown area.
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Table 2: Core Technologies for Construction of Urban Deep Underground
Transportation Infrastructure in Downtown Area

Green Strategy
Technology

Cutting-edge
Application
Technology

Core Base
Technology• Construction technology of green underground passage- Net-Zero Energy, tunnel technology- IT-based environment-friendly ventilation/disaster prevention
technology- Environmental impact reduction design/construction technology• Human-centered space utilization technology- Human sensibility ergonomic green design technology- Underground road-downtown area connection utilizing
technology- Environment-friendly green zone development technology• IT-based traffic control technology- Underground road traffic control and management systemdevelopment technology- Intelligent traffic system(ITS) construction technology• K-SMART tunnel technology- Urban deep underground tunnel water circulating systemtechnology- Underground road multipurpose utilization technology• The next generation metropolis environment-friendly express/safety
tunneling technology- Drilling equipment developing and manufacturing technology- Complex ground corresponding TBM design/operation
technology- The next generation metropolis drilling technology• Underground road integrated design/construction technology- Underground road standardization technology- Urban deep underground passage survey/exploration technology- Underground road solid facility safety design/construction
technology• Large cross-sectional duplex tunnel design/construction technology- Duplex tunnel design/construction technology- Duplex tunnel construction and maintenance equipment
development technology

5. CONCLUSIONS
It is said that the utilization of urban deep underground is unavoidable toexpand underground transportation network in Seoul metropolitan area andchange the space above the ground into green zone. Since the project on
construction of urban deep underground road network and great train
express in metropolitan area is huge project which is unprecedented
worldwide, new conceptual definition in all related areas like law, system,
tunnel, construction technology, ventilation and disaster prevention
technology is required. Until now, many debates on law, system and disasterprevention have been made rather than tunnel construction technologies, butfrom now on, the establishment of research and development strategy after
figuring out various problems in the course of constructing urban deep
underground transportation infrastructure in downtown area is urgently
needed.

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REFERENCES
C.Y. Kim, S.B. Yim, et al., 2011, Urban Deep Underground
Transportation Infrastructure Project in Korea and Technical Requirements,
Proceedings of the ITA-WTC 2011 in Helsinki , Finland, 295 pp.
C.Y. Kim, S.B. Yim, et al., 2011, Urban Deep Road Tunnel
Construction Project in Korea and Technical Requirements, Proceedings ofTwelveth East Asia-Pacific Conference on Structural Engineering andConstruction(EASEC-12) in HongKong, 325 pp.
Seoul Metropolitan, 2009, The Master Plan of the U-SMARTWAY in
Seoul Metropolitan Area, Reports of Seoul Metropolitan

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136

New Technologies for Urban Safety of Mega Cities in Asia

Development of early warning system
in Maldives
Mahmood RIYAZ1,5, Dugkeun PARK2, Chang-Yong KIM3,
Sung-Wook KIM4 and Kyung-Ho PARK5
1
Environment Research Centre,
Ministry Environment Energy and Water,Maldives,mahmood.riyaz@gmail.com
2
National Emergency Management Agency, 253-42, Gongdeok 2-dong,
Mapo-gu, Seoul, Korea
3
Korea Institute of Construction Technology, Daehwa-dong, Goyangdae-ro,Ilsanseo-gu, Goyang-si, Gyeonggi-do, Korea
4
Geo-Information Research Group Co., Ltd., 1489-4, Geoje1-dong,
Yeonje-gu, Busan, Korea
5
Asian Institute of Technology, P.O. Box 4, Klong Luang,
Pathumthani 12120, Thailand

ABSTRACTThe Early Warning System (EWS) has been developed to address thenatural disaster risks in Maldives. Prior to 2004 Indian Ocean Tsunami,
disaster the people of Maldives were not sentient about the disaster risks
and so there was no consideration of EWS for the country. Soon after thedisaster, a risk profile of the Maldives was developed and emergency
response measures for various sectors, such as tourism, communication,
education and defense etc. were considered. This study deals with thedevelopment of the EWS for the various sectors in Maldives. The National
Early Warning System in the Maldives (NEWSM) has been developed inthree main phases: (1) Phase I, establishment of the monitoring system of
the surface meteorological conditions and seismic event occurrence; (2)Phase II, strengthening the monitoring system established in phase I by
making it automated metrological monitoring system; (3) Phase III,
confirmation of the information flow, establishment of backup andalternative electric power and telecommunication systems and linkages withinternational organization. Disaster warning messages from the NEWSM istransmitted to the national, regional, atoll and island offices through acommercial communication system, mainly computer network and hotline(leased lines). The only means of dissemination of disaster advisories andwarning to general public is broadcasting through radio and television.
Radio Trunking Network that uses TETRA technology is used as backup
network.
While Maldives is exposed to various hazards, such as climate change (therisk from rising sea-level), gale force winds, storm surge, torrential rain,earthquake and tsunami, the established EWS seems to be focused only on
the distant tsunami risk. The current EWS seems not very effective incommunication and message dissemination. The establishment of proper1371

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mechanism to outreach to the general public, remote communities andislands is needed by using more user friendly mechanisms.
Keywords: Early Warning System, Disasters, Maldives

1. INTRODUCTION
Maldives is an 800 km long archipelago, precariously located in the centerof the Indian Ocean, and consists of more than 1200 low-lying coral reefislands with flat topography and grouped into 26 atolls (Figure 1). These
low-lying islands are formed of accumulations of biogenic material
provided exclusively by the local reef platform. The height of islands varies
between 1~2 m with a maximum spring tide range of 1.2 m and the meanhigh water spring tide level is approximately 0.6 m above mean sea level.

Figure 1: Location map of Maldives
Prior to the 2004 Indian Ocean Tsunami, the disaster management in
the Maldives was merely focused on the impact of global warming and sea
level rise. However, the disaster risk profile of Maldives, developed by
UNDP (2006), indicated that disaster risk scenario of Maldives cangenerally be described as moderate due to low probability of hazard
occurrence and high vulnerability from exposure due to geographical,
topographical and socio-economic factors. Apart from the exposure to the
obvious risks of seal level rise associated with the global climate change,
Maldives is also occasionally prone to various natural hazards such as
droughts, high waves caused by cyclones, gale force winds, storm surge,
torrential rain, earthquake and tsunami. Like many countries in Asia, the2004 Indian Ocean Tsunami was a wakeup call for the people of Maldives
who were not sentient about the impending threats of natural disaster risks.

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The devastating impacts of the disaster was also a test of resilience for thecountry and made people discern about the importance of adopting
measures to pragmatically integrate disaster knowledge, disaster risk
reduction measures and management perspectives into the government’splanning and policy agenda.
Aftermath of the 2004 Indian Ocean Tsunami and following the UN
Flash Appeal for the Maldives, many UN Agencies, NGOs and bilateralcountries provided assistance and initiated development of disaster risk
management programmes. The focus of the progammes is to develop multihazard Early Warning System (EWS), preparedness planning, institutional
and policy development needed for disaster management, emergency
response capacity enhancement safe area development, vulnerability andnatural hazard risk assessments. Those initiatives resulted in development ofa national plan on disaster management and emergency response measuresfor various sectors, such as tourism, communication, education and defense
etc. were established (MNDF, 2008).
This study focuses on the multi hazard EWS developed in theMaldives since the occurrence of 2004 Indian Ocean Tsunami. The study
evaluates the effectiveness and functionality of the existing EWS.
Particularly the ability to disseminate and coordinate the disaster warning
messages to the national, regional, atoll and island is considered by taking
into account recently established decentralized local government system in
the Maldives.
2. METHODS
The qualitative and quantitative information were collected by combining
the secondary sources (written reports, evaluations, media) and primary
information (collected through Maldives Meteorological Center).
The existing reports on disaster risk management, hazard early
warning system, preparedness planning, institutional and policy
development on disaster management, emergency response capacity
enhancement, safer island program, socio-economic and Environmental
vulnerability assessments, detailed national and island specific risk
assessments, training and capacity building workshops and the emergency
telecommunication plan were reviewed. Because almost of the above
mentioned reports were developed after the 2004 Indian Ocean Tsunami,
they are mainly focused on the tsunami early warning system.
3. RESULTS
In 2008, Maldivians embraced a new constitution that introduced
democratic reform and decentralized administrative system. Instead of 19
Atoll-based administrative system in the past, now the country is divided
into 7 provinces governed by elected autonomous province councils. With

Development ofDevelopmentof early
early warning
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Chiangmai,these changes, the disaster management structure of the country and theestablished EWS need to incorporate the new institutional and governancerelated developments in the Maldives. Recently developed Strategic
National Action Plan (SNAP) on Disaster Risk Reduction and Climate
Change Adaptation is designed to address disaster risk reduction andclimate change adaptation and integrate the existing EWS into the new
governance structure of the country.
3.1 Existing National Early Warning System in the Maldives (NEWSM)
National Meteorological Centre (NMC) of Maldives has the national
mandate to monitor meteorological, oceanographic and seismologicalactivities, as well as analyze and predict extreme hydrometeorological andseismic events, which may affect the country and to issue early warnings ofnatural disasters as per the EWS established. The NEWSM has beendeveloped in three main phases (ADRC, 2005):
3.1.1 Phase I (2005-2006)
Prior to the 2004 Indian Ocean Tsunami, there was no seismic andwave monitoring network in the Maldives. The surface meteorologicalobservations were conducted in five islands, Hulhulè, Hanimaadhoo,
Kadhoo, Kaadedhdhoo and Gan Islands. Equipment used for observations inthese stations were outdated, 12~30 years old. So they were not capable ofproviding continuous monitoring and online real-time displays and could
not be synchronized with modern equipment. Most data readings andmeasurements were performed manually by the local staff in 1~3 hourfrequency. The observation results were collected at the NMC in Hulhulè
Island by using a modem system connected to the commercial telephonelines. Daily weather forecast as well as weather warning information was
disseminated to the public from NMC.
As part of strengthening the existing monitoring system of the surface
meteorological conditions, tide and wave variations, and seismic event
occurrence, automated data processing functions and continuous monitoring
systems of the output of exiting tide gauges were established. A new wave
gauge, a short-period seismometer and a weather radar system were
installed in Hulhulè Island. Observation data from these equipments wereautomatically transmitted to the NMC. The data, processed at the regional
meteorological offices across the Maldives, was linked with NMC and, via
the Regional Telecommunication Hub (RTH), transmitted to New Delhi andother regional offices.
3.1.2 Phase II (2006-2008)
As part of the NEWSM development, 17 automated weather stations
across the Maldives were installed. Two broadband seismometers, two wave
gauges and two tsunami GPS buoy were installed. Real time observation
data from the equipment was transmitted to the NMC and themeteorological offices across the country. A system for acquiring
meteorological satellite imagery directly from the METEO-SAT was
installed. The seismic data from the stations were sent to IOTWS and

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ICUS Report 56transmitted to the GFZ receiving station at Jakarta, Indonesia to monitor
earthquakes across the region. The NEWSM’s Global Telecommunication
System (GTS) was equipped with a new function to allow automated inputof observation data.
3.1.3 Phase III (2008-2010)
The most important aspect in natural disaster situation is to ensure thatearly warning information is transmitted throughout the nation in a timely
and effective manner. The priority would be given to disseminate warning
to national level and mass media then to regional provinces, Atoll and island
communities. Figure 2 shows the flow of early warning information issued
by the NEWSM across Maldives.
As part of the disaster preparedness, efforts were made to use
alternative electric power particularly for the operation of equipment used
for meteorological observations in the NMC (Anon, 2006). All theautomated weather stations were solar powered and fully functional 24hours, while some equipments in the regional meteorology offices were
solar powered. National plan on emergency telecommunication incorporated
dissemination of emergency alert via broadcasting (EAB), bulk SMS on
mobile network, Radio Trunk Network that uses TETRA technology,
priority calling and national roaming and use of existing equipment (HF,
VHF, CB) for communication remote communities and vessels in the ocean(Anon, 2006). Also the NMC has established hotline between itself andmain focal points, National Disaster Management Centre (NDMC),
Maldives Police Service (MPS), Maldives National Defense Force (MNDF)
and mass media.

Province Offices
Atoll Offices

Regional & International,
WMO, New Delhi,
PTWC, JMA, INCOIS,RIMES & JATWC

Observation Data
HA. Uligam
Hdh. Hanimadhoo
HDh.Makunudhoo

Sh. Feevak

R.Vaadhoo

GTS, RTH , Fax
K. Kaashidhoo

Island Offices
NMC, Maldives EWS

K. Vabbinfaru
Adh. Rangali
F.Nilandhoo

Public & ruralcommunities
Hospitals,
Schools, Privatecompanies etc
Fisheries,
Tourism
Ports, Harbors
Utility companies,
Aviation transport

Warning Messages
dissemination via,
Hotline, Fax, SMS
Internet

K. Hulhule
K. Male’V.FulidhooDh.Hulhudheli

L. Kadhdhoo

GA.Villingili

President’s Office
NDMC, Mass Media(TV, Radio news)
MNDF & MPS, Gov.
Ministries

GDh.Kaadeedhdho

S.Hithadhoo

GDh.Gadhdhoo
Gn.Fuahmulaku
S.Hulhumeedhoo
S.Gan

NMC Regional offices
Automated weather
Stations

First order Emergency Transmission
Second order Emergency Transmission

Figure 2: Flow of early warning information

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October 2011, Chiangmai, Thailand

October
2011,
Mai,Thailand
Thailand
OctoberOctober
2011, Chiang
Chiangmai,
2011, Chiangmai,
ThailandThe NMC established criteria for NEWSM for multi hazards
generated from hydrometeorologcal and seismic condition. Figure 3 showsThe
establishedcriteria
for forNEWSM
for meanmultihazards
The NMCestablishedcriteria
NEWSM
for
multi
hazards
the NMC
warning
alert
levels,description
and
the
of
information
generatedfromhydrometeorologcal
andseismiccondition.
Figure3showsgeneratedfromhydrometeorologcal
andseismiccondition.
Figure3showsdisseminating to the public.
the warningalert
levels,description
and
the
mean
of
information
the warning alert levels, description and the mean of information
disseminating
to the topublic.
disseminating
the public.
Wind Speed 23-30 mph
Wind
Speed
23-30
Wind Speed
23-30>30
mph
Rainfallmmmph

Alert level 1
White
Alert levelAlert
1 level 1
White White

Alert level 2
Alertlevel 2
Yellow
Alert levelYellow
2
Yellow

Alertlevel
level3 3
Alert
Red
Red

Alert level 3
Red

Alert
AlertLevel
Level4 4
Green
Green

Alert Level 4
Green

Rainfall>30 mmRainfall>30 mmHigh tide wave/swells
Hightide wave/swells
High tidewave/swells
Distanceearthquake 7. 0
magnitude no tsunami
Distanceearthquake
Distanceearthquake
7. 0 7. 0
threatmagnitude
no tsunami
magnitude no tsunami
threatthreat Wind speed 30-40 mph
Wind speed 30-40 mph
Wind speed
30-40
Heavy
rainmphfor >2 hours
Heavy rain for >2 hours
Heavy rain
for >2hours
Severethunderstorm
Severe thunderstorm
Severe thunderstorm
Tropical cyclone within
Tropical
cycloneeffective
are awithin
Tropical
cycloneeffective
arewithinaeffective Significant
are atidal or swell
Significant
waves tidal or swell
wavestidal or swell
Significant
waves Distant earthquake 8.0
Distant
earthquake
8.0
magnitude
potential
magnitude
potential
Distant earthquake
8.0
tsunami threattsunamithreatmagnitude
potential
tsunami threat
Flush flood threat
Flush flood threat

Issue Alert 1,
SMS to Focal
Alert
IssueIssue
Alert
1, 1,
pointsSMS
toFocal
SMS to Focal
pointspointsEW Information
dissemination
Information to the
EWEW
Information
public andtomass
dissemination
the media
dissemination to the
ViaandEAB
publicmass media
public and mass media
Via EABVia EAB
Issue Alert 2,

IssueHotline
Alert 2,FAX SMS
IssueHotline
Alert
2,FAX
task
forceSMS
EOHD
taskFAX
force EOHD
HotlineSMS

task force EOHDFlush flood
threatTropical
cycloneTropical
cyclone3, Hotline
IssueIssue
AlertAlert3, Hotline
FAX
SMS
Internet
Tropical
cycloneFAX
SMSInternet
mass mass
Destructive
tidal
/
swell
Destructive tidal / swell
Issue
Alert
3,
Hotline
media
task
force
EOHD
media task force EOHD
waves
/ storm
surgeswaves/ storm
surgesFAXSMSInternetmass
Destructive tidal / swell
wavesDistant/ storm
surgesDistant
earthquake=>8.0 media task force EOHD
earthquake=>8.0
magnitude
tsunamithreatmagnitude
tsunamithreatDistant earthquake =>8.0
magnitude tsunami threat
Weather
Condition
Weather
Condition
improved
improved
CancelWarning
CancelWarning
Weather Condition
improved
Tsunamithreatdoesdoes
TsunamithreatCancel Warning
notnotexistsexists
Tsunami threat does
not exists

Figure 3: Multi hazard alert levels, description and meaning of information
Figure 3: Multi hazard alert levels, description and meaning of information
dissemination to the publicdissemination to the public
Figure 3: Multi hazard alert levels, description and meaning of information
dissemination to the public

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4. DISCUSSIONSThe NEWSM was developed by using fairly good three approaches. The
development of the NEWSM initiated soon after the 2004 Indian Ocean
Tsunami. Thus, greater emphasis was given in the NEWSM on tsunami
early warning rather than addressing multi hazards. This aspects is clearlyvisible in the emergency response plans and standard operational procedures,developed to address disaster risks in various sectors such as tourism(UNDP, 2005a), fisheries (FAO, 2005), telecommunication (Anon, 2006),
schools (MoE, 2009), housing development (UNDP, 2005b) and disasterrisk profiling of various islands (UNDP, 2006, 2008).
In 2006, UN International Strategy for Disaster Reduction (ISDR)
emphasized that sustainable EWS requires community based or people
centered, and gender sensitive approaches in the establishment of EWS.
Critical areas for establishing EWS are (UN/ISDR, 2004): (a) governanceand institutional arrangements, (b) risk knowledge, (c) monitoring andwarning systems, (d) dissemination and communication, (e) response
capacity, and (f) gender aspect. The following section will discuss these
critical areas in the context of the NEWSM.
4.1 Governance and Institutional Arrangements
The Government of Maldives altered its approach to disastermanagement since 2004 and shifted from more emphasis on relief andrehabilitation to a more proactive integration of mitigation and preparedness.
The institutional arrangement for disaster management has been formulated
in the Disaster Management Act of Maldives. The Act is under discussion at
the Parliament. The Act sets the necessary legal and institutionalarrangements with appropriate provisions on integrating decentralization,
providing fast relief measures and gives the NDMC legal powers to conduct
risk management activities. The Sector Specific National Disaster
Management Policy and Plan have been formulated with establishment of
EWS and clearly spelled out Standard Operation Procedures (SOP) in
various sectors. The NMC has the national mandate for issuing early
warning. However, roles of other individual agencies, institutions and thecoordination mechanism with relevant Government authorities to operate
and integrated EWS is still very vague. Linkages with the different
administrative levels and the functional way for various committees in an
emergency situation are not very clear. Figure 4 provides an overview of themain EWS functions, distributed across main institutional actor in Maldives.
4.2 Risk Knowledge
In the existing disaster management structure of Maldives, risk
warning assurance falls under the mandate of the NMC. The meteorologicalcenter only has the capacity for collection and analysis of weather andseismological data. Instead of heavily relying on a single institution, theNMC needs to be changed and efforts should be made to strengthen theDevelopment ofDevelopmentof early
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systematic collection, sharing and analysis of the data on multiple hazards
and vulnerabilities by different sources, and disseminate knowledge throughtraining and education. The existing information on hazards is in varying
data formats and within multiple sources and institutions. To gain further
knowledge on disasters, there is a need to use modern tools to analyze
historical data for the prediction of future disasters. Risk assessment,
conducted after the 2004 Indian Ocean Tsunami to understand the socioeconomic and environmental vulnerabilities, is far from complete. The
process of translation of assessment suffers from weak enforcements andlack of political willingness to integrate them into the development
strategies and plans.
Risk Knowledge
Monitoring and Warning System
NMC, NDMC, Ministry of Housing and
NMC, NDMC, Regional and international
Environment, EPA, Ministries ofAgencies, Ministry of Housing and
Fisheries and Agriculture, Ministry of
EPA, Ministry of Fisheries,
Environment,
Tourism, Ministry of Health, Department
Ministryof
Tourism
Ministry of Healthof National Planning, Maldives National
Maldives
National
DefenseForce(MNDF)
University, Schools, Private sector,
Maldives
PoliceServices(MPS),Media, provinces, Atoll & island offices
Governance andProvinces Atoll & Island offices
Institutional
Arrangements

Response Capacity
NDMC, NEOC, MNDF, MPS, Ministryof Health, Ministry of Fisheries, Ministryof Tourism, REOCs Civil society, NGOs
Maldives Red Crescent (MRC), Private
Sector, Regional and International relief
organizations

Dissemination and Communication
NMC, NDMC, National Emergency
Operation Center(NEOC) Ministry ofCommunication and Transport, Ministry of
Tourism Maldives Telecommunication
Authority, MNDF, MPS, Provincial andAtoll Emergency Operation Centers, Civil
Society NGOs, Ministry of Information andmass media

Figure 4: Institutional roles and responsibilities in the Maldives EWS
4.3 Monitoring and Warning System
Maldives has made remarkable progress towards strengthening hazard
monitoring and EWS. The NMC has established two main networks tomonitor meteorological and seismic hazards. National meteorologicalnetwork is equipped with 5 synoptic stations, 3 tide gauge stations and 20
automatic weather stations. Seismic network is linked with global seismic
network to monitor earthquakes across the region. The NMC continuously
monitors sea level data from local and regional tide gauges as well as DART
buoys deployed in the region. Also the NMC has the capability to receive
high resolution satellite image, Doppler weather Radar data, and has
established redundant communication links with local, regional andinternational centers by using 256 kbps VSAT, 10 mbps internet connection
and satellite phone. Combined impact of climate change and environmental
degradation will result in hydrometeorological disasters of unprecedented

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scales in intensity frequency and extent. Therefore monitoring and early
warning capabilities needs to move closer to the communities to preparethem to deal with these challenges.
4.4 Dissemination and Communication
As shown in Figure 2, the NEWSM has two stage warning message
transmission process. The main weakness of the system is the limited
capacity of provincial government, Atoll council and Island communities
to receive interpret and further broadcast the warning messages. This isbecause clear responsibilities with standard operating procedures (SOP)
have not been properly laid out for information exchange across government,
civil society, media and the general public. In order to improve the existing
EWS dissemination and communication to verify that the warning havereached the communities at risk, a feedback mechanism needs to beestablished.
4.5 Response Capacity
A warning system is ineffective if people do not know what to do next.
EWS should continuously seek to improve the ability of people to responddisaster at regional, Atoll and Island level, incident command systems and
SOPs. Disaster preparedness and response plans need to be developed
utilizing hazard and vulnerability maps. Maldives is in the process ofdeveloping island vulnerability GIS for the country. Frequency ofevacuation drills are still very low more work is needed to reach remoteisland communities.
4.6 Gender Aspects
Neither the draft disaster management act nor the national disastermanagement plans and policies address gender explicitly. The existing
institutions can ensure woman participation in EWS and employ a gendersensitive approach by considering specific concerns such as physicalstrength, security and protection.
5. CONCLUSIONSThe EWS of Maldives, developed in three phase approach, has been
described in this study. The existing EWS of Maldives is focused ontsunami early warning rather than multi hazards. The study found that
following issues needs to be addressed to ameliorate the existing EWS:
(1) Enactment of Disaster Management Act of Maldives, developmentof a disaster management plan and schema addressing end-to-end multihazard EWS, identification of all institutional actors and their roles,
coordination mechanism with relevant Government authorities to operate
and integrated EWS. Strengthen the disaster planning capacity of provincial

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councils, atolls and island and integrated assessment to fill the capacity gaps
in the existing Early Warning System.
(2) Systematic collection, sharing and analysis of data on multiple
hazards and vulnerabilities by different sources and disseminate knowledge
through training and education. Develop a reliable database on hazards in
the Maldives and consolidate the existing information on hazards frommultiple sources and institutions to agreeable formats. Convert risk
assessment findings into standards codes and regulations and integrate theminto the development strategies and plans.
(3) Strengthen the capacity of MNC to be able to analyze and provide
timely disaster warnings. Monitoring and early warning capabilities needs tomove closer to the communities to prepare them to deal with the challenges
and impending threats of climate change.
(4) Develop the capacity of provincial government, Atoll council andIsland communities to receive interpret and further broadcast the early
warning messages. Upgrade the existing communication infrastructure to
the international standards for efficient data exchange. Develop a feedback
mechanism to improve the existing EWS dissemination and communicationof the warning to ensure that EW message reaches islands at risk.
(5) Establish Emergency Operation Center (EOCs) at regional, Atolland Island level, incident command systems and SOPs to improve theresponse capacity and ability of people to respond disasters. Conduct more
frequent evacuation drills, build and maintain people’s risk awarenesscoping capacities.
(6) Ensure that participation in the EWS employs a gender sensitive
approach considering specific concerns such as physical strength, security
and protection.
REFERENCES
Anon, 2006. National plan on early warning dissemination andemergency telecommunications, Technical Committee on Early Warningand Emergency Telecommunications, Unpublished report, 24 pp.
ADRC, 2005. Report on the early assessment of early warning
systems in the Maldives, Asian Disaster Reduction Centre, 125 pp.
FAO, 2005. Fisheries tsunami emergency programme, Maldives,
Fisheries sector rehabilitation mission report, Project: OSRO/MDV/502/JPN,
18 pp.
Ministry of Education (MoE), 2009. Guide for school emergency
operations plan Maldives. School Health and Safety Section, Ministry of
Education, 93 pp.
MNDF, 2008. National plan on disaster management, Maldives
National Defense Force, Unpublished report,104 pp.
UNDP, 2008. Detailed island risk assessment Maldives, United

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Nations Development Programme Volume I and II, www.undp.org.
UNDP, 2006. Developing a disaster risk profile for Maldives, United
Nations Development Programme,Volume I, www.undp.org.
UNDP, 2005a. Disaster management plan, tourism sector, Republic of
Maldives, Unpublished report, 66 pp.
UNDP, 2005b. Design of safe shelters in Maldives, Disaster Risk
Management Unit, United National Development Programme, 79 pp.
UN/ISDR, 2004. Living with risk: a global review of disaster
reduction initiatives, Volume II, Annexes, New York and Geneva

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Disaster information gathering behavior
after the Tohoku earthquake part 2 :Results of foreign respondents
Michael HENRY1, Akiyuki KAWASAKI2, and Kimiro MEGURO3
Project researcher, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japanmwhenry@iis.u-tokyo.ac.jp
2
Project associate professor,
International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japan
3
Professor and Director, International Center for Urban Safety Engineering,
Institute of Industrial Science, the University of Tokyo, Japan
1

ABSTRACT
After the March 11 Tohoku earthquake, people living in Japan were facedwith confusing and conflicting messages from differing information sources
which created an atmosphere of uncertainty and led many people,
particularly foreigners, to relocate to western Japan or leave the country
entirely. In order to improve the dissemination of information after futuredisasters, a survey was conducted to understand how people in the Kanto
region – the most populous area of Japan and bordering the Tohoku region– received their disaster-related information and how it affected theirdecisions in the aftermath of the disaster. This paper focuses specifically on
the responses of foreigners, as the Kanto region has the highest number offoreigners in Japan and their response in the aftermath of the earthquake –particularly those who returned to their countries – caused various
difficulties for their companies and universities. Responses were received
from more than 850 foreigners. This paper presents a summary of their
responses, compares it to the response of Japanese nationals, and discusses
some initial impressions of the disaster information gathering behavior of
foreigners in Japan.
Keywords: Tohoku earthquake, disaster information, foreigners, social
media, traditional media
1. INTRODUCTION
As introduced in the preceding paper (part one of two), disaster information
is important for providing people with the resources necessary to makeinformed decisions and take actions. However, after the Tohoku Earthquake
there emerged a growing disparity between the information given by
domestic Japanese information sources and overseas sources (Sanchanta,2011). The conflicting information and differing approaches may have1491

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contributed greatly to the response of the foreign community in Japan. Alarge number of foreigners, primarily those located in regions surrounding
the Fukushima Daiichi nuclear power plant, relocated to other areas ofJapan or left the country entirely. This perceived mass exodus spawned theterm “fly-jin,” which is a play on the Japanese word for foreigner, “gaijin.”
The difference between domestic sources and overseas sources may
be explained by the objectives and target audiences of these sources.
Domestic (local) coverage of a disaster is primarily concerned with response
and recovery, and in the case of the Tohoku Earthquake and subsequenttsunami and nuclear disaster, Japanese sources were focused on
disseminating information to people in Japan for reducing panic; thedomestic sources can also help build social connections and provide
emotional support (Perez-Lugo, 2004). While foreigners residing in Japan
are included in this target audience, information from domestic sources isprovided almost exclusively in Japanese language and those foreigners withinsufficient language ability are unable to directly receive such information.
As a result, they turn to information sources provided in languages which
they understand – English or their native language – to gather disaster
information and understand the current situation. Unfortunately, however,
the target audience of overseas sources is not people residing in Japan, but
those people in the region of the overseas sources. Furthermore, theobjective of overseas sources is not response and recovery but focused moreon mitigation – lessons learned – or the effect of the disaster on other areas.
Therefore, foreigners in Japan who were looking for disaster informationfrom overseas sources instead found a perspective which greatly differedfrom the actual situation around them, which may have been a contributing
factor in their post-disaster actions. In addition, foreigners residing in Japan
may also have been under pressure to leave Japan from their overseas
families, who could only receive information from overseas sources which
may not have reflected the actual situation in Japan.
To resolve these problems with differing information, it is assumed
that people sought out different sources of information or accessed different
forms of media. Online information seeking and social media have been
growing as access to the internet becomes more widely available, andliterature has found that these tools have been effective for people seeking
information (Lu et al., 2007). In particular, social media provides a forum
for people to disseminate and discuss disaster issues and information and toconnect to one another (Palen, 2008).
Although there may be a variety of reasons for foreigners’ postdisaster actions, information-related problems may have played a large roleand thus it is important to understand what these problems were and how
they were resolved. The objective of this investigation, as explained in partone, is to examine and clarify people’s information gathering behavior after
the Tohoku Earthquake, to understand the relationship between informationand people’s actions, and to contribute to improving information
dissemination in the future, particularly for reducing miscommunication andmisunderstanding for foreign nationals residing in Japan. This paper – part2
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two of two – presents the survey results of foreigners residing in Japan at
the time of the earthquake and compares them with the results of theJapanese respondents given in part one.
2. SURVEY METHODOLOGY
The survey focused on the behavior of people living in the Kanto region ofJapan. Not only does this region contain Tokyo, the largest metropolitan
area in Japan, but it also has the largest concentration of foreigners residing
in Japan. Figure 1 shows the number of foreigners residing in Tokyo and thesurrounding seven prefectures and the distribution of foreigners in the Kanto
region by nationality.
Tokyo

India
2%

415.1

Kanagawa

173.0

Saitama

123.6

Chiba

115.8

Ibaraki

44.9

Tochigi

34.2

Yamanashi

16.6
0

Others
13%

China
34%

3%

56.4

Gunma

Vietnam2%
Thailand
3% USA

UK
1%

Peru
3%

Total: 979.5

150 300 450 600
Population (thousands)

Brazil7%
Philippines
11%

Korea
21%

Figure 1: Number of foreigners in Kanto region by prefecture (left)and distribution by nationality (right) as of 2009
Data source: Ministry of Justice, 2009
Data on disaster information gathering behavior were collected using
an online survey prepared in nine languages (Japanese, English, Chinese,
Korean, Portuguese, Nepalese, French, Thai, Vietnamese). The survey
contents and distribution methodology are described in full in the preceding
paper (part one).
3. SAMPLE CHARACTERISTICS
The survey received 860 responses from foreigners representing 73 different
countries. The distribution of the top ten countries is shown in Figure 2,
where it can be seen that respondents from China made up the largest
percentage. The remaining 63 countries made up 33% of the total number of
respondents.

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Others
33%

China
23%
Thailand7%

UnitedNepal
States of2%
AmericaIndonesia
7%3%FranceKorea South
4% Vietnam
6%
Brazil5%5%
United Kingdom
5%

Figure 2: Distribution of respondents by country of origin
The distribution of foreign respondents by their location andoccupation is shown in Figure 3. The majority were from Tokyo, followedby Kanagawa and Ibaraki Prefectures. Students made up the majority of the
respondents, followed by employees at overseas and Japanese companies
and Japanese educational institutions.
Yamanashi
5%

Chiba
4%

Tochigi
1%

Gunma
1%

Saitama6%
Ibaraki
10%

Kanagawa
13%

Tokyo
60%

Others, no
response
19%

Overseas
government
employee
6%

Japanese
educational
institution
employee
7%
Japanesecompany
employee
8%Student
51%

Overseascompany
employee
9%

Figure 3: Distribution of respondents by location (left) and top occupations(right)
The age and income distribution of respondents are shown in Figure 4.
The most responses were received from people in the 20-29 years old range,
with the number of responses decreasing as age increases. The annual
income of respondents fell mostly in the less than 1.95 million yen (approx.
US$24,900) range. These age and income distributions are understandable
in the context of the large number of students which responded to the survey.

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10-19
20-29
30-39
40-49
50-59
60-69
70-79
80 or higher
0

100

200

300

400

500

Number of responses
Less than 1.95 million yen
1.95 to 3.3 million yen
3.3 to 6.95 million yen
6.95 to 9 million yen
9 to 18 million yen
More than 18 million yen
0

50 100 150 200 250 300
Number of responses

Figure 4: Distribution of respondents by age (left) and annual income(right)Note: responses may not add up to the total as these responses were
voluntary
4. SURVEY RESULTS & DISCUSSION
4.1 Information sources
Figure 5 shows the top five most-trusted information sources forforeign respondents. Japanese news sources were the most-trusted source of
information, followed closely by international organizations such as the
IAEA, Red Cross, and so forth. Japanese research/academic institutions, theJapanese national government, and overseas news sources rounded out the
top five. For both foreigners and Japanese, Japanese news sources were themost-trusted source; in the case of the Japanese, however, there was a muchlarger disparity between the top most-trusted sources. Although four of the
top five were the same (albeit in a slightly different order) for both Japaneseand foreigners, foreigners trusted international organizations very highly
whereas Japanese respondents trusted their family, friends, and colleagues
very highly.

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Japanese news source
International organization (IAEA, Red Cross, etc.)
Japanese research/academic institution
National Japanese government
Overseas news source
0

100

200

300

400

500

Number of responses

Figure 5: Top five most-trusted information sources
Figure 6 shows the top five least-trusted information sources. TEPCO
topped the list, followed by overseas news sources and the national Japanese
government. Similar to the case of Japanese respondents, sources whichwere ranked in the top five most-trusted sources also ranked in the top five
least-trusted sources, such as overseas news sources, the national Japanese
government, and Japanese news sources. The top five least-trusted
information sources were the same for both foreigners and Japanese
respondents.
Tokyo Electric Power Company (Tepco)
Overseas news source
National Japanese government
Japanese news source
Third party other than f amily, f riends, colleagues, etc.
0

100

200

300

400

500

Number of responses

Figure 6: Top five least-trusted information sources
4.2 Media & language for information acquisition
Figure 7 shows the media and language which people used for
acquiring disaster information. Japanese television and English traditional
internet media were the most-utilized sources, followed by Japanesetraditional internet media, English television, English social media, andother language traditional internet media. English-language was utilized
more than Japanese or other languages for most types of media except
television, radio, and inter-personal. For the case of inter-personalcommunication, other language was the most-utilized means, which can beunderstood in the context of the large number of non-native English
speakers in the survey sample. While both Japanese and foreign respondents
primarily utilized television and traditional internet media, Japanese
respondents relied more highly on printed matter compared to foreigners.

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Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

500

600

Number of responses

Figure 7: Utilized media and language for disaster information acquisition
Figure 8 shows by what media and language foreigner respondents
would prefer to receive disaster information. English traditional internet
media is the most-preferred media, followed closely by Japanese andEnglish television. In contrast to Japanese respondents, foreigners had little
preference for radio or printed media, understandable as these media areprimarily only widely available in Japanese. Except in the case of television,
English was the preferred language for acquiring disaster information.
Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

500

600

Number of responses

Figure 8: Preferred media and language for disaster informationacquisition
4.3 Importance of information
Figure 9 shows the importance of information types for foreigners as
it changed over time. On the first day, the safety of family and friends wasby far the most important information. Although foreigners were also
concerned about the earthquake and tsunami damage and transportation
systems, they were much less concerned about these two types ofDisaster information gathering behavior after the Tohoku Earthquake Part 2: Results of foreign
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information, relative to their concern about safety of family and friends,
than Japanese respondents were. By the first week, there was a large jump in
the importance of information related to radiation level and risk, food andwater supply, government response, electricity and other utilities, andschool and business continuity. Except for radiation level and risk andgovernment response, this change in importance for foreigners was muchdifferent than the change for Japanese nationals, for whom the importanceof most information increased only slightly or decreased. By the second
week, however, the importance of all the information types had decreased
from the first week, with radiation level and risk remaining the mostimportant information type.
During the f irst day
During the f irst week
During the second week
Saf ety of f amily, friends, etc.
Earthquake & tsunami characteristics
Earthquake & tsunami damage
Radiation level & risk
Government response
Evacuation & shelters
Food & water supply
Electricity & other utilities
Transportation systems
School & business continuity
0

200

400

600

800

Number of responses

Figure 9: Importance of information types over time
4.4 Problems related to information
Figure 10 shows what information foreigners found to be unavailable,
unclear, or hard to understand over the same time period. For the first day,information related to radiation level and risk was the hardest to find or
understand, followed by the safety of family and friends and government
response. In contrast, Japanese respondents had a harder time finding or
understanding information related to transportation systems, perhaps
because it had higher importance to Japanese respondents on the first day.
By the first week, the difficulty in finding or understanding information
related to radiation level and risk, government response, food and watersupply, and electricity and other utilities had increased from the first day,following the increase in importance in these types of information over thesame time period. From the first to second weeks, the difficulty in finding or
understanding information decreased for all information types, similar to theJapanese respondents.

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During the f irst day
During the f irst week
During the second week
Saf ety of f amily, friends, etc.
Earthquake & tsunami characteristics
Earthquake & tsunami damage
Radiation level & risk
Government response
Evacuation & shelters
Food & water supply
Electricity & other utilities
Transportation systems
School & business continuity
0

200

400

600

800

Number of responses

Figure 10: Unavailable, unclear, or hard to understand information overtime
Figure 11 shows the reasons why the previously-discussed
information was unclear or hard to understand. Similar to the Japanese case,the primary reason was that people were confused by conflicting or differing
information, followed by the inability to access information due to mobile
congestion, power outage, etc. However, for foreigners the inability tounderstand information due to a lack of language comprehension was thethird-highest reason, whereas this reason was barely observed for Japanese
respondents.
Was conf used by conf licting or differing inf ormation
Unable to access inf ormation due to mobile congestion,
power outage, etc.
Couldn’t understand inf ormation due to lack of language
comprehension
Couldn’t understand inf ormation due to dif f icult or
unf amiliar terminology
Unable to f ind the inf ormation due to dif f iculty insearching or locating it
Other
0

200

400

600

800

Number of responses

Figure 11: Reasons information was unclear or hard to understandFigure 12 shows what media and language foreigners turned to inorder to clarify problems they had with information. English traditional
internet media was the most preferred method, followed by Japanese
television, English social media, and Japanese and other language traditional
internet media. The media type for foreigners was similar to that of Japanese
Disaster information gathering behavior after the Tohoku Earthquake Part 2: Results of foreign
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respondents, but the primary language was generally English except for
television. Interpersonal communication in other languages was also highly
rated.
Television
Radio
Printed media (magazines, newspapers, etc.)
Inter-personal (f ace-to-f ace, telephone, etc.)
Traditional internet media (websites, inf ormation portals,
etc.)
Direct communication tools (email, video chat, instantmessenger, etc.)
Social media (social networking sites, blogs, etc.)

Japanese
EnglishOther language

Crisis mapping (Google Crisis Response, sinsai.inf o,
etc.)
0

100

200

300

400

500

600

Number of responses

Figure 12: Media and language for clarifying information problems
4.5 Early warning system and rotating blackouts
The distribution of foreigners who were familiar with the Japanese
Earthquake Early Warning System and whether respondents could properly
receive information on the rotating blackouts is shown in Figure 13. In
contrast to the Japanese respondents, slightly more than half of the foreign
respondents were unfamiliar with the early warning system. The distributionof whether people could receive blackout information was, however, similar
to Japanese respondents.

No
56.9
%

Yes
43.1
%

Not
applicable
15.8%

No
25.7%

Yes
58.5%

Figure 13: Distributions of whether respondents were familiar with theearly warning system before the earthquake (left)
and whether they could receive information on the rotating blackouts (right)
4.6 Post-disaster relocation & usefulness of information
The survey also asked people whether they remained in the Kanto area,
relocated to another area of Japan, or left Japan within two weeks after theearthquake. In Figure 14, it can be seen that, among foreigners, most people
chose to remain in the Kanto area, but a large number also chose to leave
Japan. It can be seen in Figure 15 that, of those who left or relocated, thenumber increased from within 1 day to within 1 week, then decreased again.

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Although the number of foreigners who left or relocated was much greaterthan the number of Japanese in this survey, the timing of leaving or
relocating followed a similar pattern.
Remained in the Kanto area
Lef t Japan
Relocated to another area of Japan
0

100

200

300

400

Number of responses

Figure 14: Distribution of whether respondents stayed, relocated, or left
Within 1 day
Within 3 days
Within 1 week
Within 2 weeks
Af ter more than 2 weeks
0

50

100

150

200

250

300

Number of responses

Figure 15: Timing of relocation or leaving
Figure 16 shows that the main reason for whether foreigners stayed,
relocated or left was that it was a personal decision. Unlike the case of theJapanese respondents, where personal decision was by far the primaryreason, a relatively large number of responses for family request and job
obligation were also received. Overall, disaster-related information appeared
to be somewhat useful for foreigners as well as Japanese respondents, as
shown in Figure 17.
Personal decision
Family request
Job obligation
Concern f or babies or children
Other (please specif y)
Government directive
Unable to leave
0

100

200

300

400

500

600

Number of responses

Figure 16: Reasons for staying in Kanto, relocating, or leaving Japan

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Very usef ul
Somewhat usef ul
Slightly usef ul
Not usef ul
0

100

200

300

400

500

Number of responses

Figure 17: Usefulness of disaster-related information for decision making
5. INITIAL IMPRESSIONS AND FURTHER ANALYSISOne of the goals of this investigation is to improve the dissemination ofdisaster-related information after future disasters, particularly considering
the needs of foreigners residing in Japan. In order to make recommendations
towards such improvement, it is necessary to consider from which sources
information should be disseminated and by what media, as well as what
information is important and how the importance of that information
changes over time.
Similar to the case of the Japanese respondents, several sources whichwere in the top five most-trusted information sources were also in the topfive least-trusted sources. For foreigners, the most-trusted sources whichwere not in the top five least-trusted sources were internationalorganizations and Japanese research/academic institutions. Foreigners may
have turned to international organizations as these are experienced inproviding support for people in various countries around the world, and thus
are better at disseminating information for a varied audience. Japanese
research/academic institutions were also one of the most-trusted sources forJapanese respondents, suggesting that these institutions may be able to playa strong role in disseminating disaster information targeted not only at
Japanese people but also at foreigners as well.
The media foreigners used for gathering information were primarily inEnglish, except for Japanese television and other language for interpersonalcommunication. Television is useful for disseminating disaster information
as it can provide frequent updates with accompanying visuals anddiscussions, but the majority of domestic television is provided in Japanese
only; this may have driven foreigners to internet-based resources or to theirfriends, family, or colleagues. As English language was preferred forinternet-based media, this may be a possible method for improving
information dissemination. However, as mentioned in part one, these results
may be biased towards people who tend to use the internet regularly, as thesurvey was distributed online.
Similar to the case of the Japanese respondents, the trends ofinformation importance and the unavailability or difficulty in understanding
information were fairly similar over time for foreign respondents. The
results verified that conflicting or differing information was the primary

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reason causing information difficulties, but understanding whether thiscaused foreigners to relocate or leave Japan will require further analysis.
However, compared to the Japanese sample a much larger number offoreigners relocated or left Japan. While the top reason for their action(remaining, relocating, or leaving) was personal decision, the secondhighest reason was family request. This possibly supports the theory thatoverseas families who received information from overseas sources placedpressure on their relatives in Japan to take some action, but these results aregoing to require deeper analysis to determine which reasons correspondedwith which actions.
The next step in analyzing these results will be to more deeply
examine the relationship between demographic factors, such as nationality,
occupation, age, language ability, and so forth, and the information
gathering behavior, as well as the correlation with post-disaster actions. The
results of the deeper analyses should form the basis for therecommendations for improving the dissemination of disaster information.
REFERENCES
Lu, H.Y., Case, D.O., Lustria, M.L.A., Kwon, N., Andrews, J.E.,
Cavendish, M.A., Floyd, B.R., 2007. Predictors of online information
seeking by international students when disaster strikes their countries.
CyberPsychology and Behavior 10(5), 709-712.
Ministry of Justice, 2009. Statistics of registered foreigners. Availablefrom:
http://www.stat.go.jp/data/jinsui/2008np/index.htm (27 September
2011)
Palen, L., 2008. Online social media in crisis events. Educause
Quarterly 3, 76-78.
Perez-Lugo, M., 2004. Media uses in disaster situations: a new focus
on the impact phase. Sociological Inquiry 74(2), 210-225.
Sanchanta, M., 2011. Japanese, foreign media diverge. The WallStreet Journal. Available from:http://online.wsj.com/article/SB1000142405274870351240457620904
3550725356.html (27 September 2011).

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Disaster information gathering behavior after the Tohoku earthquake part 2:
respondents
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Survey on people’s awarenessof Earthquake Early Warning before andafter the 2011 off the Pacific Coastof Tohoku earthquake
Miho OHARA1, Kimiro MEGURO2 and Atsushi TANAKA
1
Associate Professor, Interfaculty Initiative in Information Studies/ Institute of Industrial Science,
The University of Tokyo, Japanohara@iis.u-tokyo.ac.jp
2
Professor, Interfaculty Initiative in Information Studies/ Institute of Industrial Science,
The University of Tokyo, Japan
3
Professor, Interfaculty Initiative in Information Studies,
The University of Tokyo, Japan
ABSTRACTJapan Meteorological Agency started the service of Earthquake Early
Warning (EEW) to the public since October 1, 2007. The warning is widely
broadcasted by TV, radio and mobile phone in the area whose JMA
intensity is expected to be more than 4. In order to make the best use of thelead time before the arrival of strong tremors for reducing casualties,
enhancing people’s knowledge and capacity to take proper actions after thewarning is essential.
There was a small earthquake in Fukushima Prefecture on September 29,
2010. The expected intensity in the Tokyo metropolitan area exceeded 4 andEEW was provided although observed intensity was less than 4. Recently,
the percentage of the people who can get EEW by mobile phones isincreasing. At this earthquake, a lot of people received the warning by
mobile phone in the Tokyo metropolitan area and it became a good
opportunity for making people familiar with EEW. After this, the off the
Pacific coast of Tohoku Earthquake occurred on March 11, 2011 andnumerous aftershocks continued. EEW was successfully provided in Tohoku
area at the main shocks. On the other hand, in the Tokyo metropolitan area,
EEW failed at the main shock but frequently announced at aftershocks.
However, some of the warning at aftershocks failed to estimate intensity
properly due to technical limitation.
In this paper, two questionnaire surveys were conducted to understandpeople’s awareness of EEW. The first one was done after the earthquake in
September 2010 for the people who received the warning by mobile phone.
The second one was done after the earthquake in Tohoku region in March
2011. The change of their awareness was analyzed comparing both results.
Their behavior after receiving the warning was also analyzed and1631

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suggestions for enhancing their capacity to take proper actions after EEW
were obtained.
.
Keywords: early warning, capacity building, questionnaire survey
1. INTRODUCTION
The Japan Meteorological Agency (JMA) began to provide the service ofearthquake early warning (EEW) to the public on October 1, 2007. This is a
new system that quickly analyses seismic wave data observed byseismographs near the epicenter and provides prompt alerts before thearrival of strong tremors (S-waves) as shown in figure 1. For public use,
EEW is provided to the regions where the intensity of shaking was expected
to be greater than JMA 4 in case the maximum estimated intensity is 5
lower. This system aims to mitigate earthquake-related damage by enabling
individuals to protect themselves quickly in various environments such as
houses, offices and factories. A warning is widely broadcasted by television,
radio, mobile phone and loudspeakers.
Transmit observed data

P-waveS-waveS-waveInform of the coming tremors
before their arrival

Seismograph

Focus

Focus

When P-wave was observed

When S-wave arrived

Figure 1: Concept of Earthquake Early Warning
The Iwate-Miyagi Inland Earthquake occurred in the southern inland
region of Iwate Prefecture, Japan at 8:43 JST, June 14, 2008. It was the firstearthquake since October 2007 for which EEW could be successfully
broadcasted before the arrival of strong tremors. The lead time between thewarning and the arrival of strong tremors was around 10-25 seconds in thearea surrounding its epicenter. After this, a small earthquake occurred in
Fukushima Prefecture at 16:59 JST on September 29, 2010. EEW was
broadcasted in the eastern area of Japan as the expected intensity exceeded 4.
It was broadcasted also in the Tokyo metropolitan area although observed
intensity was less than 4. Recently, the percentage of the people who can get
EEW by mobile phones is increasing. At this earthquake, a lot of people
received the warning by mobile phone in the Tokyo metropolitan area for
the first time and it became a good opportunity for making people familiar
with EEW.
The 2011 off the Pacific coast of Tohoku Earthquake occurred at
14:46 JST on March 11, 2011 and numerous aftershocks continued. EEW
was successfully provided in Tohoku area at the main shocks. On the other
hand, in the Tokyo metropolitan area, EEW failed at the main shock but was

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frequently
frequently
announced
announced
at aftershocks.
at aftershocks.
The number
The numberof broadcastedof broadcasted
EEW EEW
from fromMarchMarch2011 to2011
Augustto August2011(62011(6months)months)was 87was
although87 althoughthat numberthat number
from from
October
October
2007 to2007
February
to February2011(41
2011(41months)months)was 17.
wasHowever,
17. However,some someof theof thenumerous
numerous
warning
warning
at aftershocks
at aftershocks
failed failed
to estimate
to estimate
intensity
intensity
properly
properly
becausebecauseseveralseveral
earthquakes
earthquakes
occurredoccurredat theat samethe sametime time
could could
not benot be
identified
identified
separately
separately
or someor someseismometersseismometers
were unusable
were unusable
due todue
long-time
to long-time
powerpower
outageoutage
after theafterearthquake.
the earthquake.
TheseThese
problems
problems
were due
weretodue
technical
to technicallimitation
limitationof EEWof EEWand some
and someof themof werethem solved
were solved
by programby programmodification
modification
after March
after March
2011. 2011.
In thisInpaper,
this paper,
two questionnaire
two questionnaire
surveyssurveyswere conducted
were conducted
to understandto understandpeople’speople’sawareness
awarenessof EEW.
of EEW.
The first
Theonefirstwasonedonewas after
done theafter
earthquake
the earthquake
inin
September
September2010 for2010
theforpeoplethe people
who received
who received
the warning
the warningby mobileby mobile
phone.phone.
The second
The second
one wasonedonewas after
done theafterearthquake
the earthquakein Tohoku
in Tohoku
regionregionin March
in March
2011. 2011.
The change
The changeof theirof awarenesstheir awarenesswas analyzed
was analyzed
comparingcomparingboth results.
both results.
Their Theirbehavior
behavior
after after
receivingreceiving
the warning
the warning
was also
was also
analyzed
analyzed
and andsuggestions
suggestions
for enhancing
for enhancing
their capacity
their capacity
to taketo propertake proper
actionsactions
after EEW
after EEW
were obtained.
were obtained.
2. OUTLINE
2. OUTLINE
OF TWOOF TWOQUESTIONNAIREQUESTIONNAIRESURVEYSSURVEYS
The first
Thequestionnaire
first questionnaire
surveysurvey
was done
was after
done theafterearthquake
the earthquake
in Fukushima
in Fukushima
Prefecture
Prefecture
on September
on September
29, 2010.
29, 2010.
Main Maintarget targetof the ofsurveythe survey
was thewaspeoplethe people
livinglivingin theinTokyo
the Tokyo
Metropolitan
Metropolitan
area (Tokyo,
area (Tokyo,
Saitama,
Saitama,
Chiba,Chiba,
Kanagawa
Kanagawa
Prefectures)
Prefectures)
who received
who received
the warning
the warningby theirby theirown mobile
own mobile
phonephoneororneighbor’s
neighbor’s
mobilemobile
phones.
phones.
The number
The numberof respondentsof respondents
in eachin group
each groupwas wasshownshownin tablein table
1. The1. second
The second
surveysurvey
was donewas doneafter theafterearthquake
the earthquake
inin
TohokuTohokuregionregionin March
in March
2011. 2011.
A questionnaire
A questionnaire
sheet sheet
was sent
wastosent
thetosamethe same
respondent
respondent
as theasfirst
thesurvey.
first survey.
The ratio
The ofratio
theofrespondents
the respondents
who answered
who answered
the second
the second
surveysurvey
was 76.6％(613
was 76.6％(613
peoplepeople
amongamong800). 800).
The number
The numberof theof thegroupgroup
A respondents
A respondents
who answered
who answered
the survey
the survey
in 2011in 2011
was 153.
was Among
153. Amongthem, them,
11 people
11 people
changedchangedtheir mobile
their mobile
phonesphones
and could
and could
not receive
not receive
EEW EEW
asasof Marchof March
2011. 2011.
The number
The numberof the ofrespondents
the respondents
in eachingroupeach group
who answered
who answered
the survey
the survey
in 2011in and2011could
and could
receivereceive
EEW EEW
as of March
as of March2011 was2011shownwas showninintable 1.
table 1.
Table1:
Table1:
NumberNumberof respondentsof respondents
for surveys
for surveys
in 2010in and20102011
and 2011
2011 Survey
2011 Survey
Ratio of the
Ratio of the
Could receive
CouldEEW
receiveby mobile
EEW byphonemobile phone
Could notCould not
respondents
respondents
as of March
as of
2011
March 2011
receive EEW
receive EEW2010 Survey
2010 Survey
who answered
who answeredby mobileby mobile
total
total
ReceivedReceived
at Received
at Received
outside outside
the second
the secondof
as of
home after
home home
after after
home afterphone asphonesurvey survey
March 2011
March 2011
march 2011
marchmarch2011 2011
march 2011
ReceivedReceived
EEW by their
EEW ownby theirmobileown mobileAA
200 142200 142
118
118
91
91
11
11
153
153 76.5
76.5
phones phones
ReceivedReceived
EEW by their
EEW neighbors'by their neighbors'
BB
200 70200 7048
48
42
42
81
81
151
151 75.5
75.5
mobile phones
mobile phones
ReceivedReceived
EEW by their
EEW ownby theirmobileown mobile
C phones
C andphonesexperienced
and experienced
the stop the200
stop 119200 11965
65
52
52
31
31
150
150
75
75
of train of train
D Didn'tDreceive
Didn'tor
receivelisten EEWor listen EEW 200 71200 7149
49
36
36
88
88
159
159 79.5
79.5

on people’s
awarenessof Earthquake
Early Warning
andtheafter
theoff2011
the pacificcoast ofSurveySurvey
on people’s
awarenessof Earthquake
Early Warning
beforebefore
and after
2011
the off
pacific
coast ofSurvey on people’s awareness of Earthquake Early Warning before and after
3 1653
Earthquake
TohokuTohoku
Earthquakethe 2011 off the Pacific Coast of Tohoku earthquake

October 2011, Chiang
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3. RESPONDENTS’ KNOWLEDGE OF EARTHQUAKE EARLYWARNINGAt first, change of respondents’ knowledge of EEW was analyzed
comparing the results of two surveys. All the groups had the same tendency
between 2010 and 2011. Figure 1 shows the result of group A for example.
After the earthquake in September 2010, 50.3% knew both the name of
EEW and that it forecast a strong tremor just before its arrival. After theexperience of the main shock and aftershocks of Tohoku earthquake in 2011,
the ratio increased to be 89.5%. At the survey in 2011, the respondents who
knew neither its name nor its meaning were drastically decreased to be 2.0%.
Figure 8 shows the respondents’ knowledge of methods or conditionsof EEW broadcasting. It is a result of group A for example as all the groups
had the same tendency between 2010 and 2011. The ratio of the respondents
who knew that EEW is broadcasted on TV or by mobile phone increased
after 2010 and exceeded 90% in 2011. On TV, the name of the area wherestrong tremors are expected and the warning message are shown. On theother hand, neither expected intensity nor lead time before the arrival ofstrong tremors is explained. The knowledge on expected intensity or leadtime was low in 2010 but increased especially in 2011. However,knowledge of criteria on intensity at which EEW is broadcasted was still
low. In addition, change in the knowledge of special receiving devices wasvery small although the special receiving devices are important tools forreceiving expected intensity or lead time at home. Enhancing theseknowledges is necessary.

100%

23

3
13

80%
60%

53
137

40%
20%

77

0%
2010

2011

I knew neither its
name nor its
meaning
I knew only thename of EEW
I knew goth thename of EEW and
its meaning

Figure 2: Respondents’ knowledge of EEW

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EEW cannot
EEW cannot
be proviedbe provied
beforebefore
strong strong
tremorsin
tremorsin
the area
thewherearea whereis too close
is tootoclose
the tohypocenters
the hypocenters
SpecialSpecial
receivingreceivingdevicesdevices
can showcanexpectedshow expected
intensity
intensityand leadandtimelead time

92.2 92.2
73.2 73.2
34.6 34.6
30.1 30.1

Trains Trains
stop after
stopreceiving
after receiving
EEW EEW
EEW isEEW
annoounced
is annoounced
in someinfacilities
some facilities
such assuch as
department
department
stores stores

73.9 73.9
71.9 71.9
45.1 45.1
33.3 33.3

EEW canEEW
becan
received
be received
by mobileby mobile
phonesphones
71.2 71.2
Lead time
Leadistime
not shownis not shown
on TV on TV
39.2 39.2
Expected
Expected
intensity
intensity
is not shownis not shown
on TV on TV
20.3 20.3
On TV, On
theTV,
namethe ofnamethe dangerousof the dangerous
and warningand warning
messageare
messageare
shownshown
EEW isEEW
provededis proveded
on TV to
onthe
TV to
area
thewherearea whereexpected
expected
intensity
intensityis 4 is 4
EEW isEEW
provededis proveded
on TV inoncaseTV inmaximum
case maximum
expected
expected
intensity
intensityis 5 lower
is 5 lower
096.7 96.7
2011 2011

81.0 81.0

2010 2010

66.0 66.0
65.4 65.4

92.8 92.8

33.3 33.3
20.9 20.9
39.9 39.9
23.5 23.5

100 2010 3020 4030 5040 6050 7060 8070 9080 100
90 100FigureFigure3: Respondents’
3: Respondents’knowledgeknowledgeof methodsof methods
or conditions
or conditionsof EEWof EEW
broadcastingbroadcasting
4. 4.RESPONDENTS’RESPONDENTS’ATTITUDE
ATTITUDETOWARDTOWARDFAILURE
FAILUREOF OF
EARTHQUAKEEARTHQUAKE
EARLY
EARLY
WARNINGWARNING
AfterAfterthe earthquake
the earthquake
on March
on March
11, 2011,
11, 2011,
numerous
numerous
EEWEEW
was wasprovidedprovided
to to
the public
the public
due dueto continuous
to continuous
aftershocks.
aftershocks.
However,
However,somesomeof themof themfailedfailedto toestimate
estimate
intensity
intensity
properly
properly
becausebecauseseveralseveralearthquakes
earthquakes
at theat samethe sametimetime
couldcould
not benotidentified
be identified
separately
separately
or someor someseismometersseismometers
werewereunusableunusabledue dueto long-time
to long-time
power
power
outageoutageafterafter
the earthquake.
the earthquake.
These
These
problems
problems
wereweredue todue totechnical
technical
limitation
limitationof EEWof EEWand andwerewereannounced
announced
beforehand
beforehand
by Japanby JapanMeteorological
Meteorological
Agency.
Agency.
Here,Here,the knowledge
the knowledgeof technicalof technicallimitation
limitation
beforebeforethe earthquake
the earthquake
and their
and their
attitudeattitudetowardtowardthe failure
the failureof EEWof EEW
werewere
analyzed.
analyzed.
36.5%
36.5%
of theof respondents
the respondents
among
among
all knew
all knewthe technicalthe technicallimitation
limitation
beforebeforeMarch
March
20112011
that that
actualactualintensity
intensity
can canbe morebe moreor lessor less
than thanthe expected
the expected
intensity
intensity
withinwithinthe range
the rangeof intensityof intensity
1. About
1. About
90%90%of theof respondents
the respondents
wishedwishedto useto EEWuse EEW
eveneven
if it has
if it ahasriska ofriskfailureof failure
regardlessregardlessof whetherof whether
they theyknewknewtechnical
technical
limitation
limitation
beforebeforethe theearthquake
earthquake
or not.
or not.
55.4%
55.4%
of theof therespondents
respondents
withwith
the knowledge
the knowledgeof technicalof technicallimitation
limitation
answeredansweredthat thatthey they
would
would
like liketo useto EEWuse EEW
aggressively
aggressively
eveneven
if they
if they
havehavea riska riskof failure.
of failure.
The Theratioratio
decreased
decreased
to beto 35.0%
be 35.0%
without
without
the knowledge.
the knowledge.
It was
It wasverifiedverifiedthat thatfamiliarization
familiarization
withwithtechnical
technical
limitation
limitation
beforebeforethe eventthe eventis importantis important
in inorderorder
to increase
to increase
positive
positive
attitudeattitudein casein casethat EEW
that EEW
fails.fails.

Surveyon people’s
awarenessof Earthquake
Warning
beforeand afterthe 2011
offpacificthe pacificSurveyon people’s
awarenessof Earthquake
EarlyEarly
Warning
beforeand afterthe 2011
off thecoastcoastof ofSurvey on people’s awareness of Earthquake Early Warning before and after
5 1675
TohokuEarthquake
TohokuEarthquakethe 2011 off the Pacific Coast of Tohoku earthquake

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,
100%

0.0
2.7

90%
80%

4.4
8.5

40.6

70%
51.9

60%
50%
40%
30%

55.4

20%

35.0

10%
0%
With Knowledge

I don't have an interest
on EEW
I would not like to use
EEW at all becase of arisk of failure
I would not like to use
EEW becase of a risk offailureI would like to use EEW
even if it has a risk offailureI would like to use EEW
aggressively even if it
has a risk of failure

Without Knowledge

Figure 4: Respondents’ attitude toward failure of EEW
5. RESPONDENTS’ RESPONSE TO EARTHQUAKE EARLYWARNING
Next, respondents’ response to EEW after EEW was investigated. Morethan 80% of each group watched EEW on TV at home after March 2011.
The ratio of the respondents who received EEW at home was highest ingroup A. 88.4% of group A watched EEW on TV and 80.3% received bymobile phone at home. 59.4% received by mobile phone outside home. The
feeling of respondents in group A after receiving EEW at home wasinvestigated. Figure 5 is the comparison of their feeling after earthquakes in2010 and 2011. The ratio of the respondents who thought that strong tremor
would come soon drastically increased from 34% to 86.7%. It shows thatexperience of receiving many EEW after March 2011 led to high awarenessof warning message.
100%
90%

4.6
6.5

0.7
5.6
8.4

80%
70%
60%

I thought it is a flash
news of earthquake
intensity

45.1

50%
86.7

40%

I thought it is due to thefailure of a mobile
phones

I could not understandthe meaning quickly

30%
20%

I thought strong tremor
will come soon

34.0

10%
0%
2010

2011

Figure 5: Respondents’ feeling after receiving EEWFigure 6 shows what respondents in group A did immediately after
receiving EEW at home at the both earthquakes. Most frequent response
after both earthquakes was to get earthquake information from television or

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radio. The second one was to wait and the third one was to inform theirchildren or people near them of the EEW. The ratio of the response for
informing their children or people near them, protect their bodies, protect
their children or elderly family members increased in 2011. The aim of
EEW service is to enable residents to quickly protect themselves before thearrival of strong tremors. Considering this aim, it is said the experiences ofreceiving many EEW after March 2011enhanced their capacity to takeactions for protecting themselves or family members.
I don't remember

1

I could not do anything

1

Others1

I went outside the house or building

1

5
18
3
3

I opend a door or window

24

8

I informed children or others of EEW

34

12

I protected children or elderly people
I hide in a safe place and protect my body

2011

15

4
4

I held furniture or valuables

13

1

I put out fire

2010
22

27

8

I waited and evaluated the situation

49

39

I got information from TV or radio

66

42
0

10

20

30

40

50

60

70

80

90

100

Figure 6: Respondent’s action after receiving EEW
6. RESPONDENTS’ OPINION ON
EARTHQUAKE EARLY WARNINGEFFECTIVENESS

OF

Finally, their opinion on effectiveness of EEW was investigated. The ratioof the respondents who thought EEW was very effective for mitigating
seismic damage was about 40% at the both survey in 2010 and 2011.
Including the respondents who thought it is effective, the total ratio of
positive respondents amounted to be about 90%. When we focused on therelationship between their opinion and the experience of receiving EEWafter March 2011, the ratio of the respondents who thought to be very
effective was 38.5% as shown in figure 7. It was verified that realexperience of receiving EEW enhanced the understanding of effectivenessof EEW. Figure 8 is the relationship between their opinion and theknowledge on technical limitation before the earthquakes. In the chapter
four, we found that familiarization with technical limitation before the event
increased positive attitude toward the failure of EEW. In figure 8, the ratioof the respondents who thought to be very effective was 54.5% in case they
had knowledge on technical limitation before the earthquake. This value
was almost twice of the ratio in case of respondents without the knowledge.
It is concluded that making people familiar with technical limitation led totheir positive attitude toward EEW and it can increase high evaluation on
the effectiveness of EEWSurvey on people’s awareness of Earthquake Early Warning before and after the 2011 off the pacific coast of
Survey on people’s awareness of Earthquake Early Warning before and after
Tohoku Earthquake
1697
the 2011 off the Pacific Coast of Tohoku earthquake

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

0.2
7.2

5.7
5.7

54.1
68.6

Not Effective at all
Not Effective
Effective
Very Effective

38.5
20.0
I received EEW

I didn't receive
EEW

Figure 7: Relationship between understanding of effectivenessand the experience of receiving EEW
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

0.0
3.6

2.1
9.3

42.0
60.9

Not Effective at all
Not Effective
Effective

54.5
27.8
I knew technicallimitation

Very Effective

I didn't know
technical
limitation

Figure 8: Relationship between understanding of effectivenessand the knowledge on technical limitation
7. CONCLUSIONSIn this paper, two questionnaire surveys were conducted to understandpeople’s awareness of EEW. The first one was done after the earthquake in
September 2010 for the people who received the warning by mobile phone.
The second one was done after the earthquake in Tohoku in March 2011.
The change of their awareness was analyzed comparing both results.
After the experience of the main shock and aftershocks of Tohoku
earthquake in 2011, knowledge of EEW among residents drasticallyincreased. Some of the knowledges were low still in 2011 and required to beenhanced. Their behavior after receiving the warning was also analyzed.
The ratio of the respondents who thought that strong tremor would comesoon drastically increased from 34% in 2010 to 86.7% in 2011. It shows thatexperience of receiving many EEW after March 2011 led to high awarenessof warning message. In 2011, the ratio of the response for informing theirchildren or people near them, protect their bodies, protect their children or
elderly family members increased, compared with the answers in 2010. The
experiences of receiving many EEW after March 2011enhanced their

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ICUS Report 56

capacity to take actions for protecting themselves or family members.
People’s awareness level and capacity can decrease easily as time passes
after the disaster. It is very important to keep their awareness level by
education or training in the future.
After the earthquake on March 11, 2011, numerous EEW wasprovided to the public due to continuous aftershocks. However, some ofthem failed to estimate intensity properly due to technical limitation. Fromthe survey, familiarization with technical limitation before the earthquakes
increased positive attitude in case that EEW failed. It also increased highevaluation of the effectiveness of EEW. Continuous information
dissemination on technical limitation is important for positive attitude fortaking action after receiving EEW,
REFERENCE
The Japan Meteorological Agency: A List of Past Earthquake Early
Warning,
Website:http://www.seisvol.kishou.go.jp/eq/EEW/kaisetsu/joho/joho.html
The Japan Meteorological Agency: Earthquake Early Warning
provided after the 2011 off the Pacific coast of Tohoku Earthquake, JMA
News Release, 2011.3.29.
The Japan Meteorological Agency: Improvement of Earthquake Early
Warning, JMA News Release, 2011.8.10

Survey on people’s awareness of Earthquake Early Warning before and after the 2011 off the pacific coast of
Survey on people’s awareness of Earthquake Early Warning before and after
Tohoku Earthquake
1719
the 2011 off the Pacific Coast of Tohoku earthquake

October 2011, Chiang Mai, Thailand

172

New Technologies for Urban Safety of Mega Cities in Asia

Seismic risk evaluation on existing
RC frame buildings
for northern part of Sylhet city,
Bangladesh
Ram Krishna MAZUMDER1, Mushtaq AHMED2
and Mehedi Ahmed ANSARY3
1
Research Engineer, SHMRBBP, BUET, Bangladesh
2
Associate Professor, Department of CEE, SUST, Bangladesh
3
Professor, Department of Civil Engineering, BUET, Dhaka, Bangladesh
ansary@ce.buet.ac.bd
ABSTRACT
Bangladesh is one of the most earthquake prone countries in South Asia
where Sylhet City is located. To evaluate the existing condition of
Reinforced Concrete Frame Buildings, a multiple level assessment of theseismic vulnerability of 194 Buildings in northern part of Sylhet City, ispresented. From the Tier1 assessment, 26% of the buildings performance
score was low and 74% of buildings performance score was comparatively
good. In Tier 2, it was revealed from the study that about 11% of thebuildings fall under high risk group, 20% of the buildings fall undermoderate risk group and 70% of the buildings in low risk group.
Keywords: Immediate Occupancy, Life Safety, RC Buildings, Seismic Risk
and Sylhet City
1. INTRODUCTION
Bangladesh is running a high risk of Earthquake. The recent earthquake inIndia, Pakistan and Tsunami in Asia are the warning for Bangladesh.
Specialists are expecting a severe earthquake in this area in near future,
which will cause a serious human casualty, damages of infrastructure andother losses. One of them is the Dauki fault at the bordering area of Sylhet –Meghalaya about 70 km from Sylhet City. There are many seismic faults inthe plains around Dhaka and Chittagong Hill Tracts, which can cause
earthquakes. No earthquake occurred in these faults for many years, whichmeans huge strength has gathered underground that could cause serious
earthquakes in Bangladesh and its neighboring areas any time.
A recent study by OYO International Corporation (OIC), proposed
five earthquake scenarios, where each scenario was set as a maximum
possible earthquake (Mw) occurring within a fault zone, there are five major
fault zones in Figure 1, i.e. Madhupur fault, Dauki Fault, Plate Boundary
Fault -1, Plate Boundary Fault -2 and Plate Boundary Fault -3. In addition

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

to five scenarios, a special earthquake scenario where a magnitude-6
earthquake is occurring beneath Sylhet City was recommended, (OIC, 2009).

Figure 1: Earthquake Fault Model in Bangladesh, (OIC, 2009)
Table 1: Earthquake Scenario Parameters for Sylhet City, (OIC, 2009)
Case

Mw

Depth tofault (km)

Dip
Angle

Fault
type

Name of fault

Distance toFault (km)

1

8

3

60°

ReverseDauki Fault

> 70

2

8.3

3

30°

ReversePlate Boundary
Fault -3

> 90

3

6

15

90°

ReverseMw 6.0 beneathcity-

For determination of the addresses of seismically vulnerable buildings
within the existing building stock of ward no. 9 of Sylhet City Corporation(SCC), a multiple level assessment technique (Ozcebe et al., 2006) isapplied. Only RC frame buildings are considered in this study. This seismic
vulnerability evaluation method can be classified in three main groups
depending on their level of complexity. The first, most simple level isknown as “Walkdown Evaluation”. In this first level, does not require any
analysis and its goal is to determine the priority levels of buildings that
require immediate intervention.
Preliminary assessment methodologies are applied when more indepth evaluation of building stocks is required. In this stage, simplified
analysis of the building under investigation is performed based on a variety
of methods. These analyses require data on the dimensions of the structuraland non-structural elements in the most critical storey.
The procedures in third tier employ linear or nonlinear analyses of thebuilding under consideration and require the as-built dimensions and thereinforcement details of all structural elements.

2
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This
This
paper
paper
represents
represents
thethefirstfirst
twotwolevel
level
methodology
methodology
used
used
for forassessingassessingseismic
seismic
vulnerability
vulnerability
andanda summarya summaryof theof theassessment
assessment
being
being
done
done
for forward
ward
no.no.
9 of9 SCC
of SCCarea.
area.
2. STUDY
2. STUDY
AREA
AREA
Ward
Ward
no.no.
9 of9 theof theSCC
SCC
is mainly
is mainly
consists
consistsof madinaof madinamarket,market,bagbari,bagbari,akhalia,
akhalia,kanishail,kanishail,
surma
surma
andandtapabantapabanzones.
zones.
FigureFigure2 represents
2 represents
thetheward
ward
numbernumber9 in9 thein the
SCC
SCC
map.
map.
It has
It hasthetheareaareaof 247of 247
acres
acres
with
with
approximately
approximately
12000
12000populations
populationswith
with2789
2789structures
structures(Population(PopulationCensus,
Census,2006).
2006).
Different
Different
types
types
of occupancyof occupancy
under
under
thetheward
ward
no.no.
9 were9 weresurveyed.
surveyed.
In first
In firsttier,tier,
194194
RCRC
frame
frame
buildings
buildings
outoutof 1373of 1373were
were
surveyed.
surveyed.
In second
In secondtier,tier,
19 19
buildings
buildings
resulted
resulted
fromfromfirstfirsttiertierwere
were
analyzed.
analyzed.
Table
Table
2: Different
2: Different
Type
Type
of Buildingsof Buildings
in wardin wardno.no.
9 9(Population(Population
Census,Census,2006)
2006)
Concrete
Concrete

Structure
Structure(No.(No.
of buildings)
of buildings)
Masonry
Masonry

Tin Tin
Shed
Shed
+ +
Brick
Brick
in Cement
in Cement
Total
Total
BambooLightly
Lightly Mortar
MortarMasonry
Masonry Brick
Brick
in Cement
in Cement Bamboo
+ +
RC RC
RC RC
withwith
Concrete
Concrete Mortar
MortarMasonry
Masonry
Other
Frame
Frame Frame
Floor
Floor
Frame
withwith
Flexible
Flexible
Roof
Roof Other
1,373
1,373
60 60
77 77
1,124
1,124
1551552,789
2,789

FigureFigure2: Location
2: Locationof theof theward
ward
no.no.
9 of9 Sylhet
of Sylhet
CityCity
Corporation
Corporation

Seismic
riskriskevaluation
on existing
RC RC
frame
buildings
for fornorthern
partpartof Sylhet
city,city,
Bangladesh
Seismic
evaluationonbuildings
ofofSylhet
Bangladesh
Seismic
risk
evaluation
on existing
existing
RC frameframe
buildings
fornorthern
northern
part
Sylhetcity,
Bangladesh

31753

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

3. METHODOLOGY
3.1 Tier 1: The Walk down Evaluation
The Walkdown evaluation procedure consists of taking notes ofdifferent external feature of the buildings. Buildings are described as
belonging to high risk, moderate risk or low risk. The building featuresconsidered are described below:(a) Number of Stories: This is the total number of floors above theground level.
(b) Existence of a soft Storey: A soft storey usually exists in abuilding when one particular storey, usually employed as a commercial
space, has less stiffness and strength compared to the other stories.
(c) Existence of heavy Overhangs: Heavy balconies and overhanging
floors in multi-storey reinforced concrete buildings shift the mass center
upwards; accordingly give rise to increased seismic lateral forces andoverturning moments during earthquakes.
(d) Apparent Building Quality: A close relationship has been observed
between apparent quality and experienced damage during recent
earthquakes in Turkey.
(e) Existence of short Columns: Frames with partial infill lead to theformation of short columns which sustain heavy damage since they are notdesigned for the high shear forces due to shortened heights that will result
from a strong earthquake.
(f) Pounding Effect: When there is no sufficient clearance between
adjacent buildings, they pound each other during an earthquake as a result ofdifferent vibration periods. Uneven floor levels aggravate the effect ofpounding.
(g) Topographic Effects: Buildings on slopes steeper than 30 degrees
have stepped foundations, which cannot distribute ground distortions evenly
to structural members above.
(h) Local Soil Conditions: The intensity of ground motion at aparticular site predominantly depends on the distance the causative fault andlocal soil conditions. As there exists a strong correlation between PeakGround Velocity and the shear wave velocities of local soils, in this study
the PGV is selected as to represent the ground motion intensity. The
intensity zones are expressed accordingly, in terms of the associated PGVranges.
Zone I: 60<PGV<80 cm/s2
Zone II: 40<PGV<60 cm/s2
Zone III: 20<PGV<40 cm/s2
Based on their number of stories and the seismic hazard level at thesite buildings are assigned different base scores as shown in Table 3.

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Table 3: Base Scores and Vulnerability Scores for Concrete Buildings,(Sucuoglu et al., 2003)
No. ofStoriesBase Scores (BS)

Vulnerability Scores (VS)

Zone Zone Zone Soft
Heavy Apparent Short
Topo.
Pounding
I
II
III Storey Overhang Quality Column
Effects

1 or 2

100

130

150

0

-5

-5

-5

0

0

3

90

120

140

-15

-10

-10

-5

-2

0

4

75

100

120

-20

-10

-10

-5

-3

-2

5

65

85

100

-25

-15

-15

-5

-3

-2

6 or 7

60

80

90

-30

-15

-15

-5

-3

-2

Once the vulnerability parameters of a building are obtained fromwalk down surveys and its location is determined, the seismic performance
score, PS, can be calculated by using Eq. 1. The base scores, BS, thevulnerability scores, VS, and the vulnerability score multiplies, VSM, to be
used in Eq. 1 are defined in Tables 3 and 4, respectively.
PS = (BS) - Σ (VSM) × (VS)(1)

Table 4: Vulnerability Parameters, (VSM)
Soft storey

Does not exist = 0; Exists = 1

Heavy overhangs

Does not exist = 0; Exists = 1

Apparent quality

Good = 0; Moderate = 1; Poor =2

Short columns

Does not exist = 0; Exists = 1

Pounding effect

Does not exist = 0; Exists = 1

Topographic effects

Does not exist = 0; Exists = 1

3.2 Tier 2: Preliminary Assessment
In many instances statistical analysis based on the observed damage
and significant building attributes would provide reliable and accurate
results for regional assessments. Yucemen et al. (2004), Ozcebe et al. (2003)
and Yakut et al. (2003) employed the discriminate analysis technique todevelop a preliminary evaluation methodology for assessing seismic
vulnerability of existing low- to medium-rise RC buildings in Turkey. The
main objective of the procedure is to identify the buildings that are highly
vulnerable to damage. The procedure is applicable to RC frames and framewall structures, having up to seven stories.
Definition of Parameters
The following parameters were chosen as the basic estimation
parameters:(a) Number of stories (n): This is the total number of individual floor
systems above the ground level.

Seismic risk
Seismic
risk evaluation
evaluation on
on existing
existing RC
RC frameframebuildings
buildingsfor
fornorthern
northernpartpartofofSylhet
Sylhetcity,
city,Bangladesh
Bangladesh

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,(b) Minimum normalized lateral stiffness index (mnlstfi): This index
represents the lateral rigidity of the ground storey, which is usually the mostcritical storey. It is calculated by considering the columns and the structural
walls at the ground storey. The mnlstfi parameter computed based on thefollowing relationship:mnlstfi = min (Ix, Iy)
Where;(2)∑ (I ) + ∑ (I ) × 1000∑A,
∑ (I ) + ∑ (I ) × 1000
=
∑A
col x

I nx =

sw x

f

I ny

col

sw y

y

f

(3)

Where, ∑(Icol)x and ∑ (Icol)y are the summation of the moment ofinertias of all columns about their centroidal x and y axes, respectively. ∑(Isw)x and ∑ (Isw)y are the summation of the moment of inertias of all
structural walls about their centroidal x and y axes, respectively. Inx and Iny
are the total normalized moment of inertia of all members about x and yaxes, respectively. ∑Af is the total floor area above ground level.
(c) Minimum normalized lateral strength index (mnlsi): It indicatesthe base shear capacity of the critical storey. In the calculation of this index,
unreinforced masonry filler walls are assumed to carry 10 percent of theshear force that can be carried by a structural wall having the same crosssectional area. As in mnlstfi calculation, the vertical reinforced memberswith a cross-sectional aspect ratio of 7 or more are classified as structural
walls. The mnlsi parameter calculated by using the following equation:
mnlsi = min (Anx,Any)
Where:Anx =4)∑ ( A ) + ∑ ( A ) + 0.1∑ ( A ) × 1000 ,
∑A
col x

sw x

mw x

f

Any =

∑ ( A ) + ∑ ( A ) + 0.1∑ ( A ) × 1000
∑A
col

y

sw y

mw y

(5)

f

For each column with a cross-sectional area denoted by Acol:(Acol)x=kx . Acol, (Acol)y=ky . Acol

(5)

Where; kx=1/2 for square and circular columns; kx=2/3 for rectangularcolumns with bx>by; kx=1/3 for rectangular columns with bx<by; and ky=1-kx
For each shear wall with cross-sectional area denoted by Asw:
(Asw)x=kx . Asw , (Asw)y=ky . Asw

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Where; kx=1 for structural walls in the direction of x-axis; kx=0 for
structural walls in the direction of y-axis; and ky =1-kx.
For each unreinforced masonry filler wall with no window or door opening
and having a cross-sectional area denoted by Amw:
(Amw)x=kx . Amw, (Amw)y=ky . Amw(7)

Where; kx=1.0 for masonry walls in the direction of x-axis; kx=0 formasonry walls in the direction of y-axis; and ky=1-kx.
(d) Normalized redundancy score (nrs): Redundancy is the indication of thedegree of the continuity of multiple frame lines which distribute lateralforces throughout the structural system. The normalized redundancy ratio(nrr) of a frame structure is calculated by using the following expression:nrr =Atr (nf x − 1)(nf y − 1)Agf

(8)Where; Atr is the tributary area for a typical column. Atr is taken as 25
m2 if nfx and nfy are both greater than and equal to 3. In all other cases, Atr istaken as 12.5 m2. nfx, nfy are the number of continuous frame lines in thecritical storey (usually the ground storey) in x and y directions, respectively.
Agf is the area of the ground storey, i.e. the footprint area of the building.
Depending on the value of nrr computed from Eq. 8, the following discretevalues are assigned to the normalized redundancy score (nrs):
nrs = 1 for 0 < nrr ≤ 0.5
nrs = 2 for 0.5 < nrr ≤ 1.0
nrs = 3 for 1.0 < nrr(e) Soft Storey Index (ssi): On the ground storey, there are usually
fewer partition walls than in the upper stories. This situation is one of themain reasons for the soft storey formations. Since the effects of masonrywalls are included in the calculation of mnlsi, soft storey index is defined as
the ratio of the height of first storey (i.e. the ground storey), H1, to the heightof the second storey, H2.
H
ssi = 1(9)
H2(f) Overhang ratio (or): In a typical floor plan, the area beyond theoutermost frame lines on all sides is defined as the overhang area. The
summation of the overhang area of each storey, Aoverhang, divided by the areaof the ground storey, Agf, is defined as the overhang ratio.
Aoverhang
or =
Agf
(10)
The damage index or the damage score corresponding to the Life
Safety Performance Classification (LSPC) computed from the discriminantfunction given in Eq. 11.

(11)

Damage index for life safety (DILS)=0.620n-0.246mnlstfi-0.182mnlsi-0.699nrs+3.269ssi+2.728or-4.905

Seismic risk
Seismic
risk evaluation
evaluation on
on existing
existing RC
RC frameframebuildings
buildingsfor
fornorthern
northernpartpartofofSylhet
Sylhetcity,
city,Bangladesh
Bangladesh

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

In the case of Immediate Occupancy Performance Classification(IOPC), the discriminant function, where DIIO is the damage score
corresponding to IOPC, based on these variables is:
Damage index for Immediate Occupancy (DIIO)=0.808n-0.334mnlstfi-0.107mnlsi-0.687nrs+0.508ssi+3.884or-2.86(12)

In the proposed classification methodology, buildings are evaluatedaccording to both Performance levels. The steps followed are listed below.
(1) DILS and DIIO scores by using Eq. 11 and Eq. 12, respectively.
(2) Determine the cutoff values for life safety (CVLS) and cutoff value
for immediate occupancy (CVIO) by using Eq. 13.
The cutoff value ratio for life safety (LSCVR) and cutoff value ratio for
immediate occupancy (IOCVR) are obtained from Table 5 based on thenumber of stories above the ground level. The cutoff modification
coefficients (CMC) values are adjustment factors, which introduce thespatial variation of the ground motion in the evaluation process. These
values taken from Table 6 based on the building location relative to the fault
and the soil type at the site.
CVLS= LSCVR+│LSCVR│× (CMC -1);
CVIO=IOCVR+│IOCVR│× (CMC-1)(13)

Table 5: Variation of LSCVR and IOCVR values with number of stories
n

LSCVR

IOCVR

3 or less

0.383-0.42540.430-0.6095

0.495-0.001

6

1.265

0.889

7

1.791

1.551

Table 6: Variation of CMC Values with Soil Type and Distance to Fault
Distance to Fault (km)Soil Type

Shear Wave Velocity
(m/s)

0-4

5-8

9-15

16-25

>26

B

>760

0.778

0.824

0.928

1.128

1.538

C

360-760

0.864

1.000

1.240

1.642

2.414

D

180-360

0.970

1.180

1.530

2.099

3.177

E

<180

1.082

1.360

1.810

2.534

3.900

(3) By comparing the CV values with associated DI value calculate
performance grouping of the building for life safety performanceclassification (LSPC) and immediate occupancy performance classification(IOPC) as follows:
If DILS > CVLS take PGLS=1
If DILS < CVLS take PGLS=08180

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If DIIO > CVIO take PGIO=1
If DIIO < CVIO take PGIO=0(4) To decide the probable expected performance level of the building
the damage scores obtained from Eqs. 11 and 12 should be compared withthe storey dependent cutoff values obtained from Eq. 13. In each case, thebuilding under evaluation is assigned an indicator variable of “0” or “1”.
The indicator variable “0” corresponds to “none, light or moderate damage”
in the case of LSPC and “none or light damage” in the case of IOPC.
Similarly, the indicator variable “1” corresponds to “severe damage orcollapse” in the case of LSPC and “moderate or severe damage or collapse”
in the case of IOPC. In the final stage, the building is rated in the “low risk
group” if both indicator values are zero or in the “high risk group” whenboth indicator values are equal to unity. In all other cases buildings areclassified as the cases “requiring further study.” Further investigations haveindicated that these buildings generally lie in the “moderate risk group,”(Ozcebe et al., 2006).
4. SUMMARY OF ASSESSMENT RESULTS
The selected buildings were mainly low-rise buildings with two to six fivestories above ground. Randomly selected 194 buildings were analyzed forscoring. According to current zoning map of seismic code, for Sylhet City
(Zone I) the peak ground acceleration is around 0.25g on very firm soil,
considering site effects it can be taken as 0.30g or more. Corresponding
PGV can be taken as between 60 cm/s to 70 cm/s (Wu et al., 2003). Hencefor calculating performance score Zone I (60<PGV<80) is considered.
The walk down survey yielded the complete inventory of the building stock.
At the end of this survey the buildings were identified in terms of theirstructural systems, their number of stories and their type of use. Walkdown
survey results showed that Table 7 catalogues the RC buildings with numberof stories which are taken under investigation. Figure 3 and Figure 4
represent the existing vulnerability parameters and apparent condition of thebuildings respectively.
Table 7: Tabulation of RC Buildings according to the number of Stories
Number of Stories

≤2

3

4

5

6

7

7+

Total

No. of Buildings

108

49

25

9

2

1

0

194

Seismic risk
Seismic
risk evaluation
evaluation on
on existing
existing RC
RC frameframebuildings
buildingsfor
fornorthern
northernpartpartofofSylhet
Sylhetcity,
city,Bangladesh
Bangladesh

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Thailand
Chiangmai,

Figure 3: Presences of vulnerability parameters

Figure 4: Apparent qualities of buildings
The walk down survey yielded a preliminary seismic performance
grading of the existing RC buildings relative to each other. The calculated
performance scores of the RC buildings with 7 stories or less are given in
Table 8. This table shows that the performance scores of the buildings areinversely proportional with the number of stories. Entries in parenthesis
indicate the expected risk distribution in percentages.
Table 8 Calculated performance scores of RC buildings having 7
stories or less.
No. of Stories
1&2
3
4
5
6
7
Total

PS≤30
0(0)
0(0)
3(12.0)5(55.6)2(100)
1(100)
11(5.7)

Performance Scores
30<PS≤60
60<PS≤100
0(0)108(100)
15(30.6)34(69.4)
19(76.0)3(12.0)4(44.4)
0(0)
0(0)
0(0)
0(0)
0(0)
38(19.6)
145(74.7)

100<PS
0(0)
0(0)
0(0)
0(0)
0(0)
0(0)
0(0)

Total
108(100)
49(100)25(100)9(100)
2(100)
1(100)
194(100)

From the spatial distribution of existing RC buildings in Ward No. 9
of SCC, With respect to the calculated performance scores, it is indicates

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that the proposed methodology is capable of reflecting the adverse effects ofthe seismic hazard and building attributes on the seismic performanceclassification of buildings.
In second tier, buildings with a seismic performance score of 30 orless were given priority but due to the not allowance by the owner, all of thebuilding PS below 30 could not surveyed. There were 7 buildings in thisgroup of which a representative sample of 11 buildings has been studied. In
addition, 12 buildings with performance scores greater than 30 were also
included in the analyses. The main reason of this inclusion was to assess thecorrelation between the methods used in the first and the second tieranalysis.
A total of 19 buildings were analyzed in second level of assessment.
Field teams gathered specific information about the structural system of
each building including all dimensions of structural and non-structuralelements. This information was later tabulated in a spreadsheet format and
the Preliminary Assessment Methodology was applied. Table 9 represents
the analysis results in tier 2.
Table 9: Surveyed building data for Tier 2 (Contd.)
Building ID
L2-01
L2-02
L2-03
L2-04
L2-05
L2-06
L2-07
L2-08
L2-09
L2-10
L2-11
L2-12
L2-13
L2-14
L2-15
L2-16
L2-17
L2-18
L2-19

n
5
2
4
4
3
4
4
5
5
2
2
3
2
5
6
2
3
3
3

mnlstfi
0.01
0.03
0.01
0.01
0.02
0.01
0.01
0.02
0.01
0.02
0.02
0.03
0.02
0.05
0.02
0.02
0.02
0.02
0.01

mnlsi
0.90
2.38
1.44
1.02
1.28
1.50
1.21
1.02
0.80
2.86
2.93
3.07
3.26
1.00
1.56
1.70
2.01
1.54
1.60

nrs
2
1
1
1
1
1
2
1
1
1
1
3
3
1
1
2
3
1
1

ssi
1.05
1.00
1.18
1.11
1.10
1.05
1.05
1.18
1.05
1.00
1.00
1.00
1.05
1.17
1.11
1.00
1.00
1.00
1.11

or
0.09
0.17
0.17
0.18
0.26
0.09
0.17
0.15
0.15
0.05
0.00
0.00
0.11
0.15
0.13
0.17
0.00
0.14
0.06

Table 9: Surveyed building data for Tier 2

Building ID
L2-01
L2-02
L2-03
L2-04
L2-05
L2-06

Frame Line
(X-dir.)
4
2
3
2
2
2

Frame Line
(Y-dir.)
4
2
2
2
2
3

DILS

DIIO

CVLS

CVIO

0.31
-1.06
0.93
0.81
0.32
0.30

0.57
-1.02
0.78
0.83
0.29
0.41

1.573
1.217
1.366
1.366
1.217
1.366

0.001
0.500
0.717
0.717
0.500
0.717

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L2-07
L2-08
L2-09
L2-10
L2-11
L2-12
L2-13
L2-14
L2-15
L2-16
L2-17
L2-18
L2-19

3
2
3
2
2
4
4
2
4
4
3
2
2

3
4
2
2
4
4
3
4
2
4
4
2
4

-0.14
1.57
1.20
-1.47
-1.63
-2.44
-2.63
1.57
1.80
-1.64
-2.24
-0.39
-0.25

0.05
1.55
1.51
-1.53
-1.75
-2.34
-2.73
1.55
2.19
-1.64
-2.22
-0.26
-0.51

1.366
1.573
1.573
1.217
1.217
1.217
1.217
1.573
4.019
1.217
1.217
1.217
1.217

0.717
0.001
0.001
0.500
0.500
0.500
0.500
0.001
2.824
0.500
0.500
0.500
0.500

Figure 5: A sketch of ground floor plan in tier 2 survey
Figure 6 shows that number of buildings was classified in the seismic
risk group. The spatial distribution of those buildings which were classified
in the high seismic risk group indicated that those buildings were among themost vulnerable ones. This is mainly because of the high seismic hazard of
the region and poor building quality.

Figure 6: Results of the Preliminary Assessment Method when distanceto fault > 26.km.

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5. CONCLUSIONSThis paper presents a seismic vulnerability assessment application on alimited scale of Sylhet City. Some buildings, which were assigned very highperformance scores at the end of first tier, may be ranked in the high seismic
risk group buildings by the second tier survey.From the assessment, it wasevident that many of the buildings in ward no. 9 area fall under low &moderate risk category. Among the surveyed buildings, about 70% were
found to be in low risk group, 20% of buildings were found to be inmoderate risk group and 11% percent of the buildings were found to be inhigh risk category. Field observations reveal that the number of stories,
presence of soft storey and heavy overhang in a building are importantparameters regarding seismic safety. Apparent qualities of building,pounding effect are also other important parameters. This survey procedure
is not applicable for unreinforced masonry buildings which are also
common in the ward no. 9 in the Sylhet City Corporation. Results of therapid survey need to be followed up by other detailed seismic evaluation
techniques for taking necessary action.
REFERENCES
Ozcebe, G., Yucemen, M. S., Aydogan, V., and A. Yakut, (2003),
Preliminary Seismic Vulnerability Assessment of Existing Reinforced
Concrete Buildings in Turkey- Part I: Statistical Model Based on Structural
Characteristics, Seismic Assessment and Rehabilitation of Existing
Buildings, NATO Science Series IV/29, pp. 29-42.
Ozcebe, G., Sucuoglu, H., Yücemen, S.M., Yakut, A. and Kubin, J.
(2006), Seismic Risk Assessment of Existing Building Stock In Istanbul a
Pilot Application in Zeytinburnu District, 8th National Conference on
Earthquake Engineering, Paper No. 1737, San Francisco.
OYO International Corporation (OIC), (2009), Research Work,
CDMP-UNDP Fault Map Delineation for Bangladesh.
Population Census (2006), Community Series, Zila: Sylhet.
Sucuoglu, H., and Yazgan, U. (2003), Simple Survey Procedures for
Seismic Risk Assessment in: Urban Building Stocks, Seismic Assessment
and Rehabilitation of Existing Buildings, NATO Science Series IV/29, pp.
97-118.
Wu, Y. M., Teng, T. L., Shin, T. C., and Hsiao, N. C. (2003),
Relationship between Peak Ground Acceleration, Peak Ground Velocity,and Intensity in Taiwan, Bulletin of the Seismological Society of America,
Vol. 93, No. 1, pp. 386–396.
Yakut, A., Aydogan, V., Ozcebe, G., and Yucemen, M. S. (2003),
Preliminary Seismic Vulnerability Assessment of Existing Reinforced
Concrete Buildings in Turkey -Part II: Inclusion of Site Characteristics,
Seismic Assessment and Rehabilitation of Existing Buildings, NATO
Science Series IV/29, pp. 43-58.
Yucemen, M. S., Ozcebe, G., and A. C. Pay, (2004), Prediction of
Potential Damage due to Severe Earthquakes, Structural Safety, 26(3), 349366

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RC frameframebuildings
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Bangladesh

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Geospatial ¿²¿´§­·­analysis ±ºof groundwater
qualityÙ»±­°¿¬·¿´¹®±«²¼©¿¬»® ¯«¿´·¬§
using Ù»±¹®¿°¸·½¿´
Geographical ×²º±®³¿¬·±²
Information Í§­¬»³æ
System:«­·²¹
A
study º®±³from Maharashtraß case½¿­» ­¬«¼§Ó¿¸¿®¿­¸¬®¿ StateÍ¬¿¬»of India±º×²¼·¿
Parmeshwar UDMALE
UDMALE11 andand Sangam
Parmeshwar
Sangam SHRESTHASHRESTHA22
11
Master’s student,
Engineering and
Master’s
student, Water
Water Engineeringand Management,
Management,
Schoolof Engineering
School ofEngineering andand Technology,
Technology,
Asian Institute
Institute ofof Technology,
Technology, Thailand
ThailandAsian
pd.udmale@gmail.com
pd.udmale@gmail.com
22
Assistant Professor,
Professor, Water
Water Engineering
AssistantEngineering andand Management,
Management,
School ofof Engineering
Engineering andand Technology,
Technology,
SchoolAsian Institute
Institute ofof Technology,
Technology, Thailand
Thailand
Asian
ABSTRACTABSTRACT
Groundwater isis oneone ofof thethe most
most important
important natural
natural resources
resources forfor humanhuman
Groundwater
beings andand surrounding
surrounding environment.
environment. In
beingsIn semisemi arid
arid region
region ofof Maharashtra
Maharashtra
which receives
receives anan average
average annual
400 -700-700 mm,
mm, thetheState whichStateannual rainfall
rainfall 400
availability ofin space
space andand time.
Thisavailabilityof groundwater
groundwater isis extremely
extremely uneven
uneven both
both intime. Thisis duedue todistribution ofof rainfall
rainfall andand variations
variations inin basicisto thethe uneven
uneven distribution
basic
characteristics andcharacteristics
and physiography
physiography ofof underlying
underlying hard
hard rocks.
rocks. This
This limited
limitedavailability ofof groundwater
groundwater resources
resources inarid region
further affectedaffected byavailability
in aridregion further
byquality deterioration
deterioration restricting
quality
restricting use
use ofof groundwater.
groundwater. An
An attemptattempt isis mademade totoassess theassessthe degree
degree ofof groundwater
groundwater quality
quality andand suitability
suitability ofof groundwater
groundwater for
for
application ofof GIS
GIS tools
tools forfor thethedrinking purpose
purpose inin combination
combination with
with application
drinking
drought prone
prone study
Maharashtra
drought
study area
area ‘the‘the Dhubhdhubhi
Dhubhdhubhi watershed’
watershed’ ofof Maharashtra
State.
State.
The groundwater
groundwater quality
quality index
index (GWQI)(GWQI) has
been derived
The
has been
derived forfor five
fiveparameters namely
namely Total
Total Dissolved
Dissolved Solids
Solids (TDS),(TDS), Chloride),
parameters
Chloride ((), Nitrate
Nitrate((), Fluoride
Fluoride (( )) andand Ironbased on
on waterwater quality),
Iron (Fe)(Fe) based
quality standards
standards forfor
drinking
purposeasrecommendedbyIndianstandard
specificationofdrinking purpose as recommended by Indian standard specification ofdrinking water
water (ISO:(ISO: 10500,
of GWQIGWQI relate
relate with
withdrinking
10500, 1993).
1993). The
The highhigh value
value ofhigher concentration
concentration ofparameter inin groundwater.
groundwater. The
The inverse
inverse distancehigherof parameter
distance
weighted method
method to
power interpolationinterpolation technique
technique isspatialweighted
to poweris usedused toto obtain
obtain spatial
distribution ofof parametersparameters inin ArcGISArcGIS 9.3.
distribution
9.3.
The study
study concludes
the 100%
The
concludes thatthat the100% population
population inin study
study area
area isis dependent
dependent on
ongroundwater forfor drinking
drinking purpose.
purpose. Out
Out ofof 45
45 villages,
villages, about
about 21
21 villages
villagesgroundwatershow thethe deteriorated
About 33.06
show
deteriorated groundwater
groundwater quality.
quality. About
33.06 %
% ofof population
population isisgroundwaterwhich
isunsuitablefordrinking
purpose
and
needs
using
using groundwater which is unsuitable for drinking purpose and needs
treatment priortreatment
prior toto use.
use. TheThe groundwater
groundwater quality
quality deterioration
deterioration can
can result
result inincritical situation if adequate management practices are not implemented inrelation to sustainable development of the resource.

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Keywords: Groundwater Quality Index, Geographical Information System,
Maharashtra State
1. INTRODUCTION
Groundwater is one of the most important natural resources for humanbeings and surrounding environment. Globally groundwater is estimated toprovide at least 50% of drinking water needs, 40% of the demand of thoseindustries that do not use urban mains water, and 20% of water-use inirrigated agriculture (Zektser and Everett, 2004). As compared to surface
water, groundwater is generally of good quality, reduced susceptibility tocontamination, less subject to seasonal and perennial fluctuations, and much
more uniformly spread over large region. The problems of groundwater
depletion, along with the problems of water logging and groundwater
quality deterioration due to natural hazardous substances and anthropogenic
activities poses constraint on use of groundwater. The problems of higharsenic, fluoride, nitrate and total dissolved solids (TDS) are major concerns
in many countries, exceeding permissible limits of drinking water quality set
up by United Nation’s World Health Organization (Appelo, 2006). The
present study attempts to assess the degree of groundwater quality andsuitability of groundwater for drinking purpose in combination withapplication of GIS tools for the drought prone area ‘the Dhubhdhubhi
watershed’ of Solapur district in Maharashtra State.
2. STUDY AREAThe Dhubhdhubhi watershed (Figure 1) with geographical area of 483.63
km2 lies in Southeast part of Solapur district in Maharashtra State of India
which is bounded between latitudes 17o 21’ N to 17o 41’ N and longitudes
76o 00’ E to 76o11’ E. The Groundwater Survey and Development Agencyof Maharashtra State has delineated the study area as a watershed of subcatchment of ‘Lower Bhima up to conflict with Sina River’. It is further
divided into sub-watersheds as BM-138 with 4 miniwatersheds and BM-139
with 3 miniwatersheds.

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Figure 1: Location map of the Dhubdhubhi watershed
3. METHODOLOGY
The thematic maps of study area are obtained from Maharashtra Remote
Sensing Application Center, Nagpur and the groundwater quality data forvillage wells in the study area is obtained from database of Water Supply
and Sanitation Department, Government of Maharashtra for the year 2006.
The Water Quality Index (WQI) is generated (a mathematical instrument toconvert large quantities of water quality data into a composite number
which represents the level of water quality). In this study, groundwater
quality index (GWQI) has been derived for five parameters namely Total
Dissolved Solids (TDS), Chloride (Cl−), Nitrate ( NO3− ), Fluoride (F − ), Iron
(Fe) based on water quality standards for drinking purpose as recommended
by Indian Standard Specification of Drinking Water (ISO: 10500, 1993). It
is assumed that the weightage for various groundwater quality parameters
are inversely proportional to the standards for drinking purpose asrecommended by Indian standard specification of drinking water (ISO:10500, 1993) (Mishra et al. 2001, Naik et al. 2001 and Reza et al. 2010).

Geospatial analysis of groundwater quality using Geographical Information System:
A case study from Maharashtra State of India

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Data Collection
GPS location
wells

WS boundarymap

GW quality
data
Generation of GWQI
Spatial Interpolation
method IDW
Spatial distribution
maps

Figure 2: Flowchart of methodology for generating groundwater quality
index map
The obtained GWQI is used as input data for well locations. The‘inverse distance weighted (IDW) method to power’ interpolation technique
is used to obtain spatial distribution of GWQI in ArcGIS 9.3. The spatial
distribution of individual parameters for visual understanding is also
obtained using IDW interpolation method in ArcGIS 9.3. Following are thesteps for calculation of GWQI.
Step 1 Calculation of weightage of ith parameter
The weightage for ith parameter is calculated as,
Wi = k/ Si
Where,Wi is the unit weightage for ith parameter,
Si is the standard for ith parameter recommended by Indian standard
specification of drinking water (ISO: 10500, 1993) andk is the constant of proportionality.
The proportionality constant assuming five parameters mentioned
above are obtained as 0.0009171 and calculated unit weightage is shown in
Table 1.

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Table 1:
1: Unit
Unit weightage
weightage ofof five
five parametersparameters basedon BISBIS (ISO:(ISO: 10500,
10500,
Table
based on
1993)
1993)
Sl. no.
no.
Sl.

Parameter
Parameter

11
22
33
44
55

Highestvalue (S(Sii))
Highest permitted
permitted value

Unit weightage
weightage (W(Wii))
Unit

TDS
TDS

500.00500.000.000458552
0.000458552

Chloride
Chloride

250.00250.000.000917104
0.000917104

NitrateNitrate

45.00
45.00

0.005095022
0.005095022

Fluoride
Fluoride

1.00
1.00

0.229275997
0.229275997

Iron
Iron

0.30
0.30

0.764253325
0.764253325

Step 22 Calculation
Calculation ofStepof quality
quality rating
rating forfor eacheach ofof thethe waterwater quality
quality parameterparameter
Further individual
parameter isgiven by,for eacheach parameteris given
by,Further
individual quality
quality rating
rating scale
scale QQii forQ=CCii // SSii
Qii =Where,Qis quality
quality rating
rating based
based onon concentration
concentration ofof eachparameter,
Where,Qii iseach parameter,thth
Sii isis thethe standard
standard for
Indian standard
for ii parameterparameter recommended
recommended byby Indianstandard
S
specification ofwater (ISO:
specificationof drinking
drinking water(ISO: 10500,
10500, 1993)1993) andandis concentration
concentration ofof chemicalchemical parameterparameter inin eacheach water
water sample
Cii isC
sample(mg/liter)(mg/liter)
Then subfor eachThen
sub index
index foreach parameterparameter has
has been
been determined
determined as,
as,
SI =
Qii
SI
=W
Wii ** QthWhere, SI
parameter.
parameter.
Where,SI isis subsub index
index ofof iithStep 33 Summing
Summing ofof these
these subsub- indicesindices in
the overall
index.
in theoverall index.
Step
Groundwater quality
quality index
is thenthen calculated
calculated as,as,
Groundwater
index isThe obtained
obtained values
values ofof groundwater
groundwater quality(GWQI) forareThe
quality index
index (GWQI)
for wells
wells aredivided into
into four
four classes
classes as
dividedas very
very good
good (0-25),(0-25), good
good (25-50),(25-50), poor
poor (50-75)(50-75)and veryvery poor(75-100).
andpoor (75-100).
4. RESULTSRESULTS AND
AND DISCUSSIONSDISCUSSIONS
4.
The Figure
7, 88 shows
shows thedistribution of
The
Figure 3,
3, 4,
4, 5,
5, 6,
6, 7,
the spatial
spatial distributionof various
variousgroundwater quality
concentration. The
The groundwater
groundwater
groundwater
quality parametersparameters inin terms
terms ofof concentration.
samples exceed
exceed thethe Indian
Indian standards
standards ofof drinking
water quality
samples
drinking water
quality forfor dissolved
dissolved
solids andand ironiron concentration
concentration inpart thethe study
study area.
TDS beyond
beyondsolidsin mostmost partarea. TheThe TDS
500 mg/litercauses decrease
decrease inin palatability
palatability ofdrinking water
water andand itit maymay
500
mg/liter causesof drinking
result inin gastrogastro intentional
irritation. Excess
Excess concentration
concentration of
resultintentional irritation.
of ironiron affects
affects thethetaste andand appearance,
appearance, hasadverse effectwater supply
taste
has adverse
effect on
on domestic
domestic uses
uses andand water
supplystructures andiron bacteria.
bacteria. The
structuresand promotes
promotes iron
The concentration
concentration ofof otherother chemicalchemical
Geospatial analysis
analysis ofof groundwater
groundwater quality
quality using
using GeographicalGeographical Information
Information System:
System: A
A casecase study
study from
from
Geospatial
Geospatial analysis of groundwater quality using Geographical Information System:
Maharashtra
55
Maharashtra State
State ofof IndiaIndia
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October 2011, Chiang
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parameters such as fluoride, nitrate and chloride is within the limit of Indian
standards of drinking water quality.
The 45.83 % area exceeds the permissible limit of TDS. In most of thepart of study area, the concentration of iron is at upper concentration limit
set by BSI. The chloride concentration over the study area is less than 100
mg/liter which is within the permissible limit of 250 mg/liter. Most of thearea shows nitrate concentration in groundwater far below the permissible
limit. The fluoride concentration in groundwater is found 0.2-0.3 mg/liter at
most of the locations.
The suitability of groundwater for drinking purpose is decided basedon the classification of GWQI as very good (0-25), good (25-50), poor (5075) and very poor (75-100). The interpolation map of GWQI is shown in
Figure 9, which concludes that about 25.20 % area is unsuitable or are ofpoor to very poor quality for drinking purpose. Out of 45 villages, about 21
villages show the deteriorated groundwater quality (Figure 10) and about
33.06 % of population in the study area is using groundwater which is
unsuitable for drinking purpose.

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Figure 3:
3: Spatial
distribution ofof total
total dissolved
dissolved solids(TDS) inFigureSpatial distribution
solids (TDS)in thethe
Dhubdhubhi watershedwatershed
Dhubdhubhi

Figure 4:
4: Spatial
Spatial distribution
Figuredistribution ofof Chloride
Chloridewatershedwatershed)) inin thethe Dhubdhubhi
Dhubdhubhi

Geospatial analysis
analysis ofof groundwater
groundwater quality
quality using
using GeographicalGeographical Information
Information System:
System: A
A casecase study
study from
from
Geospatial
Geospatial analysis of groundwater quality using Geographical Information System:
Maharashtra
77
Maharashtra State
State ofof IndiaIndia
193
A case study from Maharashtra State of India

October 2011,
Mai,Thailand
Thailand
October
2011, Chiang
Chiangmai,
Thailand
Chiangmai,

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Figure 5:
5: Spatial
Spatial distribution
distribution ofof Nitrate
Nitrate ((Figurewatershedwatershedin thethe Dhubhdhubhi
DhubhdhubhiinFigure 6:
6: Spatial
Spatial distribution
distribution ofof Fluoride
Fluoride ((Figurewatershedwatershedin thethe Dhubhdhubhi
Dhubhdhubhiin

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Figure 7: Spatial distribution of Iron (Fe) in the Dhubdhubhi watershed

Figure 8: Spatial distribution of Electric Conductivity in Dhubhdhubhi
watershed

Geospatial analysis of groundwater quality using Geographical Information System: A case study from
Geospatial analysis of groundwater quality using Geographical Information System:
Maharashtra State of India
A case study from Maharashtra State of India

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October 2011, Chiang
Mai,Thailand
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Chiangmai,

Figure 9: Spatial distribution of Ground Water Quality Index in theDhubdhubhi watershed

Figure 10: GWQI for various groundwater locations of the study area,
above red line indicates groundwater is unsuitable for drinking purpose in
the Dhubdhubhi watershed

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5. CONCLUSIONSThe study concludes that the 100% population in study area is dependent on
groundwater for drinking purpose. Out of 45 villages, about 21 villages
show the deteriorated groundwater quality. About 33.06 % of population isusing groundwater which is unsuitable for drinking purpose and needs
treatment prior to use. The groundwater quality deterioration can result incritical situation if adequate management practices are not implemented inrelation to sustainable development of the resource.
ACKNOWLEDGEMENT
Authors are thankful to Maharashtra Remotes Sensing Application Centre,
Nagpur and Water Supply and Sanitation Department, Government of
Maharashtra.
REFERENCES
Appelo, T., 2006. Arsenic contamination in groundwater: a global
perspective. National Chapter of IAH. The Netherlands.
BIS (Bureau of Indian Standards) 10500, 1993 (reaffirmed). IndianStandard of Drinking Water Specification.
Mishra, P.C. and R.K. Patel, 2001. Study of the pollution load in thedrinking water of Rairangpur, a small tribal dominated town of North Orissa.
Indian Journal of Environment and Ecoplanning, 5(2): 293-298.
Naik, S. and K.M. Purohit, 2001. Studies on water quality of river
Brahmani in Sundargarh district, Orissa. Indian Journal of Environment andEcoplanning, 5(2): 397-402.
Reza, R. and Singh, G., 2010. Assessment of Ground Water Quality
Status by Using Water Quality Index Method in Orissa, India. World
Applied Sciences Journal 9 (12): 1392-1397.
Zektser, I.S. and Everett, L.G., 2004. Groundwater resources of theworld and their use. UNESCO- IHP-VI, Series on Groundwater no.6, Paris,
France.

Geospatial analysis of groundwater quality using Geographical Information System: A case study from
Geospatial analysis of groundwater quality using Geographical Information System:
Maharashtra State of India
A case study from Maharashtra State of India

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Flood risk modeling in Bangkok Province,
ThailandPhalke APARNA1, Tripathi NITIN2 and Bharambe KHAGENDRA3
1
Master Student School of Eng., RSGIS FoS,
Asian Institute of Technology, Thailand
aparnapm16@gmail.com
2
Coordinator, RSGIS FoS,
Asian Institute of Technology, Thailand
3
Research Assoaciate, RSGIS FoS,
Asian Institute of Technology, Thailand
ABSTRACT
Natural disasters like flood, drought, cyclone, forest fire, volcanic eruption,and landslide are occurring frequently all over the world. Natural disasters
happening on earth always cause loss of life, property damage as well associal and economic disruption. Bangkok is developed on the delta of the
Chao Phraya River Basin at a distance 25-56 km from its mouth and its
average land level is about 0-1.5m above mean sea level so frequent floods
have been a big obstruction in its development.
Due to climate change and its impact the risk of flooding has increased.
Over the past few years the impact of flooding has become an important
issue for Bangkok. The rapid urbanization and heavy soil settlement haveadversely affected the flooding situation in Bangkok. Study of hazards andvulnerabilities from natural disaster is always important for risk analysis sothat we can contribute somewhat in reducing damages will happen in future.
This study models flood risk for Bangkok Province of Thailand using theAnalytical Hierarchy Process (AHP). GIS is potential tool to assess the riskof flooding using parameters like rainfall, elevation, land use etc andindentified the flood risk areas in Bangkok by producing flood risk map. The
study reveals that Bangkok is too much susceptible to flood where Nong Kok
had the safe area with respect to hazard and Taling Chan amphoe had
shown maximum area with high hazard. Overlay raster analysis had beenused to predict the flood inundation area which showed that areas near
Chao Phraya River or areas having high rainfall intensities consisting
amphoe such as Taling Chan and Phasi Charoen had high flood risk.
Keywords: Natural disasters, Flood risk mapping, Arc GIS and AHP
1. INTRODUCTION
Natural disasters occurring on earth always cause loss of life, property
damage as well as social and economic disruption such as earth quake,windstorms, tsunamis, floods, landslides, volcanic eruptions, wildfires,

1991

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Chiangmai,

grasshopper and locust infestations, drought and desertification and othercalamities of natural origin. So study of hazards and vulnerabilities fromnatural disaster is always important for risk analysis so that we cancontribute somewhat in reducing damages if same disaster will happen in
future.
Here we are going to predict flood risk in Bangkok using some GIS
spatial analysis technique as well as ArcGIS software tools. Bangkok is
located on low lying alluvial deposit and most reports say that it always
flooded every year by tide, river flow and also by direct precipitation. As
Bangkok being capital of Thailand, It must be always protected from such
type of natural disasters as it has 10% of total population in Thailand in thisarea and also it contributes much in Thailand economy. It is situated on low
flat plain of the Chao Phraya River at a distance 25-56 km from its mouth
and its average land level is about 0-1.5m above mean sea level (Wikipedia).
So it holds greater risk of flooding Bangkok is within the monsoon region
which has frequent and heavy rainfall. Over the past few years the impact offlooding has become an important issue for Bangkok. Although the Royal Thai
Government has been undertaking various measures, it has not yet become
possible to mitigate the flood disasters in this capital city and economic hub of
Thailand. In the Bangkok Metropolitan and its vicinity, urban and built-up
lands have increased by 115% from 1,058 km to 2,280 in the last 15 years. The
rapid urbanization and heavy soil settlement have adversely affected theflooding situation in Bangkok. Climatic change is likely to worsen the situation.
With changes to weather patterns (effects of climate change) and the impactthat development has on water movement to streams and rivers, the risk of flash
flooding and floods has increased.
Actually there is no technique like which can interpret accurate actual
risk about natural disaster but here we have tried to work on these efforts
little bit. We cannot say it can be completely accurate analysis. Here wehave used ArcGIS software and some spatial analysis techniques for criteria
weighting.The objectives of this study are such as, 1. To create hazard map
for Bangkok 2. To create vulnerability map Bangkok 3. To create flood risk
map Bangkok 4. . To create model for flood risk mapping
2. STUDY AREA
Bangkok is the capital city of Thailand characterized by a high population
density. The city is located between 100°18'39.837" to 100°56'53.703" east
longitude and 13°28'47.57" to 14°0'31.249" north latitude (Figure 1). It isbounded by the province of Pathumthani in the north, Chacheongsao in theeast, Nakorn Pathom in the west and Samuth Prakam in the south. As of
2008, the province has an approximate population of 18 million competingfor a limited surface area of 1,500 square kilometers. The Chao Phraya
River cuts the city in the center from the north and drains towards the Gulfof Thailand. This river causes periodical flooding in the city resulting tomajor economic and social loss to its inhabitants.

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Figure 1: Location map of Bangkok province

3. METHODOLOGY
Flood risk is a function of flood hazard and flood vulnerability that involves
several physical and socio-economic contributory factors. One of the
problems associated with flood risk analysis is the handling of large amountof data as inputs for flood hazard and vulnerability models. Using GIS, data
inputs can be stored in a standardized manner and analysis can be repeatedly
performed if the desired outcome is not reached. For this project, raster
analysis was used to derived flood hazard map, flood vulnerability map andflood risk map. Weights are applied to the identified factors which were
derived using the Analytical Hierarchy Process and Rank Sum. The general
methodology that was followed to create the flood risk map of Bangkok isshown in Figure 2.

Flood risk
Floodrisk modelingmodeling inin Bangkok
Bangkok province:
Province, Thailand
Thailand2013

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Figure 2. General methodology of flood urban flood risk mapping of
Bangkok Province
Preliminary data acquisition involves gathering of digital map anddemographic data of the province of Bangkok. The data used in this project
was several thematic layers acquired from archived Thai GIS database anddownloadedfromtheinternet(http://www.rsgis.ait.ac.th/~souris/thailand.htm). Recent (2004) population
data of Bangkok was also downloaded from the internet so that an updated
population density can be derived. As a summary, the following are some of
the raster and vector layers used for this study to derive other variables forthe hazard and vulnerability mapping.
Table 1: Data used in the study

Data Layer

Data Type

Bangkok politicalboundary

Landuse map

Vector (Amphoe
andTambonlevel)
Raster (90 m)[Tile 57,10]
vectorhttp://www.star.ait.ac.th/~souris/thailand.htm

Rainfall map

Vector (point)

http://www.star.ait.ac.th/~souris/thailand.htm

Stream networks

Vector (line)

http://www.star.ait.ac.th/~souris/thailand.htm

Road networks
2004 population(amphoe level)
Elevation map

Vector (line)
Statistical data

Thai GIS Data (RSGIS Dept., AIT)
http://en.wikipedia.org/wiki/Bangkok

RasterDerived from DEM

Bangkok DEM

4202

SourceThai GIS Data ( RSGIS Dept. AIT)
http://srtm.csi.cgiar.org/

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Database preparation is required for further processing of data layers.
Flood hazard mapping was done using raster analysis specifically using theraster calculator of Spatial Analyst extension of ArcGIS. Weights derived
from Analytical Hierarchy Process were applied for each factor or criteriathat contribute to flood hazard susceptibility of Bangkok province. Several
research studies have identified various factors for flood hazard analysis. In
this study, the factors used in the study conducted by Tanavud et.al were
followed these are: rainfall, elevation, landuse based on its infiltration
capacity, distance to river (river buffer), and road density.
Table 2: Identified factors for flood hazard mapping

Factors/Criteria
Rainfall

AHP Weight
0.395

Elevation

0.075

Landusecapacity)(infiltration

River buffer
Praya River)Road density

(Chao

0.224

0.109

0.142

Subfactors< 900 mm
900 – 1200 mm
1200 – 1600 mm
1600 – 2000 mm> 2000 mm< 1.5 meters
1.5 – 3 meters
3 – 6 meters> 6 meters
Water
Airport/Bare/Urban
Grass/Agriculture
Mangrove Forest
0 – 5000 meters5000 – 10000 meters
10000 – 20000 meters> 20000 meters< 0.5 km/km2
0.5 – 1 km/km2
1 – 1.5 km/km2
1.5 – 2 km/km2> 2 km/km2

Hazard Ranking
1
2
3
4
5
4
3
2
1
4
3
2
1
4
3
2
1
1
2
3
4
5

Figure 3: Rainfall map of Bangkok

Flood risk
Floodrisk modelingmodeling inin Bangkok
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Province, Thailand
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Figure 4: Elevation map of Bangkok

Figure 5: Landuse map of Bangkok

Figure 6: Road density map of Bangkok

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Figure 7:Figure
River 7:
bufferRivermap
bufferof Bangkok
map of Bangkok
3.1.1 Flood
3.1.1Hazard
Flood Weighing
Hazard Weighing
by AHP by AHP
Designation
Designationof weights
of weights
for eachfor
flood
each
hazardflood factors
hazard wasfactors
done
was
using
done using
Analytical
Analytical
Hierarchy
Hierarchy
Process Process(AHP). The(AHP).
AHP
The
developed
AHP developedby Saatyby
inSaaty1980 in 1980
was usedwas
to constructused to constructa matrixathat
matrixweighsthat eachweighscriterion
each criterion
against eachagainstothereach otherbased onbaseda scaleon ofa scale1 to 9,of 11 being
to 9, 1ofbeing
equalofimportanceequal importanceand 9 ofand
extreme9 of extreme
importance.
importance.
Table 4 Table
shows4theshows
results
theofresults
the Relativeof the Relative
ImportanceImportance
WeightsWeights(RIW) using
(RIW)
AHP
using
derivedAHP forderivedeach forfactor.
each factor.
Table 3:Table
Table3:
showing
Table showing
the weightthematrix
weightofmatrix
relativeof importance
relative importancefor eachfor eachfactor factor
Factors Factors
Road
River
Road
Rainfall Rainfall
Landuse Landuse
Density Density
BufferRiver
ElevationElevation
BufferRainfall Rainfall 1

12

2 4

43

35

5

Landuse Landuse 0.5

0.51

1 2

23

32

2

0.25
Road Density
Road Density

0.25
0.5

0.5 1

12

22

2

0.333333 0.333333
0.333333 0.333333
0.5River BufferRiver Buffer

0.51

12

2

ElevationElevation0.2

0.50.5

0.51

1

8 9.5

9.512

12

Total

Total

0.20.50.5 0.5

2.283333 2.283333
4.333333 4.333333
8

Table 4:Table
Consistency
matrix andthe derived
4: Consistency
matrixand the weights.
derived weights.
Factors

Factors

RainfallLanduseRainfallRoad
LanduseDensityRiver
Road
BufferDensity

Row Total Row
RIW
Total
River
Elevation Elevation
BufferLambdaRIW

ConsistencyConsistency
LambdaVectorVectorRainfall

0.387102
Rainfall

0.387102
0.4181190.4181190.363636

0.363636
0.352941

0.352941
0.454545

0.454545
1.976344

1.976344
0.395269

0.395269
10.56863

10.56863
5.3475682 5.3475682

Landuse0.193551
Landuse0.193551
0.209059

0.209059
0.1818180.181818
0.352941

0.352941
0.1818180.181818
1.119188

1.119188
0.2238380.223838
5.911208

5.911208
5.2816940235.281694023

Road0.096775
Density
Road Density

0.096775
0.10453

0.10453
0.090909

0.090909
0.235294

0.235294
0.1818180.181818
0.709327

0.709327
0.141865

0.141865
3.604561

3.604561
5.0816668315.081666831

BufferRiver BufferRiver0.129034

0.129034
0.069686

0.069686
0.045455

0.045455
0.117647

0.117647
0.1818180.181818
0.543640.543640.108728

0.108728
2.684422

2.684422
4.9378647454.937864745

0.07742
Elevation Elevation

0.077420.10453

0.104530.045455

0.045455
0.058824

0.058824
0.090909

0.090909
0.377137

0.377137
0.075427

0.075427
1.958483

1.958483
5.1930255455.193025545

Flood risk
modeling
in Bangkok
province:province:
ThailandThailand
Flood
risk
in
Flood
risk modelingmodeling
in Bangkok
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Province,
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October 2011,
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Theestimated
The consistency
consistency ratio
ratio (CR)(CR) waswas calculated
calculated to
to checkcheck if
if thethe estimatedweightsbeweights areare good
good oror needs
needs toto be
be changed.
changed. The
The ideal
ideal value
value ofof CR
CR mustmust belessless than
than 0.10;
0.10; otherwise,otherwise, thethe somesome values
values inin Table
Table X
X mustmust bebe changed
changed andandrecomputed
is derived
derived byby takingthe ratio
ratio ofof Consistency
Consistency Index
Index
recomputed again.
again. CR
CR istaking the(CI)
Index (RI).
(RI). CI
CI is(CI) andand thethe Random
Random Index
is calculated
calculated using
using thethe following
following
equation:
equation:

Where isis thethe average
average value
value ofof thethe consistency
consistency vector
vector andand isis thethe number
numberWhereofthe RI
values forgiven orderofof factors.
factors. The
The following
following table
table gives
gives theRI valuesfor eacheach given
order ofmatrix:matrix:No. ofofNo.
Factors
Factors
RI
RI

Table
Table 5:
5: Random
Random index
index values
values

11

22

33

44

55

66

77

88

99

00

00

0.58
0.58

0.90
0.90

1.12
1.12

1.24
1.24

.32
.32

1.41
1.41

1.45
1.45

For
were 0.042
0.042 andand 0.037,
0.037,For this
this study,
study, thethe calculated
calculated CI
CI andand CR
CR wererespectively.
value isless thanrespectively. Since
Since thethe CRCR valueis less
than 0.10,
0.10, thethe derived
derived RIW
RIW areare good
good
enoughenough to
to be
be usedused forfor thethe flood
flood hazard
hazard model.
model.
3.1.2
Hazard Overlay
Overlay
3.1.2 Flood
Flood Hazard
The
The weighted
weighted linear
linear combination
combination was
was applied
applied toto computecompute forfor thethe floodflood
map ofof Bangkok.
Bangkok.
hazardhazard index
index map
Where
Where

is thethe flood
flood hazard
hazard index
index forfor areaarea I,I,
isis thethe calculated
calculatedisweight forfor factor
factor j,j, andandis thethe hazard
hazard rating
rating ofof sub-factor
sub-factor i.
i.
weightisTheused toto derive
derive the
The above
above equation
equation was
was used
the following
following raster
raster calculator
calculator
expression
expression inin ArcGISArcGIS Spatial
Spatial Analyst:
Analyst:3.2
3.2 Flood
Flood Vulnerability
Vulnerability Mapping
Mapping
AccordingAccording toto UNESCO-IHE
UNESCO-IHE (2011),(2011), flood
flood vulnerability
vulnerability isis thethe degree
degreeofhazard atgiven severityof loss
loss (i.e.
(i.e. property
property andand lives)
lives) forfor aa given
given flood
flood hazard
at aa given
severitylevel.
In thislevel. In
this study
study two
two vulnerability
vulnerability factors
factors was
was used;used; population
population density
densityandand landuse.
landuse. Flood
Flood vulnerability
vulnerability mapping
mapping was
was also
also done
done using
using raster
rasteranalysisextension ofof ArcGIS.
ArcGIS.
analysis using
using thethe raster
raster calculator
calculator ofof Spatial
Spatial Analyst
Analyst extension
But,
But, since
since there
there were
were only
only two
two factors
factors forfor vulnerability
vulnerability were
were identified,
identified, thetheweights
weights were
were derived
derived using
using rank
rank sumsum instead
instead ofof AHP.
AHP.
3.2.1
Vulnerability Factors
3.2.1 Flood
Flood Vulnerability
Factors
The
The ranking
ranking ofof thethe sub-factors
sub-factors forfor flood
flood vulnerability
vulnerability areare tabulated
tabulated ononthethe succeeding
succeeding table:table:

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Table
Table 6:
6: Factors
Factors forfor flood
flood vulnerability
vulnerability mapping
mapping

Factors/Criteria
Factors/Criteria

Population Density
Density
Population

LanduseLanduse(Infrastructure)(Infrastructure)

Rank Sum
Sum
Rank
WeightWeight
0.333
0.333

0.667
0.667

Subfactors
Subfactors< 60006000<
6000 –– 10000
10000
6000
10000 –– 15000
15000
10000
15000 –– 25000
25000
15000
> 25000
25000
>
Water
Water
Bare/Urban/Airport
Bare/Urban/Airport
Agriculture
Agriculture
Mangrove
Forest/Grass
Mangrove Forest/Grass

Vulnerability
Vulnerability
Ranking
Ranking
11
22
33
44
55
22
44
33
11

Figure 8:
8: Population
Population density
density map
map ofof Bangkok
BangkokFigureFigureBangkokFigure 9:
9: Landuse
Landuse map
map ofof Bangkok
3.2.2
3.2.2 Flood
Flood Vulnerability
Vulnerability Weights
Weights Using
Using Rank
Rank SumSum
Due tothe limited
limited number
number ofof factors
factors identified
identified forfor floodDueto theflood vulnerability,
vulnerability,
the Rankof obtaining
obtaining weights
weights wastheRank Sum
Sum method
method of
was used
used instead
instead ofof thetheAnalytical Hierarchy
Hierarchy Process.
In rank
rank sum
Analytical
Process. In
sum method,
method, anan arbitrary
arbitrary rank
rank waswasfirst specified
factors. A
weight forfirst
specified forfor eacheach ofof thethe identified
identified factors.
A weight
for eacheach factor
factor waswasthen computed
following formula:thencomputed using
using thethe following
formula:Flood
Flood risk
riskmodeling
inBangkok
province:
ThailandFloodrisk modelingmodeling inin Bangkok
Bangkok province:
Province, Thailand
Thailand99
207

October 2011,
Mai,Thailand
Thailand
October
2011, Chiang
Chiangmai,
Thailand
Chiangmai,

Where isis thethe number
number ofof factors,
factors, andand isis thethe arbitrary
arbitrary rank
rank ofof eachfactor.
Where
each factor.
The
the final
final weights
weights thatthat will
will
The derived
derived weights
weights areare thenthen normalized
normalized toto derive
derive thebebe usedused forfor thethe flood
flood vulnerability
vulnerability model
model (Table(Table 7).
7).
Table
each vulnerability
the Rank
Rank Sum
Sum
Table 7:
7: Derived
Derived weights
weights forfor eachvulnerability factors
factors using
using themethod.
method.
Factors
Factors

Criterion
Criterion

Rank
Rank

LanduseLandusePopulation
density
Population density
TOTAL
TOTAL

11
22

22
11

WeightWeight
r+1)
r+1)
11
22
33

(n(n-

Normalized
Normalized
Weights
Weights
0.333
0.333
0.667
0.667
11

3.2.3
Vulnerability Overlay
3.2.3 Flood
Flood Vulnerability
Overlay
Following
Spatial Analyst:
Analyst:Following raster
raster calculator
calculator expression
expression inin ArcGISArcGIS Spatial
3.3
3.3

Flood Risk
Risk Mapping
Mapping
Flood
Flood
Flood risk
risk isis aa function
function ofof flood
flood hazard
hazard andand flood
flood vulnerability.
vulnerability. To
Toderivedderived thethe flood
flood risk
risk map
map ofof Bangkok,
Bangkok, thethe two
two derived
derived layers
layers fromfrom thetheprevious
previous steps
steps where
where overlayed
overlayed using
using raster
raster multiplication.
multiplication.
Belowraster calculator
Below isis thethe raster
calculator expression
expression thatthat waswas used
used toto derive
derive the
the
flood
flood risk
risk map
map ofof Bangkok.
Bangkok.
3.4
3.4

Model
Model forfor Flood
Flood Risk
Risk Mapping
Mapping

Aside
Aside fromfrom thethe conventional
conventional way
way ofof flood
flood risk
risk mapping
mapping using
using thetherasterraster calculator,
calculator, aa model
model toto performperform all
all thethe raster
raster overlay
overlay tasks
tasks cancan bebecreatedhas two
two mainmain processes:
processes:
created using
using thethe Model
Model Builder.
Builder. The
The model
model hasweighedweighed sum,sum, andand reclassification
reclassification tool
tool

FigureFigure 10:
10: Flood
Flood risk
risk model
model
4.
AND DISCUSSIONSDISCUSSIONS
4. RESULTSRESULTS AND
In
Bangkok. For
In thisthis study
study we
we want
want toto know
know thethe risk
risk ofof flood
flood inin Bangkok.
For this
this purpose
purposewe
we havehave first
first found
found hazard
hazard andand vulnerability
vulnerability inin thethe study
study area
area as
as we
we
explained
explained inin methodology.
methodology. The
The respective
respective results
results on
on amphoe
amphoe level
level forfor
hazard,hazard, vulnerability
vulnerability andand risk
risk areare explained
explained asas follows:
follows:

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4.1 Distribution of Areas Based on the Level/Classes of Flood Hazard:
Figure 12 shows the distribution of hazard in Bangkok. According to Table
8, amount of area which has very high hazard is 13,762.03 ha but we cansee that maximum total area for high hazard is more compared to otherhazard level. So, Bangkok is too much susceptible to flood. Nong kok has
more area with very low hazard. So, Nong kok is the safe area with respect
to hazard but on other side Taling chan amphoe shows maximum area withhigh hazard
area

Following figure 11 shown graphical distribution of hazard in study

Figure 11: Area distribution of flood hazard class

Figure 12: Flood hazard map of Bangkok
4.2 Distribution of Areas Based on the Level of Flood Vulnerability
Figure 13 shows the vulnerability distribution in Bangkok. Majority of
Bangkok falls under the moderate vulnerability level with an approximate
area of 100,613.34 hectares. Amphoe Bang Su which is located in the northcentral portion of Bangkok just which is just adjacent to Chao Phraya river
has a very high flood vulnerability compared to other amphoe.
Flood risk
Floodrisk modelingmodeling inin Bangkok
Bangkok province:
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Unsurprisingly, amphoes which are far from Chao Phraya river have very
low flood vulnerability. Some of these amphoes are Bang Khen, Bang Khun
Tian, Minburi, Nong Chok, and Bankapi (Table 9)

Figure 13: Area distribution of flood vulnerability classes

Figure 14: Flood vulnerability map of Bangkok
4.3 Distribution of Areas Based on the Level of Flood Risk
Using the flood hazard and flood vulnerability layers, the flood risk
map for the entire Bangkok was derived using raster overlay analysis byemploying raster multiplication. Figure 15 and Table 10 summarizes the
distribution of flood risk in Bangkok at the Amphoe level. Majority of
Bangkok province falls under the high risk category at 48, 977.43 hectares
or 31% of the province’s total land area. As expected, areas that fall under
the high risk category are either near Chao Phraya river or areas
characterized by relatively high rainfall occurrence. Such Amphoe are
Taling Chan and Phasi Charoen. In contrast, amphoe that are far from Chao

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Phraya river like Nong Chok, Bang Khen, and Don Muang were very low
risk to flooding

Figure 15: Area distribution of flood risk classes

Figure 16: Flood risk map of Bangkok
5. CONCLUSIONSFor calculation of flood risk we used analytical hierarchical method forweighting different factors affecting flood risk which gives very efficientresults as most of high flood risk along the river named chao phraya as it
can be acceptable practically and also consistency ratio was 0.037 which
was less than 0.1 so acceptable. On other hand we used Rank reciprocal
method for calculating weights for factors affecting vulnerability which isalso found to be efficient. We used ArcGIS package which gave highcapability of utility tools in our project Flood risk analysis study is mostFlood risk
Floodrisk modelingmodeling inin Bangkok
Bangkok province:
Province, Thailand
Thailand13
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important because if we have idea about risk before disaster we can makesome protective measures and can creat capability to fight against thedisaster . As this risk is highest in such capital cities or main cities ofcountry then it can affect the economy of that country at its most.This study
results can help to government of respective countries for getting idea
before disaster or upcoming future assessment .
There is limitation in AHP method we found that we cannot use thisfor less than three parameters.We can consider more factors like runoff,drainage density etc. for increasing accuracy of result and also field survey
is important as a validation procedure.Outdated and limited data causes theresults of the analysis to be less accurate.We can use artificial neuralnetwork for calculating weights and after comparing both AHP and ANN
we can get more correct result.And also other interpolation methods can beused for rainfall and comparative results can be used for correction.
REFERENCES
Evans Sun Yan, Gunn Neil and Daniel Williams undated. Use of GIS
in Flood Risk Modelling. Environment Agency: Kent, ME 19 5SH.
Sengtianthr Virany 2007. Flood Risk Map using RS and GIS: A Case
Study of Champone District Savannakhet Province , Lao PDR. A paper
presented during the 3rd JPTM held on 13-15 March 2007 at Le Meridien,
Singapore.
Shoastal Cristy 2007. Combining GIS with a Hydraulic Food
Prediction Model: Developing a Custom GIS Tool for Near Real-Time
Flood Inundation Mapping in the Fargo-Moorhead Portion of the Re River
Basin. Volume 9, Papers in Resource Analysis, 17 pp. Saint Mary’s
University of Minessota University Central Services Press. Wirona, MN.
Tanavud, Charlchai et al. 2004. Assessment of flood risk in Hat Yaimunicipality, Southern Thailand using GIS.
UNESCO-IHE Homepage (2011). < http://www.unesco-ihe-fvi.org/>
Wikipedia
OnlineEncyclopedia
2011.
<http://en.wikipedia.org/wiki/Bangkok

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NewGeophysical investigation at
Meghna Dhonagoda Irrigation Project(MDIP)
using ground penetrating radar method
Ram Krishna MAZUMDER1and Mehedi Ahmed ANSARY2
1
Research Engineer, SHMRBBP, BUET, Bangladesh
2
Professor, Department of Civil Engineering, BUET, Dhaka, Bangladesh
ansary@ce.buet.ac.bd
ABSTRACT
Meghna Dhonagoda Irrigation Project (MDIP) is located at northern partof Chandpur district and 40 km south east of Dhaka near the confluence of
the Padma and the Meghna River. MDIP is a 60 km long embankment.
Recently, severe seepage and boiling were observed in the countryside of
MDIP. To find the reason behind these problems, various laboratory andfield tests at different locations of the embankment were carried out. After
collected geotechnical data, cement stabilization at 11 points weresuggested as remedial measures. To assess the strengthening work of
MDIP at different points, geophysical investigation was carried out using
Ground Penetrating Radar (GPR). A 100 megahertz (MHz) frequency
antenna has been used to determine the layer profile of the embankment.
Common Depth Point (CDP) and bi-static high range reflection profilinghas been used for data collection.
Keywords: Geophysical, Ground Penetrating Radar and Common Depth
Point
1. INTRODUCTION
The project is located at 19 km North of Chandpur Town and 40 km South
East of Dhaka near the confluence of the Padma & the Meghna River.
MDIP comprises the gross area of 17584 ha in Matlab Upazilla of Chandpur
district is bounded on the North and the West by the mighty Meghna and on
the East and the South by the Dhonagoda River.
The Project is encircled by a 60.7 km of flood embankment completed
in 1987. After completion of the embankment, severe seepage and boilingwere observed along the countryside of the embankment during floods. The
embankment was breached during 1987 and 1988 floods causing severe
damages. During the flood of 2004, a breach at Nandalalpur occurred but nodamage could be caused as the Bangladesh Water Development Board(BWDB) authorities repaired the breach quickly with the help of local

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people. Furthermore, sliding of the slope of embankments occurred on the
countryside at about 60 places, seepage problems developed at about 25 km
length and boiling occurred at about 120 locations. Figure 1 shows theembankment location and the affected points. The damages were severe andit remained as a threat to future performance of the embankment during
floods (Ansary et al., 2009).
To strengthening the embankment, currently BWDB authorities are
injecting cement grouting up to 5 m to 12 m below the surface. This paper
presents the geophysical study which was carried out to evaluate theperformance of the embankment after the cement grouting was completed.

Figure 1: Location of Meghna Dhonagoda Irrigation Project (MDIP) anderosion points (right)
2. SUBSOIL INVESTIGATION
The field investigation at the embankment site consisted of drilling of
boreholes, recording density or stiffness characteristics of soil layers bycarrying out Standard Penetration Tests (SPT), collection of sufficientnumbers of disturbed and undisturbed tube samples. Also portableseismograph was used to support the result obtained from SPT-N values. A
total of fifty six boreholes at eleven sites were drilled vertically at this siteusing wash boring technique. The depth of boreholes below the groundsurface varied from 10 m to 17 m. In general five boreholes were drilled ateach site across an embankment section.

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2.1 Soil Sampling
Disturbed and undisturbed samples were collected from the boreholes.
A split-spoon sampler was used to obtain the disturbed samples in
conjunction with the Standard Penetration Test. Undisturbed samples werealso retrieved from cohesive layers of the boreholes by pushingconventional 76 mm external diameter thin-walled Shelby tubes following
the procedure outlined in ASTM D1587. The locations of disturbed andundisturbed samples obtained from the boreholes are shown in the bore logs.
The drilling of the fifty six boreholes at the project site, including collectionof disturbed and undisturbed tube samples and performance of Standard
Penetration Test (SPT) were carried out by the Groundwater Hydrology
Division of BWDB.
2.2 Soil Profile and Parameters across Embankment Alignment

A typical soil profile across the embankment is shown in Figure 2.
Particle size distribution was obtained following procedures
mentioned in ASTM D422, ASTM C136 and ASTM D1140 on samples
from different boreholes and from different depths. Particle size
characteristics (d10, d15, d30, d50, d60, d85, percentage of non plastic fines, Cu,Cc) are also presented tabular form. A summary of the amount of finematerial (% finer than #200 sieves i.e. 0.074 mm) in soils at different depths
and in different locations tested (Ansary et al., 2009).
As has been mentioned earlier the subsoil consisted mostly ofcohesionless soil and undisturbed samples could not be retrieved from theboreholes. It therefore became apparent that shear strength parameters forthis layer has to be interpreted from the field-N values based on appropriate
corrections and available empirical relations. Since the soil mineralogy andgrain characteristics could be different from those for which correlations isavailable, it was decided to perform laboratory shear strength tests on
samples reconstituted from disturbed samples at different densities in orderto achieve possible highest and lowest range of strength parameter (Ansary
et al., 2009)..

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Figure 2: Typical Soil Profile across MDIP embankment(after Ansary et al., 2009)

Direct shear tests were performed on reconstituted (near to fielddensity as depicted from SPT) disturbed soil samples from several locationand depth to obtain the angle of internal friction, and cohesion intercept, c ofthe sub-soil. The tests were performed on air dry soil. Specimens were
tested under three different normal stresses (45 kPa, 90 kPa, and 180 kPa)
and the strength parameters were determined from the failure envelope withvarious physical properties of the soil encountered. For the soils tested
apparent cohesion, c was found to be negligible and in the range of 0-16
kN/m. The angle of internal friction, the soils is in the range of 26.7 to 35.8.
It can be seen that the range of void ratio (e) of the soil is 0.81 to 1.13
corresponding to porosities (n) of 0.45 to 0.53 respectively. The
experimental results indicate that the soils of the site are predominantly finesand existing in a loose to medium dense state.
Constant head permeability test was carried out on specimen preparedby mixing soils from different boreholes and depths. For better
representation of field conditions the flow of water was allowed upward
through the specimen by using a special constant head permeameter. The
boiling phenomenon was simulated for the field conditions using thisapparatus. The gradient was found to be lower than the theoretical value of
1.0. The permeability of the soil was also estimated using Allen Hazens wellknown empirical formula of k=Cd210 using the range of C values of 100 to
150 (Lees and Chuaqui, 2004).

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3. GPR PRINCIPLE
Geophysical exploration is a non-destructive, cost effective way to help
locate and characterize features beneath the ground at many sites; GPR is
one of the better techniques for this search in the shallow subsurface. GPR
is a near-surface geophysical technique that can provide high resolution
images of the dielectric properties about 20 meters of the earth. It is a very
useful technique which employ the radio waves typically 16 to 2000 MHz
frequency range, to study structure and features buried in the ground,groundwater, subsurface faulting, and underground cavities (natural or man).
A trigger pulse is generated in the control unit at a normal repetition
rate of about 100 kHz. The trigger pulse is sent through the control cable tothe transmitter electronics in the antenna. In the transducer, each trigger
pulse is transformed into a bipolar pulse with higher amplitude than thetrigger pulse. The pulse shape varies with the electronics and the antenna.
The transmit pulse then propagates along the antenna and is radiated into thesubsurface. The size of the antenna and electrical properties of thesubsurface determine the frequency of the propagating energy. In thesubsurface, reflections occur at boundaries where there is a dielectric
contrast. The reflected portion of the signal travels back to the antenna. The
receiver in the antenna detects the returning signal and sends it back to thecontrol unit. In the control unit the signal is processed and displayed. The
output of the graphic recorder or the display on the video is a representationof the analog signal. Horizontal axis is distance along the surface andvertical axis is two-way travel time of the radar pulse in nanoseconds (ns).
The signal amplitude determines the shade of grey on the paper or the color
on the video display.
The penetration depth is controlled by the GPR centre frequency, theelectrical conductivity and the attenuation of the subsurface deposits. In
low-loss (i.e., resistive) deposits a low centre frequency achieves a large
penetration depth whereas a high centre frequency results in a lower
penetration depth. Figure 3 shows the fundamental principal of GPR.

Figure 3: Fundamental principal of GPR

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3.1 Modal propagation Theory
Modal propagation within a layer waveguide (of permittivity ε2) refers
to lossless propagation and is especially dispersive when the layer thickness
is close to or less than an in-situ wavelength λ¸ (Arcone et al., 1998). In a
two layer dielectric ground, lossless (nonleaky) modes occur when theconfining layers (e.g. air above, for which ε1=1 and dry sand ε3 below) havelower permittivities than the waveguide. In this case, a refraction will occur
in the lower layer at the critical angle, and dispersive modes will develop in
the upper layer (Figure 2). Depending on waveguide thickness d and ε2,higher order modes will develop which have phase fronts that propagate at
speeds determined by discrete angles (measured from vertical) greater thanthe critical angle. The lowest order mode is always the strongest and mostimportant. The modes are determined by the modal equation (Budden,1961) for either transverse electric (TE) or transverse magnetic (TM) waves,such that
R01R12 exp (i2k2d cosθ) = 1
Where R01 and R12 are the TE or TM reflection coefficients for theupper and lower layer interfaces, respectively; k2=k0√ε2 is the propagation
function for the refracting layer; and θ is the modal angle of a particularfrequency with respect to vertical. The quantity k0=2πf/c, where f isfrequency in Hz and c=30 cm/ns. The phase velocity of any particularfrequency is
vph=c/√ε2sin θFor our case of parallel and facing antennas, we consider only TE
waves. In this case all modes have a minimal cutoff frequency where phaseand group velocities equal the velocity within an adjacent, refracting layer
and a higher frequency at which minimum group velocity occurs and energy
is theoretically maximized. This latter phenomenon is known as the Airyphase (Grant and West, 1965). For given values of d and the permittivitiesof each layer, several modes might exist, each of which can support all
frequencies above their own particular cutoff frequency.
Modal propagation losses are caused by transmission through the waveguideinterfaces, intrinsic attenuation within the medium itself, and geometricwavefront spreading. Interface transmission losses and intrinsic attenuation,such as caused by conduction currents or scattering, may be expressed
through a complex, equivalent propagation angle θ + ίγ, for which the phasevelocity then becomes
vph=c/√ε2sinθ coshγ
If ε1>ε2, then transmission leakage into the lower layer can produce
values of γ near unity and attenuation rates can approach several tens ofdecibels per meter. For the case of our refractive waveguide, however, realenergy loss occurs strictly through medium attenuation mechanisms.
Apparent energy loss at any particular frequency occurs from the dispersive
process itself.

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For geometric spreading losses we consider that the amplitudes ofmodes, refractions, and any kind of lateral surface wave decay in proportion
to r2, where r is the range separation between transmitter and receiverantennas. The range is both several wavelengths from the source and muchgreater than the surface layer depth. We assume this range dependency
because very thin layers (in terms of γ) support nearly interfacial waves;interfacial waves along homogeneous ground follow this behavior (Annan,1973), and so do seismic refractions (O’Brien, 1967). Furthermore, the lowfrequency wave velocity that developed in our surface waveguide emulates
refraction along the lower interface (Steven et. al., 2003)
4. FIELD TECHNICS
We used the Geophysical Survey Systems, Inc. (GSSI) model SIR-3000
control unit to set radar parameters and record data to hard disk. We used
separate transmitter and receiver resistively loaded antennas withbandwidths nominally centered near dominant frequencies of 100 MHz(GSSI model 3207).
4.1 Reflection profiling
In reflection profiling mode the antennas are kept at constantseparation, while they are moved along a profile (Figure 4). The
electromagnetic pulses are transmitted at fixed time or distance interval. The
signal is recorded and displayed immediately on a computer screen as GPR
profiles, in which the vertical axis is two-way travel time in nanoseconds(ns) and the horizontal axis is distance along the measured profile. The GPR
data are either collected along a single profile or in a grid of profiles toobtain 2D or pseudo 3D information on structures in the ground. The GPR
data can also be acquired along lines so densely spaced that the line spacing
equals the stepwise along the line. This leads to a 3D data cube, where dataalso can be displayed as time or depth slices. Study was conducted using bistatic high range profiling mode at distance interval according to Figure 4.

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Figure 4: Diagram of the transmit (Tx) and receive (Rx) antennas, airwave,
waveguide dispersive modes, and refraction (Top). 100-MHz antennas withfiber optic circuitry to trigger the receiver and antennas on the study line(bottom).
4.2 Common Depth Point
A common depth point dataset, CDP, is also called a velocity
sounding, since the technique is commonly used for signal velocity
establishment. In CDP mode the antennae separation is increased for eachrecording, while they are kept over a common midpoint (Figure 5a). A CDP
plot contains the direct wave transmitted in the air above the ground, thedirect wave transmitted in the ground and waves reflected from interfaces in
the ground, where the dielectric properties change (Figure 5b). Refracted
waves are seldom present in CDP soundings. This is related to the fact thatthe electromagnetic wave velocity decreases with depth together withincreasing water content with depth.
5. RESULT ANALYSIS AND DISCUSSION
The test area of this study consisted of 75m along embankment foot andformed a 2-D section of underground stratum structure. Figure 6 displays
the GPR section for distance on ground surface, at 0 m~40m. From the
Figures, a clear surface of reflection can be observed along ground surface
at underground depth of 6m, which shows different electrical properties ofstratum above and below the reflection interface. This reflection interface isalmost parallel to the ground level.

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Figure 5: Principles of GPR in CDP mode. a) In CDP mode a set of atransmitting antenna (Tx) and a receiving antenna (Rx) are moved awayfrom each other. The six first antenna positions are shown with the path of
the reflected wave from the first reflector. b) Sketch of the path of the mostcommon waves that is present in a CDP.
Groundwater table is present just below the 3m. Figure 6 implies that
cement grouting has been successfully injected about 6m below the surface.
The reflection signal is also very strong at 13m depth, which shows that theproperty of this layer differs a lot from the layers above and below it. Figure
7 shows the wiggle shape. This figure indicates that the strong signal ofreflection below 6m depth is caused by rich content of underground water.
Figure 8 shows the data collection in CDP mode. This data is used toestimate velocity of the soil with respect to depth profile.

Figure 6: GPR Section at a distance of 0m~40m from ground surface(different color)
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Figure 7: GPR Section in wiggle mode at a distance of 0m~75m fromground surface

Figure 8: Multifold data are normally acquired or sorted in CDP gathers as
represents in ray path form (left). An optimum stacking velocity versus
travel time can be extracted which permits coherent summation of multifold
survey data as well as a velocity depth function such as shown (right).
4. CONCLUSIONSIn this study, a 100 MHz frequency GPR antenna was used at Meghna
Dhonagoda Irrigation Project (MDIP) site to evaluate the remedial measures
undertaken using cement grouting technique at the river side in two affected
embankment points. Common Depth Point (CDP) and bi-static high range
reflection profiling was used for data collection. The collected data
indicated that a water table did exist at a depth of 3m which wassubstantiated by the piezometer located at the investigated points. Also thecollected GPR data indicated that the soil up to a depth of 6m might have
improved by cement grouting technique.

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REFERENCES
Ansary, M. A., Yasin, S. J. M., Siddque, A., Abedin, M.Z. andSafiullah, A. M. M., (2009), Soil Investigation of Meghna Dhonagoda
Irrigation Project (MDIP) Embankment, Proceedings of the Bangladesh
Geotechnical Society’s Conference in 2009 in Dhaka, Bangladesh.
Annan, A. P., (1973), Radio interferometry depth sounding: Part ITheoretical discussion, Geophysics, Vol. 38, pp. 557–580.
Arcone, S. A., Lawson,D. E., Delaney,A. J., Strasser, J.C., andStrasser, J. D., (1998), Ground-penetrating radar reflection profiling ofground water and bedrock in an area of discontinuous permafrost.
Geophysics, Vol 63, pp. 558-669.
ASTM (2006), American Society for Testing and Materials Standards,
Vol. 04.08.
Budden, K. G., (1961), The wave-guide mode theory of wave
propagation, Prentice-Hall, Inc.
BWDB (2007), Cross Section of Flood Embankment at Boring Points
of MDIP, Memo. No.PMO-JMREMP/ S-83/ 632, Project Director,
JMREMP, Bangladesh Water Development Board, July 2007.
Grant, F. S., and West, G. F., (1965), Interpretation theory in appliedgeophysics, McGraw-Hill Book Co.
Lees, D. & Chuqui, M. (2004), Soil Grouting: Means, Methods andDesign, Grouting 2003, pp. 1347-1359.
O’Brien, P. N. S., (1967), The use of amplitudes in seismic refraction
survey, in Musgrave, A. W., Ed., Seismic refraction prospecting: Soc. Expl.
Geophys, pp. 85-118.
Steven, A. A., Paige, R. P. and Lanbo, L., (2003), Propagation of aground penetrating radar (GPR) pulse in a thin-surface waveguide,
Geophysics, Vol. 68, No. 6 P. 1922–1933.

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New Technologies for Urban Safety of Mega Cities in Asia

Review of nuclear energy demandin urbanareas of India;
VIS-À-VIS seismic disturbances
T.Sai Sumanth REDDY1 and Ramancharla Pradeep Kumar2
1
B.Tech Student, Pandit Deendayal Petroleum University,
Ahmedabad, India
sumanth.bunty@gmail.com
2
Associate Professor, Earthquake Engineering Research Centre,
IIIT Hyderabad, Hyderabad, India.
ramancharla@iiit.ac.in
ABSTRACTDisaster Demand for electricity in urban areas is increasing world over,because electricity is the prime lifeline support. Due to increase in fossil
fuel prices coupled with concerns related to global warming, demand fornuclear energy is increasing. Around 30 countries are now using nuclear
energy for production of electricity. However, its share in electricity
production is varying from country to country. In some countries it is only
3% and in some countries it is around 50%. In light of March 2011 nuclear
energy are reviewing the safety of their reactors against natural disasters.
In this regard, authors proposed to study the current and projected nuclear
energy demand for electricity supply in urban areas of India on one handand scenario of seismic hazard and risk on the other hand.
Keywords: Nuclear accident, active faults, seismic risk, safe energy
1. INTRODUCTION
Electricity is one of the world’s fastest-growing form of end-use energy
consumption.Net electricity generation worldwide will rise by 2.3 percent
per year on average from 2007 to 2035 as compared to 1.4 percent per year
growth for total world energy demand. The growth in electricity generation
for non-Organization for economic Co-operation and development countries
increase by an average annual rate of 3.3 percent, as rising standards ofliving increases the demand. Figure 1 shows the distribution of electricity
generation from different sources till 2035.
The rise of global warming concerns throughout the world over thelast ten years has led to an interest in what once considered a dead marketnuclear energy. After the Cold War, nuclear energy development waslargely forgotten for many years until this renewed desire among developed
nations for alternative energy sources once again thrust the idea of nuclear
power into mainstream consciousness. As the price of oil and global

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warming concerns both continue to raise steadily, a renewed interest in theclean-burning properties of nuclear power are becoming much more
attractive.

Figure 1: Electricity Consumption Bar Graph
Nuclear power is energy which is produced with the use of acontrolled nuclear reaction. The process of generation of nuclear power
starts with the mining and processing of uranium and other radioactive
elements. These elements are used to feed the reactor of a nuclear power
plant, generating a reaction known as fission which creates intense heat,turning water in the plat into steam. The steam powers steam turbines,
which generate electricity and feed the electricity into electrical grid .When
nuclear power is used to power something like a submarine, the reactor runs
the engines, with the steam directly powering the engines. In both cases, thereactor requires careful supervision, because runway nuclear reactions must
be stopped as quickly as possible to prevent serious problems. Many nuclear
power plants have extensive automated systems which help to identify
potential trouble spots, and these systems can also re-route power, turn off
parts of the plant, and perform other tasks which make the plant safer andcleaner.
2. NUCLEAR POWER SCENARIO AROUND THE WORLD
The world’s first nuclear power station became operational in 1956 at
Calder Hall in Sellafield, US with an initial capacity of 50 MW (later 200
MW). A year later in 1957 the United States got its first commercial nuclear
generator, the Shipping port Reactor, in Pennsylvania. The worldwide
capacity rose quickly to 100 GW by late 1970’s and then to 300 GW by late1980s. However, thereafter the growth slowed down reached only by 366
GW in 2005. It was largely due to rising economic coasts, coming fromextended construction time and the lower oil prices.

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Nuclear power provides about 6% energy and 14% electricity
requirement of the world. About 40% of electricity requirement is met bycoal, followed by gas (21%) and hydro (16%). France, Japan and US
account for about 50% of the nuclear generated electricity. Currently, there
are 443 commercial nuclear reactors operating in 31 countries with about
378 GW total capacity. Over 60 power reactors are under construction in 15
countries, notably China, South Korea, India and Russia. The International
Atomic Energy Agency (IAEA) anticipates addition of 73 GW in new
capacity by 2020 taking the total to 463GW, and then to 546-800 GW by
2030.
Table 1: Top ten countries in 2010 with largest contribution from nuclear
power
S.no

Country

Percentage

1

France76.2

2Lithuania

72.9

3

Slovakia

56.4

4

Belgium

53.8

5

Ukraine47.4

6

Sweden42

7

Slovenia

41.7

8

Amenia39.4

9

Swizerland

39.2

10

Hungary

37.2

Table 2: Top10 countries by number of nuclear reactors in 2010 andnuclear energy as percentage of total energy
S.noCountry

Number of Reactors

Percentage

1

US

104

19.7

2

France

58

76.2

3

Japan

54

24.9

4

Russia

31

16.9

5

South Korea

20

35.6

6

UK

19

17.4

7

Canada

18

14.9

8

India

18

2.9

9

Germany

17

28.3

10

Ukarine15

47.4

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Table 3:The top ten countries planning for new nuclear reactor and MW
planned
S.no

Country

New Reactors
PlannedNumber of
MW Planned

1

China

37

38,3602

France23

21,500

3

Japan

13

17,9154

US

11

13,8005

Russia

7

8,000

6

South Korea

6

8,190

7

UK

4

6,600

8

UAE

4

5,600

9

Canada

4

4,400

10

South Africa

3

3,565

3. NUCLEAR POWER SCENARIO IN INDIA
India’s electricity sector is struggling to cope with current demand, which
has been mushrooming as a consequence of high population growth levels
and continued economic expansion. This presents a major obstacle to thecountry’s business environment and economic development, and cements
existing regional wealth discrepancies. In response to the problem, utilities
all over the country are busy growing their generation capacities.
Electricity demand in India is increasing rapidly the 830 billion
kilowatt hours produced in 2008 was triple the 1990 output, though still
represented in some 700 kWh per capita for the year. With hugetransmission losses, this resulted in only 591 billion KWh consumption.
Coal provides 68% of electricity at present, but reserves are limited. Gas
provides 8% whereas hydro provides 14% of electricity.
Currently India produces about 4,780 MW power from its 20
operational nuclear power plants, which is only 3 percent of total power
generated in the country. Indian stand on nuclear energy is clear, it sees it as
an important clean source of energy along with other renewable sources thatwill reduce dependence on import of crude oil as well as help mitigate
global warming.
India’s energy requirement is growing at about 6 percent annually,
fueled mostly by a growing population and a robust economy, the thirdlargest in Asia. Besides, still nearly 40 percent of households have no accessto electricity. Hence, it wants to expand the nuclear power program to coverits future energy need. It plans to add 20 GW of nuclear power capacity by2020 and aims to meet 25% of its needs through nuclear power by 2050.
This expansion became possible after the nuclear ban on India was lifted in2008 after 34 years.

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Table 4: New nuclear reactors on the anvil in India
S.no

Reactor type

Location

Capacity(MWe)1

Indigenous PHWRs

Kumharia,Haryana

4 x 700

2

Indigenous PHWRs

Bargi , MP

2 x 700

3

LWR(Russian VVER)

Koodankulam,TN

4 x 1000*4LWR(French EPR)

Jaitapur, Maharashtra

6 x 1650

5LWR(US, GE-Hitachi)

Chhanyamithi Virdi, Gujrat

6 x 1000**6LWR(US, GE-Hitachi)

Kovvada, AP

6 x 1000**7LWR(Russian VVER)

Haripur, WB

6 x 1000***Additional Potential 2 x 1000 Mwe already under construction**Final capacity will depend on the actual rating of reactors selected
PHWR-Pressurised Heavy Water Reactors, LWR-Light Water Reactors

4. MAJOR NUCLEAR DISASTER IN THE WORLD
4.1 The Three Mile Island Accident
This accident pertains to pressurized water reactor (PWR). A
malfunctioning in the secondary water supply caused the pumps to stop
working. Although the Emergency Core Cooling System started as it was
designed to do, human error led to mistaken decision to shut it down. Largeamounts of coolant escaped leading to heat buildup in the reactor. It resulted
in severe core meltdown.
Some of the radioactive material from the fuel rods leaked into theprimary coolant system, and was released into the atmosphere. However,since the reactor building and the structures remained intact, most of theradioactivity remained safely contained within the reactor building. The
impact on the outside world was minimal.
4.2 The Chernobyl Disaster
The design of the Chemobyl was totally different from the Three Mile
Island reactor in US. It was moderated by graphite and cooled by water. The
accident occurred during a design test when safety interlocks were bypassed
and the reactor was never actually shut down, thus the fission processcontinued uncontrollably, and the sudden surge in output shattered thereactor, opening up a gaping hole in the upper part of the building. The
combustible graphite moderator then caught fire, sending out vast clouds ofradioactive material over a huge area.
Despite several irregularities during tests on the reactor’s power
supply, including an unexpected drop in reactor output, operators continued
the test, repeatedly violating operating procedures. Structural flaws in thereactor also exacerbated this situation.

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Table 5: Comparison of Major Disasters in the world
Fukushima(Japan)

Chernobyl(Former
USSR)

Three Mile Island (USA)

Date of incident

March 11,2011

April 26,1986

March 28,1979

Rating on the
nuclear events
scale(1-7)

Level 7

Level 7

Level 5

Type of reactor

Light water
reactor(BWR)

RBMK-type reactor
graphite-moderated
water cooledLight water
reactor(pressurized water
reactor)UNITS 1-4(total of 6
reactors)

Units 4(total of 4
reactors)

Units 2 (total of 3 reactors)

Output capacity
at the time of
accident

1244mw

1000mw

960mw

Date ofCommensing

1971-1978

1984,march

1978,december

Causes andnature ofaccident

Loss of cooling due
to damage caused byearthquake andtsunamiPower surge during
testing causes fire andexplosion.release oflarge amount ofradioactive material

Equipment failure andhuman error causes
leakage of reactor
coolant.The reactor coreundergoes 45% meltdown

Reactor(s)affected

4.3 The Fukushima Nuclear Disaster
The fukushima disaster was triggered by earthquake and aggravatedby the tsunami. The plant comprises of six separate boiling water reactors(BWRs). Experts consider this accident to be the second largest nuclear
accident after the chemobyl disaster, but more complex as multiple reactors
were involved. At the time of the quake, reactor 4 had been de-fueled while
5 and 6 were in cold shutdown for planned maintenance. The remaining
reactors shutdown automatically after the earthquake, the electricity grid
was knocked out and generators started operating the cooling water supply.
The plant was protected by a seawall designed to withstand a 5.7 m tsunami
but not the 14m maximum wave which arrived 40-60 minutes after theearthquake.
The entire plant was flooded and the diesel generators got damaged.
All power for cooling was lost and reactors started to overheat, due tonatural decay of the fission products. Three reactors experienced complete
melt down and hydrogen explosions led to release of radioactivity into theenvironment.

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5. NUCLEAR ACCIDENTS IN INDIA
Nuclear establishment in India is known for its secrecy and the public, by
and large, knows little about how the functioning of nuclear activities. In
absence of an independent safety regulation body, people fear the safety
standards are actually not very high in India. Following is a list of accidents
that is known in the public domain.
April 2010: In a bizarre radiological accident in Delhi, the improper
disposal of a derelict gamma-ray research device at the university of Delhi
found its way to a scrap market in west Delhi and resulted in the death of ascrap-metal worker.it was owned by the university since 1968,but unused
since 1985,and was sold to a scrap dealer in Feb 2010.Scrap workers
dismantled and cut it into pieces unaware of the hazardous nature to thedevice. Eight were hospitalized where later, one died of exposure.
November 2009: Fifty-five employees consume radioactive material
after triturated water finds it way into the drinking water cooled in kaiga
generating station. The NPCIL attributes the incident to “an insider’smischief”
April 2003: Six tones leak of heavy water at reactor 2 of the narrowatomic power station (NAPS) in Uttar Pradesh, indicating safety measures
have not been improved from the leak at the same reactor three years
previously.
January 2003: Failure of a valve in the kalpakkam atomic
reprocessing plant in Tamil nadu results in the release of high level waste,
exposing six workers to high doses of radiation. The leaking area of theplant had no radiation monitors or mechanisms to detect valve failure,
which may have prevented the employees’ exposure. A safety committee
had previously recommended that the plant be shut down. The management
blames the “over enthusiasm” of the workers.
May 2002: Titrated water leaks from a downgraded heavy water
storage tank at the tank farm of Rajasthan atomic power station(RAPS) 1 &2 into a common dyke area. Substantial amount of radioactivity was
released into the environment.
November 2001: A leak of 1.4 tons of heavy water from themoderator system at NAPS unit 2.Various workers involved in the clean-up
received ‘significant uptakes of tritium’, although only one had a radiationdose over the recommended annual limit.
March 1999: Somewhere near four and fourteen tonnes of water leaks
from the pipes at madras atomic power station (MAPS) at kalpakkam, Tamilnadu, during a test process. The pipes have a history of cracks and vibration
problems. Forty-two people were reportedly involved in mopping up theradioactive liquid.

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February 1994: Helium gas and heavy water leak in unit 1 of RAPS.
The plant was shut down until March 1997.
March 1993: Two blades of the turbine in NAPS unit 1 break off,slicing through other blades and indirectly causing a raging fire, whichcatches onto leaked oil and spreads through the turbine building. The smoke
sensor fail to detect the fire, which is only noticed once workers see theflames. It causes a blackout in the plant, including the shutdown of thesecondary cooling systems, and power is not restored for seventeen hours.
In the meantime, operators have to manually activate the primary shutdown
system. They also climb onto the roof to open valves to slow the reactions in
the core by hand. The incident was rateds as level 3 on the international
nuclear event scale, INÉS.
May 1992: Tube leak causes a radioactive release of 12 curies ofradioactivity from tarapur atomic power station.
January 1992: Four tons of heavy water split at RAPS.
December 1991: A leak from pipelines n a vicinity of CIRUS and
Dhruva research reactors at the Bhabha atomic research center (BARC) in
Trombay, Maharashtra, results in Cs-137 soil combination of thousands oftimes the acceptable limit. Local vegetation was also found to becontaminated, through contract workers digging of the leaking pipeline werereportedly not tested for radiation exposure, despite the evidence of theirhigh dose.
July 1991: A contracted laborer mistakenly paints the walls of RAPS
with heavy water before applying a coat of whitewash. He also washed his
paintbrush, face and hands in the deuterated and titrated water, and has notbeen traced since.
March 1991: Heavy water leaks at MAPS take four days to clean up.
6. SEISMIC HAZARDS IN INDIA
The massive earthquake in japan and the subsequent nuclear crisis has
triggered fears of nuclear security across the world, including India.
Most of the India falls in the moderate risk to very high risk seismic
zones and so do majority of India’s nuclear reactors. While there are no
nuclear projects in zone 5(seismic intensity of 8 and above),the proposed
Jaitapur nuclear power plant falls in zone 4 on the earthquake hazard zoning
map. The map below plots India’s nuclear power plants on a seismic map.

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Figure 2: India map showing location of NPP and seismic zonation.

Figure 3: Seismic Faults in India [Based on GSI, 2003]

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CONCLUSIONS
Energy has been crucial to the survival of mankind and every major step inour evolution has seen a manifold increase in energy consumption. Current
perception is that nuclear energy holds the key to survival and growth of
mankind for this century and beyond. Nuclear energy is proven to be theenergy that the man will rely on in the future as alternative energy due toavailability of the nuclear fuels and the low running cost and its long life.
In this paper it is clearly shown that world over there is a great
demand for producing nuclear energy and India too is trying to increase its
production. On the other hand, accidents world over have caused a great
concern. Looking at the prevalent seismic hazard in the country India needs
to cautiously decide whether to go for nuclear energy or other non-harmfulenergy sources.
REFERENCES
http://www.world-nuclear.org/education/wast.htm
http://timeforchange.org/pros-and-cons-of-nuclear-power-andsustainability
http://www.upi.com/Business_News/EnergyResources/2011/06/01/In
dia stands-firmon-nuclear-power/UPI-29561306941789/
http://www.npcil.nic.in/main/Maps.aspx
http://www.world-nuclear.org
http://www.energyquest.ca.gov
http://www.globalsecurity.org/wmd/world/india/reactor.htm.

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Basic study on restoration
capability of bio-cemented sandy soil
1

Reiko KUWANO1, Makoto HOSOO 2
ICUS, IIS, The University of Tokyo, Japankuwano@iis.u-tokyo.ac.jp
2
Kajima Corporation, Japan

ABSTRACTA new technique of ground improvement by microbial function has been
recently proposed, as more eco-friendly technique than conventional one.
Metabolic function of microbes produces carbon dioxide, which helps togenerate calcium carbonate when sufficient amount of calcium ion is
supplied in pore fluid of soil. Such a cementation process may be operated
repeatedly as long as microbes’ function is active.
In this study, a series of triaxial test was conducted in order to evaluate therecovery of shear-damaged cementation generated by those function in
Toyoura sand specimens. The ureolytic bacterium, Bacillus pasteurii, wasused to accelerate the precipitation of calcium carbonate (CaCO3). It was
found that stiffness of the bio-cemented specimen degraded by shear but it
recovered when the microbes in the specimen were activated by grouting.
The strength of the damaged specimen can be also recovered to some extent
as long as the damage given by shear was not too large.
Keywords: microbe, bio-cementation, sand, triaxial test, stiffness andstrength recovery
1. INTRODUCTION
It was reported that urease enzyme from “Bacillus Pasteurii” could be used
to add cementation in sand (Dejong et al., 2006; Whiffin et al., 2007).
Bacillus Pasteurii helps to precipitate calcium carbonate through thechemical process as shown in Equations (1), (2) and (3). Precipitatedcalcium carbonate on a soil grain and/or between soil particles seem tocontribute to stiffen and strengthen the ground.
CO(NH2)2 +2H2O → 2NH4+ +CO32CO2+H2O→CO32-+2H+
Ca2++CO32-→CaCO3↓

(1)
(2)
(3)

Hosoo and Kuwano (2010) and Hosoo (2011) conducted a series oftrial test in order to evaluate the degree of soil cementation generated bythose microbial function in Toyoura sand, and reported that the degree of
cementation in soil can be monitored by the change of calcium ion in pore2351

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liquid. In this study, a series of triaxial test was carried out in order toevaluate the recovery of shear-damaged cementation generated by microbesin Toyoura sand specimens.
2. TEST PROCESURE
A cylindrical specimen of diameter of 5cm and height of 10.5cm was
prepared by air pluviation method, using Toyoura sand. The specimen was
initially water-saturated and isotropic stress of 50kPa was applied, before
Pasteurii (2x106 cells/ml) of 100ml was penetrated into the specimen. Grout
was then percolated into the microbe mixed specimen to accelerate thefunction of microbes. Composition of the grout is shown in Table 1. The
bio-cemented specimen was sheared to some extent by triaxial compression,then axial force was unloaded to bring isotropic stress state. Grout was
percolated again into the shear damaged specimen to restore the mechanicalproperties of the specimen. Shearing, grouting, and curing cycle was thenrepeated to examine the recovery of stiffness and strength of the specimen.
In all process of the test, the density of calcium ion in the grout out-flown
from the specimen was monitored. Small cyclic loading of 0.001% axial
strain level was also applied to evaluate small strain stiffness of thespecimen. Test procedure and condition are summarized in Table 2.
Table 1: Composition of the grout
Component
Bacto nutrient broth
Urea
CaCl2・2H2O
NH4Cl
NaHCO3

Amount (g/L)
3
30
70
10
2

Table 2: Test procedure and test condition

Initial state and cementation
density：Dr=90%
Grouting was applied to the microbe mixed specimen
5 times at every 24 hours.

Shearing and restoration
Curing for 24hours, Shearing (1)→Curing for
24hours, Shearing (2)→Shearing(3)→grouting→Curing for 24hours, Shearing(4)→→repeating cycle of grouting, curing andshearing, until shearing (13)

3. TEST RESULTS
The evolution of Young’s modulus in the process of the cementation underisotropic stress of 50kPa is shown in Figure 1. The value of Young’s
modulus was increased with grouting and elapsed time. Relationshipbetween Young’s modulus and the content of calcium carbonate in thespecimen is plotted in Figure 2. It is indicated that the stiffness notably
increased with the precipitation of calcium carbonate in the range of 1 to 4%.

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Figure 1: Young’s modulus evolution during cementation process
under isotropic stress of 50kPa

Figure 2: Relationship between small strain stiffness
and calcium carbonate content during cementation process
Stress strain relationships until the 8th shearing and until the end areshown in Figure 3 and 4 respectively. At the 1st shearing, the maximum
deviator stress, qmax, was about 1100kPa. Shearing was continued until thedeviator stress dropped to 600kPa. Then axial unloading was made to theisotropic stress state. After 24 hours, the 2nd and 3rd shearing were given to
confirm no further development of cementation, grouting was applied to thespecimen and was cured for 24 hours. At the 4th shearing, the maximum
deviator stress, qmax, was recovered to 750kPa. Such a process, shearing
until q exceeding its peak and dropping to 600kPa, grouting and 24-hourBasic study on restoration capability of bio-cemented sandy soil
Basic study on restoration capability of bio-cemented sandy soil

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curing, was repeated. As shearing steps progressed, qmax recovery became
smaller. From 10th shearing, qmax recovery could not be recognized.

Figure 3: Stress strain relationship up to 8th shearing cycle

Figure 4: Stress strain relationship
Figure 5 shows the relationship between qmax and calcium carbonate
content. When the shearing damage was accumulated, recovery of thestrength could not be expected. Young’s moduli are plotted against calcium
carbonate content in Figure 6. (1) to (9) indicates the stiffness value justbefore the shearing process. After the 10th shearing, small strain stiffness
could not be obtained because strain level exceeded the working range of4
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LDT. Young’s moduli increase and decrease according to grouting andshearing. It seems that even though the specimen was severely damaged,
stiffness increased to some extent as the grout tended to penetrate into thedamaged location. The specimen after the test was found to be separated
into several blocks, and the surface of the blocks was hardened. The grout
appeared to penetrate along clacks and particular water pathway in thespecimen.

Figure 5: Maximum deviator stress and calcium carbonate content

Figure 6: Small strain stiffness and calcium carbonate content
4. SUMMARY
In the bio-cemented sand specimen using the function of Bacillus Pasteurii,
degree of cementation was monitored by the measurement of small strain
Basic study on restoration capability of bio-cemented sandy soil
Basic study on restoration capability of bio-cemented sandy soil

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stiffness. It was found that the increase in stiffness had good agreement withthe amount of calcium carbonate precipitation. The stiffness of the specimen
significantly reduced when it was damaged by shear, but notably recoveredby re-grouting to activate the function of microbes. The strength of thespecimen was also recovered to some extent as long as the damage given by
shear was not too large. Such restoration of mechanical property of biocemented soil by re-activating the function of microbes was continued forabout two weeks.
REFERENCES
Jason T. DeJong, Fritzges, M.B. and Nüsslein, K., 2006. Microbiallyinduced cementation to control sand response to undrained shear. Journalof Geotechnical and Geoenvironmental Engineering, Vol.132, No.11, 3811392.
Marien P. Harkes, Van Paassen L.A., Booster J.L., Whiffin V.S., Van
Loosdrecht M.C.M., 2010. Fixation and distribution of bacterial activity insand to induce carbonate precipitation for ground reinforcement.
Ecological Engineering, Vol.36, Issue2, 112-117.
Hosoo,M. and Kuwano,R., 2010. Effects of nutrient concentration on
microbial cementation in Toyoura sand, Proc. 9th International symposiumon new technologies for urban safety of mega cities in Asia, USMCA, Kobe,
October 2010, CD-ROM.
Hosoo,M., 2011. Study on Healing Capability of Bio-Cemented Sandy
Soil. Master thesis, faculty of Engineering, the University of Tokyo (inJapanese).

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Asia
NewTransformation of hybrid color spacefor road extraction
using high resolution image
Sanit ARUNPOLD
Remote Sensing and Geographic Information System,
Asian Institute of Technology, Thailand
sanit.arunpold@ait.asia
ABSTRACTThis paper presents a methodology for the extraction of roads in urban areaby using multi-color spaces rather than the convention RGB color space.
The color spaces include HSI, YCbCr and I1I2I3. The model was thoroughly
investigated for accuracy using a high resolution Quick bird image for
Dhaka City. The results showed that the hybrid color spaces are a better
option for feature extraction as compared to RGB as they were able to show
an accuracy of 75.42% by extracting 1317 m. of road from an actual 1746
m. of road
Keywords: Feature extraction, color space transformation, urban mapping
1. INTRODUCTION
Road network is changed at a rapid rate in recent years because of urban
development. Therefore, it is difficult to maintain the accuracy andprecision of the road network for some applications such as city planning,drainage system, and urban expansion management system. Semi-automaticand automatic extraction of roads for updating city map has recently cometo research area.
Road extraction strategies can be divided into two categories as, semiautomatic extraction and automatic extraction. In terms of semi- automatic
road extraction, all the initial points or road seeds need to be provided.
However, in fully automatic extraction, the road seeds can be detected
automatically and linked to complete the road network (X. Y. Jin and C. H.
Davis, 2003). In generally, automatic way is more preferable than the
manual operations that acquire lots of manpower and time in mapping theroad network (A. Chang S. K. Kyu and B. R. Sang, 1997)
There are alternative ways suggested was based on “simply the best
concept.” In this project, to study new algorithm based on hybrid simple
color spaces segmentation is proposed for the road extraction. Moreover,hybrid color spaces segmentation can be extracted more information aboutroad network categories separated into highway road network (asphalt road)2411

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and rural road network (non-asphalt road).
Classification was based on different color spaces model, including
HSI (Hue, Saturate, Intensity), I1I2I3, YCbCr, RGBNIR and Intensity
emphasis. All of models may obtain advantages to separate vegetation, build,highway and rural road network. Because each object characteristic affected
an image scene with systematic reduction of reflectance caused by sun angle
and light intensity, every area in the same scene are affected by the same
condition. There are different reflectances in each characteristic of eachobject. Therefore, the color space segmentation can be seen by enhancing
some color spaces in different ways.
1.1 Color Space Components
The satellite images in used were captured in full color forms. Thus,
the basic RGB color model can be utilized to study the characteristics of thesatellite image. In this study with more color models namely YCbCr, HIS,
I1I2I3 and intensity emphasis were selected for investigations. A meaning ofeach color space model as below:YCbCr model, which is commonly used as digital video formats,consists of below:• Y (represents luminance or a measurement unit of the energy
amount that an observer perceives from a light source)• Cb (represents the difference between the blue component and areference value)• Cr (represents the difference between the red component and areference value)
HSI model meanings of below:• Hue (a color attribute that describes a pure color like yellow,
orange, or red)
• Saturation (a measurement of the degree to which a pure color isdiluted by white light)• Intensity (intensity or average value of R, G and B at specificlocation).
I1I2I3 model is performed systematic experiments of region
segmentation derive a set of effective color features. Intensity emphasis is
modification formula from I1I2I3 and calculated into six different channels
such as average all bands, find range and emphasis each band.
1.1.1. RGB(Cheng, 2001) The RGB color space can be geometrically represented
in a 3-dimensional cube. The coordinates of each point inside the cube
represent the values of red, green and blue components, respectively. The
laws of colorimetry are: (1) any color can be created by these three colors
and the combination of the three colors is unique; (2) if two colors areequivalent, they will be again equivalent after multiplying or dividing the2242

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three components by the same number; (3) the luminance of a mixture ofcolors is equal to the sum of the luminance of each color. The tristimulus
values that served as the color basis are: 425.8 nm for blue, 546.1 nm forgreen, and 700.0 nm for red. Any color can be expressed by these threecolor bases.
1.1.2 HSI Color Space
The color space is established in 3 dimensions including hue,saturation and intensity.Hue is what most of us think of when we think of"color." It is the generic name used to describe a color, e.g., red, green,
yellow, orange, etc. (Sara Agee, 2006)Saturation is how pure the color is. A
fully saturated color is the truest version of that color. Primary colors (red,yellow, and blue) are "true", so they are also fully saturated. (Sara Agee,2006). Intensity is brightness or dullness of a color. A pure color is a highintensity color. A dulled hue (a color mixed with its complement is called alow-intensity color.) (Johannes Itten,1916)
1.1.3 YCbCr(David B.L. Bong,2009) is a family of color spaces used as a part of
the Color image pipeline in video and digital photography systems. Y is theluma component and Cb and Cr are the blue-difference and red-difference
chroma components.
1.1.4

I1I2I3(Cheng, 2001) Performed systematic experiments of region
segmentation derive a set of effective color features. At each step of therecursive region splitting, new color features are calculated by KarhunenLoeve transformation of R,G, and B. It applied eight kinds of color pictures,
analyzed over 100 color features, and found a set of effective color features
as follows:
I1 presents the average of DN in three bands same as I axis in HSI
color space.
I2 presents the different of DN between longest and shortest
wavelength.
I3 present the different of DN emphasis to the shortest wavelength.
1.1.5 Intensity Emphasis is modification formula from I1I2I3 by emphasis
each band so that in Intensity emphasis in this project will have six
parameter as below:I1 presents the average of DN in four bands.
I2 presents the different of DN between longest and shortest
wavelength.
I3 present the different of DN emphasis to the NIR.
I4 present the different of DN emphasis to the red.
I5 present the different of DN emphasis to the green.
I6 present the different of DN emphasis to the blue.

Transformation ofTransformationof hybridhybrid color
color space
space forfor roadroad extraction
extraction using
usinghighhighresolution
resolutionimage
image

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2. METHODOLOGY
2.1 Software and data uses
The processing in this paper was processed on raster and vector data.
Thus there is necessary to use these software including• ERDAS Imagine 9.1 was used for image processing, color spaces
transformation, and model maker.
• ArcView GIS 3.2a was used for check accuracy assessment.
This paper works on the process to solve the problems on highresolution images. A scene of high resolution images was induced forprocessing including:• Image : RGBNIR, Multi-spectral Satellite Image from Quickbird• Resolution : 0.6 meter• Captured date:22 November, 2007
• Study Area : Dhaka Cooperation City
• Area for experiment : 467,500 sq.m.
2.2. Model
The methodology of this paper tries to extract/identification road
network from high-resolution remote sensing image by using different color
spaces then to select suitable color model for them. Moreover, createmodeler to semi-automatic to classify road network by setup threshold of
highway and local road.
2.3 Color space transformation
The color space which are using in this project as:• HSI (Hue, Saturate and Intensity)• I1I2I3• YCbCr• Intensity emphasis or I1I2I3I4I5I6
In this research, this study concentrates on color spaces, which issuitable for extracting road feature network and classifying road type asasphalt and non-asphalt. The color space transformation is the process oftransform data(RGB) to differentiate types for enhancing color of eachobject. In this study, hypothesis of color space which classified andextracted road network are HIS, I1I2I3, YCbCr and Intensity emphasis. Thus,
the research tried many different band for extracting the meaningful ofimage, checking the spectral signature by selection on Area of Interest(AOI), and comparing together.

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FigureFigure2.1:
2.1:
Flowchart
Flowchart
forforhybridhybrid
color
color
space
space
forforroad
road
extraction
extraction
Since
Sinceallallcolors
colorscancanbebematchedmatchedbybyproper
properamounts
amountsofofthree
threeprimaryprimary
colors,colors,three
threenumericalnumericalcomponents
componentsarearenecessary
necessaryand
andsufficientsufficienttotodefine
definea acolor.
color.It Itis isthen
thennatural
naturaltotorepresent
representcolors
colorsasaspoints
pointsinina athree-dimensional
three-dimensional
vectorvectorspace,
space,called
calledcolor
colorspace
spaceororcolor
colormodel.
model.A Acolor
colorspace
spaceis isthus
thusa amathematicalmathematicalrepresentation
representationofofspectral
spectralcolors
colorsinina finite
a finitedimensional
dimensionalvector
vectorspace.
space.It Itallows
allowsanalyzes
analyzesandandmanipulates
manipulatescolor.
color.ByBydefining
definingdifferent
different
primary
primarycolors,
colors,that
thatis isbasis
basiselements
elementsofofthethevector
vectorspace,
space,different
differentcolor
color
modelsmodelscancanbebedevised.
devised.Moreover,Moreover,additional
additionalrepresentation
representationsystems
systemscan
canbebedeveloped
developedaccording
accordingtotophysical,
physical,physiologicalphysiologicalororpsychologicalpsychologicalproperties.
properties.
(Salvador,(Salvador,
2004)
2004)
2.52.5Extract
Extract
andand
Identification
Identification
Road
Road
Network
Network
InInthis
thisprocessprocessstart
startfromfromcreate
createreference
referenceAOI
AOIforforcomparing
comparingbetween
betweeneach
eachcolorcolordifferent
differentmodule.
module.And
Andthen,then,setup
setupcomparing
comparingspectral
spectralprofile
profileinin
eacheachobject.
object.Moreover,Moreover,create
createstatistics
statisticstotoanalysis
analysisandandsetup
setupthreshold.
threshold.InIn
finally,
finally,create
createERDASERDASmodelermodelermodule
moduletotoextract
extractroad
roadnetwork
networkand
andprocessprocessnoise
noise
reduction.
reduction.
The
The
flow
flow
ofof
work
work
after
after
selected
selected
color
color
model
model
arearesuitablesuitable
forforextract
extract
road
road
is is
extraction
extraction
andandidentification
identificationasas
below:below:-

Transformation
Transformationof ofhybridhybrid
color
color
space
space
forforroad
road
extraction
extraction
using
using
high
high
resolution
resolution
image
image
Transformationofhybrid
color
space
for
road
extraction
using
high
resolution
image

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3. RESULT AND DISCUSSION
3.1 Color spaces transformation experiment for road network extract
RGBNIR
R, G, B, NIR are the spectral available of Quickbird image.
Combination of grey value of each band presented in RGB color space canmake true color and false color image.

Figure 3.1 : RGBNIR images in separated bands

Figure 3.2 Normalize image in Band

Figure 3.3: Spectral chart of RGBNIR image

As figure 3.2, show output of normalized image and visualization in 3
band of NIR-Red-Green. The spectral chart, Vegetable is easy to extract out
from this image by using band 4 and 3 (NIR-Red) which is related to NDVI
equation.
3.1.2 HSI (Hue, Saturate and Intensity)
Regarding refer to previous chapter, this project want to find thesuitable color space for identify road type and extraction road network. In
this part, HSI is testing to enhance in different band as below:-

6
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Figure 3.4: Spectral chart of HSI
combination from blue green red
bands(Band 1-2-3 = Intensity-HueSaturated)

Figure 3.5: Spectral chart of HSI
combination from blue red NIR
bands(Band 1-2-3 = Intensity-HueSaturated)

Comparing HSI from RGB with NIRBR, the range of local road in
RGB->HSI is easier to classify than NIRBR->HSI. Both of them are mixed
up with high intensity building but it separated from another objects.
3.1.3 YCbCr
From YCbCr color model above , All of layer is mixed up and cannot
separated any object from imagery. So It mean this color model is notsuitable for extraction.
3.1.4 I1I2I3
Another color space which is using to extract in this project is I1I2I3 or
Intensity for each meaning following below:I1 presents the average of DN in three bands same as I axis in HIS
color space.
I2 presents the different of DN between longest and shortest
wavelength.
I3 present the different of DN emphasis to the shortest wavelength.
Comparing both of spectral chart of I1I2I3 from RGB and NIRBR, thefigure of
RGB-> I1I2I3 cannot classify and separated each object from image.
By the way, another module NIRBR-> I1I2I3 have some different fromprevious one, if we identify the trend of slope between I3-I2, So we canseparate group of object into 2 groups as:- 1.highway and water 2. Localroad, building and Vegetation. In case want to using this model, it cangenerate model to separated highway and local road by mask out water andvegetation area before using this model.
3.1.5 Intensity Emphasis
This model is modification equation from I1I2I3 for enhancing every
bands, average band and find different rang of (short-long wavelength) as
below meaning:Transformation ofTransformationof hybridhybrid color
color space
space forfor roadroad extraction
extraction using
usinghighhighresolution
resolutionimage
image

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I1 presents the average of DN in four bands.
I2 presents the difference of DN between longest and shortest
wavelength.
I3 present the difference of DN emphasis to the NIR.
I4 present the difference of DN emphasis to the red.
I5 present the difference of DN emphasis to the green.
I6 present the difference of DN emphasis to the blue.

Figure 3.6: Spectral chart Figure 3.7 : Spectral chart ofof YCbCr combination
I1I2I3 combination from blue
from red green blue bands green red bands(Band 1-2-3 = Y-Cb-Cr)

Figure 3.8: Spectral chartof I1I2I3 combination fromblue red NIR bands

3.2 Selection hybrid color space
As a result above from the spectral chart and satellite image, The
result of each color space which is related in this project in brief a result as
below:• HSI-RGB : Good• HSI-NIRBR : Fair
• YCbCr: Bad• Intensity emphasis : GoodIn finally, in this project decided to use HSI-RGB and intensity
emphasis color model for hybrid road network extraction.
3.3 Mark AOI and Set threshold from signature profile
Another step is to classify road network to mark AOI for viewing
spectral profile of highway and rural road network. This project createdabout the point of AOI by random sampling to get signature the objects indifferent features.

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Figure
3.11:
Mark
AOI
AOI
Figure3.11:3.11:
MarkMark
AOIforfor forFigureFigureFigure3.9:
3.9:Spectral
3.9:
SpectralSpectralchart
chartchart
ofof of Figure
Figure
3.10:
Mark
AOI
AOI
Figure3.10:3.10:
MarkMark
AOIforfor for Figure
highway
andand rural
ininintensity
in intensity
highway
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intensity
II11II22II33II414II525II636Icombination
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fromfromfrom
blue
blue blue highway
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ininHISin HIS highway
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HIS
4combinationemphasisemphasis
color
color
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(Left
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green
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red
redNIRNIR
red bands
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color
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(Left
(Left(Lefthandhandhandside)side)side)
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andSpectral
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3.4.1
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3.4.13.4.1
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Following
Following
this
this figure
show
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ininHuein channel,
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3.1:Show
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Hue
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3.4.2
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signaturesignaturesignature
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ininoutput
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Moreover,Moreover,Moreover,beforebeforebeforestack
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ititwill
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Transformation
Transformation
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using
usingusinghighhighresolution
resolution
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Transformation
of
for
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high
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Transformationof hybridhybridcolor
space
forextraction
road
extractionusing
highresolution
resolution
image

99 2499

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2011,
ChiangMai,
Thailand
October
2011,
Chiangmai,
Chiangmai,
ThailandThailandFigureFigure
3.13:
3.13:
Show
Show
OutputOutput
of of
Road
Road
extraction
extraction
ononhighway(Lefthighway(Left
hand
hand
side)
side)
and
and
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(Right(Right
hand
hand
side)
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byby
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FigureFigure4.16:
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3.63.6
Accuracy
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Assessment
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The
Thelastlastprocessprocessis isananaccuracy
accuracyassessment
assessmentto tomeasurement
measurement
performance
performance
of of
this
this
hybridhybrid
color
color
model
model
to to
extract
extract
andandclassifyclassify
road
road
network.
network.
It Itwaswasdonedonebybydigitizing
digitizingoriginal
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intovector
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calculating
total
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of of
each
each
road
road
type.
type.
After
After
getting
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network
fromfromsatellite
satellite
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and
and
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andandcalculated
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Highway
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Accuracy
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assessment:
assessment: Local
Local
road
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accuracy
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assessment
assessment: :ActualActualhighway
highwayroad
road
network
network
lengthlength Actual
Actual
rural
rural
road
road
network
network
lengthlength=== 1,746= 1,746
m.m.
4,378
4,378
m.m.
Highway
Highway
extraction
extraction
using
using
hybridhybrid
Rural
Rural
road
road
extraction
extraction
using
using
hybridhybrid
color
color
space
space
component
component= 1317= 1317m.m. color
color
space
space
component
component= 2846= 2846m.m.
Accuracy
Accuracy
assessment
assessment==
Accuracy
Accuracy
assessment
assessment==
1317*100/1746
1317*100/1746= 75.42= 75.42%%2846*100/4378
2846*100/4378= 65.00%= 65.00%

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Urban
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Asia
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4. CONCLUSION
This study propose the simply method to extracted road network, also thebenefit of this method is not only classify road network but it can beextracted road type information as highway and local road. By the way, theaccuracy extracted of road network in some of area not good enoughbecause there are high density traffic vehicle on the road that is effect into
the classification method. And local road classification type not so accurate
because it effect from the shade and shadow of satellite image, when it
transform into color space model, some parts of the object are mix up into
the same categories.
REFERENCES
A. Chang S. K. Kyu and B. R. Sang. (1997). A Road Extraction
Method from Topographical Map Images. IEEE Communications,
Computers and Signal Processing, Vol 2. pp.839-842,.
A.J. Spink, M.O.S. Buma and R.A.J. Tegelenbosch. (2000).
EthoVision color identification: A new method for color tracking using both
hue and saturation, 3rdInternational Conference on Methods and Techniques in Behavioral
Research, 15-18 August 2000, Nijmegen, The Netherlands
Cheng. (2001). Color image segmentation: advance and prospect,
Available at www.elsevier. com/locate/patcog. Access on: 17 July 2009.
C. L. Jia, K. F. Ji, Y. M. Jiang and G. Y. Kuang, (2005). Road
Extraction from High-Resolution SAR Imagery Using Hough Transform.
Proceedings of IEEE International Geoscience and Remote Sensing
Symposium, Vol 1. pp. 1-4, 2005.
David B.L. Bong, Koon Chun Lai, and Annie Joseph. (2009).
Automatic Road Network Recognition and Extraction for Urban
Planning ,International Journal of Applied Science, Engineering andTechnology 5:1 2009
Elena Salvador. (2004). Shadow segmentation and tracking in realworld
conditions,
Availableat:ieeexplore.ieee.org/iel5/9455/30012/01374677.pdf. Access on 8 July 2009.
J. Amini, M.R. Saradjian, J.A.R. Blais, C. Lucas, A. Azizi. (2002).
Automatic road-side extraction from large scale imagemaps, International
Journal of Applied Earth Observation and Geoinformation 4 (2002) 95–107
J.B. Mena *, J.A. Malpica. (2005). An automatic method for road
extraction in rural and semi-urban areas starting from high resolution
satellite imagery, Pattern Recognition Letters 26 (2005) 1201–1220
M. Mokhtarzade *, M.J. Valadan Zoej. (2007). Road detection fromhigh-resolution satellite images using artificial neural networks,
International Journal of Applied Earth Observation and Geoinformation 9(2007) 32–40
Taejung Kim. (2001). Semi-Automatic Road Extraction from IKONOSImages Using Template Matching, Asian conference on Remote
Sensing,2001 Singapore

Transformation ofTransformationof hybridhybrid color
color space
space forfor roadroad extraction
extraction using
usinghighhighresolution
resolutionimage
image

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252

New Technologies for Urban Safety of Mega Cities in Asia

Future plan for the world longest undersea
tunnel projects in Korea
Chang-Yong Kim1, Seong-Won Lee1, Ho-Geun Kim1
1
Korea Institute of Construction Technology,
Daehwa-dong 283, Goyangdae-ro, Ilsanseo-gu,
Goyang-si, Gyeonggi-do, 411-712, Korea
cykim@kict.re.kr
ABSTRACT
Korea has several big islands. The largest island in Korea is Jeju. In Jeju
island, almost 570,000 persons are accommodated, and Jeju island is about
73km wide and 41km long with a total area of 1,848 km2. To go to Jeju,
normally using airplane and the others are transported by ship. Jeju
international airport has a total of 16 direct airlines within 12 local and 6
international airlines. But, air flight services heavily depend upon weather
conditions, for example, 707 flights are canceled and 222 flights aredelayed every year in average. The provision of secure and safe newtransport mode might be needed. Already the construction of Honam highspeed rail line was started, so the extension of this Honam rail link to Jeju
by subsea tunnel was suggested and staged in feasibility study. In thisproject, the route from Mokpo to Jeju(167km) consist of three part, the firstis Mokpo-Haenam(66km) on Surface, and the second is HaenamBogildo(28km) by oversea bridge and finally Bogildo-Chujado-Jeju(73km)
by undersea tunnel
Service and technical of the system will take the same standard as Honam
High-speed Rail in order to prevent service disruption. The design speed of
the train will be almost 350km/h and the operating speed about 300km/h. If
this project will be launched, Seoul station to Jeju island will take 2 hours
and 26 minutes
The challenge is the great depth of undersea level (maximum 120m) andovercoming the various geological conditions. Also, artificial islands areneeded for the ventilation of the long and deep tunnels
In this paper, we will present the detailed plan of this project and thetechnical weakness and challenging factors are also discussed.
Keywords: Longest undersea tunnel, Artificial islands, Ventilation system
1. INTRODUCTION
Korea has several big islands; the largest island in Korea is Jeju. In Jeju
Island, almost 570,000 persons are residing and it is about 73km wide and
41km long; the total area of 1,848 km2. To go to Jeju, airplane and ship are2531

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usually used. Jeju international airport has the total of 16 direct airlines;
linked with 6 nations and 12 regions (Figure 1). But, air flight services
heavily depend upon weather conditions; for example, 707 flights arecanceled and 222 flights delayed every year in average. In case of thetransportation by ship, it takes 3 hours or more between Wando and Jeju and
10 hours or more between Incheon City and Jeju. In 2007, 8,288,967
persons, ten times more than ones who traveled the island by ships, enteredJeju by airplane, so the travelers have been under the increased fare burden.
Accordingly, the Honam-Jeju undersea high-speed rail can be an alternative
through linking the high-speed rails under the situation to need a newtransportation mode for overcoming the limitation of existing transportation
modes and it's possible to link and develop the services and green industry
promoted by both economic zones through linking the transportation
between Honam and Jeju.

Figure 1: Jeju’s flight routes

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2. ROUTE
The Honam-Jeju route refers to a 176km line to link from Mokpo to Jeju,
which is connected to Seoul through KTX and expressways. The HonamJeju route is divided into 3 parts: a ground section of about 66km from
Mokpo to Haenam; a bridge (marine transportation) of about 28km from
Haenam to Bogildo; and a undersea tunnel section of about 73km from
Bogildo to Jeju via Chujado (Figure 2).

Figure 2: Honam-Jeju route
3. TECHNICAL REVIEWThe western coast and southern coast show a very complicated coastline
unlike the eastern coast; especially, the southwestern coast, a archipelagoregion, consists of many islands and peninsulas and shows a worldrenowned ria shoreline. The average water depth at the tunnel section isabout 66.7m and the maximum depth around 130m (Figure 3).
Future plan
plan forFuturefor thethe worldworld longest
longest undersea
undersea tunnel
tunnel projects
projectsin
inKorea
Korea

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Given the ventilation and environment problems, including the route
length and waste gas treatment, it’s recommended that the route would be
operated centering on the passenger transportation through high-speed rails
and the freight traffic through high-speed freight rails. As for the undersea
tunnel structure, the two methods can be reviewed: the excavation of mainline after excavating a service tunnel beforehand; and the direct excavation(Table 1).

Figure 3: Water depth of the applied section
Table 1: Undersea tunnel structure

Lines paralleled + service tunnel

A plan to operate the high-speed rails throughexcavating the paralleled tunnels after taking thenecessary actions beforehand through excavating aservice tunnel and grasping the undersea groundsituation. It’s judged that the service tunnel can beused not only for a vehicle to handle disaster, butalso for a side track in time of operating thefreight rails.

Line-paralleled tunnel

A plan to use the excavated medium-sizedparalleled tunnels as the rails for high-speed rails
and freight rails. It can be complementarily used
for disaster prevention and maintenance throughconstructing a connecting gallery by each section.

4. FUTURE PLAN

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4. FUTURE PLAN

The Honam-Jeju project is planned to be operated with a design speed of
350km/h and an operation speed of 300km/h like the existing high-speed
4rails. Accordingly, it is anticipated to take lessNew
for Urban
thanTechnologies
about two hours
and Safety
30 of Mega C
minutes from Seoul to Jeju, about one hour and 40 minutes from Osong, theHonam intersection, about 40 minutes from Mokpo and two hours and 30
minutes form Daegu to Jeju (Figure 4).
The project is expected to take about 11 years: One year for a feasibility
study and a master plan; one for a basic plan; one for a detailed design; andeight years for the construction of bridges and tunnels.
The construction is anticipated to cost about 14 trillion and 600 billion won:
about 2 trillion and 800 billion won for ground section; 3 trillion won for theconstruction of sea bridges; and 8 trillion and 800 billion won for undersea
tunnel (Table 2).
Table 2: Project overview

Construction
periodContents

costs

Contents

1st year

Feasibility study and masterplan

2 trillion and800 billion
won

Ground section

2nd year

Basic design2조 8천억

지상부분

2차년도

기본 설계

3 trillion won

Bridges on sea

3rd year

Detailed design

3조

해상 교량

3차년도

실시 설계

8 trillion and800 billion
won

Undersea tunnel

4th-11th year

Bridge and tunnel
construction8조 8천억

해저터널

5. EFFECTS
The Honam-Jeju high-speed rail makes the national development and theacquisition of new growth engine possible through lining with the existinghigh-speed rails and makes the linkage of service and green industry
promoted both economic zones possible through linking the ground traffic
between Honam and Jeju.
In addition, the route can become an alternative transportation modeto overcome the limitation (high cost, severer climate, security etc.) of theexisting transportation modes (ship and airplane).
Furthermore, the foreign undersea tunnel projects are under theplanning stage for the super long tunnel linking continents and islands, so
the establishment of global transportation-network can lead to a huge
geographical, economic change at the relevant region and give an
opportunity to expand the business boundary for Korea’s construction
companies.

Future plan for the world longest undersea tunnel projects in Korea
Future plan for the world longest undersea tunnel projects in Korea

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Figure 4. Living zone around Honam-Jeju high-speed rail
5. CONCLUSIONS
Undersea tunnels around the world are very active in construction orplanned. In particular, over 80km super longest undersea tunnel there are notmany examples around the world. Korea has very large tunnel construction
experiences in urban area, mountain area and under river. Recently,
immersed tunnel in Busan area are constructed. Many tunnels on theoccasion of immersed tunnel construction will be built and planned in Korea.
Especially, long and deep undersea tunnel projects as shown above are stillplanned.

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In order to overcome technical weakness, many research projects also
will be launched for the world subsea tunnel market. South Korea's
government also recognizes the need for technical assistance in theseundersea tunnel projects, and related areas will be continued support.
Near the future, the plan of the Korea-China and Korea-Japan undersea
tunnel construction will be realized.
REFERENCES
Ministry of Construction and Maritime, 2011, The Feasibility Studyon the Connection between Honam and Jeju with High Speed Rail Link,
Reports on MOCT .
C. Y. Kim, 2010, A Study on Present Status of Deep Underground
Tunnel and Future Technologies, the 21st KICT-JICE Joint Workshop.
C.Y. Kim, S.B. Yim, et al., 2011, Urban Deep Underground
Transportation Infrastructure Project in Korea and Technical Requirements,
Proceedings of the ITA-WTC 2011 in Helsinki , Finland, 295 pp

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longest undersea
undersea tunnel
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260

New Technologies for Urban Safety of Mega Cities in Asia

Assessment of community fire hazard
vulnerability: A case study of ward 65
in Dhaka city
Sharmin ARA
Research Planner, BNUS, Dhaka, Bangladesh
sharmin.ara14@gmail.com
Mehedi Ahmed ANSARY
Professor, Department of Civil Engineering, BUET, Dhaka, Bangladesh
ansary@ce.buet.ac.bd
ABSTRACT
Fires cause the greatest loss of life and property in urban areas. Urban fires
have devastating impact on communities. Unplanned urbanization has
intensified the problem further. The number of fire incidents in Dhaka was
1,686 in 2009, 1902 in 2010, and 605 up to March 2011 (Fire Service andCivil Defense, 2011). To mitigate such disasters at community level,
community participation is important. To strengthen the resiliency of acommunity to natural and man-made hazards, before they become a disaster,a comprehensive risk and vulnerability assessment is must. Community
Vulnerability Assessment Tool (CVAT) is a useful method to assessvulnerability of a community to any hazard. In this study, a traditional
community of ward 65 of Dhaka has been selected. CVAT method will beapplied here in three steps. At first, a hazard map has been created by land
use in the study area. Then different vulnerability analyses have been
conducted namely social vulnerability, critical facilities vulnerability, andeconomic vulnerability. To accomplish these vulnerability analyses different
field surveys are required getting complete scenario of the community. Eachof the vulnerability analysis includes certain specific steps which ultimately
lead to a vulnerability map. After the preparation of hazard map, it isrequired to overlay the maps with each other. By using some parameters
and attributes, community vulnerability has been evaluated with respect tofire hazard. Finally the overall vulnerability of the community has beenassessed. This study might provide a baseline to prioritize mitigation
measures and to evaluate the effectiveness of those measures over time inthe community.
Keywords: Fire hazard, community vulnerability, hazard map, vulnerability
map, mitigation.

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1. INTRODUCTION
Fire hazard is something that increases the risk of fire. It causes immense
loss of life and properties. In the urban area with haphazard development
fire event occurs frequently and it has devastating impact on communities aswell as the whole country. Social and economic effects are mostconspicuous than the other impacts to the country. In Dhaka city unplanned
urbanization and rapid industrialization are the major causes of large
number of fire related accidents and increasing the vulnerability of thecountry’s major population and its economy. Not only in Dhaka but also othermajor cities in Bangladesh which are unplanned and densely populated,suffering the rage of fire for many years. Congested building orientation,
mixed type of use in a same building, flammable building materials, electricalsystem and lack of awareness regarding fire event are increasing the risk offire in the residential area of Dhaka city especially in the older portion of
Dhaka. Statistics shows that most of the residential fire events occurred in2009 than the other statistical year (see figure 1). But the economic loss offire is in decreasing trend. From table-1 it is evident that the economic loss
due to fire incidents is very high. As Bangladesh is a developing country
cannot afford the huge amount of loss due to fire accidents every year.
Especially in most of the cases the victims are the low income group of thesociety.

Figure1: No of residential fire event in Dhaka city
(Source: Bangladesh Fire Service and Civil Defense)

Table1: Extent of losses due to fire hazards in recent years(1 Million USD = Taka 7 crore)Year
Amount of loss due to residential fire (in Taka crores)
2010
107.42
2009
92.90
2008
56.45
2007
172.78
2006
238.7
2005
272.642004
213.782003
110.592002
112.21(Source: Bangladesh Fire Service and Civil Defense)

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Dhaka metropolitan area is divided into ninety wards foradministrative purpose. Among these wards of Dhaka city, Ward 65 is mostvulnerable to fire hazard than other because of its traditional land use andpopulation density. Fire incidents are very common phenomenon in thisportion. That’s why a portion of this ward is selected as study area. Ward 65
of Old Dhaka is one of the oldest areas of Dhaka city. This area is mainly
used as manufacturing area in Dhaka city. There is also other use exists here
like go down, commercial use, chemical shop, clamber storage andprocessing shops are also prominent. Land use of this area makes it uniquethan the other area of Dhaka city which can be responsible for severe fire
hazard. So that a fire hazard vulnerability of the community has done to
examine the existing severity of the area and prepare the residents to face thissort of manmade disaster.

Map1: Study Area (ward 65 of Dhaka city)
Source: Dhaka City Corporation

2. EXISTING STATUS AND TRENDS OF FIRE INCIDENTS IN
DHAKA CITY
The current trend of fire incidents in the mega city Dhaka shows increasing
in number. Fire incidents are categorized into different causes. This
categorization has done according to the building use, electrical system inthe building. The figure 2 and 3 describes the number of recent fire events in
Dhaka city with different reasons from 2005 to April 2011.
Residential fire events are increasing in every year tremendously andit causes loss of property and injures many people badly. Industrial fire isalso in increasing trend. In between 2007 to 2010 fire caused by electric
short circuit is higher in 2008 (40.26%) and for cooking appliance most ofAssessment ofAssessmentof community
community fire
fire hazard
hazard vulnerability:
vulnerability: aAcasecasestudy
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the fire incidents occurred in 2010 (24.5%) and chemical reaction causes
most fire accidents in 2009.

Figure 2: Trends in fire accidents in Bangladesh (2005 to April 2011)(Source: Bangladesh Fire Service and Civil Defense)

Figure 3: Causes of fire accidents in Dhaka city
(Source: Bangladesh Fire Service and Civil Defense)

3.

FIRE HAZARD VULNERABILITY ANALYSIS

To assess the community vulnerability in old Dhaka, Community
Vulnerability Assessment Tool (CVAT) is used to find out the existing
scenario of the area. This tool has step-by-step process and it includes 7
steps with methods and tools for analysis within the steps. These 7 steps are:• Hazard identification• Hazard analysis• Critical facilities analysis• Social analysis• Economic analysis

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Environmental analysis
Mitigation opportunities analysis

The tools and methodologies used in this analysis consist of GIS and spatial
mapping analysis. In this paper only critical facilities analysis, social
analysis and economic analysis has done to assess the vulnerability of thecommunity.
For analysis the study area is divided into three risk zones according
to their land use from expert opinion. In this different risk zone land use isdifferent than other (see map 2). The livelihoods of its inhabitants areprimarily based on plastic processing industries. Here plastic manufacturing,
recycling and processing factory exists with residential use is considered ashigh risk area. The name of this portion is Islambag. It displays a highbuilding density with multi-storey buildings and very few urban public
spaces left. In the moderate risk area clamber store and processing factoryand different go down (plastic go down, cattle food storage) are dominant.
In the low risk area residential use with commercial (retail shop, office,bank, and clamber storage) are found.

Map 2: Fire risk zone in the study area
3.1 Critical facilities analysis
Critical facilities analysis mainly focuses on determining thevulnerabilities of lifelines, health care facilities, and special community
facility like religious centre, club, cultural center and educational
institutions within the community. Main steps includes in this analysis are:••Prepare a critical facility inventory and categorize the results
Intersect critical facilities with different risk areas

Assessment ofAssessmentof community
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Conduct a vulnerability assessment on highest risk critical facilities

To do this at first all the critical facilities in ward 65 were identified
and a complete inventory of these facilities was prepared. Then criticalfacilities that are in and within close proximity to high risk areas wereidentified by overlying the critical facilities location over the map of firevulnerable areas. The most common critical facilities in an area are as
following:• Educational institutions• Religious centers (Mosque)• Government organizations/ NGO offices• Healthcare facilities• Bank/other office• Community facilities• Police stations• Water pump house/ electrical sub station
Map-3 shows that 26% critical facilities are located in the high risk
area and Islambag area is more vulnerable other part of the ward. The
critical facilities in this portion are educational institution and religious
center. Plastic industries are located in very close proximity to thesefacilities. On the other hand most of the critical facilities are located in the
Lalbagh area. Because land use is completely different in these two riskzones. In the low risk area main land use is residential and in some case
mixed (residential, retail shop, commercial) and the people in this area areless vulnerable to fire hazard.

Map 3: Critical facilities in the study area

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So it can be said that the critical facilities of the study area are not athigh risk from fire. It has a significant impact on the later stages of disastermanagement. If the service is interrupted during any fire disaster it may
cause another grievous situation to the locality. Because these facilities
always play an important role in post disaster management stage.
3.2 Social vulnerability analysis
In terms of preparedness, identification of the community’svulnerability gives a clear picture of risky and susceptible groups. By
identifying these vulnerable groups, a better disaster preparedness plan canbe undertaken and better public awareness studies can be developed in the
pre-disaster phase. Social vulnerability analysis is very essential for any
kind of vulnerability assessment. Because people lives in the society are
most vulnerable to any sort of natural and manmade disaster. So to know theexisting status of the society with respect to disaster, social vulnerability
assessment is mandatory. For social vulnerability analysis two steps has
been followed.
••

Social indicators were identified
Intersect special consideration areas with different risk areas

Social indicators include education level, population composition andnumber of total population in one holding. In the study area most of thepeople are not educated. Among them maximum people are working as
employer in a plastic processing and manufacturing factory, shoe making
factory etc. here proportion of male and female residents are almost same.
From field survey it has found that population density is very high here.
Because the working place and living place of the worker is in same area. In
the plastic recycling and processing factory mainly women are working.
With respect to these conditions of the area it can be said that the area isvulnerable to fire hazard.

Map 4: Population density in individual building of
the study area
Assessment ofAssessmentof community
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fire hazard
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3.3 Economic vulnerability analysis
To identify the economic vulnerability to fire hazard this analysis has
done. Because in this area various economic activities are going on the samebuilding and which leads to severe fire hazard in the area. To analyze thisvulnerability two steps are followed. They are:••Economic sectors and its inventories were selected from thestudy area by land use survey and located in the map
The economic activity maps were overlaid with the fire risk
consideration areas analyzed its vulnerability

Four types of economic activities are distinctly dominant here. Theseare plastic manufacturing and processing industry, different type of factory,
go down, clamber storage and processing shops, chemical shops (see figure4). Location of these economic activities was determined by land use survey.
Some economic activities makes the study are vulnerable to fire hazard.
Among them plastic manufacturing industry is totally based on chemicalmaterials which promote fire to spread within few seconds to the locality.
So it is important to know how many hazardous economic activities arelocated in the study area.

Figure 4: Land use in the Ward 65(Source: Field survey, 2011)

3.4 Structural Vulnerability Analysis
There are other factors in the area which makes it vulnerable to fire
hazard. These factors are width of staircase, road width of the area andaccessibility to the building, position of transformer and electricity pole. If
the roads are not accessible to fire service vehicle to douse/ put off the fire it
may cause a loss to the community. For the emergency evacuation process

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staircase width is also a vital issue to the resident of a building. That’s why
these factors get importance to the vulnerability assessment.
3.4.1 Staircase width
From field survey it has observed that in the study area most of thebuildings (289 out of 781 surveyed buildings) are one storied and most ofthem are not RCC or masonry building. They are constructed by tin. Thesebuildings are mainly used as clamber storage and processing activity andplastic manufacturing and processing. In this structure fire can propagate
very swiftly. 164 buildings are two storied and mainly used as residential
and plastic processing activity. The staircase width of these buildings varies
from 2-3 ft. but some recently constructed buildings the width may varyfrom 3-4ft.in the older portion of Dhaka city it is a tradition that the width ofstaircase is very low than the new part of Dhaka. So that from the fieldsurvey it has observed that most of the elevated buildings staircase widthvaries from 2-3.5 ft. In case of some newly constructed buildings the width
is 4 feet. Wider staircase is essential for any building during the evacuation
process for any disaster. For fire hazard it get special priority because fire
propagate very quickly in a building. So people need to protect themselvesfrom the rage of fire in a very short time. In this respect the study area isvulnerable to fire hazard.
3.4.2. Road width/ Accessibility to building
For emergency response during any disaster road width is an
important factor. If the road is not sufficiently wide to move fire service’s
vehicle it may cause another disaster to the people and it may extend theloss very much than the expected. In case of fire accidents in a building it
can spread very quickly and can engulf lots of properties and life. This kindof event is very common in Bangladesh especially in old Dhaka. In the
study area accessibility to each household is not found. The main roads arewide and accessible to the fire service vehicle but the local roads andconnecting roads to the buildings are not accessible to the vehicle (see map5). Road width varies from 5-2 feet. In most of the case from the main roadthe narrow connecting roads extends to the end of the block. These narrowroads are totally impossible for evacuation and recue process. In this respect
this community is also vulnerable to fire hazard. They are not aware about
widening the road.
3.4.3 Transformer and electricity pole
Position of transformer and electricity pole to a building is also
assessed in this study because these may cause serious fire hazard to the
locality. Recently in old Dhaka a fire incident occurred due to the blast oftransformer. The death toll is around 150 due to this blast/ burst. It is
examined with highly importance because the buildings in this area areconstructed very closely to each other. So that fire can spread out to anotherbuilding very ghastly. Among the surveyed buildings transformer is locatedin front of the building is 6%.

Assessment ofAssessmentof community
community fire
fire hazard
hazard vulnerability:
vulnerability: aAcasecasestudy
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2 feetMap 5: Road network in the study area
4. CONCLUSIONS
From the above study it is obvious that the community is vulnerable to fire
hazard. The land use pattern of ward 65 indicates the possibility of this kindof hazard. There are many plastic manufacturing and processing factory in
the area. Mainly chemical materials will induce fire. Since ward 65 is a
residential area, the loss due to fire will be catastrophic. To minimize theeconomic loss a coordinated planning is required and need to change thepresent land use pattern. A wider road network is also required to evacuate
the community people.
REFERENCES
http://www.spaenvis.nic.in/pdfs/monographs/fire-hazard.pdf; accessedon 24th August, 2011
http://etd.lib.metu.edu.tr/upload/1252196/index.pdf; accessed on 24th
August, 2011

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NewA study on the preferable urban structureof provincial small town
in the depopulation age
Shimpei IWAMOTO1, Takahiro TANAKA2, Daisaku NISHINA3
1
Graduate Student, Graduate School of Engineering,
Hiroshima University, Japan
m105912@hiroshima-u.ac.jp
2
Associate Professor, Hiroshima University, Japan
3
Professor, Hiroshima University, Japan
ABSTRACT
Recently, the population is decreasing in Japan. If urban area keeps
expanding to the suburbs, various problems will be caused. For example,
daily lives without cars become difficult, efficient development andmaintenance of urban structure will be also difficult, and energy
consumption will be higher. To solve them, compact urban structure isrequested corresponding to the population decrease especially in provincial
small town. However, it is not clear where dense urban area should belocated and how much population should be located there. Therefore, it isnecessary to examine the appropriate future urban structure from several
viewpoints. This is because the preferable urban structure from one
viewpoint may not be good from other viewpoints.
Consequently, this study aims at examining the preferable future urban
structure from several viewpoints, such as energy consumption, urban
infrastructure development and maintenance cost, resident’s livability. In
this paper, authors examine the future urban structure from the viewpoint ofurban infrastructure development and maintenance cost and energy
consumption. Actually, this research is performed in Fuchu city, Hiroshimathat is a provincial small town. Concretely, authors make 43 kinds of urban
structure scenarios in 2035 such as “Complete compact type”, “Partly
compact type” and “Not compact type”. Then, authors calculate the energy
consumption for each scenario. As a result, it can be said that compact
urban structure will lead to reducing energy consumption, and the effects
are different from each other widely depending on scenarios.
Keywords: urban structure, urban infrastructure cost, energy consumption,compact city
1. INTRODUCTION
After the World War II, Japanese city has expanded to the suburbs becauseof rapid economic growth, population increase, and motorization.

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Consequently, various urban problems, such as decline of downtown areas,urban sprawl, air pollution by car use, and increase of urban infrastructuredevelopment/ maintenance cost, have been caused. On the other, in Japan,
population begun to decrease is rapidly increasing in recent years. Therefore,
if urban area keeps expanding to suburbs, it is expected that urban area will
become lower dense. In this case, it is though that daily lives without cars
become difficult because keeping public transportation will not be easy.
And, efficiency of urban infrastructure development and maintenance also
decrease. From such background, compact urban structure is proposedcorresponding to the population decrease. The followings are expected bymaking the urban structure compact: Revitalizing downtown, cutting urban
infrastructure development and maintenance cost, decreasing environmentload, and making daily lives without cars possible. Therefore, some local
governments make the plan of compact city. However, such plan do notshows proper compactness quantitatively from the view of the issues above.
Therefore, this study aims at making some scenarios for the target cityquantitatively and evaluating the scenarios from the view of cutting urban
infrastructure development and maintenance cost, decreasing energy
consumption, and resident’s livability, quantitatively. And, authors pursue
better future urban structure. As a first step, this paper shows the results ofmaking future scenarios and evaluating the scenarios from the view of
cutting urban infrastructure development and maintenance cost and energy
consumption.
This study considers about compact urban structure of provincial
small town. Because, population is decreasing and aging rapidly, inprovincial small towns. In addition, the number of provincial small town ismany and the number of cities that have population of fifty thousand or lesscity is half or more in Japan. Therefore, this study focuses on provincial
small town. It is one of the reasons that lots of past studies are case study oflarge population city.
As existing related studies, relationship between population
distribution structures and energy consumption by car use were examined in
Utsunomiya [1], cost benefit of compact city was analyzed in Fukuoka[2],traffic action change of people by making compact city was examined in
Matsue[3].These existing studies consider urban structure from one
viewpoint such as energy consumption of car, maintenance cost, and traffic
action of people. But, it is necessary to examine comprehensively fromsome viewpoints in case of considering future urban structure. Because, thepreferable urban structure from one viewpoint may not be good from otherviewpoints. Therefore, urban structure should be appreciated from several
viewpoints and examined most well-balanced from each viewpoints.
Therefore, this study aims at examining the preferable future urban
structure from several viewpoints such as urban infrastructure development
and maintenance cost, environmental load, resident’s livability in Fuchu
City, Hiroshima. Fuchu City is a town where the population is 39,345 andthe area is 110.2km2.As mentioned above, this paper, urban structure

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scenarios in 2035 are evaluated from the viewpoint of urban structuredevelopment and maintenance cost and energy consumption.
2. METHODSThis study is performed according to the following procedures. This paper
describes from 1) to 3).
1) Making several scenarios (urban structure scenarios in 2035).
2) Evaluating scenarios from viewpoint of urban structuredevelopment and maintenance cost and environment load.
3) Evaluating scenarios from viewpoint of energy consumption.
4) Promoting questionnaire survey/workshop for evaluating scenariosand examining preferable future urban structure with local
residents.
3. SCENARIO MAKING
3.1 Definition of word
In this study, “Urban structure” is defined as distribution form ofurban land use. Urban land use is chiefly a land use with artificial facilities.
For example, urban land uses are residential site, industrial site, commercial
site, public facility site, and road site. “Compact district” is district where
urban land use is concentrated.
3.2 Kind of scenarios
Authors made 43 kinds of scenarios in all. Table 1 shows the kinds ofthe scenarios. The scenarios are roughly classified into the following threekinds.
Table 1: Kind of scenarios
Out ofcompact
district

In compact district
Model

Shinglcore
model

Layout typ
number of district
Fuch station
1 district

StationcenteredIn urbanplanningarea
4 district
In entirecity
6 district

In urbanComplete
planning
compact
area
scenario Multi- Elementary
6 district
schoolcore
model district
In entirecity
7 district
In urbanplanningOld
area
elementary 9 district
schoolIn entire
district
city
12 district

Population
Population Area
Population
density（person/ha）

150
100
50
150
100
50
150
100
50
150
100
50
150
100
50
150
100
50
150
100
50

（person）（ha）

25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9（person）

In compact district
Model

Population

Layout typdensitynumber of district（person/ha）

In urban0
planning
0
Juniorarea
Complete Multi0
high 3 district
compact core
0 scenario model school In entire
districtcity
0
4 district0
0
0
ShinglFuch stationcore
0
1 district
model
0
0
0
In urban
0 Partlyplanning
0 compactarea
scenario0
4 district
Multi0Stationcore
centered0
model
0
In entirecity
0
6 district00
Not compact scenario

150
100
50
150
100
50
90
80
70
60
50
90
80
70
60
50
90
80
70
60
50
-

Out ofcompact
district

Population Area
Population（person） （ha）
（person）

25,793 172.0
25,793 257.9
25,793 515.9
25,793 172.0
25,793 257.9
25,793 515.9
23,214 257.9
20,634 257.9
18,055 257.9
15,476 257.9
12,897 257.9
23,214 257.9
20,634 257.9
18,055 257.9
15,476 257.9
12,897 257.9
23,214 257.9
20,634 257.9
18,055 257.9
15,476 257.9
12,897 257.9-

A study
study onA
on thethe preferable
preferable urban
urban structure
structure ofof provincial
provincial small
small town
townininthe
thedepopulation
depopulationage
age

0
0
0
0
0
0
2,579
5,159
7,738
10,317
12,897
2,579
5,159
7,738
10,317
12,897
2,579
5,159
7,738
10,317
12,897
25,7932733

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,(1)Complete compact scenario
In this is scenario, urban area is compacted. And, population is
distributed in only Compact district.
(2)Partly compact scenario
In this scenario, urban area is compacted. And, population is
distributed also besides Compact district.
(3)Not compact scenario
In this scenario, urban area is not compacted. And, Compact district
don’t exist.
Besides, Complete compact scenario and Partly compact scenario areclassified into the following two kinds.
(a) Single core model
In this scenario, urban area is compacted to one district. Consequently,
there is a Compact district. Fuchu station that is pivot of transportation in
Fuchu City is centered on Compact district.
(b) Multi-core model
In this scenario, urban area is compacted to plural districts.
Consequently, there are plural Compact district. Stations, elementary
schools, junior high schools, and main intersections are centered on
Compact district. And, authors also two kinds of scenarios. One is that
Compact districts are located in only urban planning area, the other is that
Compact districts are located in the entire city.
In Complete compact scenarios, population density of Compact
district is set to 150 per hectare, 100 per hectare, and 50 per hectare. In
Partly compact scenarios, population density of Compact district is set to 90
per hectare, 80 per hectare, 70 per hectare, 60 per hectare and 50 per hectare.
Besides, in Partly compact scenario in which population density of Compact
district is 90 per hectare, 90% of population is located in Compact district
and 10% of population is located in outside. And, in Partly compact
scenario in which population density of Compact district is 80 per hectare,
80% of population is located in Compact district and 20% of population is
located in outside.
3.3 Method of making scenarioFirst, authors forecast the population of each district in 2035[7]. Next,
authors step the following procedures.
(1)In case of Complete compact scenario[1] Setting of population and center of Compact district
The population was set as shown in Table 2. The center was set inconsideration of location such as station, bus stop, shop, school, community
center and assembly halls based on hearing to local government officials.
[2] Setting of area that satisfy condition of Compact district
The criteria of Compact district were set as shown in Table 3. Because,
Compact district should not be located in the area that is urbanizationrestricted area, slope ground and high disaster risk area.
[3] Setting of Compact district boundaryCompact district boundary was set near distance from the center andsatisfies all conditions of Table 3. And, the boundary was set so that

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Asia
New

ICUS Report 56

population
population
density density
become become
150 per150
hectare,per hectare,
100 per100
hectareper hectare
and 50 andper 50 per
hectare. hectare.
(2)In case(2)Inof Partlycase ofcompact
Partly compact
scenarioscenario[1] Setting[1] ofSetting
populationof population
and boundaryand boundaryof Compact
of Compact
district district
CompactCompact
district boundary
district boundary
is Compact
is Compact
district boundary
district boundaryof Completeof Complete
compactcompact
scenarioscenario
with population
with population
density 100
densityper 100
hectare.
per hectare.
The population
The population
was calculated
was calculated
by multiplying
by multiplying
CompactCompact
district area
districtby population
area by population
density. density.
[2] Setting[2] ofSetting
outsideof Compact
outside Compact
district population
district population
The population
The population
was calculated
was calculated
by subtracting
by subtracting
CompactCompact
district district
population
populationfrom allfrom
population.
all population.
And, thisAnd,
population
this population
was apportioned
was apportioned
each each
district. district.
(3) In Case
(3) Inof CaseNot compactof Not compact
scenarioscenario
The population
The population
is forecast
is forecast
population
populationof each district.
of each district.
Table 2:Table
Setting
2:of
Setting
populationof populationTable 3:Table
Condition
3: Conditionof Compact
of Compact
district district
Kinds of scenarios
Kinds of scenarios
Setting population
Setting population

ConditionConditionof Compact
of Compact
district district

Single coreSingle
modelcore model all population
all population
Urban planing
Urban
areaplaning area
Out of urbanOut
planingof urbanareaplaning areaeachstationridershipeachstationridership
stationstationurbanization-designatedurbanization-designatedarea
area × all population
× all population
all stations ridership
all stations ridershipsurround surroundout of restricted
out industrialof restrictedzoneindustrial zone MultiMultielementaryelementary
core
core
slope angleslope
is 8 degree
angle isor8lessdegree or lessmodel old elementarymodel old elementaryeach districteachpopulation
district populationout of sedimentout ofdisastersediment
damagedisastersupposition
damage supposition
district
district
junior high junior highoutside river
outsideand lakes
river and lakes

school districtschool district

3.4. Examples
3.4. Examplesof madeofscenario
made scenario
ExamplesExamplesof scenariosof scenarios
are shown
areinshown
Figurein1Figure
and Figure
1 and2.Figure
Figure2.1Figure
shows1 shows
examplesexamplesof Completeof Complete
compactcompact
scenarios.
scenarios.
Figure 2Figure
shows2 examples
shows examples
ofofPartly compact
Partly compact
scenariosscenarios
and Notand
compact
Not compact
scenario.scenario.
In addition,
In addition,
CompactCompact
district isdistrict
surroundedis surroundedarea by broken
area byline.
broken line.
Complete compact Complete compact
Complete compact
Complete compact
Complete compact Complete compact
scenario
scenario
scenario
scenario
scenario
scenario
Multi-core model Multi-core modelMulti-core model Multi-core model
Single core model Single core model
Elementary schoolElementary
district
school district
Elementary schoolElementary
district
school district
150 person/ha
150 person/ha
Urban planning area
Urban planning area
Entire city
Entire city
50 person/ha
50 person/ha
100 person/ha
100 person/haCompact
districtCompactJapanrailways
StationStationdistrict0

Japan railways

1

2

0

4 1

2

6
km

4

6
km

Figure 1:
FigureExamples1: Examplesof Completeof Complete
compactcompact
scenarios
scenarios
Partly compactPartly compact
scenario
scenario

Partly compactPartly compact
scenario
scenario

Multi-core model Multi-core model
Station centered Station centered
Urban planning area
Urban planning area
90 person/ha
90 person/haMulti-core model Multi-core model
Station centered Station centered
Urban planning area
Urban planning area
50 person/ha
50 person/ha

Not compact
scenario

Not compact
scenario

80

80

Compact district / Urban
Compact
land district
use population/ Urban density
land use(person/ha)
population density (person/ha)
010

Station

0

20 10
Japan
railways
Station

30 20
Japan railways

40

30

50

40

60

50

0

70
1

60

2

0

70

4 1

2

90

6
km

4

90

6
km

Figure 2:
FigureExamples2: Examplesof Partlyofcompact
Partly compact
scenarios
scenarios/ Not compact/ Not compact
scenarioscenario

A study on
the preferable
urban structureof provincial
small town
in thedepopulationage
A study
study
on
urban
of
small
town
in
age
A
on thethe preferable
preferable
urban structure
structureof provincial
provincial
small
town
inthe
thedepopulation
depopulation
age

5

2755

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

4. EVALUATION FROM THE VIEWPOINT OF URBANSTRUCTURE DEVELOPMENT AND MAINTENANCE COST
4.1 Calculation of urban structure development and maintenance cost
The necessary costs for development and maintenance of road,waterworks, sewer, elementary school, junior high school, preschool andcommunity center are calculated for all scenarios. And, they are compared.
The following formulas (Table 4) were used for calculating the costs. These
formulas are made based on actual track record in the local government. In
addition, X is development cost, Y is maintenance cost, and unit is JPY. The
development cost is cost until 2035 and the maintenance cost is yearly cost.
Table 4: Formulas of urban infrastructure cost
Urban infrastructure
Road
Waterworks
Sewer
Elementary school, Junior high school,
Preschool, Community center

Formulas
YR = A* 684,362 (JPY/projects)
XW = 10,853,346 (JPY/ha) *B
YW = C+D+E+F
XS = 264,250,463 (JPY/year) * G
YS = 113,060 (JPY/ha) * H+I
XB = J*KYEJP = Σ (L+M)
2
YC = Σ (1,047,189 (JPY/ m ) *N)

(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)

A: number of maintenance services (projects)
F: water pipe maintenance cost (JPY) K: development cost per square meter (JPY/m2 )B: development area (ha)G: development period (year)
L: administrative cost for each facility (JPY)
C: filtration plant maintenance cost (JPY)
H: disposal area (ha)M: personnel cost for each facility (JPY)
D: distribution reservoir maintenance cost (JPY) I: renewal cost (JPY)
N: floor area for each community center (m2 )E: pump station maintenance cost (JPY)
J: development floor area (m2 )

4.2. Result of calculation
Result of calculation is shown Figure 3 and Figure 4. Figure 3 isdevelopment cost. Figure 4 is maintenance cost. The major findings arefollowings.
1) Development and maintenance cost become lower in the following
order.
-scenario type [1] Complete compact scenario [2] Partly compact scenario[3] Not compact scenario-population density [1]150person/ha [2]100person/ha [3]50person/ha-model of scenarios [1] Single core model [2] Multi-core model-Compact district layout type [1] urban planning area [2] entire city
[1] station centered [2] junior high school district [3] elementary school
district [4]old elementary school district.
2) In case of Complete compact scenario, the effect of changing
100person/ha from 50person/ha is smaller than the effect of changing
150person/ha from 100person/ha.
3) Among the cases of Complete compact scenario with same population
densities, the costs are different from each other by layout of Compact
district. And the difference is larger in the case of 50person/ha scenario
than others.
4) Among the cases of Complete compact scenario with same numbers ofCompact districts, densities, the costs are different from each other by

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ICUS Report 56

layoutlayoutof Compact
of Compact
district.,
district.,
The Thescenarios
scenarios
in which
in whichsomesome
Compact
Compact
districts
districts
are nearare near
fromfrom
eacheachotherotherand andtheytheycan cansharesharethe facilities
the facilities
make
make
the cost
the cost
lower.
lower.
5) In5)case
In caseof Partlyof Partly
compact
compactscenario,
scenario,
cost costdifference
difference
by Compact
by Compact
district
district
layoutlayouttypetype
is small.
is small.
6) In6)development
In development
cost,cost,
the proportion
the proportionof costof costfor sewer
for sewer
is higher.
is higher.
7) In7)maintenanceIn maintenancecost,cost,
the proportion
the proportionof costof costfor building
for building
facilities
facilities
is higher.
is higher.
From
From
the above,
the above,
In orderIn orderto reduce
to reduce
urban
urban
infrastructure
infrastructuredevelopment
development
and andmaintenancemaintenancecost,cost,
it is itthoughtis thought
mostmost
effective
effective
to maketo makeclearclear
the inhabitedthe inhabitedareaarea
and andthe non-inhabited
the non-inhabitedarea.area.
120.0

120.0

100.0
80.0
60.0
40.0
20.0

development cost（billion yen）

140.0

development cost（billion yen）

140.0

100.0
80.0
community community
centercenter

60.0

preschool preschool
juniorhigh juniorhighschoolschool40.0

elementary elementary
schoolschool

20.0

sewer

Not compact scenario

population population
100 50150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
10050501509010080507090608050709060805070906080507090608050709060805070 60 50
density 150
density
urban
urban
urban
urban
urban
urban
urban
urban
entirecityentire
1
1 4 area
4 6area
6 city6 area6 7area
7 city9 area
9 12area
12city3 area3 4area
1 urban planning
4 urbanarea
4
6 cityentirecityentire
entirecityentire
entirecityentire4 city 1planning
planning
planning
planning
planning
planning
planning
planning
entireplanning
area6 cityentire

district123district
1 district 1 district 4 district 4 district 6 district 6 district
9 district 912
district
6 district 6 district
7 district 7 district
4 district 4 district
4 district 4 district
6 district 6 district
district 3 district
1 district 1 district

Compact Compact
district
district
Singlelayout type layout type

core
model

sewer

waterworks waterworks

0.0

elementaryelementary
school oldschooljuniorschoolhigh school
elementary
old elementary
school juniorschoolhighSingleStation centered
Station centered
Station centered
Station centered
Single coreSingle core
district district
district district
district district
core
model model Multi-compact
Multi-compact
model model
model
model
Multi-compact
Multi-compact
model

Complete
Completecompact
compactscenarioscenario

Partly compact
Partly compact
scenarioscenario

Not compact scenario

0.0

FigureFigure3: Calculation
3: Calculation
resultresultof developmentof development
cost cost

20.0

20.0

15.0

10.0

5.0

maintenance cost（billion yen）

25.0

maintenance cost（billion yen）

25.0

community community
centercenter

15.0

preschool preschool
juniorhigh juniorhighschoolschool10.0

elementry elementry
schoolschool
sewer

5.0

sewer

waterworks waterworks

-

road

Not compact scenario

cityentire
cityurban4planningurbanarea
1 district 1 district
district
4planning
district entire
6area
district
6 district
1 district 1 district
district 3 district
4 district 4 district
4 district 4 district
6 district 6 7
district
9 district 912
district
6 district 6 district
district 7 district
district123district

Compact Compact
Singledistrict
district
layout type layout
type
core

model

juniorschoolhigh school
Singleelementary
old elementary
school juniorschoolhighelementaryelementary
school oldschoolSingleStation centered
Station centered
district district
district district
district district
core
core
model
model modelMulti-compact
Multi-compact
model

Complete
Completecompact
compactscenarioscenario

Singlecore
model

Station centered
Station centered

Multi-compact
Multi-compact
model model

Partly compact
Partly compact
scenarioscenario

Not compact scenario-

population population
100 50150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
1005050150
150
100
10050501509010080507090608050709060805070906080507090608050709060805070 60 50
density 150
density
urban
urban
urban
urban
urban
urban
urban
urban
1
14
4 6 cityentire
6 city6
6 7 cityentire
7 city99 12cityentire
12city3 area3 4area
4 city 1
1urban planning
4 urbanarea
4
6 cityentireentirecityentire
planning
area6 cityentire
entireentireentireplanning
planning areaplanning
area planningarea
planning
area planningarea
planning
area planningroad

FigureFigure4: Calculation
4: Calculation
resultresultof maintenanceof maintenancecost cost
5. 5.
EVALUATIONEVALUATION
FROM
FROM
THETHE
VIEWPOINT
VIEWPOINT
OF OF
ENERGYENERGYCONSUMPTIONCONSUMPTIONThe Thecoolingcooling
and andheatingheatingenergyenergyconsumption
consumption
in houses
in houses
and andthe urban
the urban
infrastructure
infrastructuredevelopment
development
energyenergyconsumption
consumption
are calculated
are calculated
for all
for allscenarios.
scenarios.

A studyon theurban
structureof provincial
smallsmall
towntown
in theinage age
A study
study
on
the
urban
structureoftheA
onpreferable
the preferable
preferable
urban
structureof provincial
provincial
small
town
indepopulation
thedepopulation
depopulationage

7 2777

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

5.1.1. Calculation of cooling and heating energy consumption in houses
The following formulas (Table 5) were used for calculating the energy
consumption.
In addition, R and T were set by thermal load calculation program
LESCOM[8], as shown in Table 6.And, detached house is wooden structure.
Collective housing is reinforced concrete structure.
5.1.2. Result of calculation
Result of calculation is shown Figure 5. The major findings arefollowings.
1) The more the rate of household of collective housing is, the smaller
annual cooling and heating energy consumption in houses in entire
city is.
2) Annual cooling and heating energy consumption in houses in entire
city of every scenario is smaller than that of Not compact scenario.
But, the reduction effect has a big difference by scenarios.
3) In same compact district layout type scenario, the higher population
density in compact district is, the smaller annual cooling and heatingenergy consumption of house in entire city is. However, annual
cooling and heating energy consumption in houses in entire city is
not proportional to population density. Therefore, the higher
population density in compact district is, the smaller reduction effectof annual cooling and heating energy consumption of house in entire
city is.
4) In same population density of compact district scenario, annual
cooling and heating energy consumption in houses in entire city isdifferent by compact district layout type. In general, it becomes
small in order of the following.
[1] old elementary school district [2] elementary school district[3] junior high school district [4] single core [5] station centered.
But, the difference before and behind order is small.
5) The annual cooling and heating energy consumption in houses inentire city of Partly compact scenario is bigger than that of Complete
compact scenario. But, this difference is small.
From the above, in order to reduce annual cooling and heating energy
consumption in houses in entire city, it turns out that it is most effective to
make high population density urban structure. Only by raising the DID
population density of Fuchu city (34.1[person/ha]) to 50 [person/ha] , thedifference of annual cooling and heating energy consumption in entire citywith Not compact scenario is small, and it can seldom expect the big
reduction effect.

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Urban Safety
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ICUS Report 56

Table 5: Formulas of cooling and heating energy consumption in houses
ZH=O+P

O=Q*R

P=S*T

(9)

ZH: annual cooling and heating energy consumption in house in entire city (MJ)
O: annual cooling and heating energy consumption in detached house (MJ)
P: annual cooling and heating energy consumption in collective housing (MJ)
Q: the number of detached house (building)
R: basic unit of annual cooling and heating energy consumption in detached house (MJ/year*building)
S: the number of collective housing (building)
T: basic unit of annual cooling and heating energy consumption in collective housing (MJ/year*building)

In Compact district

Out of Compact
district

Q+aS=bcQ+dS=e

(10)

Q=f*g

S=f*h

(11)

a: the number of household per one collective housing (Table 6)b: the number of household of entire city in 2035 (9,384 households[4])c: site area of detached house (Table 6)
d: site area of collective housing (Table 6)
e: area of housing site of entire city in 2035 (ha)f: the number of household by district in 2035 (household)g: rate of detached house by district in 2005 (%)
h: rate of collective housing by district in 2005 (%)

Table 6: Setting of house and basic unit of annual energy consumption
Basic unit of annual Basic unit of annual
Number ofcooling and heating cooling and heating
Number ofhouseholdenergy consumption energy consumption
stories（households（story）
per one building
per one household）（MJ/year・building） （MJ/year・household）
2
1
51,22751,22720
120
3,831,743
31,9311060
1,936,073
32,268954
1,746,506
32,3438
48
1,556,939
32,4367421,367,372
32,5566
36
1,177,805
32,7175
30
988,238
32,941

Kind of house

Detached house
150 [person/ha]
100 [person/ha]
90 [person/ha]
80 [person/ha]
Collective
70 [person/ha]
housing60 [person/ha]
50 [person/ha]

Annual energy consumption（*1000GJ）

Out of Compact district
Not compact scenario

3

18609,104

33,839

500

400

300

200

100

完全集約シナリオ
Multi-compact
model

単心

多心scenario
Complete compact

model

単心Partly compact scenario
多心Not compact scenario

0

population 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 90 80 70 60 50 90 80 70 60 50 90 80 70 60 50
density
urban
urban
urban
urban
都市計画区
全域city 都市計画区
全域city 都市計画区
全域city 都市計画区
全域
都市計画区域内
全域cityurban
entireplanning entire
planning entire
cityplanning entire
planning entire
府中駅
1 district
域内
6ヵ所
域内
7ヵ所
域内
12ヵ所
域内
4ヵ所
4ヵ所area
6ヵ所
planning
area
area
area
1 district
area
1ヵ所
4ヵ所
6ヵ所
9ヵ所
3ヵ所
Compact
6
district
4 district
Single 4 district 6 district 6 district 7 district 9 district 12district 3 district 4 district
district
Singleschool old elementaryjunior high school
core
Stationcentered elementary
Stationcenteredlayout type 府中駅
駅周辺
小学校区
旧小学校区
中学校区
府中駅
駅周辺
core
district
schooldistrict
district
1ヵ所
1ヵ所
model
Multi-compact model

Figure 5: Calculation result of cooling and heating energy consumption inhouse

A studyAon
the preferable
urban structureof provincial
small town
in town
the depopulation
age
study
on the preferable
urban structureof provincial
small
in the depopulation
age

9 279

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

5.2.1. Calculation of urban infrastructure development energy
consumption
Urban infrastructure development energy consumption is the energy
consumption which will occur by 2035. The following formulas (table 7)
were used for calculating the energy consumption.
Table 7: Formulas of urban infrastructure of development energy consumption
FormulasUrban infrastructure
Waterworks

[6]

(12)

[6]

(13)

ZW =U*74.312(MJ/1000JPY)

Sewer
Elementary school,
Junior high school, Preschool
Community center

ZS=U*45.331(MJ/1000JPY)

2 [6]

(14)

ZEJP=V*15.759(MJ/m )

2 [6]

(15)
ZC=V*12.105(MJ/m )Z: urban infrastructure development energy consumption (MJ) U: development cost (1000JPY) V: development floor area (m2 )5.2.2. Result of calculation
Result of calculation is shown Figure 6. The same tendency as 1) ~ 6)
result of urban infrastructure development and maintenance cost can be readfrom this figure 6. From the above, In order to reduce urban infrastructuredevelopment energy consumption, it is thought most effective to make clear
the inhabited area and the non-inhabited area and to reduce the amount ofsewer development.
6. CONCLUSION
In this study, several urban structure scenarios were made in order toexamine proper future urban structure of provincial small town. And,quantitative urban infrastructure development and maintenance costs,
cooling and heating energy consumption of house and urban infrastructuredevelopment energy consumption were calculated for all scenarios. And,
these scenarios are compared and examined.
Development energy consumption (*1000GJ)

800
700
600
500
community
center400

preschool

300
200

juniorhighschool100

sewer

elementary
schoolCompact
district
layout type1 district

Singlecore
model

4 district

6 district

Station centered

6 district

7 district

9 district 12 district 3 district

4 district

elementary school old elementary school junior high school
district
district
district
Multi-compact model

Complete compact scenario

1 district

Single coremodel

4 district

6 district

Station centered
Multi-compact model

Partly compact scenario

Not compact scenario

0

population
density 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 150 100 50 90 80 70 60 50 90 80 70 60 50 90 80 70 60 50
urban
urban
urban
urban
1
4 area entire
6 city planning
6 area entire
7 city planning
9 area entire
12city planning
3 area entire
4 city1
4
6 cityplanning
entireurban planningarea

waterworks

Figure 6: Calculation result of development energy consumption

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In evaluation of urban infrastructure development and maintenance cost anddevelopment energy consumption, it was the conclusion that there was a big
difference between Complete compact scenario and Partly compact scenario,
and a big reduction effect to making clear the inhabited area and the noninhabited area. However, in the viewpoint of the cooling and heating energy
consumption in houses, there is almost no effect of making clear the
inhabited area and the non-inhabited area.
As a next step, it is necessary to evaluate the future urban structure fromseveral viewpoints such as traffic energy consumption and resident’s
livability.
REFERENCES
Hori,Y., Hosomi,A. and Kurokawa,T. 1999. Study on the Effects on
Energy Consumption by Vehicle Trips in a Compact City. Papers on theCity Planning Institute of Japan, No.34, pp.241-246, Japan.
Takahashi, M and Deguchi, A. 2007. Method for Cost-Benefit
Evaluation System of Impact by Forming Compact City. Papers on the City
Planning Institute of Japan, No.42-3, pp.487-492, Japan.
Yamane, K., Zhang, J. and Fujiwara, A. 2007. Influences of city
compactness on travel behavior patterns in a local city. Papers on the City
Planning Institute of Japan, No.42-3, pp.595-600, Japan.
National Institute of Population and Social Security Research, 2008.
Future estimated population by municipality of Japan, National Institute ofPopulation and Social Security Research, Japan.
Takeda,H., Inanuma,T., Yoshizawa,N., Isozaki,K., 2005. Standard
meteorological data and a thermal-load-calculation program LESCOM,
Inoue Shoin, Japan.
Architectural Institute of Japan, 2006. The LCA indicator of abuilding- The evaluation tool for warming, resource consumption, andprovision for waste, Architectural Institute of Japan, Japan.

A study
study onA
on thethe preferable
preferable urban
urban structure
structure ofof provincial
provincial small
small town
townininthe
thedepopulation
depopulationage
age

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Microscopic risk analysisof rear-end collisions
on Tokyo Metropolitan Expressway
1

Shinji TANAKA1 and Hisashi MIURA2Assistant professor, IIS, The University of Tokyo, Japan
stanaka@iis.u-tokyo.ac.jp
2
Graduate student, IIS, The University of Tokyo, Japan

ABSTRACTThis paper analyzed the potential risk of traffic accidents on Metropolitan
Expressway in Tokyo in a detailed way.
Tokyo Metropolitan Expressway (MEX) is the busiest urban motorway inJapan. It carries approx. one million vehicles every day and it also holds
approx. 11,000 traffic accidents in a year. Rear-end collision is the mosttypical type of traffic accidents in MEX, which occupies about half of thecauses of the total traffic accidents. Therefore it is very important to analyze
accident risk in a microscopic way in order to make effective
countermeasures for rear-end collisions.
This study analyzed traffic flows immediately before an accident in detailusing pulse data from traffic detectors, and identified conditions which maylead to an accident. This condition is verified using pulse data from different
time period, and a significant correlation between the number of accidents
and this condition was found. Then a method to forecast this situation fromobserved data in advance was proposed. Applying this method to an actual
dataset, it was confirmed that this method can forecast the situation ofserious speed drop which can cause an accident with relatively highaccuracy.
Keywords: traffic accidents, rear-end collision, risk analysis
1. INTRODUCTION
Traffic accident is one of the major risks in mega cities all over the world.
The number of fatalities by traffic accidents in Japan is decreasing recently,
but still a lot of accidents occur every year. Tokyo Metropolitan Expressway(MEX) is the busiest urban motorway in Japan, which carries approx. one
million vehicles every day. It also holds approx. 11,000 traffic accidents in a
year, and about half of them are rear-end collisions. Moreover, it causes
approx. 12 % of traffic congestion. Therefore, effective countermeasures areneeded not only to reduce traffic accidents but also to realize smooth traffic2831

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flow. For this purpose it is important to analyze influential factors on traffic
accidents in detail.
There are some existing researches which tried to analyze rear-end
accidents in MEX in a macroscopic way. They used traffic flow data such as
1 minute or 5 minutes aggregated data, but they did not analyze it in an
individual vehicle’s movement.
This study aims at identifying the microscopic traffic states of highrisk of accidents by analyzing raw data (pulse data) from traffic detectors ata sag section which holds a lot of rear-end collisions. And, an anticipation
method of such high risk traffic states is also considered.
2. OUTLINE OF THE STUDY SECTION AND THE
METHODOLOGY
2.1 Study section
A sag section which holds the highest accident rate of rear-end
collisions in MEX is selected for the study section. Figure 1 shows thelongitudinal sectional view of the section with the grade of the slope. Thissection has two lanes carriageway and lane change is prohibited at thedownstream section from the 0.39kp.
Location 1
downstream

Location 2
upstream‐5.00%

2.03%
0.4kp

0.5kp

0.6kp

0.7kp

Figure 1: Longitudinal sectional view of the study section
2.2 Situation in the study section
The number of rear-end accidents in this section is extracted. As a
new by-pass route opened during the period of this analysis, the results areshown in the separate figures. Figure 2 shows the number of the accidents
by location during 3 months before the opening and Figure 3 shows theoccurrence time of rear-end collisions out of them. Figure 4 and 5 shows theones after the opening of the by-pass route.

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16
14

左車線
left
lane
right
lane
右車線

numberof accidents
事故発生件数

12

18
6

10
8

traffic
flow
進行方向

6
4
2

3.0

2.8

2.6

2.4

others
追突以外

2.2

2.0

1.8

1.6

rear‐end
追突

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

0
kp

5
4
3
2
1

22:00

20:00

18:00

16:00

14:00

12:00

10:00

8:00

6:00

4:00

2:00

0

0:00

numberof rear‐end collisions
追突事故発生件数(0.5～0.7kp)

Figure 2: Number of accidents by location (Jan-Mar, 2010)

time
時刻

Figure 3: Number of rear-end collisions by time of day (Jan-Mar, 2010)16
14

numberof accidents
事故発生件数

2

左車線
left
lane
right
lane
右車線

12

2

10
8

traffic
flow
進行方向

6
4
2

3.0

2.8

2.6

2.4

others
追突以外

2.2

2.0

1.8

1.6

rear‐end
追突

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

0
kp

Figure 4: Number of accidents by location (Apr-Jun, 2010)

4
3
2
1

22:00

20:00

18:00

16:00

14:00

12:00

10:00

8:00

6:00

4:00

2:00

0

0:00

追突事故発生件数
numberof rear‐end collisions(0.5～0.7kp)

5

time
時刻

Figure 5: Number of rear-end collisions by time of day (Apr-Jun, 2010)
Figure 2 indicates many of the accidents occur in the down slope
section (0.5-0.7kp) which is just upstream of the sag, and most of them arerear-end collisions. They occur much more on the left lane than the rightlane, and most of them occur in the daytime (Figure 3). However after
Microscopic risk
Microscopic
risk analysis
analysis ofof rear-end
rear-end collisions
collisions on
on TokyoTokyo Metropolitan
Metropolitan Expressway
Expressway

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opening of the by-pass route, the number of accidents in the same section
decreased drastically, which means traffic situation change by new routeinfluenced on the accident risk.
2.2 Analyzed data
In order to analyze the traffic flow around the sag section, pulse datafrom traffic detectors at two locations shown in Figure 1 was used.
Location 1: 0.41kp (downstream)
Location 2: 0.56kp (upstream)
Term: Feb 1 – 15, Mar 1 – Apr 30, 2010
We can tell the passing time, the speed and the length of the individualvehicles by analyzing the pulse data. Here, we assume all vehicles run in thesame speed without lane change between two detector heads.
3. ANALYSIS ON TRAFFIC FLOW BEFORE ACCIDENTS
3.1 Extraction of target accidents
11 rear-end collision accidents were extracted from the accident
record for detailed accident analysis. They were 5 cases on the left lane and3 cases on the right lane before the opening of the by-pass route, and 1 caseon the left lane and 2 cases on the right lane after the opening.
3.2 Analysis on traffic flow just before accidents
Analysis results of 5 cases are shown in Figure 6. It shows thetransition of each passing vehicle’s speed at the location 1 and 2 during 5
minutes just before the accident. The right end of the x-axis shows theaccident occurrence time. Here, the accident occurrence time was estimatedfrom the disturbance of the pulse data.

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accident左車線
on Feb14 (left lane)
地点2(上流)
2月14日
追突事故

80

地点1(下流)location 2(upstream)

速度 (km/h)
speed[km/h]

70
60
50
40
30

location 1(downstream)

20
10
0
12:43

12:44

12:45

12:47

12:48

3月2日 左車線
追突事故
accidenton Mar2 (left lane)
地点2(上流)8070

地点1(下流)location 2(upstream)60

速度(km/h)
speed[km/h]

12:46

time
時刻

50
40
30
20

location 1(downstream)

10
0
6:44

80

6:45

6:46

時刻
time

6:47

6:48

6:49

3月7日 左車線
追突事故
accidenton Mar7 (left lane)
地点2(上流)地点1(下流)location 2(upstream)

70

speed
速度[km/h](km/h)

60
50
40
30
20
10
0
12:42

80

location 1(downstream)
12:43

12:44

12:45

12:46

時刻
time

12:47

3月8日 左車線
追突事故
accidenton Mar8 (left lane)
地点2(上流)地点1(下流)70speed
速度[km/h](km/h)

60
50
40
30
20
0
16:32

80

location 1(downstream)

location 2(upstream)

10
16:33

16:34

16:35
time
時刻

16:36

accidenton Apr追突事故
29 (left lane)
4月29日 左車線
地点2(上流)16:37
地点1(下流)location2(upstream)

速度 (km/h)
speed[km/h]

70
60
50
40

location 1(downstream)

30
20
10
0
13:53

13:54

13:55

time
時刻

13:56

13:57

Figure 6: Speed transition before a rear-end collision accident
The common feature of these graphs is a sharp speed drop at thelocation 1 before 1 minutes of the accident. The speed at the location 1 getsless than 20 km/h temporarily while that at the location 2 is relatively high,Microscopic risk
Microscopic
risk analysis
analysis ofof rear-end
rear-end collisions
collisions on
on TokyoTokyo Metropolitan
Metropolitan Expressway
Expressway

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Chiangmai,that is 30 – 60 km/h. This fact implies that the rear-end collision might becaused by a vehicle which could not react to a decelerating shockwave by
the speed drop propagated upward from the location 1.
The cause of the speed drop at the location 1 cannot be identified fromthe range of the analyzed data. However, looking at the fact that most of theaccidents occurred at the downhill section, the propagated shockwave fromthe uphill section to the downhill section may have increased the risk ofrear-end collision accidents.
3.3 Conditions of high-risk traffic flow state
From the analysis mentioned in the previous section, we extracted theconditions of the high-risk traffic flow state as follows.
I) Sharp speed drop less than 20 km/h at the downstream uphillsection and generation of decelerating shockwaveII) Propagation of the shockwave toward the upstream downhill
section of 30 km/h or higher speed
These conditions are commonly seen in 7 cases out of 11 analyzed
accidents. They were verified in the next section.
4. VERIFICATION OFHIGH-RISK TRAFFIC FLOW CONDITION
For the verification the conditions proposed above, the correlation between
the number of accidents and the frequency of assumed high-risk traffic flow
state by the proposed conditions were analyzed. The process of the analysis
is shown as follows.
i) extract detector pulse data of 1 week without accidentsii) count the cases when the speed at the location 1 dropped to below
20 km/hiii) extract the cases when the speed at the location 2 dropped fromabove 30 km/h to below 20 km/h within 60 seconds from the speed drop at
the location 1iv) count the number of cases in iii) and compare it with the number ofaccidents
The following dataset is used for this verification.
Term: Feb 3 – 9, Apr 10 – 16, 2010
Time: daytime: 7am – 5pm, nighttime: 8pm – 6am
Lane: both left and right lanes
Table 1 shows the result of this analysis by lane, by time of day andby time before/after the opening of the by-pass route. The number ofaccidents in the right column shows the number of rear-end collision
accidents during 3 months in the corresponding categories. Table 2 shows

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ICUS Report 56

the correlation coefficient of these 2 variables X and Y. The value shows asignificant correlation between them, therefore we consider the conditions
proposed in the previous section as valid to identify the high-risk traffic
flow state.
Table 1: Comparison of traffic flow states and accidents

beforeopening

after
opening

left
right
daytimenighttime
left
right
daytimenighttime

Number of traffic flow statesby proposed conditions (X)
154
85
235
4
15
81
96
0

Number ofaccidents (Y)
16
2
18
0
2
2
4
0

Table 2: Correlation between traffic flow states and accidents
correlation coefficientnumber of observationlevel of significance (1%)

0.914
8
0.834

Figure 7 shows the flow-speed relationship diagram by 1 minutetraffic detector data using the proposed high-risk traffic flow condition. The
high-risk traffic flow states occur more around 25 – 30 veh/min traffic flow
region on the left lane, while there are fewer cases of that on the right lane.
That means the occurrence of high-risk traffic flow state highly depends on
the lanes because they are affected from the different routes in thedownstream, and sometimes congestion propagates from there.

Microscopic risk
Microscopic
risk analysis
analysis ofof rear-end
rear-end collisions
collisions on
on TokyoTokyo Metropolitan
Metropolitan Expressway
Expressway

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100
90
80
70
60
50
40
30
20
10
0

高リスク交通流なし
normalstate
高リスク交通流あり
high‐risk
state

speed
[km/h]
速度(km/h)lane 昼間
供用前 left
左車線

0

5

100
90
80
70
60
50
40
30
20
10
0

10

15

20

25

traffic
flow [veh/min]
1分間交通量(veh/min)

30

35

40

normalstate
高リスク交通流なし
high‐risk
state
高リスク交通流あり

速度(km/h)speed [km/h]

rightlane 昼間
供用前
右車線

0

5

10

15

20

25

traffic
flow [veh/min]
1分間交通量(veh/min)

30

35

40

Figure 7: 1 minute flow-speed diagram during high-risk traffic states(Feb 3-9, 2010, daytime)
5. ANTICIPATION OFHIGH-RISK TRAFFIC FLOW STATEThe next challenge is to anticipate the occurrence of the high-risk traffic
flow state in advance. However, it is difficult to tell a speed drop at thelocation 1 from the data of this time as mentioned before. Then this study
focuses on anticipating an occurrence of speed drop propagation to thelocation 2 after the speed drop at the location 1 has been observed.
The speed at the location 1 after the speed drop and the traffic density
at the location 2 were used as variables for the discriminant analysis. Here,
we used 10 seconds for the aggregation duration considering the
propagation time of the shockwave. The results of the discriminant analysis
using 1 week daytime data are shown in Figure 8 and Table 3, that show
about 80% of the occurrence of the shockwave propagation can be
anticipated using this method.

8
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New Technologies
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density at location 2 [veh/km]：地点2密度(veh/km)

ICUS Report 56

80 80

discriminantdiscriminant
判別式：
判別式：
X2X
= 12 .=471.X471 +X10
1 +.8310.83
functionfunction

70 70
60 60

伝播なし
伝播なし
without
without
with
with
伝播あり
伝播あり
propagation
propagation

50 50
40 40
30 30
20 20
10 10
0

0
0

0

5

5

10 10

15 15

20 20

25 25

30 30

speed
at location
at location
1 [km/h]
1 [km/h]
X 1 ：地点1速度(km/h)
Xspeed1 ：地点1速度(km/h)

35 35

FigureFigure8: Distribution
8: Distributionof speedof speedat location
at location
1 and
1 and
densitydensity
at location
at location
2 2
Table
Table
3: Hit3: Hitratio
ratio
by discriminantby discriminant
analysisanalysis
discriminantdiscriminant withwith
propagation
propagation
resultresultwithout
without
propagation
propagation
hit ratio
hit ratio

actualactualdatadata
withwith
propagation
propagation without
without
propagation
propagation
151 151
32 32
42 42
120 1200.780.78
0.790.79

6. SUMMARY
6. SUMMARY
ThisThis
study
study
analyzed
analyzed
the thepulse
pulse
datadata
fromfromtraffic
traffic
detectors
detectors
beforebeforean accident
an accident
in ainmicroscopic
a microscopic
waywayandandidentified
identified
the theconditions
conditionsof theof thehigh-risk
high-risk
traffic
traffic
flow
flow
state
state
of rear-endof rear-end
collisioncollisionaccidents.
accidents.
TheTheconditions
conditions
are aresummarizedsummarized
as asa sharpa sharp
speed
speed
drop
drop
at theat theuphilluphillof theof thesagsagsectionsectionandandits propagation
its propagation
to theto theupstream
upstream
downhill
downhill
section.
section.
They
They
were
were
verifiedverified
using
using
different
different
periodperioddatadata
without
without
accidents
accidents
andandan anticipationan anticipation
methodmethodof theof the
speed
speed
drop
drop
shockwave
shockwave
propagation
propagation
waswasalsoalso
proposed.
proposed.
WeWe
could
could
notnotanticipate
anticipate
the theoccurrence
occurrenceof theof thehigh-risk
high-risk
traffic
traffic
flow
flow
state
state
from
from
the thenormalnormalcondition
condition
duedueto theto thelimitation
limitationof theof thedata.
data.
However,
However,it itis still
is still
usefulusefulbecausebecauseif we
if wecancandetectdetecta sharpa sharp
speed
speed
drop
drop
at theat thedownstream
downstreamof theof thesagsagsectionsectionwe wecancanprovideprovidean alert
an alert
accordingaccordingto ourto our
proposed
proposedmethodmethodfor forupstream
upstream
drivers
drivers
so thatso thattheytheycancanpreparepreparefor foran expected
an expectedrisk.risk.
ThisThiskindkindof microscopicof microscopic
riskrisk
analysisanalysis
methods
methods
shouldshouldbe be
explored
exploredmore
moreandandshouldshouldbe beincorporated
incorporated
withwitheffective
effective
countermeasurescountermeasures
to reduce
to reduce
the thetotaltotal
riskrisk
of oftraffic
traffic
accidents
accidents
andandto enhance
to enhance
the theurban
urban
safety.
safety.

Microscopic
riskrisk
analysisof rear-end
collisions
on Tokyo
Metropolitan
Expressway
Microscopic
analysisofcollisionson
Metropolitan
Expressway
Microscopic
risk
analysisof rear-end
rear-end
collisions
on TokyoTokyo
Metropolitan
Expressway

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292

New Technologies for Urban Safety of Mega Cities in AsiaÜ»ª»´±°³»²¬ ±º Ù»±­°¿¬·¿´ Ü·­¿­¬»® Ó¿²¿¹»ó³»²¬ ×²º±®³¿¬·±² Í»®ª·½» øÙÜÓÍ÷ ¿­ ¿ Í±½·¿´
Í§­¬»³
Takaaki KATO1, Mitsuaki KOBAYASHI2, Katsuyuki Yoshida3
and Jin NAKAMURA4
1
Associate Professor, ICUS, IIS, The University of Tokyo, Japankato-t@iis.u-tokyo.ac.jp
2
Director, ICT Business Dept. JR East Consultants Company
3
Deputy Director, ICT Business Dept. JR East Consultants Company
4
Project Researcher, ICUS, IIS, The University of Tokyo, Japan
ABSTRACTThe information-collecting in disaster stricken region is essential to implement
contingency response and recovery smoothly. According to Basic Act on Disaster
Countermeasures in Japan, the disaster countermeasures headquarter establishedof a local government has responsibility to do, however, the limitation of ability of
the headquarter makes each organization concerned gather and analyze
information independently. A scheme to share such information with all theorganizations concerned such as lifeline companies and public agencies willcontribute to quick response for a disaster. This research proposes “Geospatial
Disaster Management Mash-up Service” as a social system and develops
supporting systems to the service. The service is based on two platforms: Google
earth as a GIS technology, and a collaborative organization with concerned
companies such as data vendors, GIS system vendor, and lifeline companies. The
social system, “Geospatial Disaster Management Mash-up Service” will haveparticipants from public and private sectors. This paper introduces the outline of
the system and the trial use in the East-Japan Earthquake Disaster.
Keywords: GIS, disaster prevention, disaster information, recovery support

1. INTRODUCTION
Scheme for handling large-scale disasters is defined in Basic Act on Disaster
Countermeasures in Japan. According to the act, local governments, publicagencies, and public service companies in the disaster-stricken region are
responsible for taking actions. Such bodies outside the region also devise effective
support schemes and take measures based on agreements or from a humanitarian
standpoint. The act stipulates that when a disaster happens, the disaster
headquarter will be set up in the local government and all related organizations in
the area should share all kinds of information needed to disaster response.
However, the actual situations in the past indicate that each organization gathered
information separately and took measures individually.

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Our goal of this study is to eliminate waste of time and energy in collecting
information and to support efficient use of information by mashing-up thosewhich each organization can gather or already has. This study would enablesmooth disclosure of information regarding disaster situations and progress inrecovery works.
According to Wikipedia, “mash-up” is “a Web page or application that uses andcombines data, presentation or functionality from two or more sources to create
new services. The term implies easy, fast integration, frequently using open APIs
and data sources to produce enriched results that were not necessarily the original
reason for producing the raw source data.” An example of mash-up is to integrate
CRM applications on the Web with open API services such as Google Map.
In this study, we redefine “mash-up” as “gathering various kinds of informationor services scattered on the Web or in-house systems of each company, andintegrating those information by putting them easily on one platform to achieve
better result than just piling them up.”
We focused on two platforms. One is an organizational platform to operate thisservice on a commercial basis and the other is a systematic platform to store
information. As an organizational platform, we plan to set-up “GDMS
Consociation (tentative name)”. As a systematic platform, we adopted Google
Earth, 3D GIS provided by Google Inc. In this paper, we call disastercountermeasures service that utilizes these two platforms as GDMS (Geospatial
Disaster prevention information Mash-up Service.)

2. OUTLINES OF GDMS
2.1.Basic Concept
Basic concepts of GDMS are 1) independence 2) self-sustaining expansion 3)
practicality and feasibility 4) private leading.
1) Independence: GDMS should be beneficial for participant companies’
primary business and every relevant participant should cooperate voluntarily.
2) Self-sustaining expansion: Anyone who joins in this scheme can mash-up
everything. This is based on the shared sense that what is helpful for someone isalso helpful for others. As we do not venture to seek a perfect system from thestarting point, we plan to put feasible functions into practice at the beginning. In
addition, we plan to create a basis where those involved can offer data voluntarily.
3) Practicality and feasibility: Our top priority is to make this service useful atbusiness. This will encourage companies to participate positively, which will leadto improving practicality and feasibility. We will secure feasibility by setting up a
structure where every participant can establish give-and-take relationship.
4) Private leading: Core members of GDMS Consociation will be companies thatprovide infrastructure, which will facilitate to meet demands of companies in thesame field.
The service will be provided for concerning major users of information,collectable information, and service operation. We supposes that major users of294

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this service at the first stage will be public service companies such as railway
companies, electric power companies, gas companies, telecommunications
companies. These companies are responsible for recovery of life-support services
in case of natural disaster. If their information is mashed-up, it will be practicalfor local governments, companies, volunteer organizations, and citizens.
As for collectable information, we plan to collect data required for disaster drills,
for post-disaster emergency recovery and for full-scale recovery. In addition, weplan to mash-up data possessed by local governments which is related to disasterprevention and preparedness. We also look forward to mash-up satellite images
and aerial photos which are commercially available, and other useful data andapplication provided by private companies.
We finally plan to establish GDMS Consociation to coordinate the participants:
public service companies, academic experts and contents providers. It will take an
initiative role in operational management.
2.2.

Constitution of GDMS

Those who will be involved in GDMS are public service companies, which areresponsible for recovery work, service providers (contents venders and softwaresellers), local governments, government agencies and government institutions (Fig.
1). Core members of GDMS among these organizations will be public service
companies.
Core members will provide disaster information which they used to collect andstore individually upon GDMS, the common platform. On the other hand, they
will be able to collect information through GDMS. This structure simply has theadvantage that those companies will be able to share data with other companies,
which will contribute to cost reduction in data gathering and its management. It
will streamline recovery efforts.
Service providers will be able to sell information or software to public service
companies. Government institutions can open information to citizens. We
anticipate that universities and research institutes will also provide information orsoftware. These information and software will be provided through GDMS
platform.
Users of mashed-up information on GDMS will be the core members of GDMS,
government institutions, and the public. GDMS will be opened for anyone who
would like to utilize the data upon its platform. The paid and free services would
be controlled separately on GDMS. We will collect fee when users require paid
services. However, we consider that it is essential for GDMS that free services arevaluable enough.
If this plan is put to practical use, the data could be distributed to everyone who
needs them. What is important for suppliers of data or services is that who pays
for their data or services, or whether is more convenient for them to supply theirservices through GDMS compared to their conventional methods. From users’
standpoint, the most important key to establish GDMS is that the data or services
on GDMS are worth the cost.
2.3. SIGNIFICANCE OF GDMS

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needs them. What is important for suppliers of data or services is that who pays
for their data or services, or whether is more convenient for them to supply theirservices
through
GDMS
compared to their conventional methods. From users’
October
2011, Chiang
Mai,
Thailandstandpoint, the most important key to establish GDMS is that the data or services
on GDMS are worth the cost.
October 2011, Chiang Mai, Thailand

2.3. SIGNIFICANCE OF GDMS
Public service companies will be able to obtain necessary information promptly
on GDMS. They will be able to streamline their recovery work; in other words,
Your
paperbetitle
they willable to focus on what is most important. Moreover, it would be rather
inexpensive to gather information through GDMS than to gather it on their own.
Advantage for contents and software providers will be that their data or services
will be more valuable by mashed-up, and that their data or services will spreadeven faster in society. Even if they provide their services at a lower price, it will
benefit them on their business activity as they could possibly acquire morecustomers.
Governmental agencies will be able to acquire more channels to release
information. It will be an efficient method to educate citizens about disasterprevention.
For citizens, GDMS will be helpful not only because it will increase their
method to collect information, but also it will help them to obtain all necessary
information at once. Universities and research institutes will be able to make useof GDMS to apply their research outcome to practical business.
To sum up, GDMS will be profitable to every organization or people concerned,
and it will be beneficial socially and commercially if we could manage it properly.

Fig. 1: Constitution of GDMS
2.4. QUALITY AND IMMEDIACY OF INFORMATION
When we discuss information gathering and sharing system, we must note thatgenerally there are problems about quality and immediacy of information.
However, it does not seem to fit in case of GDMS. Quality of information should
be guaranteed as each organization would mash-up information they use in theirordinary activities. In other words, useless information will be cleared out in eachorganization. As for the immediacy, it should not be a problem, as organizations
offering information are on the front line to cope with disaster. Market mechanism
will also ensure immediacy. Paid services cannot attract customers if they are
outdated, that is, it would be pointless if contents providers mash-up services
without immediacy.

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3. GEOSPATIAL DISASTER PREVENTION INFORMATION MASH-UP
SYSTEM (GDMS STSTEM)
3.1. System Configuration
GDMS system is consists of 4 components (Fig. 2).
1) Application for client computers to mash-up disaster information (GDMS
Application);
2) Server which delivers data uploaded by GDMS Application (GDMS Server);3) Server which compiles information (KML or KMZ files) from associatedservice providers or companies and delivers these files to GDMS Application(KML Server);4) Google Earth Enterprise Server which delivers satellite images as base maps.

Fig. 2: GDMS System configuration diagram
GDMS Application is an add-on function for Google Earth, which transfers dataand program commands interactively between external applications and Google
Earth. KML file collection and delivery server is the site where KML files are
uploaded or downloaded, and it collects updated KML files and adds them to the
database automatically. And then it include search engine for users to find out thedata needed.

4. UTILIZATION OF GDMS
4.1. INFORMATION CLASSIFICATION ACCORDING TO PHASESWe had workshop discussions to define information which would be necessary
in case of disaster. We adopted simulation approach. Participants included public
service companies and academic experts.
The information is categorized in three phases:
1) The first phase to grasp outline of the damage in the area (Phase 1);

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Mai, Thailand

2) The second phase to grasp the detail of the damage in the area (Phase 2);3) The third phase to grasp information to assist recovery work (Phase 3).
In addition, there should be another phase to prepare in advance for Phase 1, 2
and 3.
In the pre-disaster phase, we plan to prepare basic information such as satellite
images, statistics (population distribution, etc.), spatial information (condition ofurban areas and roads), and hazard information (active fault zone and groundcondition, etc.) (Fig. 3.)
In phase 1, the Meteorological Agency announces the seismic center andintensity of an earthquake. We will convert the information and mash-up them
onto GDMS. We will also show damages estimated by damage-model (Fig. 4.)
In phase 2, we will provide photos shot in the area or shot by aerial photographs,
and field survey results such as traffic conditions (Fig. 5.)
In phase 3, users will be able to collect and share necessary information to draw
up a maneuver for recovery work. Assumed information is newest field survey
results, conditions around the area, traffic report, and weather information (Fig.
6.)
We anticipate that other useful data will be accumulated on GDMS as it
develops in the future.

Fig. 3: Subsurface geological map and Active fault zone

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Fig. 4: Estimation of seismic shaking ( CRIERI, Japan)

Fig. 5: Aerial photo after an earthquake and satellite image before the earthquake

Fig. 6: Weather information in a disaster-stricken region (Weathernews Co.)

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October
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Mai, Thailand

4.3. COLLECTING BASIC DATA
We have listed up necessary data from interviews with local governments andpublic service companies. Our business targets are railway companies, gas
companies, electric power companies, water and sewerage departments, telecom
companies, and local governments. Information is categorized by the phases
mentioned above. We classified demands according to business categories andinformation categories.
Although we have collected necessary data, we acknowledge that we need toverify consistency between the data list and the requirements of users. We plan tointerview with users again, and to update the data list based on the result of theprevious interview. At the same time, we plan to estimate the costs required tomeet the demands and define minimum contents which we should prepare at thestartup of service operation.
In 2010 FY, we had a demonstration experiment in corporation with Shizuoka
Prefecture to clarify the gap between our supply and demands of local governmentor public service companies.
5. GDMS in the Post-Disaster Phase in East-Japan Earthquake
East-Japan earthquake occurred on March 11 2011. GDMS had not been
completed yet. We tried to support the contingency response and recovery works
for the related organization inside and outside the affected region. We haveprovided KML files on Web since two weeks later. In addition, we expanded theobject of support to reconstruction planning phase from the original.
The activities has continued, therefore evaluation of the outcome achieved by theactivity will need more time. However, at present, it can be said that it performeda certain role at some points related to the fact that this disaster was super largescale. Because of hugeness of the affected region, the whole image of the disaster
was incomprehensive during the initial phase and, the strategy was essential
because the needs for recovery exceeded to the supply. The accumulation of theinformation on GIS platform promoted the understanding and support to develop
strategy and to make decision.

Fig. 7 the area damaged by tsunami and population distribution (GDMS)

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Fig 8 estimation of seismic intensity (AIST, Japan )Fig. 9 the vehicle probe data (Honda Motor Co.)Fig 10 pre-disaster scenery in the tsunami afflicted city (Kato.T lab. ICUS, IIS)
6. CONCLUSION AND FUTURE WORK
There are many challenges and difficulties left. There are some technicaldifficulties to be solved such as improvement of user interface and searching
function. Moreover, we need to demonstrate whether this service makes goodbusiness sense. The important point is that we must demonstrate the efficiency
and usefulness of GDMS for the related organization through the real experiencein the disaster. It will be clarified in the feasibility survey.
Acknowledgment

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301

There are many challenges and difficulties left. There are some technicaldifficulties to be solved such as improvement of user interface and searching
function. Moreover, we need to demonstrate whether this service makes good
October
2011, Chiang
businesssense.Mai,
TheThailand
important point is that we must demonstrate the efficiency
and usefulness of GDMS for the related organization through the real experiencein the disaster. It will be clarified in the feasibility survey.
October 2011, Chiang Mai, Thailand

Acknowledgment
This project has been supported by Ministry of Education, Culture, Sports,
Science and Technology of Japan.
Your paper title

REFERENCES
Takaaki Kato, Mitsuaki Kobayashi, Teruyoshi Yotsuyanagi (2010). A report on
the present situation of GDMS and discussion on requirement for success,Institute of Electrical Engineers of Japan
Takaaki Kato, Mitsuaki Kobayashi, Naohide Sato, Teruyoshi Yotsuyanagi (2009).
Prototype Development of “Geospatial Disaster Control Mash-up System”,
Institute of Electrical Engineers of Japan302

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Comparison of neural network learningalgorithms; BR and LM for flood
forecasting, upper ping catchment
Tawee CHAIPIMONPLIN1, Linda SEE2,3 and Pauline KNEALE4
1
Department of Geography, Faculty of Social Sciences,
Chiang Mai University, Thailand
tawee.c@cmu.ac.th
2
Senior lecturer, International Institute of Applied Systems Analysis,
Schlossplatz 1, A-2361 Laxenburg, Austria
3
Senior lecturer, School of Geography, University of Leeds,
Woodhouse Lane, Leeds, LS2 9 JT, UK
4
Professor, Faculty of Science and Technology, University of Plymouth,
Plymouth, PL4 8AA, UK
ABSTRACTThe flood issue for forecasters at Chiang Mai derives from the monsoon
rainfall, which leads to serious out-of-bank flooding two to four times a year.
Data for stage and rainfall of hourly in Upper Ping catchment is limited as
the historical flood record is limited in length. Neural Network forecastingmodels are potentially very powerful forecasters where the data are limited.
However, insufficient data for Neural Network training reduces the model
performance. All data for Neural Network is divided into three datasets:
training, validation and testing. In addition most of learning algorithms
require data for validation but Bayesian Regularization (BR) algorithm
does not need validation data, as a result, the training dataset size isincreased. The powerful of BR to forecast effectively where data set arelimited. Therefore, this algorithm is worth exploring for the Upper Ping
catchment. The Neural Network model is used to predict water stage at P1
station at lead times of 6 and 12 hours with two different learningalgorithms. The results have found that Neural Network performancetraining with BR algorithm is better than Levenberg-Marquardt (LM)algorithms by improving the peak stage.
Keywords: neural network, flood forecasting, Bayesian Regularization,
Levenberg-Marquardt, Upper Ping Catchment
1. INTRODUCTION
Monsoon rainfall leads to serious flooding in Thailand almost every years.
Particularly this year 2011, the tropical storm NOCK-TEN hit Thailand andcaused flood over northern, upper northeastern and central of Thailand,
approximately 30 provinces (Nan, Phrae, Lampang, Mae Hong Sorn,
Lamphun, Chiang Mai, Sukhothai, Nakhon Sawan, Phra Nakhon Si

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Mai,Thailand
Thailand
Chiangmai,

Ayutthaya, Nakhon Nayok, Phitsanolok, Ang Thong, Prachin Buri, Phichit,
Uttradit, Tak, Prachuap Khiri Khan, Kamphaeng Phet, Nong Khai, Ubon
Ratchathani, Mukdahan, Nakhon Phanom, Sakon Nakhon, Phetchabun, Roi
Et, Kalasin, Loei and Udon Thani) were suffered by flood and 46 death(Department of Disaster Prevention and Mitigation, 2011).
There are many types of flood modeling such as physical based modelor conceptual model or black box model. The disadvantage of physical andconceptual model is required lots of physical data. In contrast, neuralnetwork is one of the black box models and the big advantage is the ability
to generalize to unseen data and does not concern the physical relationships.
The Upper River Ping, which is the focus for this study, is a large catchmentwith very limited long-term data records. Calibrating a physical orconceptual model for a catchment of this size is inherently very difficult;many parameters would have to be estimated rather than known quantities
within such a model. There are limited data available for hour stage atstations on the River Ping that can be used to drive a neural network model.
The city of Chang Mai in the lower part of the catchment is subject toflooding, and would benefit from effective real-time flood warning. The
black box neural network model approach offers the opportunity to createmodels that can be run in real-time, and which can be updated relatively
easily as new data become available each year.
2. METHODOLOGYThe use of neural networks can be found throughout different areas ofhydrology and water resource management. The ASCE (2000) review into
the use of neural networks in hydrology considered applications across a
range of areas including rainfall-runoff modeling, modeling streamflows,
water quality modeling, ground water applications, estimation of
precipitation and miscellaneous areas such as reservoir operation and flood
wave propagation.
The most common neural network arrangement is three layers: theinput layer, where data are supplied to the model, a hidden layer, necessary
for processing, and an output layer, where the forecast or prediction is
produced. In addition there are bias nodes necessary for the calculations towork. The number of hidden layers and hidden layer nodes is determined by
the operator. Some neural networks have more than one hidden layer
although it has been shown that any continuous function can beapproximated with this neural network structure using only one hidden layer(Hornik, 1993). There are many types of backpropagation algorithm, which
can be classified into two main groups. The first group is described as slow
learning and uses batch gradient descent or simple gradient descent with
momentum. The second, fast learning, group may employ conjugate
gradient descent (CGD), quasi-Newtonian algorithms (which require morestorage and computation for each iteration) and the Levenberg-Marquardt
numerical optimization technique. The fast learning techniques can perform
at 10 to 100 times the speed of the slow learning processes. The difference

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between CGD and simple gradient descent is that it does not proceed along
the direction of the error gradient but in a direction orthogonal to the one in
the previous time step. The advantage for the modeler is a relatively fasttraining time. It has been used in hydrology for short and longer term stream
flow forecasts (Kisi, 2007). Where the model has a very large number ofhidden layer nodes, this process can be very efficient. However, where theinput nodes and weights are small, there does not appear to be any
advantage in using CGD over first order backpropagation methods.
Levenberg-Marquardt (LM) is probably the most commonly employedalgorithm (Beale et al., 2011). Fun and Hagan (1996) compared theperformance of three different algorithms including Levenberg-Marquardt
and found that it produced the best performing result. Bayesian
regularization (BR) is another type of training procedure that can be applied
to Levenberg-Marquardt (Mackay, 1992; Forsee and Hagan, 1997) andessentially reduces the impact of the network weights. It simultaneously
minimizes the overall error function and the sum of the squared weights. A
big advantage of the BR algorithm is that it does not require a validation
data set, unlike in early stopping and therefore makes BR a potentiallysuitable algorithm where data are limited (Beale et al., 2011). This meansthat more data are available for the training process. The BR algorithm has
been used in a few recent hydrological modeling applications (Anctil andLauzon, 2004; Anctil et al., 2004a, b; Anctil et al., 2006; Chaipimonplin etal., 2010, 2011; Zhang and Govindaraju, 2000). To compare the mostcommon used and fast learning algorithm (LM) with algorithm for limited
data (BR) thus in this paper the neural network models are trained with LM
and BR.
3. STUDY AREA
3.1 Upper Ping catchment
The Ping catchment is located in the Northern part of Thailand and isdivided into two parts: the Upper and the Lower Ping. The entire Ping
catchment covers approximately 33,898 km2. The Upper Ping is a large
complex river basin covering two provinces (17° 14′ 30′′ – 19° 47′ 52′′ N,
98° 4′ 30′′ – 99° 22′ 30′′ E); Chiang Mai and Lam Phun (Mapiam andSriwongsitanon, 2009). It has an area of approximately 23,600 km2 (Figure1) with 15 sub-catchments.

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Figure 1: The 15 sub-catchments of the Upper Ping basin.

Source: Regional Centre of Geo-Informatics and Space Technology (2006)

The main concern of this paper is to forecast the water stage at P1
station which is located at Chiang Mai city. The available data are hour data
at P1 (Second Part of the Mae Nam Ping sub catchment), P67 (Second Partof Mae Nam Ping) and P75 (Upper Part of Mae Nam Ping) (Figure 2).
Chiang Mai is in a catchment with a relatively steep terrain (approximately80%) with elevation higher than 500 meter (m) above sea level (Rodratana
and Piamsa-nga, 2008). The elevation of the Ping River basin ranges from
380 m to 2,275 m above sea level

Figure 2: Study area sub catchments

Source: Regional Center of Geo-Informatics and Space Technology (2006)

3.1 Flooding at Chiang Mai
All water gauge stations along Ping River are recorded by the
Hydrology and Water Management Centre for the Upper Northern Region.
At P1 station will be flood when the water discharge more than 440 m3/s
and water stage levels in the main channel exceeding 3.70 m above local
datum (304.2 msl) (Hydrology and Water Management Centre for Upper
Northern Region, 2011). According to the flood records for the past 50
years in the Chiang Mai city area, the four highest monsoon flood eventsoccurred in 1987, 1994, 1995 and 2005 (x axis) with water levels (y axis) of

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4.53, 4.43, 4.27 and 4.93 m, respectively. Since 2004 the flood level at P1
has been changed from 3.40 m to 3.70 m due to, construction the extra flood
defense wall along the river (Figure 3).

water level (meter)

6.0
5.0
4.0
3.0
2.0
1.0
0.0
Max level

1956 1957 1963 1967 1969 1970 1971 1973 1987 1994 1995 2001 2003 2004 2005 2006
4.18 4.16 4.15 4.13 4.06 3.87 3.96 4.17 4.53 4.43 4.27 4.18

3.7

3.7

4.93 4.33

flood level 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.40 3.70 3.70
year

Figure 3: Record of maximum flooding at P1 station from 1956-2007.
Source: Chatchawan (2005)

4. DEVELOPMENT MODEL
As the Levenberg-Marquardt (LM) algorithm is fast training and common
used and the power of Bayesian techniques to forecast effectively wheredata sets are limited therefore, both techniques were used to forecast waterstage at the Upper Ping. Water stage from three water gauge stations at timelag: t, t-3,t-6, …, t-24 and moving average 6, 12 and 24 hr were input
variables, then all input variables were selected with Stepwise regression
and the Bayesian Regularization (BR) and LM algorithm were run 50 times,
taking the average of the 50 runs as the model forecast after Anctil andLauzon (2004). The models were designed to forecast water stage lead timeat 6 and 12 hour.
Data from only the main monsoon season were then used to develop
and test the neural network models, in particular August to October between
2001 and 2005. The neural network trained with the Levenberg-Marquardt(LM) algorithm requires the dataset for validation but the BayesianRegularization (BR) algorithm does not require a validation dataset.
Therefore the longer 2001-2004 dataset was used for training with BR andtraining with LM was dataset 2001 - 2003 and 2004 was used for validation.
For these tests the number of hidden nodes was set to 10 after
Chaipimonplin et al. (2008a, b). Data for the year 2005 was used fortesting because it contains the biggest event in the record
Since the water stage changed from 3.40 to 3.70 meter in year 2004, it
would has the effect to the flow behavior, then the training dataset was
selected only storm 2005 (September to October) and testing the first storm
in 2005 (August). Due to few training dataset, BR algorithm will take anaction to perform this experiment. In addition, the lead time to forecast
water stage at P1 is 12 hour to compare the results with Chidthong et al.
(2009).

Comparison of neural network learning algorithms; BR and LM for flood forecasting,Comparison of neural network learning algorithms; br and lm for flood forecasting, upper ping catchment
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5. RESULTS
5.1. 6 hour lead time
Figure 4 contains the plots of actual and predicted stage for all storms
in 2005 with x axis is time (day/month/year) and y axis is water stage(meter) and Table 1 provides the evaluation measures. These results clearlyshow that the overall performance of the BR algorithm is better than trainedwith LM as the MAE, RMSE and CE are all better.

Figure 4: Results of foresting 6 hour lead time with BR and LM algorithms,
2005 storms.
Table 1: Goodness of fit statistics for LM and BR models at lead time of 6
and 12 hour

Statistics
MAE
RMSE
CE

6 hour lead time
LM
BR
0.086
0.035
0.139
0.072
0.974
0.993

12 hour lead time
LM
BR
0.176
0.071
0.142
0.140
0.972
0.973

Visual inspection of the hydrographs shows that models developedwith the BR algorithm all have more accurate peak stage and rising time
results particularly the storm in October (Figure 5).

Figure 5: Comparison of the BR and LM algorithms, three big storms in
2005, t+6

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5.2. 12 hour lead time
The evaluation measures are listed in Table 1 and the hydrographs are
displayed in Figure 6. Visual inspection shows that the BR algorithm
performs better than the LM algorithm as with the 6 hour lead time, and thestatistical measures once again demonstrate the superiority of the BR
algorithm over LM.

Figure 6: Results of foresting 12 hour lead time with BR and LM algorithms,
2005 storms
To forecast water stage using upper water stage station has the limited
to predict lead time at 12 hour as both models predicted delay at rising timeand underestimate at the peak. However, when look at the peak closer thehydrographs shows that BR models have more accurate peak stage at stormin August and October but not all BR models perform better results of risingtime (Figure 7).

Figure 7: Comparison of the BR and LM algorithms all three big storms in
2005, t+12

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5.2. An extra experiment of forecasting 12 hour lead time

(a)

(b)

(c)
Figure 8: Comparison of three results at t+12 hours, first storm 2005
Figure 8 shows the results of BR model training with 2001-2004
dataset (hydrograph ‘a’), while both hydrograph ‘b’ (result of Chidthong etal., 2009) and ‘c’ (BR model) are trained with only 2005 dataset. It is
obviously that the model’s performance increases when training models
with only 2005 dataset as the lead time increase from 6 hour to 12 hour.
6. CONCLUSIONSThe Bayesian regularization (BR) algorithm clearly proved to have an
overall advantage over the Levenberg-Marquardt (LM) algorithm on its own
in terms of forecasting accuracy. However, model performance was
improved by training neural network model with only 2005 data because theincreasing flood level along Ping River at P1 then it has changed the waterflow behavior. It also can draw the recommendation that for forecast waterstage at P1 in the future, water stage recorded (P1, P67 and P75) before
2005 are not longer needed.

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ACKNOWLEDGEMENTS
Thank you to the Hydrology and Water Management Center for the Upper
Northern Region for the water stage data, also Faculty of Social Sciences,
Chiang Mai University, Thailand for the funding of this research.
REFERENCES
ASCE, 2000. Artificial neural networks in hydrology. II: Hydrologic
applications. Journal of Hydrologic Engineering, 5, 124-137.
Anctil, F. and Lauzon, N., 2004. Generalisation for neural networks
through data sampling and training procedures, with applications tostreamflow predictions. Hydrology and Earth System Sciences, 8, 940-958.
Anctil, F., Lauzon, N., Andreassian, V., Oudin, L. and Perrin, C.,2006. Improvement of rainfall-runoff forecasts through mean areal rainfall
optimization. Journal of Hydrology, 328, 717-725.
Anctil, F., Michel, C., Perrin, C. and Andreassian, V., 2004a. A soil
moisture index as an auxiliary ANN input for stream flow forecasting.
Journal of Hydrology, 286, 155-167.
Anctil, F., Perrin, C. and Andreassian, V., 2004b. Impact of the lengthof observed records on the performance of ANN and of conceptual
parsimonious rainfall-runoff forecasting models. Environmental Modeling& Software, 19, 357-368.
Chaipimonplin, T., See, L.M. and Kneale, P.E., 2011. Improving
neural network for flood forecasting using radar data on the Upper Ping
River, International Congress on Modelling and Simulation, Perth,
Australia, Dec 2011, (In Press).
Chaipimonplin, T., See, L.M. and Kneale, P.E., 2010. Using radar
data to extend the lead time of neural network forecasting on the River Ping.
Disaster Advances, 3(3), 35-43.
Chaipimonplin, T., See, L.M. and Kneale, P.E., 2008a. Neuralnetwork prediction of flooding in Chiang Mai, Thailand: comparison of
input determination techniques. EGU, Vienna, Austria, 13-18 April 2008.
Chaipimonplin, T., See, L.M. and Kneale, P.E., 2008b. Use of neuralnetwork to predict flooding in Chiang Mai, Thailand: comparison of input
determination techniques. AOGS, Pusan, South Korea, 13-18 June 2008.
Chatchawan, S., 2005. The report of flood's situation and resolving at
Chiang Mai City 2005 (published in Thai). 2005 Annual Conference.
Chonburi.
Chidthong, Y., Tanaka, H. and Supharatid, S., 2009. Developing a
hybrid multi-model for peak flood for forecasting. Hydrological Processes,
23, 1725-1738.
Beale, M.H., Hagan M.T. and Demuth, H.B., 2011. Neural Network
Toolbox TM 7: User's Guide. [Online], [Accessed 26 August 2011],
Available at http://www.mathworks.com.
Department of Disaster Prevention and Mitigation, 2011. Flood
Situation Report. [Online] [Accessed 26 August 2011], Available at
http://disaster.go.th/dpm/flood/flood.html.

Comparison of neural network learning algorithms; BR and LM for flood forecasting,Comparison of neural network learning algorithms; br and lm for flood forecasting, upper ping catchment
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Foresee, F.D. and Hagan, M.T., 1997. Gauss-Newton approximation
to Bayesian learning, Proceedings of the 1997 International Joint
Conference on Neural Network, 1930-1935.
Fun, M.-H. and Hagan, M.T., 1996. Levenberg-marquardt training formodular networks, Proceedings of the 1996 International Conference on
Neural Network, 1, 468-473.
Hornik, K., 1993. Some new results on neural network approximation,
Neural Networks, 6, 1069-1072.
Hydrology and Water Management Centre for Upper Northern Region,
2011. Flood warning posters [Online], [Accessed 26 August 2011],
Available at http://www.hydro-1.net
Kisi, O., 2007. Streamflow Forecasting Using Different Artificial
Neural Network Algorithms, Journal of Hydrologic Engineering, 12, 5,
532-539.
Mackay, D.J.C., 1992. Bayesian interpolation. Neural Computation, 4,
415-447.
Mapiam, P.P. and Sriwongsitanon, N., 2009. Estimation of the URBS
model parameters for flood estimation of ungauged catchments in the upper
Ping river basin, Thailand. SciencesAsia, 35, 49-56.
Regional Centre of Geo-Informatics and Space Technology, 2006.
Faculty of Social Sciences, Chiang Mai University, Thailand.
Rodratana, P. and Piamsa-Nga, N., 2008. 'The study of flood
alleviation of Chiang Mai city area', The 13th National Convention on Civil
Engineering (published in Thai) Phataya, Thailand.
Zhang, B. and Govindaraju, R. S., 2000. Prediction of watershed
runoff using Bayesian concepts and modular neural networks. Water
Resources Research, 36, 753-762

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NewBuilding back right learning from Tohoku
Tomoko MATSUSHITA1) and Kimiro MEGURO2)
1)
Graduate Student, Department of Civil Engineering,
The University of Tokyo, Japanmatsushita-t@risk-mg.iis.u-tokyo.ac.jp
２)
Director/Professor, ICUS, IIS, The University of Tokyo, Japanmeguro@ iis.u-tokyo.ac.jp
ABSTRACTIn the process of reconstruction after mass destruction from the Great East
Japan Earthquake, speed and quality is required to respond to theimmediate needs of people. The authors assert the importance ofregenerating human activity as a vital part of reconstruction process andintroduce the process of making architecture as a means to promote
people’s participation and revitalization of local industry. As a part ofrelief effort by the Japan Committee for UNICEF to reconstruct destroyed
kindergartens, specific methods were introduced in the process and theresult after six months is evaluated in this paper.
Keywords: disaster response, reconstruction, community building
1. INTRODUCTION
A common problem in the Tsunami-affected area after the Great East Japan
Earthquake is that there are not enough suitable sites for rebuilding. All
types of buildings including housing and public institutions such as
hospitals and schools have suffered severe damage due to the Tsunami.
Many of them cannot be rebuilt on the same location since there is apossibility of them being flooded again. Some locations have experienced asignificant drop in the grade elevation due to the earthquake. Specificallythe severely damaged coastal areas have a limited amount of flat surface
area and some towns have entirely lost their ability to function because mostbuildings were built on flat areas. These towns are having difficulty in thereconstruction phase because they must first decide where to relocate theirmunicipality which involves massive earthwork as well as surveys anddrafting new town maps.
After conducting a number of hearings and visits to the affected sites amonth and a half after 3.11, the condition of the evacuees proved to be quite
stressful due to the lack of adequate space and privacy at provisional
shelters. Many evacuees had no immediate hope of returning to a normallife at home, going to work or school as they used to. Children had no place
to play which adds to the stress of the parents.

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Local governments were making great efforts to restart schools so thatchildren would not fall behind with their coursework. Most schools werebuilt at higher elevations so they mostly survived the damage and were able
to start classes as soon as the necessary infrastructure was restored. On theother hand, facilities for preschool children such as kindergartens andnurseries were typically built in the downtown area and many of them were
washed away by the Tsunami.
Therefore in order to restart thekindergartens, local government had to start by locating a suitable buildingsite.
It was evident from the interviews with local government officials andprincipals of kindergartens that they were in desperate need to restart daily
operations as soon as possible not only for the children's sake, but also forparents and teachers. Since it was not realistic to wait until the completionof a new town map, the local government prepared temporary sites to build
temporary kindergartens to be used for 3 to 5 years.
2. ACHIEVING SPEED AND QUALITY
The given task was to achieve both speed and quality and we propose two
possible alternatives to answer the needs: First, is to provide light-steel
prefabricated structures and second is to make architecture.
The prefabrication technology in Japan is highly developed with astable supply system able to produce safe and high quality habitable spacein a short period of time. Compared to wood, steel is easier to control and it
is suitable for factory production, its production system has reachedmaturity due to the competitive market in the Japanese housing industry
after the housing shortage during the post WWII era. It does not matter
where to source the production, from south to north within the JapaneseIslands there is a robust, efficient and stable supply chain. As far as
construction duration, it takes only a few months including the preparatory
infrastructure, to restore all the facility needs as they were provided before,
which is astonishingly fast. It is true that it sacrifices flexibility for the sakeof efficiency, which is to say that size and shape are confined within limited
parameters. However it is possible to customize to some degree, by using
different materials such as natural wood, planning the arrangement of units
to maximize the use of land, or by creating rich exterior space that isconnected to the interior space.
2.1 Recovering Lost Human Activity
Another alternative we propose here is the main focus of this paper
and it is the making of architecture. To respond to the required speed andquality, prefabricated structures seem to be the answer, then why makearchitecture? To make architecture means to facilitate human involvement
and activity. Human in this case refers to both the creator and the recipient,
who are both victims of the disaster. The creators are local craftsmen who
know the local climate, materials and construction methods with

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theinetwork of craftsmen. Making architecture with the local craftsmen
necessitates the revitalization of the damaged local industry.
The recipients in this case are the beneficiaries who will be the endusers of donated facilities. Typically when a disaster transpires, thebeneficiaries are treated as a helpless mass. At first they need to recoverfrom the shock and painful experience but after a while, they need to moveon and a first step is to start human involvement and activity. In the processof making architecture, the beneficiaries will be able to participate by
expressing their opinions which will foster a sense of responsibility andattachment to the end product that is not possible to obtain if thebeneficiaries are excluded and given a completed result. In other words,
this is an empowerment process where the victims themselves areproactively working to improve their own situation and gain strength
through the experience. By making an effort to take control of their own
future as a stakeholder in the process, it provides a sense of ownership.
What is lost after the mass destruction of natural disasters is not only
physical buildings and infrastructure but also human activity itself.
Rebuilding human activity is a vital part of the reconstruction process andthere are several ways to achieve it. We believe that making architecture
can contribute to both physical reconstruction as well as the facilitation ofhuman involvement and activity.
We are not proposing which method is better, be it providing
prefabricated structures or making architecture. Both methods satisfy theneeds respectively and it is most important to understand what is reallyneeded by carefully listening to the voices of people from the disasteraffected area and to choose the best alternative. When the situation isabsolutely urgent and allows no time to spare, speed is prioritized andprefabricated structures will be the right choice. However, if the users canafford some time to wait, two alternatives may be suggested for them tochoose.
After suggesting these two options and carefully listening to people, it
became evident that most people did not consider making architecture as an
option for it typically costs more and takes a longer time. However they
preferred making architecture to prefabricated structures if they had theoption of choosing and they were willing to wait for better quality. Thereseem to be two reasons for this choice. If it is only for a few more extra
months of waiting, they were willing to accept less favorable conditions.
The other reason is the uncertainty for the future. Nobody knows for certain
how long the reconstruction process may take and the use of the temporary
facility may be longer than initially promised, thus people preferred morepermanent structure.

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3. METHODS
Total of nine kindergartens and nurseries in Miyagi prefecture were selected
for reconstruction after careful hearings. In order to smoothly execute themission at the time of emergency, we introduced three methods; 1) making
with local craftsmen’s initiative; 2) making with people’s participation; and3) formation of an experts advisory group to supervise quality for mass
production.
3.1 Making with Local Craftsmen’s Initiative
To proceed with a project during the time of confusion, we propose to
take a phased approach. At the disaster-affected area, unusual conditions
such as the lack of certain building materials, craftsmen, or difficulty in theconstruction management are expected. In order to assess the actual
situation, it is necessary to start with a ‘trial & error’ approach andrecognize the importance of making the first step to move forward.
A pilot project will be initiated as Phase I. Its main objective is to
grasp the situation as much as possible by running an actual project with alocally organized team of craftsmen to discover any potential issues. By
running a pilot project, the limits of locally based activity becomes clear andit will provide important information as to what is missing at the local level
and what kind of support is necessary from outside. It is vital to locate a
key local coordinator who is well acquainted with the local craftsmen andconstruction industry to coordinate the first phase.
Based on findings from the pilot project, during Phase II, the team will
be reorganized and supplemented by outside support. It will explore thepossibility of the locally initiated activities that can further strengthen theoverall idea.
3.1.1 Examples of Locally Initiated Activity
One example is a proposal to design a wooden structure that will
revive the traditional carpenters’ skill of a particular region – Kesen Daiku.
The regional carpenters should be able to give hope and strength to the local
people by performing their work and in return they will receive a sense of
pride and contribution to the declining carpenters’ world.
Another example is the effective use of a massive stock of knocked
down trees of shelterbelt. A large amount of old trees that were planted
along the coast became debris after being knocked down by the power of
Tsunami, washed away and soaked in the salt water. It is possible to use
such wood for new construction as flooring materials or finish materials but
coordination is required between the fabricators and local government inorder to handle the public property in a proper manner.

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3.2 Making with People’s Participation
People’s participation helps to promote empowerment and ownershipas discussed earlier. It is also an important process to understand the trueneeds of the people. Two ways to participate in the process are via: 1)
design meetings and 2) workshops. These are nothing new and generally
conducted as a part of typical development process. However, we find it
important to promote these processes at the time of emergency during therecovery process.
3.3 Formation of Advisory Group
There are many stakeholders with different interests such as architects,
craftsmen and beneficiaries that are involved in the making of architecture.
Sometimes the discussion may be biased or one-sided due to diverse
backgrounds or level of knowledge and it needs to be brought to aconclusion by a third party. A group of experts with relevant specialties
will form an advisory group to play this role.
To take into account the fact that there will be more than a single
facility to be constructed, the quality must be controlled to maintain acommon standard. Although individual facilities will have uniquenessbased on site conditions and specific needs of its users, it is advisable toshare a common goal in the larger picture. The advisory group is
responsible for creating a basic principle that represents a big concept withactual suggestions to be shared.
4. RESULT
To evaluate each of the alternatives taken for the reconstruction project ofkindergartens, it can be said that the prefabricated structures were able torespond fully to the needs at the time by providing a building quickly. The
making architecture approach is still ongoing and too soon to be evaluatedbut the following observations were made;1) The pilot project was effective in identifying strong local networks
and the availability of the local players with strong commitment tocontribute to their own region. This was contrary to the expectations ofsome people who did not believe it was possible for local actors to takeinitiative due to the confusion.
2) Active participation by the beneficiaries was observed during themeeting and workshops and the design process was invigorated due to theinvolvement by many actors.
3) Basic principles worked effectively to provide guidelines to thedesigners while allowing room for creativity. In a process of designing anursery on a difficult site condition, an expert from an advisory group joined
the meetings to provide opinions and helped resolve the issue to everyone’s
consent.

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The awareness of people has changed once they became active participantsin the process of making architecture. Designing actual space and functionof their future building, people started to speak freely to express concerns
for their future and making a difference by taking ownership.
5. CONCLUSION
After mass destruction from a natural disaster, a municipality and its people
face the long and phased process towards restoration of their lost entities,
starting from emergency response through recovery phase to final
reconstruction. It is important to start with the correct action in the earlier
process for it influences the subsequent activities. In the case of thekindergarten reconstruction project, the decision to make architecture
generated positive influences by revitalizing the local network of craftsmen
and cultivating the people’s consciousness, and by doing so, we believe it
provided an important foundation for the regeneration of the region as awhole. Furthermore, this method allows for relief funds to stay within theaffected community, providing employment and income directly to victims,
thereby kick starting the local economy, rather than paying factories in
distant regions unaffected by the disaster.
It is the people that hold the key to the success in the reconstruction
process. Without the local people taking initiative, there is no recovery inthe true sense. Locally based experts and craftsmen should be recognized asa valuable resource and key players. To learn from this experience in
Tohoku, we suggest the establishment of a people’s common ground joinedby residents, community architects and craftsmen to discuss the future of
their town and environment.
ACKNOWLEDGEMENT
We would like to express special thanks to the hard working people of local
governments and the kindergartens / nurseries in Miyagi prefecture, mighty
collaborators including local coordinators, advisors, architects, contractors
and subcontractors, and the colleagues of Japan Committee for UNICEF fortheir cooperation throughout the project.
Note
The views and ideas discussed in this paper do not necessarily represent
those of Japan Committee for UNICEF or UNICEF in any way

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NewOral Sessions

Importance of engineering judgment
against unexpected hazards
Taketo UOMOTO
Chief Executive, Public Works Research Institute, Japanuomoto@pwri.go.jp
ABSTRACTThe disasters caused by the Great East Japan Earthquake taught us theimportance of engineering judgment against unexpected hazards, such as
Tsunami, and nuclear plant accident. This paper shows how the engineers haveto decide what to do in case of unexpected hazards.
Keywords: engineering judgment, hazards, engineers
1. INTRODUCTIONOn March 11, 14:46, 2011, the massive “Great East Japan Earthquake” hit thecountry of Japan just off the Pacific coast. The magnitude of the earthquake wasreported as 9.0, and shook Japan from Hokkaido to Nagoya City.
The disaster was tremendous compared to the Hanshin-Awaji Great Earthquake
which took place in Hyogo prefecture in January 17, 1995. Table 1 summarizes acomparison of the two earthquakes. A large difference can be seen in not only thevibration of the ground caused by the earthquake, but also the tsunami and nuclear
power plant accident.
Table 1: Comparison of the Great East Japan Earthquake
and Hanshin-Awaji Earthquake
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This paper is aimed to introduce the disasters caused by the Great East Japan
Earthquake and explain the importance of engineering judgment against
unexpected hazards
2. WHAT HAS HAPPENED DUE TO THE GREAT EAST JAPAN
EARTHQUAKEThe epicenter of the Great East Japan Earthquake was about 130 km from theSanriku area with a depth of 24 km. The maximum JMA (Japan Meteorological
Agency) Seismic Intensity was 7.0, the maximum acceleration was more than
1000 cm/sec2, and the maximum value observed was 2933 cm/sec2. As shown in
the Figure 1, more than one third of the whole Honshu Island and Hokkaido
Island was above PGA 5cm/sec2.

Figure 1: Maximum acceleration caused by the Great East Japan Earthquake(Earthquake Research Institute, University of Tokyo)
Furthermore, the aftershocks were also tremendous. As shown in Figure 2, thenumber of aftershocks above magnitude 5.0 within one month after the Great East
Japan (up till April 10, 2011) was more than 440. As a result, some of thestructures which were not damaged by the initial earthquake were severely
damaged by the aftershocks.
After the earthquake a huge tsunami occurred. The total length of the tsunami wasabout 450 km from north to south, and it reached most of the coastal lines ofJapan as shown in Figure 3. As shown in the figure, the coastal lines of the northeastern part of Japan were attacked by a huge tsunami (more than 3 m in height)
and the south-eastern part of Japan was also attacked by large tsunami. The figureis the tsunami warning issued by the Japan Meteorological Agency (JMA) justafter the earthquake (March 11, 16:08). The estimated maximum height at thetime of warning was more than 3 m, but the actual height was more than 10 m atsome parts of the coast line.

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9Magnitude of Earthquakes

8

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7

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0Figure 2: Number of aftershocks after the Great East Japan Earthquake

Figure 3: Tsunami warning issues by JMA just after the earthquake
Due to the huge tsunami, many structures located on the coast line were damaged
and many houses were swept away. The newspapers reported that most of thehouses located close to the coast line from Iwate Prefecture to Miyagi Prefecture
were damaged and more than 15,000 people lost their lives and more than 8,000
people were missing (as of June 6, 2011). The damage was far larger than thatcaused by the earthquake. Most of the houses located near the coast were swept
away and the houses located at hilltops could remain as shown in Figure 4.
Due to the tsunami, the Fukushima No.1 nuclear power plant was damaged. The
tsunami attacked the plant by over-flooding the dikes and the sea water flooded
the electric power facilities which shut down electric control of the plant. Due tothe damage, the nuclear plants went out of control, causing hydraulic explosion
and meltdown of the boiling water reactors (BWR).

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Figure 4: Houses located on a hilltop which were spared tsunami damage
3. CAUSES OF THE DISASTER
Looking at the Great East Japan Earthquake, the main cause was quite simple. As
shown in the Figure 5, the original cause was the earthquake with the magnitudeof 9.0. In case of the Great Hanshin Awaji Earthquake which occurred in 1995,
magnitude of the earthquake was 7.3, and the damages of the structures were
mostly caused by the earthquake ①. However, the Great East Japan Earthquake
was followed by a huge tsunami, damaging both the structures and the people ②.
One of the structures was the nuclear electric power plant of Fukushima No.1 ③.
The BWR of the power plant went out of control due to the loss of electricity(both normal and temporary electric supply were not available for some time) ④.
As a result, meltdown of the BWR occurred ⑤.
Great Earthquake（M9.0,150kmx450km）

Huge Tsunami②
Damage ofStructures①②
Damage ofStructures①

Limitations of Electric Power Supply④

Huge Tsunami

Damage of
Nuclear Plant③
Nuclear fallout
and meltdown⑤

Figure 5: Causes of the disaster
After the hydrogen explosion, radioactive contamination spread around thesurrounding area. This forced people to evacuate from the vicinity of the power
plant, and citizens have been forced to live outside the evacuation area.

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One of the main reasons why such a disaster occurred is that these situations were
not expected even when the structures were designed. The expected conditions
during the design of the structures were that a large earthquake may occur during
their service lives, but the attack of tsunami was not strongly considered.
Structures constructed after 1998 or strengthened using the modified standard
specifications considering the damages of the Hanshin-Awaji Earthquake were
not severely damaged by the Great East Japan Earthquake. But in the case oftsunamis, for structures such as houses and bridges the load was not considered.
This is one of the reasons why so many houses and bridges were damaged.
After the earthquake, some engineers mentioned that “we did not expect to havesuch a large tsunami attacking the structures.” Although the available standard
specifications did not mention the design considerations for when a tsunami
attacks the structures, the engineers must think about the safety of the people who
use the structures. It is important for the designer and construction engineers torealize how we should keep the structures safe enough or should give theinformation to what extent the structure can resist against any unexpected loads.
Nowadays, many engineers are conducting their work to meet the available
standard specifications, but many engineers forget the fundamental works theyshould consider during designing and constructions. I hope engineers willreconsider the methodologies we are using now and check the most importantconcept “worst case scenario” during their works.
4. CONCLUSION
After the Great East Japan Earthquake, many investigations and research works
have begun. We know that natural hazards may occur at any time and may exceed
the expected situation and scale. Engineers must always be careful to conduct
their works considering the “worst case scenario” and try to keep the users of thestructures safe through any situation.

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Seismic functional vulnerability of the road
network of the metropolitan areaof San Jose, Costa Rica
Grettel MOLINA1, William VARGAS2 and German VALVERDE3
1Graduate Student School of Eng., University of Costa Rica
grettel.molina@gmail.com
2 Associate Professor, School of Civil Engineering, University of Costa Rica.
3 Adjoin Professor, School of Civil Engineering, University of Costa Rica.

ABSTRACTThe seismic functional vulnerability of the road network of the San Jose’s
Metropolitan Area (SJMA) as a lifeline was assessed in terms of the impact ofan earthquake upon the travel time between the Desamparados County, and the
SJMA’s most important public hospitals. According to a previous study,
Desamparados is one of the counties of the SJMA with the highest density of
population, physical vulnerability of residential buildings.
The analysis is based on a simplified model of the network of urban highways,
roads and streets introduced into the computer software TSIS (Traffic Software
Integrated System). A bi-proportional model, based on a travel survey
conducted by a previous study, was used to generate the initial input origindestination (OD)matrix. The number of vehicles for the target areas wasprojected to the year 2010 with an econometric model. The resulting OD matrix
was then calibrated using the Single Path Matrix Estimation (SPME) method(Nielsen, 1994) and the traffic assignment tool of TSIS. Travel times were alsomeasured in four different traffic conditions, ranging from the minimum
expected traffic to the normal rush hour. The hourly traffic variation in thevicinity of the main hospital was also obtained by an automated counter.
Several different scenarios of events with epicentre in or near the study area
were analyzed. An earthquake of magnitude 6.3 denominated Tablazo,
originated in the Aguacaliente – Orosi fault was chosen, because of its vicinity
to the Desamparados County. The earthquake effects upon the bridges of the
SJMA were modelled by Campos and Marenco (2001) and, according to theseauthors, the Tablazo event has the largest probability of producing damage tobridges in the Desamparados – San Jose road network that would cause theirtemporary closure, even if they do not collapse. The SJMA’s social seismic risk,in terms of the population exposed to suffer injuries or fatalities in a seismic
event, as modeled by Salas (2003), was used to introduce changes in the OD
matrix in the emergency scenario.
The impact of the earthquake on the functionality of the road network wasanalyzed using the service indicators in the output obtained from the TSIS
simulation. Changes on the network and on the trip matrix were considered, as
well as the social post-emergency behaviour. The most important functional
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identified. Based on the results of the model recommendations are made to
reduce the functional vulnerability, strategies and alternate routes forfacilitatingmovement from Desamparados to the medical centres in case of an
emergency.
Keywords: seismic functional vulnerability, road network

1. AREA OF STUDYThe San Jose’s Metropolitan Area of (SJMA) delimits the study area of thisproject. It is shown in the figure below.

Figure 1: Location of the area of study
The project focuses on the urban zone of Desamparados County, on
the zones and road network that connect the center of this county with themost important centers of medical attention in San José, the hospitals:
Calderón Guardia, México and San Juan de Dios.
The network of the Metropolitan Area as a result of its complexity has
important limitations in relation to accessing the central area from thesurrounding urban zones. In addition to the complexity of the road network
the central area of this study is bordered by the rivers Torres and Maria
Aguilar; the roads over these rivers are reduced to a few bridges with justone lane in most cases.
Besides this physical limitation, the current volume of traffic on theaccess routes generates critical conditions and saturation during peak2
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periods of the day. It is predictable that in case of a seismic emergency theroad system could collapse in a few minutes.
There are studies that supply valuable information to this project, themost relied upon studies are: Seismic Vulnerability of the Road Systems by
William Vargas in 1985, the project about the impact of an earthquake on
the road network of the San José’s Metropolitan Area by Silvia Campos andOscar Marenco completed in 2001 and the graduation project about
Evaluation of the Seismic Risk in Residential Buildings of San José’sMetropolitan Area of in regards to loss of human lives by Luis Salas in 2003.
The objective of this project is to analyze the seismic functional
vulnerability of the road network in Desamparados and its connections withthe major hospitals of San José.
1.1 Seismic Vulnerability of the bridge
The seismic model utilized in this project is derived from the worst
case scenario of the Tablazo earthquake in Campos and Marenco 2001,
depicting impassible bridges.
1.2 Social Seismic Vulnerability of the area of study
In 2003 Salas determined the map of social seismic risk as a result ofcombining the statistic distribution of social vulnerability and social threat.
2. METHODOLOGY

The following image contains the methodology used for the thedevelopment of this investigation.

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Figure 2: Methodology of the Investigation
steps:The process of modeling the road network consists of the following

Figure 3: Methodology of the Model of the road network in TSIS 5.1

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This is a screen capture of the model of the road network in the program
TSIS 5.

Figure 4: Model of the road network in TSIS 5.1
The calibration of the O/D matrix consists of the following stages:

Figure 5: Methodology of the calibration of the O/D trip matrix
2.1 Model of the road network in different scenarios
The seismic scenario of the Tablazo earthquake is used for the model
since that is the scenario that most directly affects the area of study. The
Tablazo earthquake best embodies the worst consequences for
Desamparados. The next image shows the four different scenarios that were
simulated:

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Figure 6: Modeled Scenarios
Scenario A represents the current geometry of the road network withthe current trip matrix. In scenario D the network model is modified bymarking the bridges indicated in Campos and Marenco, 2001 as impassable.
Then using Salas 2003: the percentages of Social Risk Index are factored
into the trip matrix.
Scenario B represents the conditions after the emergency in which thegeometry of the network continues being affected due to the seismic
emergency that happened but the event that caused the emergency has ended,
so the trip matrix returns to its initial state.
Finally, in scenario C the emergency happens, using Salas 2003: thepercentages of Social Risk Index are factored into the trip matrix. The
geometry of the road network is not affected, because of the premise that thebridges are not critical elements of the network and they do not affect thefunctionality of the road network.
3. RESULTS
It is possible to quantify the functional seismic vulnerability of the road
network analyzing the indicators of TSIS 5.1 and the travel time.
3.1 Analysis of Indicators of TSIS 5.1
A comparison of the indicators given by the program TSIS 5.1 foreach scenario was made. The following table of comparison was obtained:

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Table 1: Indicators of the road network

3.2 Analysis of the travel time
The travel time between Desamparados and the three major medical
centers of San José was measured for the different scenarios, and thefollowing table of comparison was obtained:
Table 2: Travel time in different scenarios

Scenario A of present conditions is similar to scenario C of case of
emergency where the network is not affected. This means that in case of an
emergency the trip matrix will always get altered. If the road network does
not get affected and it keeps being functional the scenario has better traffic
indicators than the scenario B that represents the post emergency conditions
with normal conditions of traffic and a still affected road network. Thisshows that the traffic system is more sensitive and it gets more altered bychanges on the road network geometry than with changes on the trip matrix.
Scenario D indicates fewer vehicles per mile than scenario A because
the cars cannot get into the system or move inside of it due to impassible
spots that are impeding traffic flow. The indicators in the model show thatafter 899 seconds of scenario D, the network becomes saturated, thesaturated state remains for the final 2700 seconds of the simulation.
The travel time of the different scenarios shows that in scenario D theaverage speed decreases by 44.5% compared to scenario A with the present
conditions. After the emergency in scenario B, the speed stabilizes at 30%
less than scenario A. In the ideal case C the travel time diminishes by just
10% compared to A.

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4. RECOMMENDATIONSThis project is a pilot study, specific for the Metropolitan Area and thetraffic circulation between Desamparados and the major medical centers of
San José. The goal of this study is to provide a methodology for a new lineof investigation in the planning and analysis of urban development andemergency response systems.
This methodology can be applied with infrastructure elements otherthan bridges; for example, hospitals, schools, electrical and water systems.
Other natural disasters and threats which are more frequent and which canhave similar effects on the functionality of the road network can also bemodeled; such as, hurricanes, flooding, landslides, and tornadoes.
It is fundamental for investigations to use an actualized database with thevolumes of traffic, traffic sign locations and traffic signal timings. In Costa
Rica the most recent traffic volume information was taken in 1997 by the
Ministry of Transportation and Public Works. There is no database of traffic
sign locations and traffic signal timings. An incomplete and outdated
database limits control of the road network’s function, as well as planningand improvements of the road network.
It is very important and it should be a priority for Costa Rica torebuild and maintain their bridges that in this moment represent the criticalpoints of the road network. The functionality of the network depends on thebridges as components of the system.
Some of the specific possible solutions to decrease the seismic
functional vulnerability of the road network are: The Ministry ofTransportation and Public Works should retake the project to extend rout
175 starting on route 213 because it would give a bigger redundancy andcapacity to the road network of Desamparados.
It is recommended to model the seismic vulnerability of the road
network with all bridges in the area in order to determine the priorities of its
reconstruction, improvements and measure with greater accuracy the impactof each bridge on the functionality of the road network.
It is necessary to effectuate counts of the vehicle traffic in all themetropolitan area to increase precision of the initial O/D matrix.
Building a hospital in Desamparados would also alleviate stress on theroad network in the case of an emergency. Desamparados has a very highpopulation and this project demonstrated that its connection to the major
medical centers is San José is seriously limited by the seismic functional
vulnerability of the road network.
Another way to decrease the seismic functional vulnerability of theroad network is to build public heliports, which can transport the population

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of Desamparados to the closest medical centers in case of a major seismic
event.
5. CONCLUSIONS
Through this investigation it was possible to model for the first time in
Costa Rica, the functionality of a road network in case of an earthquake,different scenarios of damages were modeled. The on the zone between
Desamparados and the most important health centers of San Josédemonstrated a need to decrease the seismic functional vulnerability of theroad network of the metropolitan area.
This study concludes that it is extremely important to model andanalyze the seismic risk of a vital system like road infrastructure to
determine not only the damage that its seismic vulnerability can produce,
but also to analyze the possible reduction of the functionality and capacityof the system or suspension of traffic circulation between different points.
This implies that the behavior model of the system as a vital systemshould be modeled as a network composed of components like structures,
population and traffic behavior not as isolated road segments or
infrastructure.
The methodology used in this study allows quantifying the seismic
functional vulnerability with indicators of the situation before and after an
emergency. The bridges stood out as the critical components of the systemthat impede the functionality of the network.
REFERENCES

Araya, J., 1996. Study of the validity of a model of simulation TRAFNETSIM for the conditions in Costa Rica. Graduation Project of the Civil
Engineer School, University of Costa Rica, San José, Costa Rica.
Campos, S., Marenco, O., 2001. Evaluation of the impact of anearthquake on a road network on the San Jose’s Metropolitan Area.
Graduation Project of the Civil Engineer School, University of Costa Rica,
San José, Costa Rica.
Climent, A., 2008. Evaluation of the seismic thread of Costa Rica.
Resis Project II. NORSAR, Costa Rica.
De Solminihac, H., 2005. Administration of road infrastructure.
Alfaomega,México.
Federal Highway Administration, 2003. TSIS User Reference Guide.
Office of Operations Research, Development and Technology. McLean,
Virginia, USA.
Figueroa, D., 2009. Travel time of the public transportation system in
San Jose’s Metropolitan Area. Graduation Project of the Civil Engineer
School, University of Costa Rica, San José, Costa Rica.

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National Institute of Statistics and Census, 2009. Projected populationfor 2015. San José, Costa Rica.
ITT Industries, Inc., Systems Division, 2003. TSIS User’s Guide
version 5.1McLean, Virginia, USA.
Han, A., Dowiling R., Sullivan, E., 1981. Deriving OrigenDestination information from routinely collected traffic counts. Institute ofTransportation Studies. University of California, Berkeley.
Regional and Urban Planning of the Metropolitan Area, 2009.
Proposal for the plan PRUGAM 2008-2030. San José, Costa Rica.
Salas, L., 2003. Evaluation of the seismic risk of residential buildingsof San Jose’s Metropolitan Area in function of the human loss. Graduation
Project of the Civil Engineer School, University of Costa Rica, San José,
Costa Rica.
Schmit, V., 1997. Costa Rican Spectral Strong Motion Attenuation.
NORSAR, Laboratory of seismic engineery. University of Costa Rica.
Solórzano, S., 2010 Road re-organization of the central area ofEscazu, implementing pedestrian analysis. Graduation Project of the Civil
Engineer School, University of Costa Rica, San José, Costa Rica.
Valverde, G., 2004. Calibration of a model of growth of travel
demand using panel microeconomic data. Graduation Project of the Civil
Engineer School, University of Costa Rica, San José, Costa Rica.
Vargas, W., 1985. Seismic vulnerability of the vital systems. Project of
the Civil Engineer School, University of Costa Rica, San José, Costa Rica.
Vargas, W., Garro, J., 2003. Administration of natural risks of theroad infrastructure. National Laboratory of Materials and Structural Modelsof the University of Costa Rica.

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NewEarthquake hazard in Ulaanbaatar cityand its surrounding area
Ulziibat MUNKHUU 1, Yasuyoshi ICHIHASHI 2,
and Demberel SODNOMSAMBUU 3
1
Head Seismological Department, RCAG, MAS, Mongolia
ulzibat@rcag.ac.mn
2Visiting Professor, ICUS, IIS, University of Tokyo, Japan
Ysich555@iis.u-tokyo.ac.jp
3
Scientific Secretary, RCAG, MAS, Mongolia
demberel@rcag.ac.mn
ABSTRACT
Mongolia is one of the most seismic active intra-continental regions in theCentral Asia. In last century Mongolia suffered four great earthquakes ofmagnitude 8 and above in a period of 53 years (Tsesterleg 1905, Mw=7.9 Bolnay 1905, Mw=8.3, Fu Yun 1931, Mw 8.0 and Gobi-Altay 1957,
Mw=8.1). Beside that the large number of active faults capable ofproducing a devastating earthquake in Mongolia makes the prospect ofstrong events very concerning. About 70% of area of country belongs towith region intensity between VIII and XII (MSK).
Earthquake hazard has become one of the most important issues for
Ulaanbaatar city because of the following reasons. First, since 2005 highseismic activity has been taking place near and within Ulaanbaatar area.
Recent geological and seismological studies reveal strong clues about
active structures around city that can dramatically increase the seismic
hazard of the capital of Mongolia. Second, Ulaanbaatar is not only mostpopulated city but also political and economic centre of the country.
According to the economical growth and mechanical increase of the
population of the Ulaanbaatar, intensive constructions are going on. These
are translate into a significant level of seismic risk that needs to berealistically assessed and updated as new knowledge becomes available.
The seismicity recorded by local permanent and temporary networks reveals
strong increase of seismic activity rate in region around U.B. For instance,
2 times as many earthquakes were recorded during the last five years(2005-2010) as between 1970 and 2004. Moreover, these swarms,
consisting in more than 1600 events with a magnitude between 0.5 until 4.2,
are mainly located close to 2 major active structures: NS Emeelt and EW
Hustai striking faults. At the beginning (2005-2009), the swarm activity
mainly concerns the Emeelt fault and was characterized by a strong timedependency consisting in a propagation of the activity toward North andSouth fault edges with an increase of the seismicity rate. In 2009, theseismic swarm extended his activity to the eastern edge of the Hustai fault
which is the largest known structure near Ulaanbaatar able to produce
large destructive earthquake on the city. Despite the relatively low

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magnitude of these earthquakes, the lack of large magnitude earthquake inthis area combined with the clear active fault morphology of the Hustai andEmeelt structure make the study of this recently triggered seismic swarm
fundamental for the estimation of Ulaanbaatar seismic hazard. In thispresentation, we will discuss some preliminary results of the analysis of thishigh seismic activity recorded by permanent and dedicated mobile networks,
such as its spatial and time evolution or their relation with the regional
seismo-tectonic context, as well as its impact on the seismic hazard
assessment of Ulaanbaatar area.
Keywords: seismic activity, swarm, seismic hazard
1. INTRODUCTION
A seismic activity is taking place near and within Ulaanbaatar area since2005 and it is still active up to now. The seismicity observed by local
permanent and temporarily deployed networks has reveals significant
increase of seismic activity in the Ulaanbaatar area. Twice high number ofearthquakes were recorded during last 5 years than events recorded between
1970 and 2004 in the considering area. Such seismic activity mightdramatically increase seismic hazard of the capital of Mongolia where 1/3 ofthe Mongolian population lives and the majority of industries of the country
is concentrated. Moreover, these swarms consist of more than 1600 events
within magnitude range of 0.5 to 4.2. Most of these events are located close
to the 3 major active structures that are NS-Emeelt and EW-Hustai striking
faults and Gunjiin active fault were located NE of city. Despite therelatively low magnitude events and lack of large magnitude earthquakes
occurred in the area with combination of the clear active fault morphologyof the Hustai and Emeelt structures shows that the recently triggered seismic
swarms are fundamental factor for the estimation of Ulaanbaatar seismic
hazard. On this paper we will discusses some preliminary results of theanalysis of this high seismic activity recorded by permanent and dedicatedmobile networks. The spatial and time evolution or their relation with theregional seismo-tectonic context as well as its impact on the seismic hazard
assessment of Ulaanbaatar has been evaluated.

2. SEISMIC ACTIVITY AROUND ULAANBAATAR CITY
Since 2004, significant increase of occurrence of small to moderate
earthquakes began to occur beneath a Hustai and Emeelt active fault areathat are located about 10 to 40 km west of Ulaanbaatar (figure 1). The highseismic activity of Ulaanbaatar area starts from middle of 2005 and it is still
continuing up to now. During this period, moderate size earthquake (Ml~
4.2) occurred in the Hustai active fault area in May, 2008 and other twoearthquakes with magnitude of ~4 occurred about 60 km south and northfrom Ulaanbaatar city in Oct, 2008 and Mar, 2009 respectively. Thesestatistics showing seismic activity is increasing and migrating. Distributionof these swarms, with more than 2000 events, has interconnected the major

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active structures in Ulaanbaatar area by a steeply dipping fault surface
striking East-West Hustai and North to South Emeelt fault. The 2005/2010
swarms mostly occupied the Emeelt fault and its increasing number of
events shows of extreme sites of this structure. It means fracturing is
propagating two sites of fault and this process is happening caused byreactivation of paleoseismic active faults. The Hustai fault area activated by
the 2009/2010 swarms and it shows probable main potential structure which
may produce large earthquakes. Most activity is occurring east end of thisactive fault and shows somehow connection between these two active faults.

Figure 1: Seismic distribution map of Ulaanbaatar
The number of earthquakes occurred between 1970 and 2010 contains
totally 3000 events, 900 events recorded during 1970 - 2003 and about 2100
events occurred from 2004 to 2010. There were 508 and 543 earthquakes
correspond only for 2009 and 2010 respectively, and 210 events werealready occurred in 2011 (Figure 2).

Figure 2: Statistic behavior of the seismic activation of the Ulaanbaatar
area. Cumulative number of the events

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3. SEISMIC NETWORK OF THE ULAANBAATAR AREA
The triangles denote the location of seismic stations around Ulaanbaatar andcolor of triangles shows time period of operation of those stations. First
installations of the high sensitive seismic network within the area is started
1994. In 2000, this network expanded by ten elements of mini array thatlocated 50 km apart from Ulaanbaatar to the west. Figure 3 shows locationof seismic stations of Ulaanbaatar network.
Brief history of the network- 1957: First installation of seismic station in Ulaanbaatar. (Threecomponents, analogical low gain station SKM-3 with Galvanometricrecords)- Since Nov. 1994: (2 stations with three components/long and short period
station. 4 short period/vertical component)- Since 2000: (1 station with three components long and short period
sensors and 9 short period vertical component seismic array stations)- Since Dec. 2008: (6 broad band + 3 short period three component mobile
stations)

Figure 3: Seismic network around of Ulaanbaatar area
Figure 4 and 5 shows a sample seismograms of seismic eventsoccurred nrear Ulaanbaatar city. All those events are felted well in
Ulaanbaatar basin. Each signal traces are the vertical Z components
recorded permanent and mobile seismic network of Ulaanbaatar.

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Figure 4: Sample record of shows an event on Oct 10, 2008 that was about
45 km from the Ulaanbaatar basin

Figure 5: An seismogram shows an event on May 06, 2008 that was about
70 km West from the city, occurred in Hustai fault.

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4. DEPTH DISTRIBUTION OF SEISMIC ACTIVITY
Depth distribution of seismic activity around Ulaanbaatar city, are shown infigure 6. Most of events are located shallow depth. However, majority of
depth distribution are concentrated between 3 and 13km. According to the 2cross-sections, all events are distrubuted 0-20km in depth. Concentrated
events are corresponds to the Emeelt active structures where 2 volumes arecrossing.

Figure 6: Depth distribution of seismic activity around Ulaanbaatar area.
The colors are shows depth range.

Figure 7: Cross-section of the depth distribution of seismic activity of the
Ulaanbaatar area. Top picture is shows NS and down EW directed crosssection along central activity.

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5. DISCUSSION AND CONCLUSION
Preliminary observation and study on this area was a step which gives us
important information about existence of active structures around
Ulaanbaatar area. As following above information we discovered that
Ulaanbaatar area is high seismic hazard region and one of important
conclusion could be potential seismic source in this area starts to bereactivated. The potential seismic sources (active faults and seismicity) that
could make very heavy damage in Ulaanbaatar area, is existing very shortdistance. Due to their impact on the hazard for Ulaanbaatar, it is absolutely
necessary to upgrade or renew of seismic hazard assessments of Ulaanbaatar
city.
REFERENCES
Baljinnyam, I., A. Bayasgalan, B.A. Borisov, A. Cisternas, M.G.
Dem'yanovich, L. Ganbaatar, V.M. Kochetkov, R.A. Kurushin, P. Molnar,
H. Philip, and Y.Y. Vashchilov (1993), Ruptures of Major Earthquakes andActive Deformation in Mongolia and its Surroundings. Vol. Memoir 181 of
Boulder, Colorado: The Geological Society of America, Inc..
Khilko S.D., R.A. Kurushin, V.M. Kochetkov, L.A. Misharina, V.I.
Melnikova, N.A. Gilyova, S.V. Lastochkin and D. Monhoo, (1985).
Earthquakes and the base of the seismic zoning of Mongolia. Vol. 41 of The
joint Soviet-Mongolian scientific - Reasearch Geological Expedition. 225 p.
Natsag-yum, L., 1. Balzhinnyam, and D. Monkho (1971). Earthquakes
in Mongolia, in Seismic Regionalization of Ulan Bator,, S. V. Medvedev,
Moscow, Nauk, 54-82
Antoine Schlupp, Dugarmaa T, Adiya M., Ankhtsetseg D., Baasanbat
Ts., Battulga B., Batsaikhan Ts., Bayar G., Bayarsaikhan Ch., Demberel S.,
Dugarmaa T., Erdenezul D., Mungunsuren D., Munkhsaikhan A., Munkhuu
D., Narantsetseg R., Odonbaatar Ch., Selenge L., Tsembel B., Ulziibat M.,
Urtnasan Kh., “ Seismic Hazard Assessment of Ulaanbaatar, capital of
MONGOLIA. Seismic microzoning map” , 2006, Report of RCAG, MAS

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Seismic risk analysis for intercity railway
system in Tokyo metropolitan area
Yoshimasa MAEDA1, Hisamichi HATTORI2, Toshiro SHIZUMA3and Hiromichi YOSHIKAWA4
1
Assistant Manager, Civil Technology Dept, Tokyu Construction Co., Ltd, Japanmaeda.yoshimasa@tokyu-cnst.co.jp
2
Chief Manager, Civil Technology Dept, Tokyu Construction Co., Ltd, Japan
3
Chief Manager, Shinozuka Research Institute, Japan
4
Professor, Advanced Research Laboratories, Tokyo City University, Japan
ABSTRACT
When railway structures are damaged by a large earthquake, the train service
will be suspended for a long time. In such situation, passengers will want to know
recovery time for their lines, and the owner will want to estimate how the numberof passenger will recover.
In this paper, the railway system consists of three railway lines is simulated
covering 40km2 in Tokyo metropolitan area, assuming that the Great Kanto
Earthquake occurred and railway viaducts are damaged. Seismic risk analysis iscarried out by calculating recovery time expectancy, passenger recovery curve,
and bottleneck index for the railway system.
Keywords: railway system, seismic risk analysis, recovery time expectancy,
recovery curve, bottleneck index
1. INTRODUCTION
When railway lines are stopped by a large earthquake, passengers will want toknow the information of recovery time for their lines, and the owner has theobligation to explain them. On the other hand, in order to formulate a business
continuity plan (hereafter BCP) 1), the owner will want to estimate how thenumber of passenger will recover.
In this paper, the seismic risk for intercity railway system is estimated, assumingthat the Great Kanto Earthquake2) is occurred and railway viaducts are damaged.
The railway system consists of three railway lines covering 40km2 in Tokyo
metropolitan area. Seismic risk analysis for the railway system is carried out by
calculating recovery time expectancy, passenger recovery curve, and bottleneckindex. On analyzing the damage of railway viaducts, it is considered that groundmotion intensity in attenuation equation and site amplification factor at location
ground.

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2. SIMULATION MODEL
The simulation model is a railway system that consists of three lines connecting
the suburbs and urban area as shown in Figure 1. It consists of radial A line in theinland, radial B line along the sea, and belt C line in the banks of a river. Everyline in the system is a virtual line, the encircled number in Figure 1 shows themain stations made by reinforced concrete viaduct structure. Viaducts in C line
constructed along the river bank on the soft ground, and the other viaducts are on
normal ground.
In this paper, assuming that the Great Kanto Earthquake whose magnitude is 8.0(JMA scale) occurred as the scenario earthquake and railway viaducts aredamaged, seismic system risk are estimated. In addition, the region surrounded bysolid line and dashed lines in the Figure 1 indicates fault plane of the plateboundary for the Great Kanto Earthquake. The system model is intended for one
way route, stations in the suburbs (Excluding No.5, 11, and 13) are origin, stationsin the central Tokyo metropolitan area (No.5, 11, and 13) are destination, where
many companies locate.

Figure 1 Railway system and scenario earthquake
Destination(stations in central city)

Origin（stations in suburbs）
A-1
A-2
A-3
B-1
B-2
B-3

0.117

0.209

0.276

1

2

3

0.206

0.373

6

7

A Line0.474

4 0.318 5

0.501

0.591

12 0.8168

910Influence level =

0.451

11
0.226

B LineMain series : 6
Total series : 30

0.323

C Line13

The number of passengers through each station
The number of total passengers

Figure 2 System model and influence level

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This railway system can be modeled by the ladder system shown in Figure 2, andsix main transport pathways (A1-A3, B1-B3) are shown in it. Considering thepassengers who ride on along the way, six main lines can be divided into the 30
series. The ratio of the passenger’s number in 30 series was added at each station,
it shows by bar chart as an influence level to the entire railway system in Figure 2.
3. EVALUATION METHOD OF PROBABILITY FUNCTION FORRECOVERY TIME
Since this model is intended for one way route, this system can be modeled as
multiple serial systems. Recovery time in serial system, because it has been aimed
at early recovery of facilities, shall be promoted to work on damaged facilities atthe same time, recovery works shall be completed in the shortest time. According
to this rule, the maximum time needed to recover in the system equals to that of
the entire system.
When recovery time to N number of the facilities (hereafter component) shown in
Figure 3 is represented by a random variable T1 ~ Tn, recovery time can be
expressed as Equation (1) under the condition that x is the seismic ground motion
intensity.
要素1 1
Component

要素2 2
Component

T1

T2

要素n n
Component

….

Tn

確率分布
Probability distributions

….
T2

T1
0 Recovery
time 0
復旧期間

Tn

0Figure 3 Recovery time in serial system
1.0
Damage Factorof Component
No Damaged
Damaged

Probability

FTi(t | x)

1.0 - Pi(x) 1 .0- Pi(x)
Pi(x)

1.0

RecoveryTime (Day)

1.0 - Pi(x)

0
30
0.0

0

30

t

Figure 4 Cumulative distribution function of component i
T| x = max(T1 , T2 ," , Tn | x)

(1)

Assuming the independence of the component’s damage, cumulative distributionfunction of the recovery time FT (t | x) in the serial system, is shown as follows.
FT (t | x) = P(T1 ≤ t , T2 ≤ t , ", Tn ≤ t | x )n

FT (t | x) = ∏ FT i (t | x)
i =1

(2)
(3)

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FTi (t | x) = 1.0 − Pfi ( x) , 0 ≤ t < t max(4), t = t max= 1.0

FTi (t | x) represents cumulative distribution function of each component to therecovery time, it can be gotten by probability of damage to the components Pfi(x)and recovery time t shown in Figure 4, and be given by Equation (4). Probabilityof damage Pfi (x) is determined by the Fragility Curve based on structuralreliability3). Furthermore, Figure 4 is an example of two branches that the damage
has occurred or not, if necessary, it can be changed at least three branches
consisting no damage, moderate, and extensive etc.
4. EVALUATION METHOD OF SYSTEM RISK
4.1 Recovery curve
The recovery curve defined as the process to complete recovery, after the originalfunction is reduced or stopped. The horizontal axis represents the time required
for recovery, the vertical axis represents the recovery ratio, when the originalfunction equals to 1.0. Figure 5 shows schematically the recovery curve, and therecovery curve is represented as equation (5)4).
∞R (rL ) = ∫ (1 − FT (t , rk ) )dt , k = 1 ~ L(5)0Complete recovery
recoveryComplete

1.0
1.0
Recoveryratio
Recovery ratio

Function1 (Ratio=0.5)(Ratio=0.5)
Function1
Recovery time
time == D1
D1
RecoveryRecovery ofof function1function1
Recovery

0.5
0.5

Function2 (Ratio=0.5)(Ratio=0.5)
Function2
Recovery time
time == D2
D2
Recovery

D1
D1

00

D2
D2

RTE =
= 0.5D1+0.5D2
0.5D1+0.5D2
RTE

Recovery time
time
RecoveryFigure 5 Recovery curve
Here, FT (t, rk) is the probability function of recovery time about function k, rk is
the recovery ratio, if the original state is defined 1.0.
In addition, RTE (Recovery time expectancy, hereafter RTE) in the Figure 5 are
typical of the recovery time, it can be obtained by multiplying the recovery ratioof the component by the expected value of recovery time as shown in the
Equation (6).
L

RTE = ∑ R (rk ) ⋅ rk
k =1

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4.2 Bottleneck index
In order to understand effectively the bottleneck component on the system which
has many components, bottleneck index (hereafter, B.I.) has been proposed5). B.I.
is gotten by multiplying the influence (importance) level to the entire system byvulnerability (seismic performance), the Equation is as follows.
(7)

Bi = ei ⋅ E (Ti ) , i = 1 ~ nHere, i is component, ei represents the influence level, and E(Ti) is the expectedvalue of recovery time to each component.
5. SIMULATION ANARYSIS
5.1 Vulnerability of viaducts
Three types of viaducts were adopted for analysis, referring to the history ofrailway design standards. TYPE 1 is shear failure type based on past design
standard, TYPE 2 is flexural failure type of which seismic performance iscomparatively middle, and TYPE 3 is flexural one whose seismic performance iscomparatively high based on existing design standard. Damage level of the
viaduct is classified to four states, non damage, minor, moderate, and extensive.
Furthermore the mean value to each damage state is set on by elastic response
acceleration basing on equal energy principle.
The mean value of seismic performance and recovery time to each damage levelis indicated in Tables 1 to 3. In the case the viaduct TYPE 1 is retrofitted, it
Table 1 Vulnerability of viaduct TYPE 1
Damagestate

Peak elastic
response acceleratinαR(gal)Recovery
time
(day)

Response
spectrum ratio
S

Normal ground （G3）

non damage

0

0

1.825

site amplification
factorλ
1.4extensive

472

60

1.825

1.4

Damagestate

Peak elastic
response acceleratinαR(gal)Soft ground (G5）peak bedrock
acceleration
αR/S/λ(gal)0site amplification
factorλ
1.6

peak bedrock
acceleration
αR/S/λ(gal)
0

185

1.6

162

Table 2 Vulnerability of viaduct TYPE 2
Recovery
time
(day)

Response
spectrum ratio
S

Normal ground （G3）site amplification
factorλpeak bedrock
acceleration
αR/S/λ(gal)Soft ground (G5）site amplification
factorλpeak bedrock
acceleration
αR/S/λ(gal)non damage

0

0

1.825

1.4

0

1.6

0

minor

720

3

1.825

1.4

282

1.6

247

moderate

1188

10

1.825

1.4

465

1.6

407

extensive

1800

60

1.825

1.4

705

1.6

616

Table 3 Vulnerability of viaduct TYPE 3 (Post retrofitting TYPE 1)
Damagestate

Peak elastic
response acceleratinαR(gal)Recovery
time
(day)

Response
spectrum ratio
S

Normal ground （G3）site amplification
factorλpeak bedrock
acceleration
αR/S/λ(gal)Soft ground (G5）site amplification
factorλpeak bedrock
acceleration
αR/S/λ(gal)non damage

0

0

1.825

1.4

0

1.6

0

minor

1296

3

1.825

1.4

507

1.6

444

moderate

2088

10

1.825

1.4

817

1.6

715

extensive

3060

60

1.825

1.4

1198

1.6

1048

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assumed that the vulnerability becomes same as TYPE 3.
The mean value of peak bedrock acceleration (hereafter PBA) which is converted
to seismic performance is shown on the right of Tables 1 to 3. This value can bederived by dividing site amplification factor and response spectrum ratio
normalized by the PBA by peak elastic response acceleration. Here, characteristic
periods of three kinds of viaduct are 0.7~0.75 second, response spectrum ofground surface and bedrock surface are referred to Level 1 Earthquake ofreference 6). In the above conditions, response spectrum ratio is given 1.825, site
amplification factor is given 1.4 on normal ground and 1.6 on soft ground. Thus
the mean value converted by PBA is able to collectively manage the seismic
performance of variety facilities that are designed in different ages.
Upon risk analysis, PBA to each site is simulated by attenuation equation ofAnnaka7), a variation (logarithmic standard deviation) of the ground motion
intensity is set to 0.5, and one of vulnerability of structure is set to 0.3.
5.2 Simulation caseThree simulation cases are carried out, Table 4 shows the combinations of thesimulation cases and the viaduct types. Simulation Case 1 is the case before
retrofitting, viaducts on A line are TYPE 2 (seismic performance are middle), andthem on line B are TYPE 1 (seismic performance are small), and the other are
TYPE 3 (seismic performance are big). Simulation Case 2 is the case that viaducts
No.6 ~ 11 whose type is TYPE 1 are completed retrofitting and seismic
performance becomes same as the viaduct TYPE 3. Moreover, simulation Case 3
is the case that all viaducts of TYPE 1 except viaduct No.9 are retrofitted.
Table 4 Simulation case

Stationground(Railway viaduct) classification
1
Sagamiko Normal (G3)2
Yabe
Normal (G3)3 Shinyurigaoka Normal (G3)
4
KomaeSoft (G5)5Shibuya
Normal (G3)
6
Hakkeijima Normal (G3)7
IsokoNormal (G3)8
Yokohama Normal (G3)9Kawasaki Normal (G3)10
Hatanodai
Soft (G5)11
Ebisu
Normal (G3)12ToshidaiSoft (G5)13
OsakiSoft (G5)

Case 1Case 2

Case 3

Type 2Type 2Type 2Type 2Type 2Type 1
Type 1
Type 1
Type 1
Type 1
Type 1
Type 3
Type 3

Type 2Type 2Type 2Type 2Type 2Type 3
Type 3
Type 3
Type 3
Type 3
Type 3
Type 3
Type 3

Type 2Type 2Type 2Type 2Type 2Type 3
Type 3
Type 3
Type 1
Type 3
Type 3
Type 3
Type 3

5.3 Result of simulation
Figure 6 shows the passenger recovery curves of each simulation case. Every
curve has 30 stages equal to the number of combinations of series. Case 1
recovered about 20 percent from 10 days to 20 days, the remaining 80 percent has
recovered in 49 days and 60 days. Since 80% of recovery is delayed, RTE of theentire system has become 47.65 days. In Case 2, recovery time was reduced
significantly by retrofitting, RTE has become 8.44 days. On the other hand, sinceCase 3 is not completely retrofitted and one viaduct has not been retrofitted, RTE
did not significantly improve, it has become 33.16 days.

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Figure 7 shows the expected value of recovery time of each station (viaduct) withbar chart using GIS (Geographic Information Systems). It is obvious that expectedvalue of recovery time can be expressed clearly and visually using the GIS.
Table 5 shows the results of expected value of recovery time from the departure
stations to the destination stations, in case for example departure stations are No.2
and No.8. If the departure station is the same, expected value of recovery time isdifferent depending on the destination stations. Thus, by using this model, it ispossible to explain the recovery time for each pathway, and can meet the needs ofthe passenger.
1.0
0.9
0.8
Recovery ratio

0.7

Case1

0.6
0.5

RTE=47.65

0.4

Case2

0.3

RTE=8.44

0.2

Case3

0.1

RTE=33.16

0.0
0

10

20

30

40

50

60

70

80

Recovery time (day)Figure 6 Comparison of passenger recovery curves

Figure 7 Comparison of expected value of recovery time
Table 5 Expected value of recovery time to destination stations(For example No.2 and No.8 as departure stations)
Simulation Case1
Departure

Destination

5 Shibuya
11 Ebisu
13 Osaki
5 Shibuya
8 Yokohama 11 Ebisu
13 Osaki
2 YabeSimulation Case2
Recoverytime (day)
15.1
52.7
49.9
55.3
55.8
55.3

Departure

Destination

5 Shibuya
11 Ebisu
13 Osaki
5 Shibuya
8 Yokohama 11 Ebisu
13 Osaki

2 YabeSimulation Case3
Recoverytime (day)
15.1
14.7
14.7
11.3
3.1
3.4

Departure

Destination

5 Shibuya
11 Ebisu
13 Osaki
5 Shibuya
8 Yokohama 11 Ebisu
13 Osaki

2 YabeSeismic risk analysis
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Recoverytime (day)
15.1
14.7
14.7
47.4
47.2
47.2

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The results of influence level, vulnerability (recovery time), and B.I. are shown in
Table 6. Focusing on the vulnerability in Case 2, by comparing No.3 on thenormal ground to No.4 on the soft ground, in spite of the far distance from theepicenter, vulnerability of No.4 has become greater. In addition, comparing No.9
to No.10, the same matter can be said. It is considered that the result is affected by
the site amplification. By taking in the site amplification factor, the vulnerabilityof the structures located in wide area is able to evaluate properly.
As mentioned previously, B.I. is represented by multiplication of influence leveland vulnerability. In Case 1, B.I. of B Line are greater overall, the largest
bottleneck has become No.10, because of both large influence and vulnerability.
In Case 2, since TYPE 1 viaducts have been retrofitted, a significant bottleneck is
not observed. The largest bottleneck was No.4, it is obvious that component ofbottleneck was improved by retrofitting. In Case 3, B.I. of No.9 became greater, it
is obvious that one component’s damage impacts the entire system. Figure 8
shows the B.I. by using the GIS. The GIS makes the results of B.I. easier tounderstand.
Table 6 Bottleneck index(1) Case1(Before retrofitting)damege element
10 Hatanodai
9 Kawasaki
8 Yokohama
11 Ebisu
7 Isoko
6 Hakkeijima
4 Komae3 Shinyurigaoka
2 Yabe5 Shibuya
1 Sagamiko
12 Toshidai
13 Osakiinfluence vulnerability
0.816
49.66
0.591
47.22
0.501
49.51
0.451
45.01
0.373
50.78
0.206
51.56
0.474
13.16
0.276
11.18
0.209
13.46
0.323
8.61
0.117
16.54
0.318
3.30
0.226
2.85

B.I.
40.53
27.89
24.82
20.31
18.96
10.63
6.23
3.08
2.81
2.78
1.93
1.05
0.64

(2) Case2 (After retrofitting)damege element
4 Komae3 Shinyurigaoka
2 Yabe5 Shibuya
10 Hatanodai
1 Sagamiko
8 Yokohama
9 Kawasaki
7 Isoko
12 Toshidai
11 Ebisu
6 Hakkeijima
13 Osakiinfluence vulnerability
0.474
13.16
0.276
11.18
0.209
13.46
0.323
8.61
0.816
3.02
0.117
16.54
0.501
2.96
0.591
2.30
0.373
3.44
0.318
3.30
0.451
1.83
0.206
3.78
0.226
2.85

B.I.

6.23
3.08
2.81
2.78
2.46
1.93
1.49
1.36
1.28
1.05
0.83
0.78
0.64

(3) Case3 (Ongoing retrofitting)damege element
9 Kawasaki
4 Komae3 Shinyurigaoka
2 Yabe5 Shibuya
10 Hatanodai
1 Sagamiko
8 Yokohama
7 Isoko
12 Toshidai
11 Ebisu
6 Hakkeijima
13 Osaki350

influence vulnerability
0.591
47.22
0.474
13.16
0.276
11.18
0.209
13.46
0.323
8.61
0.816
3.02
0.117
16.54
0.501
2.96
0.373
3.44
0.318
3.30
0.451
1.83
0.206
3.78
0.226
2.85

B.I.
27.89
6.23
3.08
2.81
2.78
2.46
1.93
1.49
1.28
1.05
0.83
0.78
0.64

Figure 8 Comparison of Bottleneck index

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6. CONCLUTION
This paper deals with seismic risk analysis for intercity railway system covering
40km2 in Tokyo metropolitan area. The particular features in this paper are
summarized as follows.
・ By considering the site amplification factor and attenuation equation to theground motion intensity, the vulnerability of facilities can be evaluatedproperly.
・ Three cases of simulation were carried out, recovery curve, recovery time
expectancy and bottleneck index were evaluated quantitatively.
・ Expected value of recovery time to the destination stations which passengers
will want to know is able to simulate by the proposed method.
・ Due to simulate the bottleneck of the entire system, it was obvious that therecovery time expectancy of the entire system may be delayed because of one
component’s damage.
・ By utilizing the GIS, the simulation results can be shown clearly and visually.
・ The seismic risk analysis is considered to be effective for seismic
management planning and formulation of BCP.
REFERENCES
1) Cabinet Office, 2007. Business Continuity central government guidelines firstedition2) Ryosuke Sato, 1989. the Japanese earthquake fault parameters handbook,
Kajima Publishing3) Takaaki Nakamura, 2007. Evaluation of earthquake probability of loss
function for buildings considering the correlation, Proceedings of the Instituteof Structural and Construction, No. 623, pp.49-56.
4) Toshiro Shizuma, 2009. Theoretical consideration of recovery curves andapplication to BCP, Business continuity Symposium on Seismic Risk
Management Part 1 -Current Status and Issues SRM & BCP - Proceedings,
pp.231-236.
5) Takaaki Nakamura, 2009. Studies on the function securement of the building
with the aim to contribute to the BCP, Journal of the Society for General
Construction, construction related to urban safety and security of the frontier
No.7, pp.87-92.
6) Railway Technical Research Institute, 1999. Railway structure design
standards, etc. (Seismic Design).
7) Tadashi Annaka, Fumio Yamazaki, Fuyuki Katahira, 1997. Proposal of theestimated maximum earthquake and response spectrum for strong-motion
seismograph records JMA 87-type, Proceedings of the 24th Research
Conference on Earthquake Engineering, pp.161-164.

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SSI effect on seismic responseof high-rise building in Jakarta, Indonesia
Kullachai TANTAYOPIN1, James FRANK1, Seong-Won Lee2and Kyung-Ho PARK1
1
School of Engineering & Technology, Asian Institute of Technology,
P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
E-mail: kullachai@gmail.com
2
Korea Institute of Construction Technology, Daehwa-dong 283,
Goyangdae-ro, Ilsanseo-gu, Goyang-si, Gyeonggi-do, 411-712, Korea
ABSTRACT
High-rise buildings are conventionally analyzed under fixed baseassumption without considering soil-structure interaction (SSI) because it
provides a conservative design. However, recent studies show thatconventional fixed base analysis may underestimate the seismic response
and lead to unsafe design. This study deals with the effects of SSI for atypical high-rise building in Jakarta, Indonesia. Nonlinear time history
analysis is performed and the inclusion of seismic SSI is modeled throughdynamic beam on nonlinear Winkler foundation method. The results showthat the peak story shear is reduced when considering SSI, while SSI
analysis gives a larger interstory drift ratio than that of the non-SSI analysis.
Especially the results show large different of the interstory drift ratio at thefirst floor and basement level, that might lead to be misconception in thedesign. Therefore, the effects of SSI for the typical example building are notalways beneficial and may be detrimental in giving unsafe results in the
deformation response.
Keywords: soil-structure interaction, high-rise building, nonlinear seismic
response
1. INTRODUCTION
High-rise buildings are conventionally analyzed under fixed baseassumption without considering soil-structure interaction (SSI) because it
provides a conservative design. However, recent studies show thatconventional fixed base analysis may underestimate the seismic response
and this may lead to unsafe design.
Mylonakis et al. (2000) investigated the role of SSI on the collapse of 18
piers of the Hanshin expressway during Kobe earthquake and found that theeffects of SSI might cause collapse of Hanshin Expressway. Jeremic et al.
(2004) studied the influence of SSI on seismic response of an elevatedhighway bridge (the I-880 viaduct) and found that the SSI can have bothbeneficial and detrimental effects. Yue and Wang (2009) studied the3531

October 2011, Chiang
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Thailand
Chiangmai,

influences of SSI on the high-rise frame shear wall structure in Fujian
province of China. The results show that effects of SSI amplified dynamic
response of structure in some stories which indicated that SSI cannot be
neglected in analysis.
The previous studies indicate that fixed base analysis on seismic
response can lead to unsafe design and the SSI effects shall be investigatedfor each different site. This study discusses the SSI effects on the seismic
response for a typical high-rise building in Jakarta, Indonesia. As Indonesia
has been well known with its high seismic activity (Irsyam et al., 2008), theseismic response of the high-rise building in Jakarta is important to beanalyzed.

Figure 1: Transversal building cross section and layout of building plan

2. STUDY BUILDING
The selected typical building consists of 18-story floors and 4-levelbasements with central concrete core wall system. The basements are
essentially larger in floor plate area comparing to the tower foot print area asshown in Figure 1. The gravity framing system at the tower is reinforced
concrete post-tensioned beam with reinforced concrete slab. The gravity
framing system at the ground floor and basement floor is reinforced
concrete flat-slab with drop panel at the slab-column connection. The
structure configurations are briefly described in Table 1.
Soil investigation and laboratory soil test were conducted to identify
the subsoil condition at the site. The subsoil at the site can be divided into 3
major zones. The upper zone is occupied with recent deposits which are low
in strength. The old deposits at the middle zone are competent as a bearing
layer. The older deposits at the lower zone are also competent but less stiff
than the middle zone. The generalized soil profile is presented in Figure 2
including shear wave velocity (Vs) obtained from field downhole seismic
test. With the presence of relatively deep basements (4-level), the building is2354

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ICUS Report 56

originallyoriginallydesigneddesigned
withwithraftraftfoundation
foundation
which
which
is ableis ableto sitto directly
sit directlyon theon themiddlemiddlezone.
zone.
In orderIn orderto study
to study
the theeffects
effectsof SSIof SSIfor fordeep
deep
foundation,foundation,
the thebuildingbuildingis alsois alsodesigneddesigned
using
using
pilepile
foundation.
foundation.
Bored
Bored
pilepile
withwiththe thediameterdiameterof 800mm
of 800mm
andandthe thelengthlengthof 24mof 24mis utilized
is utilized
to support
to support
the thebuilding.
building.
TheThe2D 2Ddynamic
dynamic
analysisanalysisis performed
is performedin transversal
in transversal
buildingbuilding
cross
cross
section.
section.
Table
Table
1: Structure
1: Structure
model
model
configuration
configuration
VerticalVerticalelement
element

Level
Level

CoreCorewallwallthicknessthickness
Outer
Outer Inner
Inner

Horizontal
Horizontal
element
element

ColumnColumnsize size

fc' fc'm2 m2

MPaMPaBeam
Beam flat-slab
flat-slab fc' fc'
sectionsection thickness
thickness

m m

m m

B4 B4

0.450.45

0.250.25 0.90x0.90
0.90x0.90 50 50

-

-

MP MP
a a
0.250
0.250 32 32

B2-B3
B2-B3

0.450.45

0.250.25 0.90x0.90
0.90x0.90 50 50

-

-

0.175
0.175 32 32

B1 B10.450.45

0.250.25 0.90x0.90
0.90x0.90 50 50

-

-

0.200
0.200 32 32

L1 L1

0.450.45

0.250.25 0.90x0.90
0.90x0.90 50 50 0.45x0.65
0.45x0.65

0.200
0.200 32 32

L2 L20.450.45

0.250.25 0.90x0.90
0.90x0.90 50 50 0.45x0.65
0.45x0.65

0.150
0.150 32 32

L3-L11
L3-L110.450.45

0.250.25 0.90x0.90
0.90x0.90 40 40 0.45x0.65
0.45x0.65

0.150
0.150 32 32

L12-L16
L12-L160.250.25

0.250.25 0.80x0.80
0.80x0.80 32 32 0.45x0.65
0.45x0.65

0.150
0.150 32 32

L17-L18
L17-L180.250.25

0.250.25 0.75x0.75
0.75x0.75 32 32 0.45x0.65
0.45x0.65

0.150
0.150 32 32

m2 m2

m m

S-WaveS-WaveVelocity
Velocity(Vs) (Vs)Max Shear
Max Shear
Modulus
Modulus(Gmax)(Gmax)(m/s) (m/s)(MPa)(MPa)02000 400
200 600
400 800600

800
02000 400
200 600
400 800
6001000
8001200
10001400
1200 1400= 17 kN/m3Cu = 60
FILL FILL γ = 17 γkN/m3
CukPa= 60 kPa
ZONEZONE1
1= 17 kN/m3Cu = 60
CLAYCLAY
11γ = 17 γkN/m3
CukPa= 60 kPaγ =16.5γ =CLAYCLAY
1b 1b
Cu = 150
Cu =kPa
150 kPa
kN/m3
16.5 kN/m3= 20 kN/m3φ ' = 38
= 38 Deg
SANDSAND22γ = 20 γkN/m3
φ 'Deg= 18 kN/m3Cu = 300
CLAYCLAY22γ = 18 γkN/m3
Cu =kPa
300 kPa

ZONEZONE2
2= 20 kN/m3φ ' = 38
= 38 Deg
SANDSAND22γ = 20 γkN/m3
φ 'Deg= 18 kN/m3Cu = 300
CLAYCLAY22γ = 18 γkN/m3
Cu =kPa
300 kPa= 20 kN/m3φ ' = 38
= 38 Deg
SANDSAND22γ = 20 γkN/m3
φ 'Degγ = 17 γkN/m3= 17 kN/m3Cu = 150
CLAYCLAY
3a
3a
Cu =kPa
150 kPa

ZONEZONE3
3= 18 kN/m3Cu = 250
CLAYCLAY33γ = 18 γkN/m3
Cu =kPa
250 kPa

FigureFigure2: Generalized
2: Generalizedsoilsoilprofileprofile3. NONLINEAR
3. NONLINEAR
MODEL
MODEL
TheThebuildingbuilding
is expected
is expected
to exhibit
to exhibit
the thenonlinear
nonlinear
behavior
behavior
under
under
severesevereearthquake
earthquake
level.
level.
In orderIn orderto identify
to identify
the theactualactualresponse
responseof theof thebuilding,building,
the theSSI SSI
Effecton seismic
responseof high-risebuilding
in Jakarta,
Indonesia
SSI
Effecton seismic
seismic
responseof high-risehigh-risebuildinginIndonesia
effecton
responseofbuilding
in Jakarta,
Jakarta,Indonesia

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Mai,Thailand
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Chiangmai,

behavior of the SSI and structure elements need to be described using
nonlinear model.
3.1 SSI Model
The nonlinear SSI is modeled based on the dynamic beam on
nonlinear Winkler foundation (BNWF) method suggested by Boulanger etal. (1999) using the lateral load-displacement (p-y) element of the pile. The
nonlinear (p-y) element conceptually consists of elastic, plastic and gap
component in series. The gap and plastic components represent the nearfield component while the elastic component represents the far-fieldcomponent. Radiation damping is modeled using a dashpot in parallel withelastic component.
3.1.1 Pile Foundation
Boulanger (2000) originally implemented the nonlinear SSI model
into OpenSees computer program platform for pile foundation case using
three types of nonlinear SSI element: nonlinear (p-y); nonlinear (q-z);
nonlinear (t-z) to represent the load-displacement behavior of lateral load
capacity; bearing at pile tip; skin friction of the pile, respectively. In thisstudy, only the PySimple1Gen command is used to generate nonlinear (p-y)
elements along the pile in OpenSees developed by Brandenberg (2004). The
influence of two other nonlinear elements is insignificant to the response of
the pile.
3.1.2 Raft Foundation
Raychowdhury and Hutchinson (2008) modified the loaddisplacement relationship of the pile foundation to be applied for shallow
foundation case. The nonlinear behavior of SSI for raft foundation is
described using three nonlinear SSI elements: nonlinear (p-y); nonlinear (qz); nonlinear (t-z) which represent the load-displacement behavior of lateralpassive earth pressure at footing side; bearing capacity of footing; friction
resistance along base of the footing, respectively. The nonlinear (p-y), (q-z),
and (t-z) for shallow foundation case are implemented in OpenSees as
PySimple2, QzSimple2, and TzSimple2 material models, respectively.
3.1.3 Structural Element
The nonlinear behavior of the structural element is described using
lumped plasticity model which consists of elastic element and concentrated
plastic hinge at each end. Concentrated plastic hinge is modeled using
rotational spring where the monotonic backbone curve is calibrated from theexperimental reinforced concrete test. The monotonic backbone curve of theconcentrated plastic hinge is described by five parameters: yield moment(My), yield chord rotation (qy), hardening stiffness (Ks), capping rotation(qcap), and post-capping stiffness (Kc). These five parameters are
determined based on the modeling parameter by Haselton et al. (2008) asrecommended in PEER/ATC-72-1 (2010). The monotonic backbone curveof the concentrated plastic hinge is defined using Clough material model in
OpenSees platform.

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Table 2: Selected earthquake ground motions
No.

Earthquake EventYear

Denotation

Mw

PGA
(g)

1

Cape Mendocino

1992

CM-EUR-090

7.0

0.18

2

Hector Mine

1999

HM-H-000

7.1

0.27

3

Imperial Valley

1979

IMP-CH-012

6.5

0.27

4

Loma Prieta

1989

LP-HSP-000

6.9

0.37

5

Superstition Hills

1987

SH-PR-360

6.5

0.30

6

Mentawai Island

2007

MEN-ISL-HNN

7.9

0.13

7

South Sumatra

2007

SO-SUM-HNN

8.4

0.04

4. SEISMIC INPUT MOTIONSThe seismic input motions for the building are specified based onIndonesian Seismic Code SNI 03-1726-2003. The code determines theseismic design load based on design basis earthquake (DBE) corresponding
to the uniform seismic hazard level of 10% probability of exceedance in 50
years. According to the code, Jakarta city is located in seismic Zone 4 withthe peak base rock acceleration of 0.20g. Based on the subsoil condition at
the site, the site can be categorized as medium soil site. The nonlinear time
history analysis is required to be performed in maximum considered
earthquake (MCE) level which is assumed to be 1.5 times the DBE level.
The design response spectrum for MCE level is therefore defined foranalysis.

Figure 4: Response spectra of scaled ground motions
Seven earthquake records are used in this analysis to satisfy seismic
design code requirement (UBC 1997, EURO8) for average response. Fivestrong earthquake records from worldwide database and two earthquake
records from inside Indonesia area are selected to cover the wide range of

SSI Effecton seismic
seismic response
response ofof high-risehigh-rise building
SSI
effect onbuilding inin Jakarta,
Jakarta, Indonesia
Indonesia

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October
2011,2011,
Chiang
Mai,Thailand
Thailand
October
Chiangmai,
Chiangmai,
Thailandearthquake
earthquake
variation
variation
as shown
as shown
in Tablein Table
2. The2. ground
The groundmotions
motions
are scaled
are scaled
to to
match
match
with with
the MCEthe MCE
response
response
spectrum
spectrumby using
by using
spectral
spectralmatching
matching
softwaresoftwareRspMatch2005
RspMatch2005(Hancock(Hancock
et al.,et2006)
al., 2006)
as shown
as shown
in Figurein Figure
4. Free4. Freefield fieldsite responsesite response
analysisanalysisis thenis thenperformed
performed
usingusing
SHAKE91
SHAKE91
softwaresoftware(Idriss(Idriss
and andSun, Sun,
1991)1991)
to provide
to provide
the seismic
the seismic
inputinput
motions
motionsalongalong
the thedifferent
different
depthsdepthsconsidered.
considered.
5. ANALYSIS
5. ANALYSISRESULTSRESULTS
In orderIn orderto identify
to identify
the effects
the effectsof SSIof on
SSIseismic
on seismic
response
responseof theofbuildings,
the buildings,
the nonlinear
the nonlinear
time time
historyhistory
analysisanalysisis performed
is performed
for three
for threefoundation
foundation
cases:cases:
fixedfixed(Non-SSI),(Non-SSI),
raft (SSI),
raft (SSI),
and pileand (SSI)
pile (SSI)
foundation
foundation
casescases
and theandanalysis
the analysis
modelsmodelsfor three
for threefoundation
foundation
casescases
are shownare shownin Figurein Figure
5. 5.

a) Fixeda) Fixed(Non-SSI)(Non-SSI)b) Raftb)(SSI)
Raft (SSI)c) pilec)(SSI)
pile (SSI)

FigureFigure5: Fixed,
5: Fixed,
raft andraft pileand foundation
pile foundation
modelsmodelsThe nonlinear
The nonlinear
time time
historyhistory
analysisanalysisis performed
is performed
to obtain
to obtain
the seismic
the seismic
response
responseof theof building.
the building.
The Theseismic
seismic
responses
responsesof theof building
the building
are aredetermined
determinedin termin termof forceof force
and deformationand deformation
responses.
responses.
The force
The force
response
response
is describedis describedas shearas shearforceforce
whilewhile
the deformation
the deformation
response
response
is describedis described
as asinterstory
interstory
drift drift
ratio.ratio.
5.1 Shear
5.1 Shear
Force
Force
Response
Response
The Theaverageaverage
response
response
profilesprofilesof shearof shearforceforce
fromfrom
the thesevensevenearthquake
earthquake
groundgroundmotions
motions
are summarized
are summarized
in Figurein Figure
6. Non-SSI
6. Non-SSI
analysisanalysis
shows
shows
the maximum
the maximum
response
responseof shearof shearforceforce
with withthe large
the large
reduction
reductionat theat thefirst floor.
first floor.
For SSIFor analysis,
SSI analysis,
pile casepile case
shows
shows
lowerlower
shearshear
forceforce
response
responsethan thanraft caseraft case
excepting
exceptingat theat bottom
the bottom
basement
basement
which
which
has high
has high
restrain
restrainof pileof pilefoundation.
foundation.

6 6
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Fixed
Fixed
Case
Case

16 16

PilePile
Case
Case
RaftRaft
Case
Case

STORY LEVELSTORY LEVEL

11 11

6 6

1 1

-4 -4
0.00E+00
0.00E+00

5.00E+06
5.00E+06

1.00E+07
1.00E+07

1.50E+07
1.50E+07

2.00E+07
2.00E+07

Shear
Shear
Response
Response(N) (N)

FigureFigure6: 6:
Average
Average
response
response
profileprofileof shearof shear
force
force

16 16

Fixed
Fixed
Case
Case

STORY LEVELSTORY LEVEL

PilePile
Case
Case
11 11

RaftRaft
Case
Case

6 6

1 1

-4 -4
0 0

0.1 0.1

0.2 0.2

0.3 0.3

0.4 0.4

0.5 0.5

0.6 0.6

0.7 0.7

Average
Average
InterStory
InterStory
Drift
Drift
(%)(%)

FigureFigure7: 7:
Average
Average
response
response
profileprofileof interstory
of interstory
drift
drift
ratio
ratio
5.25.2
Deformation
Deformation
Response
Response
TheTheaverageaverage
response
response
profilesprofilesof ofthetheinterstory
interstory
drift
drift
ratio
ratio
from
from
thetheseven
seven
earthquake
earthquake
groundgroundmotions
motions
arearesummarizedsummarized
in inFigureFigure
7. 7.
TheTheSSISSI
analysisanalysis
forforpilepile
andandraftraftfoundations
foundations
show
show
similarsimilarpatternpatternof ofinterstory
interstory
drift
drift
ratio,
ratio,
while
while
thethelarge
large
valuesvaluesof ofinterstory
interstory
drift
drift
ratio
ratio
areare
found
found
at at
thethefirst
first
floor.
floor.
TheThenon-SSI
non-SSI
analysisanalysis
shows
shows
very
very
small
small
results
results
at basement
at basement
level
level
andandfirst
first
floor.
floor.
SSISSI
Effecton onseismic
responseof high-risebuilding
in Jakarta,
Indonesia
SSI
Effectonseismic
responseof high-risehigh-risebuildinginIndonesia
effectseismic
responseofbuilding
in Jakarta,
Jakarta,Indonesia

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6. CONCLUSION
The effects of SSI have been considered for a typical high-rise building in
Jakarta, Indonesia. The results show that the peak story shear is reduced
when considering SSI, while the SSI analysis gives larger interstory drift
ratio than that of the non-SSI analysis. Especially the results show large
different of the interstory drift ratio at the first floor and basement level, thatmight lead to be misconception in the design. Therefore, the effects of SSI
for the typical example building are not always beneficial and may be
detrimental in giving unsafe results in the deformation response.
REFERENCES
Boulanger, R. W., Curras, C. J., Kutter, B. L., Wilson, D. W., andAbghari, A., 1999. Seismic soil-pile-structure interaction experiments andanalyses. Journal of Geotechnical and Geoenvironmental Engineering, Vol.
125, No. 9, pp.750-759.
Boulanger, R. W., 2000. The PySimple1, QzSimple1, and TzSimple
material documentation. Document for the OpenSees platform.
Branderberg, S. J., 2004. PySimple1Gen OpenSees command.
Document for OpenSees platform.
FEMA, 2000. Prestandard and commentary for the seismic
rehabilitation of buildings. Report No. FEMA–356, Federal Emergency
Management Agency.
Hancock, J., Lamprey, J. W., Abrahamson, N. A., Bommer, J. J.,
Markatis, A., McCoy, E., and Mendis, R., 2006. An improved method ofmatching response spectra of recorde earthquake ground motion using
wavelets. Journal of Earthquake Engineering, Vol. 10, Special Issue 1, pp.
67-89.
Haselton, C. B., Liel, A. B., Taylor Lange, S., and Deierlein, G. G.,
2008. Beam-column element model calibrated for predicting flexural
response leading to global collapse of RC frame buildings. PEER Report
2007/03, Pacific Earthquake Engineering Research Center, University ofCalifornia, Berkeley, California.
Idriss, I. M., and Sun, J., 1991. User's Manual for SHAKE91. Center
for Geotechnical Modeling, Department of Civil and Environmental
Engineering, University of California, Davis, CA.
Irsyam, M., Dangkua, D. T., Hendriyawan, Hoedajanto, D., Hutapea,
B. M., Kertapati, E. K., Boen, T., and Petersen, M. D., 2008. Proposed
seismic hazard maps of Sumatra and Java Island and microzonation study ofJakarta city, Indonesia. Journal of Earth System Science, Vol. 117, pp.865878.
Jeremic, B., Kunnath, S., and Xiong, F., 2004. Influence of soilfoundation-structure interaction on seismic response of the I-880 viaduct.
Journal of Engineering Structure, Vol.26, Issue 3, pp.391-402.
Mylonakis, G., Gazetas, G., Nikolaou, S., and Michaelides, O., 2000b.
The role of soil on the collapse of 18 piers of the hanshin expressway in the
Kobe earthquake. Proceedings of 12th World Conference on Earthquake
Engineering, New Zealand, Paper No. 1074.

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PEER, 2007. PEER Column Database. Pacific Earthquake
Engineering Research Center, University of California, Berkeley, California.
PEER/ATC-72-1, 2010. Modeling and acceptance criteria for seimic
design and analysis of tall buildings. Applied Technology Council,
Redwood City, California.
Raychowdhury, P., and Hutchinson, T., 2008. Nonlinear material
models for Winkler-based shallow foundation response evaluation.
Proceedings of GeoCongress 2008, New Orleans, Louisiana, March,
pp.686-693.
SNI, 2003. Indonesian Seismic Code for Buildings. SNI 03-17462003, Standard National Indonesia, Department of Public Work.
Yue, M., and Wang, Y., 2009. Soil-structure interaction of high-risebuilding resting on soft soil. Electronic Journal of GeotechnicalEngineering, Vol.3, Bund. D,pp.1-20

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seismic response
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SSI
effect onbuilding inin Jakarta,
Jakarta, Indonesia
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362

New Technologies for Urban Safety of Mega Cities in Asia

A fundamental study
on social vulnerability for public safety
in China
Nan ZHANG1 and Hong HUANG2
Institute of Public Safety Research (IPSR),
Tsinghua University, Beijing, China
2
Professor, IPSR Tsinghua University, Beijing, China
hhong@tsinghua.edu.cn
1

ABSTRACT
It is greatly significant to analyze social vulnerability for taking measures ofdisaster prevention and emergency response for disaster relief. In this paper,taking Beijing as an example, the social vulnerability analysis index system
was studied and an improved AHP (Analytic Hierarchy Process) method
was developed. The social vulnerability evaluation index system including
27 influencing factors was established according to the data of social
economy and demography of Beijing. Beijing is divided into 333 areas indetail according to the town and district distributions. The weight of eachfactor was evaluated through the improved AHP process which obviously
decreases no-passing ratio of inconsistency of experts’ questionnaire. At
last, the following five kinds of distribution maps of Beijing: Social
vulnerability, population vulnerability, career vulnerability, economy
vulnerability and infrastructure vulnerability were obtained. The maps
directly express the amount of different kind of vulnerability and thecharacteristic of distribution. Through the sensitivity analysis, the sensitive
factors of each area were listed in the order of importance. The process andresults are helpful for reducing social vulnerability and improving thecapacity of public safety insurance.
Keywords: public safety, social vulnerability, analytic hierarchy process,parametric sensitivity analysis, Beijing
1. INTRODUCTION
All people put their attention on nature disasters because of the devastating
destruction of 9.0-magnitude earthquake in Japan several months ago. If thisdisaster occurred in Beijing, what result it will be?
8.0 level earthquake occurred in Wenchuan caused 69,226 death,
17,923 missing, and direct economy loss was 8,451 hundred million RMB.
The hurricane Katrina in USA in 2005 led to 973 people died and 400thousand people unemployed. The 9.0 level earthquake in Japan in 2011 led
to 15,534 people died and 7,092 people missed. Researchers recognize

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Chiangmai,

gradually that the vulnerability of disaster’s acceptor is an important reasonof disaster occurring and loss difference for different areas. Analyzing thevulnerability of disaster’s acceptor to provide the methods to reduce
vulnerability is an effective measure of raising social disaster prevention
ability and reducing emergency disaster’s loss. It will be seen from this thatthe research of vulnerability is very important in public safety
In recent years, there are some researches on social vulnerability.
Cutter et al. (2003) established the Social Vulnerability Index (SoVI) to
examine the spatial patterns of social vulnerability to natural hazards at thecounty level in the United States. Christopher (2008) incorporated social
vulnerability into numerical hurricane impact modeling to improve loss
prediction; Jose (2010) constructed an index of social vulnerability tonatural and technological hazards and to social risks in the Centre Region of
Portugal, for all the municipalities of the region. The Portuguese center was
divided into 78 areas. In China, the relevant research is little. As the capitalof China, the research of Beijing’s vulnerability should be given more
attention. This research combines with the characteristic of Beijing toresearch the vulnerability of 333 areas of Beijing.
To analyze the vulnerability of all areas and to do relevant
assessments focusing on Beijing’s characteristic will contribute toimplement responding action based on vulnerability situation of each areas
and to act according to circumstances. When disaster is coming, we canmake the emergency plan to rescue as soon as possible.
2. SOCIAL VULNERABILITY ANALYSIS
2.1 Area’s Separation of Beijing
Because the newest 2010 census information will be published in2012, the majority of these data published in 2000 was used in this study.
Beijing has 18 districts which including 16808 km2 and 13,569,194
population. In this study, Beijing is divided into 333 areas according to thetown and district distributions.
As a modern metropolis, Beijing has normal male-female ratio andage distribution. But the vulnerability of Beijing is increasing because ofnumerous transient population and migrant workers. Especially in urban
areas, there is a big density of population, serious traffic jam and many
narrow roads which are built before 1949 bring some negative influence invulnerability. In rural areas, worse infrastructure, inconvenient traffic andhigh percentage of illiterate and ethnic minorities population also increase
the vulnerability.
2.2 The brief instruction and distribution of influencing factor
In this study, social vulnerability divided into 4 primary indices:
population vulnerability, career vulnerability, economy vulnerability and2364

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ICUS Report 56

infrastructure vulnerability. These four indices contain 27 secondary indices(Barry et al., 2001; Susan et al., 2003). The details are shown in Fig.1:

Figure 1: Indices metrics
For the “percent of old houses” (usage period over 40 years), the dataof 18 districts of Beijing is used because of the limitation of data source.
The data of smaller areas in the districts is regarded as the same with the
districts.
3. METHOD
3.1 Data processing
The majority of these 27 influencing factors are from census
information of Beijing, 2000 and census information of 18 districts, 2000,
respectively. The number of subway stations and fire stations per square
kilometer is acquired from metro route map of Beijing, 2010 and firesquadron several months ago respectively (Because these two factors havegreat changing in recent years, all data come from the information of 2010.)
SPSS is used to process the data in Z-score standardization in thisstudy. Z-score standardization is a standard deviation standardization andthe processed data conforms normal distribution. The invert function is:

A fundamental
fundamental study
A
study onon socialsocial vulnerability
vulnerability forforpublic
publicsafety
safetyininChina
China

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October 2011, Chiang
Mai,Thailand
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Chiangmai,

x * =

x − μ

σ
μ: the average of all sampled data
σ: the standard deviation of all sampled data
All data can be standardized according to this method.

(1)

3.2 Weight calculation
This study adopt AHP methods of subjective weighting methods(Wang et al., 2003) to calculate weight because there are many correlative
spatial characteristics with each influencing factors which need to subjective
judgement (Xueqiang Shan, 2010). AHP method has 4 steps:① To analyze the relationship of each influencing factor and to build
level structural model.
② To compare factors in the same level and to construct comparison
matrix.
③ To calculate relative weight and to use coincidence indicator to
make consistency check.
④ To calculate the weight of bottom influencing factor and makecombined consistency check to general indices according toformulas.
(1) To build level structural model
Objective(top) level: social vulnerability
Primary indices level: population vulnerability, career vulnerability,
economic vulnerability and infrastructure vulnerability.
Secondary indices level: 27 influencing factors(2) To construct judgement matrix
In AHP method, scale is very important, and it can reflect the experts’
evaluation to different factors. The following scale meaning table (Table 1)
is suitable according to predecessor’s experiment. Each factor can becompared using this table.
scale
1
3
5
7
9
2,4,6,8,
reciprocal

Table 1: Scale meaning table

Meaning
Two factors have the same importanceOne factor is a little important than other one
One factor is evident important than other one
One factor is intensive important than other one
One factor is extreme important than other one
The average of above adjacent value
If the value of factor i compare to factor j is aij, the value offactor j compare to factor i is aji=1/aij

The shortcoming of this method is that expert’s discretion easily goes
wrong (The original judgement is different from later one.) when there aremany indices. To consider this problem, there are two principles:① Don’t put 7-9 indices on one indices level otherwise expert easily
makes inaccurate judgement.
② The different of indices classification shouldn’t be too large, that is,
every indices must be comparable.

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ICUS Report 56(3) Consistency check
Level Sorting and consistency checking of result are very importantwhen calculating weight. Level sorting is, according to judgement matrix，
to calculate the factor's weight of importance sequence which is related toits own level against to factors from upper level. Calculating the consistentindex CI is the first step when doing consistency check.
λ −nCI = max(2)
n −1

λmax :the max characteristic root of judgement matrix. n:the degree of thematrixSecond, to look up average random consistency index in Table 2.
n
R.I.

1
0

Table 2 Average random consistency index R.I.
2
0

3
0.58

4
0.90

5
1.12

6
1.24

7
1.32

8
1.41

9
1.45

Finally, to calculate the consistency ratio CR:
CI
CR =
(3)
RI
Generally, when consistency ratio CR<0.1, the inconsistent degree isin an acceptable range, which have gotten satisfied consistency and passed
the test of consistency. Otherwise, we need to reconstruct compared matrix.
The normalized characteristic vector can be treated as weight vector toadjust aij. The principle of weight calculating is shown below:
Given the matrix as A, the A is positive reciprocal matrix. First, weshouldn calculating the product of per line and per column of A
Aij ,i=1,2,3…n). Second, to calculate the n-th root of m ( w i = n mi ).
( mi = Πi =1Finally, to take normalized processing to vector w.i .

wi =

wi
n

∑w
j =1

(4)

w i = n minm i = Π Aij
i =1

j

wi: the weight of influencing factor.

(4) The particularity of this research
In this study, there are 84 judgements in the judgement table due tonumerous influencing factors. The discretion of the people is influenced bynumerous judgements. Considering the problem above, we change themethods in some point from judgement comparison to expert’s direct
marking. The specific method is that experts mark the influencing factors
between 1 and 9 (1: the most unimportant factor; 9: the most importantfactor). Using this method, we can get the result through 35 judgements andthe workload is two fifths compared with original method. The experts cankeep awake to improve the efficiency and validity through this improved
A fundamental
fundamental study
A
study onon socialsocial vulnerability
vulnerability forforpublic
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safetyininChina
China

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October
2011,
Chiang
Mai,Thailand
Thailand
October
2011,
Chiangmai,
Chiangmai,
Thailandmethodmethod
which
which
turns
turns
qualitative
qualitative
comparison
comparison
to quantitative
to quantitative
comparison.
comparison.
ThroughThroughthe themarking,
marking,
the theimportanceimportancecomparison
comparisonof everyof every
influencing
influencing
factorfactoris easy
is easy
to calculate.
to calculate.
In thisIn thisstudy,
study,
there
there
are are21 21
expertsexperts
includingincluding
4 top
4 top
expertsexperts
andand17 17
normalnormalexpertsexperts
participate
participate
the themarking.
marking.
We We
set theset theweightweightof 4oftop
4 top
expertsexperts
3 3
times
times
to theto theweightweightof 17
of normal
17 normal
expertsexpertsin thein theweightweightcalculating.
calculating.
TheThefinalfinal
statisticalstatisticalcomputingcomputingwillwillbe obtained
be obtainedby comparing
by comparing
the theexperts’
experts’
judgement
judgement
withwith
experts’
experts’marking.
marking.
ThisThis
methodmethodreduces
reduces
the theconsistency
consistency
demanddemandbased
based
on theon theexpertexpertseriousseriousmarking.
marking.
(5) (5)TheTheweightweightcalculating
calculating
andandintegrated
integrated
consistency
consistency
check
check
TheThecorresponding
corresponding
weightweightof eachof eachlevel’slevel’s
influencing
influencing
factorfactorcancanbe becalculated
calculated
throughthroughthisthis
method.
method.
To To
calculatecalculate
the theweightweightthroughthroughevery
every
experts’
experts’marking,
marking,
the thefinalfinal
resultresultis obtained
is obtained
throughthroughthe theweightedweighted
mean
mean
of of
21 21
experts.
experts.
After
After
that,that,
every
every
weightweightmust
must
be multiplied
be multiplied
by bya coefficienta coefficient
which
which
is theis thenumbernumberof secondaryof secondary
indices
indices
includedincludedby byprimary
primary
indices.
indices.
Otherwise
Otherwise
if theif theprimary
primary
indices
indicesare aremore
morethanthansecondarysecondaryindices,
indices,
the theweightweightof everyof everysecondarysecondaryindices
indices
willwill
decrease.
decrease.
It will
It willinfluence
influence
the theweightweightof influencing
of influencing
factors.
factors.
Finally,
Finally,
every
every
finalfinal
weightweightof influencing
of influencing
factorfactoris isobtained.
obtained.
Table
Table
3: Weights
3: Weights
of influencing
of influencing
factors
factors

Influencing
Influencing
factorfactor
weightweightInfluencing
Influencing
factorfactor
weightweightpopulation
population
densitydensity
0.0536
0.0536 percent
percentof householdof household
0.01960.0196
percent
percentof femaleof female
0.03220.0322 percent
percentof ethnicof ethnic
minorities
minorities
0.02230.0223
percent
percent
of populationof population
underunder
5 years
5 years 0.0491
0.0491percent
percent
of populationof population
over over
65 years
65 years
0.05230.0523
percent
percentof illiterateof illiterate
0.03520.0352 percent
percentof divorceeof divorcee
0.02750.0275percent
percentof temporaryof temporary
population
population
0.02960.0296 rate of
rate
unemploymentof unemployment
0.01610.0161percent
percentof offarming,farming,
forestry,
forestry,
0.00730.0073 percent
percentof miningof mining
0.00860.0086
animalanimalhusbandry
husbandry
and fisheryand fisherypercent
percentof constructionof construction
0.01050.0105 percent
percentof carryingof carrying
tradetrade
0.00780.0078percent
percentof socialof socialservices
services
0.00800.0080 percent
percentof socialof socialwelfarewelfare0.00760.0076
percent
percentof sanitationof sanitation
0.01420.0142 average
average
GDPGDPof localof localpopulation
population
0.0537
0.0537per capita
per capita
incomeincome0.07560.0756 ratio ratio
of incomeof incomeand payand pay
0.04650.0465engelengel
coefficient
coefficient
0.05250.0525infrastructure
infrastructure
investment
investment
0.0532
0.0532
percent
percentof oldofhouses
old houses
0.04090.0409numbernumberof fireofstations
fire stations
per square
per square
kilometer
kilometer
0.07030.0703
numbernumberof subwayof subway
stations
stations
per per
0.04490.0449numbernumberof ofhospital
hospitalbeds beds
per per
10001000
0.07850.0785squaresquarekilometer
kilometer
inhabitants
inhabitants
numbernumberof doctorsof doctors
and nurses
and nurses
per per
0.08240.082410001000
inhabitants
inhabitants

Level
Level
sortingsorting
consistency
consistency
index
index
is CI
isj and
CIj andrandomrandomconsistency
consistency
index
index
is is
RIj,RI
thej, theconsistency
consistency
ratioratio
of integrated
of integrated
level
level
sortingsorting
is: is:a CIa CIa m+CI
a mmCI m+ a +CIa CI+ a +CIa CI+ …++…
(5) (5)
CR CR= 1= 11 1 2 22 2 3 33 3
a 1 RIa11 RI+ a1 2+RIa 22 RI+ a2 3+RIa33 RI+…
a m+RIa mmRI m
3 ++…
Integrated
Integrated
level
level
sortingsorting
cancanbe be
passpass
the theconsistency
consistency
check
check
when
when
CR<0.1.
CR<0.1.
If CR>0.1,
If CR>0.1,
we weshouldshouldreadjust
readjust
the thefactor’s
factor’s
value
value
of judgementof judgement
matrixmatrixwhich
which
consistency
consistency
ratioratio
is toois too
high.
high.

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4. CALCULATION OF THE INTEGRATED SOCIAL VULNERABILITY SCORE
4.1 The classification of influencing factors
After the weight calculating, the population vulnerability, career
vulnerability, economic vulnerability, infrastructure vulnerability andintegrated social vulnerability will be calculated.
According to the function of influencing factors, 27 influencing
factors are classified to two categories, one is negative, the other is positive(negative: the vulnerability will increase when the value of influencing
factor increases. positive: the vulnerability will decrease when the value of
influencing factor increases).
The influencing factors increasing the vulnerability includes:
population density, percent of female, percent of ethnic minorities, percent
of population under 5 years, percent of population over 65 years, percent of
illiterate, percent of divorcee, percent of temporary population, rate ofunemployment, percent of farming, forestry, animal husbandry and fishery,
percent of mining, percent of construction, percent of carrying trade, Engelcoefficient and percent of old houses. Other influencing factors decrease thevulnerability.
Due to the two functions play a contrary part in the vulnerability, thedata’s polarity must be transformed. Finally, all influencing factors have thepositive correlation with vulnerability.
4.2 Calculating the vulnerability scores
After all data normalized by Z-score method, the data of influencing
factor which decreases the vulnerability should multiply -1, then 27 final
data which through normalization and polarity transformation will beobtained. Now, two methods can be used to calculate the social vulnerability
index (SOVI), linear and nonlinear weighted integrated function method,respectively. The characteristic of later method adapts to condition which
has intensive relationship of each indices and former method is contrary.
Because every index is independent in this study, the linear weighted
integrated function method is used to calculate the SOVI(Yi Ge, 2006). The
equation is below:
27

SOVI = ∑ ( wi ⋅ xi )

(6)

i =1

I(1-27): each 27 influencing factors.
wi : the weight of each influencing factor.
xi : the handled final data of every areas
The SOVI is a relative value through this method, and it can compare
the vulnerability of 333 areas. As shown from the data, the SOVI of Beijing
is between -0.5 and 0.5.

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SOVI<-0.5: the vulnerability of the area is very low-0.5<SOVI<0: the vulnerability of the area is lower, the ability to resist
disaster is higher
0<SOVI<0.5: the vulnerability of the area is higher, the ability to resist
disaster is lower
SOVI>0.5: the vulnerability of the area is very high
The SOVI of integrated social vulnerability equals the summation of
the SOVI of population vulnerability, career vulnerability, economic
vulnerability and infrastructure vulnerability.
5. RESULTS
5.1 Distribution of Beijing’s vulnerability
The distribution of Beijing’s social vulnerability is shown in Fig.2.
Fig.3 shows the distribution of social vulnerability of central Beijing. Blueshows the lowest vulnerability and red shows the highest vulnerability andthe intermediate stage is gradual changed from one color to another.

Figure 2: Distribution map of social vulnerability of Beijing

Figure 3: Distribution map of social vulnerability of central Beijing
The map (Schmidtlein et al., 2008) of Beijing’s social vulnerability
distribution is drew according to the relationship of SOVI and colors. It canbe seen that the social vulnerability in the center is lower than that in thesuburban in spite of high population density in the center. This is because

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that there are better personnel quality, economy and infrastructure in thecenter.
5.2 Sensitivity analysis
Analysis steps are below:(1) All processed data will be listed and each influencing factor mustbe multiplied by a coefficient (>1) , the coefficient (=5) is set inthis study (The value of coefficient doesn’t influence the result, it
only increases the diversity of each data. But we should attention
that the coefficient must be smaller than 1.0. At first, the firstinfluencing factor is multiplied by 5 in the case that otherinfluencing factor’s weights are maintained to be constant.
(2) To assure that the proportion of other 26 influencing factor’s
weights are constant, we adjust other 26 influencing factor’s
weights and let the sum of these 27 influencing factor’s weights
equal 1. The method is as follow: Before the calculating, each
influencing factor’s weights are assumed to be Xm1…Xm2, andeach new weights after the calculating are assumed to be
Xn1…Xn27.The equation is :X np =

X mp ⋅ (1 − C ⋅ X mq )(1 − X mq )p, q ∈ [1,27] ; p and q are integer(7)

Xnp: the new influencing factor’s weights after calculating
Xmp: the original weights of soluted influencing factor
Xmq: the original weights of changed influencing factor
C: the coefficient. In this study, we define it to be 5.
The 27 new influencing factor’s weights can be calculated, and a
27×27 data array can be obtained.
(3) The new vulnerability scores are obtained through the 27-arrays
data’s calculating of each area. The sensitivity is defined to be thedifference between the original normal vulnerability scores andthe new vulnerability scores. The higher the value of sensitivity is,
the bigger the influence of this influencing factor is. We can turnthe value to a curve to reflecting the sensitivity of influencing
factors of each area and it’s easy to get the characteristics ofsensitivity changing.
(4) The most sensitive influencing factor can be found. The
vulnerability level can be improved efficiently through improving
the influencing factor.
The result of sensitivity analysis can be obtained through the above
method. We can improve their vulnerability level through the sensitivity
analysis, and it contributes to the urban plan and construction of Beijing.

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fundamental study
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vulnerability forforpublic
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Mai,Thailand
Thailand
Chiangmai,

Figure 4: Sensitivity analysis result
ACKNOWLEDGEMENT
This work was supported by National Natural Science Foundation of China
under Grant No. 71173128 and Ministry of Science and Technology of thePeople´s Republic of China under Grant No. 2011BAK07B02.
REFERENCES
Barry E. Flanagan, Edward W. Gregory, Elaine J. Hallisey, Janet L.
Heitgerd, Brian Lewis, 2001(8). A Social Vulnerability Index for Disaster
Management. Journal of Homeland Security and Emergency Management
3,1-22Christopher G.Burton,2008(4). Social Vulnerability and Hurricane
Impact Modeling. Risk Analysis,58-68.
Jose Manuel de Oliveira Mendes, 2010(1). Social vulnerability
indexes as planning tools: beyond the preparedness paradigm. Nature
Hazards Review, 59-68.
Kun Wang, Haizhou Song, 2003(6). The comparison and analysis ofthree objective weighted methods.Technical economy and management
research, 48-49
Susan L Cutter, Bryan J Boruff, W lynn Shirley,2003. Social
Vulnerability
toEnvironmental
Hazards[J].
SocialScience
Quarterly,84:242-261.
Xueqiang Shan, 2010(5).System Research of Risk Evaluation on
Primary and Secondary Schools’ Emergent Events ， Department ofEngineering Physics of Tsinghua university.
Yi Ge, 2006(4). Research of social vulnerability committed by floodtaking -----Changsha,Hunan as example.The research institution of disarster
and public safety in school of resource,Beijing Normal university.

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NewFlood and debris flow disastermanagement of Mae-Ngon basin
Fang District Chiangmai Province
Januwat Leardsiljalearn1 Chatchai Pedugsorn2
Engineering Branch Director, 2 Head of Dam Safety Management,
Regional Royal Irrigation Office No.1, Royal Irrigation Department
1

ABSTRACT
Debris flow disaster occurred in Mae-Ngon basin 3 times in 40 years,
recently 9 October 2006, there are 7 people death and 638 million bath loss.
Flood and landslide sediment are studied by ground survey, soil survey,
geological survey and laboratory testing for debris flow properties. Resultshows that landslide sediment volume are about 343,148 m3 consisting ofcourse particle (boulder, cobble, gravel) 47,548 m3, fine particle (sand)
236,480 m3 and soil particle (silt & Clay) 59,120 m3. Landslide sedimentvolume is 127.54 times of erosion sediment volume or erosion sediment is
0.78 percent of landslide sediment. Debris flow properties such as Densityof debris flow 1.690 ton/m3, Sediment concentration 0.636. From X–ray
diffractometer test, rock name is Carbonate alterate Meta – pelite. Claymineral consists of Quartz, Magnesiumcalsite and Dolomite. Compositionof clay mineral is Illite. A group name for non-expanding. Rock property is
durable from swelling and expanding under water condition. Rockmechanic testing is accomplished in Hoek & Brown (2006) system.
Basement rock has GSI about 30 – 35. Flood and debris flow disastermanagement of Mae-Ngon basin by non–measuring structure can reduce
erosion sediment only 0.78 percent. Measuring structure can control 99.22
percent of basin sediment. Slit sabo dam of Japan are modified for MaeNgon basin which can reduce construction cost about 50 percent. Openingsof slit structure are designed follow “Mizuyama (1995)” trapping sedimentcorresponding to its gradation which allows water and finer particle passthrough its structure and dissipate flow energy. The flow passes todownstream to sediment-water storage dam. Modification of sabo dam tomultipurpose as water storage and trapping fine sediment which can be
flushed to maintain storage while original sabo dam functions as sediment
trap structure. Research output is construction drawing of flood and debris
flow prevention structures suitable to Thailand.
Keyword : Flood and Debris flow disaster Management of Mae-Ngon Basin,
Landslide Sediment, Erosion Sediment, Debris Flow, Slit Sabo Dam andSabo dam3731

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

1. PROBLEM OF FLOOD AND LANDSLIDE
Flood and Landslide in Thailand
After 1970, Thailand is increasingly susceptible to flood and debris
flow (table1). Year after year the flood and debris flow disaster is more
severely damage to property and lives because more people settle in floodand debris flow area, land use change, climate change from global warming.
Example of damage from flood and landslide are in table1.
Table1. Damage from flood and landslide (Varakorn, 2003)(Chatchai, 2010)

Month/Year

Area

Number of Death

November 1970
January 1975

Tapsagae District, Prajunb Provinece
Ronpiboon District , Nakornsritamarig
Province
Sribanphot District, Patalung Province
Pipoon District, Nakornsritomaraj
Province
Kichakood District , Juntaburi Province
Vangchin District , Phrae Province
Lomsak District, Petchaboon Province
Fang District, Chiangmai Province

1258

December 1982
November 1988
August 1998
June 2001
August 2001
October 2006

4
>200
1
>30
135
7

Flood and Landslide in Mae-Ngon basin
During 6-9 October 2006, there are heavy rains in Mae-Ngon basin.
Rain gauge stations at Ang – Khang, Fang District, collect the following rain
fall data
6 October 2006, 3.80 millimeter
7 October 2006, 24.60 millimeter
8 October 2006, 138.60 millimeter
9 October 2006, 34.40 millimeter
After 4 successive days of rain fall, flash flood and landslide occurs.
Debris flow which consists of lumber, boulder, cobble, gravel, sand and mudbring about 7 people death and damage 13 villages. There are effected to
3,520 families and 9,390 rai of agriculture area. Public infrastructures arewidely destroyed. Evaluation of loss is totally 638,859,687 baths (Figure1)
Mae–Ngon basin is in Fang district north of Chiangmai city about 154
km. by road No.107 (Chiangmai – Fang ) Mae–Ngon basin has boundary
area by following direction
North: Myanmar and Mae-eye district, Chiangmai Province
East: Mae-suai district, Chiangrai ProvinceSouth: Chaiprakan district, Chiangmai Province
West: Myanmar
Research area is in Mae–Ngon Sub district, Fang District of
Chiangmai Province at 47 QNC 173 – 060 (051729 mE,2206048 mN)
4848–IV Sheet, L7017 Series by military map

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Laoao

Viet nam

Myanmar

Mae-Ngon basin, Fang District,
Chiangmai Province

Cambodia

Viet namFigure: Location of Mae-Ngon basin in Mae-Ngon Sub district,
Fang District Chiangmai Province and damages from Debris flow in
9 October 2006
Objective of study
The research objectives are to study about flood and landslide
management of Mae-Ngon basin by measuring structure and non–measuring
structure. Objective of measuring structure proposed on suitable of structure
for Mae – Ngon basin while objective of non-measuring structure isparticipatory of community.
Methodology
The methodologies of this research are 4 steps
1) Study the properties of landslide sediment of Mae – Ngon basin,
by ground survey, soil survey and geological survey.
1. Ground survey is investigated the depth and boundary of landslide
sediment deposition (Figure2.)

Figure 2: Boundary of land slide sediment deposit, by ground survey
Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province3753

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

2. Soil survey and geological survey
Landslide sediment deposition is investigated by hand auger drilled from
deposition surface to original ground surface. Depth of landslide sedimentdeposition is the difference between deposition surface and original groundsurface. Sample of landslide sediment are collected by test pit (Figure3.). The
objective of soil survey and geological survey are to investigate the boundaryand depth of course sediment (boulder, cobble, gravel), fine sediment (sand,silt&clay) and to collect sediment sample.

Figure 3: Sample of landslide sediment collected by soil survey indeposition area2) Study the geological property of Mae–Ngon basin basement foundation
1. Geological survey at proposed sediment – water storage dam
Two proposed sediment – water storage dam site are bored totally 190
m. Location of bore hole are left abutment, river bed and right abutment
as show in Figure 4.

Figure 4: Location of bore hole along sediment – water storage dam axis
2. Rock testing
Rock sample from dam foundation are testing in both rock mechanic
Laboratory and lithology and petrography Laboratory

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Figure.5 Rock sample preparation for rock mechanic testing
Clay minerals are investigated by X – ray Diffractometer. Engineering
properties of rock sample are tested by Hoek & Brown (2006) system toevaluate strength of rock mass from intact rock3) Study measuring structure for flood and landslide sediment of Mae– Ngon basin
Detail designs are accomplish. Course sediment trap structure thatsuitable for flood and debris flow ofMae–Ngon basin is design following physical model of “Mizuyama at el(1995)” (Figure6.). Relation of sediment trap and dimensionless parameters
are used equation 1.

Figure 6: Physical Model study the relation of opening size and sediment
trap “Mizuyama et al (1995)”
Mizuyama et al (1995)
eq.1

Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province3775

October 2011, Chiang
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Thailand
Chiangmai,

eq. 2

ST =

Vsa - Vsb

Vm
Where
ST = Sediment storage rate (0 ≤ ST ≤ 1.0)
Vm = Maximum sediment deposited volume at dam upstream
Vsa = Sediment volume in the debris flow before passing through aslit dam.
Vsb = Sediment volume in the debris flow after passing through a slitdam.
Σb = Total spacing of slit dam
B= Channel width
Ca = Sediment Concentration
Dmax = Maximum diameter of sediment4) Study of non-measuring structure and participatory of people in
Mae–Ngon basin.

Participatory in Mae–Ngon basin are set by several government
officer groups such as Royal Irrigation Department, Land Development
Department and Huaihongkrai Royal Development Study Center. Meetingare at Mae – Ngon Sub district office, 1 April 2010, there are totally 42
people (35 male, 7 female) meeting (Figure7).

Figure 7: Non-measuring structure and participatory of Mae – Ngon basin
Research result
1) Damage areas of Mae – Ngon basin, 9 October 2006, (Figure.8) arecaused by landslide sediment. Land slide sediment composes ofboulder, cobble, gravel, sand and mud flowed under non-cohesive
condition. As it flows with high velocity, it has high impact force.
The debris flow has high potential of destruction. The result fromlaboratory test shows that landslide sediment has 127.54 times overerosion sediment volume. The result of this study corresponding to“Tera L. Curry (2007)” that conduct comparison study between
land slide sediment and erosion sediment of Redwood Creek basin,
north coastal California, USA, 244 square kilometers. Tera L.
Curry (2007) analyzed recorded data from 1954 to 1981 and foundthat land slide sediment at fault zone of river basin has more than
100 times of erosion sediment volume.

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Landslide Area

Disaster Area from debris flow

Figure.8 Area of land slide and damage area by land slide sediment2) Properties of landslide sediment of Mae – Ngon basin. From survey andlaboratory testing, the significant debris flow properties are as following.
2.1 Volume of course sediment (Boulder, Cobble, Gravel) = 47,548 m3
2.2 Volume of fine sediment (Sand, Silt & Clay) = 295,600 m3
2.3 Area of course sediment deposit (Boulder, Cobble, Gravel) = 190,790m2
2.4 Area of fine sediment deposit (Sand, Silt & Clay) = 496,104 m2
2.5 Fine sediment is consisting of sand 80 percent and silt & Clay 20 percent.
2.6 Density of Debris Flow = 1.690 ton/ m3
The result show that density of debris flow of Mae – Ngon basin is lower
than density of debris flow in Japan river basin (Table 2)
2.7 Sediment Concentration, Cd = 0.636
2.8 Peak Discharge of Debris Flow, Qs = 53.118 m3/sec
2.9 Erosion Sediment = 2,690 m3/year
2.10 Ratio of landslide sediment to erosion sediment = 127.54:1
2.11 Gradation of fine sediment (Sand, Silt & Clay) from laboratory test isshow in Figure 9.
Table 2: Density of debris flow comparison between Mae – Ngon basin
and Japan river basinRiver
Mt YakeNojiri River
Mae – Ngon River basin

Maximum
2.110
2.039
-

Minimum
1.631
1.121
-

Average
1.861
1.784
1.690

Figure 9: Gradation of fine sediment (Sand, Silt & Clay)

Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province3797

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,3) Geological and propertied foundation
3.1 Basement at sediment-water storage dam1 and dam2 aresupported by sandstone shale and altered Cambrian siltstone,
named Carbonate Alterate meta–pelite (meta–sandstone//Meta–
mudstone) by testing for optical properties
3.2 Geological foundation along centerline of sediment-water
storage dam1 and dam2 consist of shale and altered sandstone.
Weathering condition is moderately to highly weathering. Shallow
shale has high permeability while deeper have moderate to highpermeability.
3.3. Stability of abutment is susceptible to sliding. Topography ofsteep slope appears the collapse of slope that characterize the rockfall and slide of soil and land mass. As a result of landslide hazard
may induce some sliding around reservoir rim.
3.4 By analysis type of clay minerals using X – ray diffractrometer,basement rock consist of Quartz Magnesiumcalcite Dolomite. The
composition of clay minerals is Illite, a group name for non –expanding so properties of rock is durable to swelling anddecomposition.
3.5 Engineering and Physical properties of basement rock. The
factors that affect rock mass and rock movement are discontinuities
and weathering of rock. From lithology, basement rocks are meta–
sandstone, meta–siltstone and meta–mudstone. Structure anddiscontinuities of rock are estimate by GSI value as follows
3.5.1 Sediment-water storage dam1, sandstone siltstone andmudstonearealtered.
Discontinuityis
Blocky/Disturbed/Seamy – Blocky and surface is smooth toslickenside that related high altered minerals, estimate the GSI
value about 30 -55
3.5.2 Sediment-water storage dam1, sandstone siltstone andmudstone are metamorphased like phyllite. Discontinuity is
Very Blocky – Blocky and surface is smooth to slickenside andboth altered minerals occurs thus the GSI value is 30 -55(Figure.10)

DAM

Figure 10: GSI of Sediment-water storage dam1 and Sedimentwater storage dam2

8
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4) Result of flood and landslide management of Mae–Ngon basin bymeasuring structure.
Sediment–water storage dam for Mae – Ngon basin should compatible
to steep canyon. Sabo Dam of Japan is chosen as prototype due to similarityof dam site and objective. Modification of sabo dam to multi purpose damthat function as water storage and sediment trap structure can benefit both
irrigation purpose and disaster management. As debris flow occurs 3 times
in 40 years, the rest of critical time the dam are used as storage dam. The
adjustment is installing of 4 gate valves at downstream opening andoperating bridge. When basin is in critical API (Antecedent Precipitation
Index), gate valves are automatically full open in that condition it function
as original sabo dam. The gate valves are control by telemettering system.
Sediment-water management due to relation of storage function andsediment concentration. Sediment deposit can be flushed out after debris
flow stop. Due to similarity of dam site and river basin, sabo dam arechosen as prototype for modification. Both Japan river basin and Mae–Ngonriver basin are similarity (Figure. 12) such as steep slope of river bed,
stability of geological foundation, requirement of self cleansing.
Comparisons are in table 3
Table 3 Comparison objective between original sabo dam and Modification
for Mae – Ngon basin
Original sabo dam••

Modification for Mae – Ngon Basin

For flood protection
For debris flow protection• For flood protection• For debris flow protection• Storage water for Irrigation
purpose• Storage water for water supply
purpose• For recreation and tourism

General lay out of sediment trap structure and sediment – water
storage dam are in Figureure 11
Catchment Area = 21.903 sq.km.
River Length = 7.372 km.

Catchment Area of Mae – Ngon
Basin
Sediment trap structure in Mae –Ngon riveer No 2
Sediment trap structure in Mae –Ni
N 1

Sediment – water storage dam
Sediment – water storage dam

Disaster Area from debris flow
9 October 2006

Sediment trap structure in Mae
Khan riveer No 2

Sediment trap structure in Mae
Khi
N 1N 1Figure 11: Location of sediment trap structure and sediment – water
storage dam

Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province3819

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 12: Similarity of Sediment – water storage dam site No.1 (Left) andoriginal sabo dam (Right)

Figure: 13 Original sabo dam of Japan for Nagano city protection
Original Sabo dam of Japan is single purpose of disaster protection
structure (Figure. 13)

Figure 14: Sediment–water storage dam No.2 of Mae–Ngon basin

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Design criteria for sediment trap structure of Mae – Ngon basin are
follow “Mizoyama (1995)” to catch course particle. The sediment that
gradation matches to opening size is deposit in front of structure. Original
slit sabo dam of Japan (Figure. 15) are modified so that new pattern cansave the construction cost more than 50 percent. The modification isnecessary due to material should be easily to supply and to construct insteep area. Sediment trap structure of Mae – Ngon is show in Figure. 16 andFigure 17.

Figure 15: Original slit sabo dam of Japan
Sediment trapping characteristic curve of sediment trap
structure in Mae – Ngon No. 2• Sediment trap structurein Mae – Ngon river No.2
• Steel slit structure on concreteSmgravity footing• Crest Width 3.00 m.

Vsa/VmSediment trapping characteristic curve of sediment
trap structure in Mae – Ngon No. 1• Sediment trap structure in
Mae – Ngonriver No.1
• Steel slit structure on concrete
gravity footing• Sediment trap structurein Mae – Khan river
No.2• Steel slit structure on
concrete gravity
footing• Sediment trap structure in M
Khan river
No.1• Steel slit structure on concr
footing• Crest Width 3.00 m.

• Crest Length 91.50 m.

Sm
V /V

sa m
Sediment trapping characteristic curve of
sediment trap
structure in Mae – Khan No. 2

Sm
Vsa/VmSediment trapping characteristic curve of sediment trap
structure in Mae – Khan No. 1

Sm

Vsa/VmFigure 16: Sediment trap structure and sediment trap behavior
Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province11383

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Sediment trap structure in Mae – Khan No.2

Sediment trap structure in Mae –Khan No.1

Figure 17: Sediment trap structure for Mae–Ngon basin
5) Result of flood and landslide management of Mae-Ngon basin by
non-measuring structure by participatory and awareness of community.
5.1 People take part in this project can get all project information
they express very good to excellent satisfied about 84.76 percent.
5.2 People participated this project can share idea and set plan to
manage flood and debris flow of Mae-Ngon basin. People receive
project information, fact so that they can set suitable nonmeasuring structure following their need. Participatory from
community can reduce conflict to the project. By questionnaireevaluation they feel very good to excellent about 86.90 percent.
5.3 What people need from this research project during
participatory meeting is they want to take part in making
management plan about flood and landslide by non–measuring
structure. The summaries of people need are as following :1. People need reservoir in Mae – Ngon sub district to solve
flood and debris flow and to storage the water for dry season.
2. People request for reservoir to prevent flash flood.
3. People want reservoir and irrigation system for high land
agriculture activity.

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4. People need social measuring to increase quality of life.
5. They want project that enhance occupation and agriculturalwhich reduce the use of chemical substance.
6. They want retaining wall along Mae – Ngon river bank toprotect erosion and increase efficiency of drainage
7. People want to know project information and to enhance theparticipation for every kind of project (Small medium and Largesole) and every process of project (Before during and after
construction).
8. They need field trip to learn from other basin that successfrom flood and landslide management by non-measuring
structure.
Conclusion of Research
1) Damage area from flood and debris flow is in Mae–Ngon basin.
The disaster occurs on 9 October 2006. 13 Village and 3520 family
effect from debris flow, 7 people death and 12 people wounded.
Direct and indirect loss is totally 638,682,682 baths. The loss is cause
by debris flow which composed of lumber, boulder, cobble, gravel,
sand and mud. As debris flow with high velocity and no cohesion, it
has high potential of devastation. Land slide sediment volume is127.54 times over erosion sediment volume.
2.) To manage flood and land slide of Mae – Ngon basin, It needmeasuring structure together with non- measuring structure. Non–measuring structure can control only erosion sediment that limitation
is 0.78 percent of total basin sediment. Non–measuring structure
cannot control landslide sediment 99.22 percent of total basin
sediment. Using only measuring structure is not sustainable, because.
It lack of participatory and collaboration from community.
3.) Relocation by moving community out of risk area is not feasible
and not possible, compare with measuring structure. Relocation hassocial effect moreover it shift the problem from Mae – Ngon basin toanother basin. Flood and landslide management by relocation is notsustainable.
4.) In case of limitation of budget, construction should can accomplishin 2 phase
First phase construct sediment–water storage dam No.1 together withsediment trap structure in Mae –Ngon No.1 and sediment trap structure in Mae–Khan No.1.
Second phase construct sediment–water storage dam No.2 together
with sediment trap structure in Mae –Ngon No.2 and sediment trap structure in Mae–Khan No.2.
Benefits of measuring structure are flood and debris flow protection
and water usage. It is feasible if
Compare with investment cost.
5.) Management of sediment–water storage dam should use
application of real time telemetering. Real time telemetering whichmonitoring soil moisture and rain fall forecast before critical conditionof landslide. Operating gate of the dam can control by telemeteringthat can change purpose from storage dam to debris flow protection.
Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province13385

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Mae–Ngon basin should have warning system. CCTV and movement
sensor should be installed along the river to detect debris flow andwarning to people living in risk area. By this mean people haveenough time to excavate.
Recommendations
1. Physical Model of 4 sediment trap structure and 2 sediment–water
storage dam should be study in laboratory. Physical model should
focus of hydraulic properties and sediment trap behavior to recheckthe design.
2. API and other Indicators of land slide and debris flow should be
study that can apply with flood and land slide Management
ACKNOWLEDGEMENT
The author wishes to express most profound gratitude to National
Research Council of Thailand (NRCT) and Royal Irrigation
Department (RID) executives.
1. Mr.Chalit Damrongsak, Royal Irrigation Department Director
2. Mr.Suthep Noipairoi, Hydrology and Water Management OfficeDirector
3. Mr.Venai Phongjinda , Regional Royal Irrigation Office No.1
Director
REFERENCE
Ashida, K. and Takahashi, T. 1980, Study on debris flow controlhydraulic function of grid type open dam, Annuals. Disaster Prevention Res.
Inst., Kyoto Univ., No. 23B-2, .pp. 1-9 (in Japanese).
Fiebiger, G. 1997, Structures of debris flow countermeasures.
Proceedings, First International Conference on Debris-Flow Hazards
Mitigation: Mechanics, Prediction, and Assessment: pp. 596-605, New
York: ASCE.
Food and Fertilizer Technology Center. 1995, Soil conservation
handbook. Food and Fertilizer Technology Center for the Asian and PacificRegion, II-41.
Gregoretti, C. 2000, The initiation of debris flow at high slopes:
experimental results. Journal of Hydraulic Research, Vol. 38, No. 2, pp. 8388.
Heumader, J. 2000, Technical debris-flow countermeasures in Austria– a review. Proceedings, Second International Conference on Debris-Flow
Hazards Mitigation: Mechanics, Prediction, and Assessment: pp. 553-564,
Taipei, Taiwan: ASCE.
Ikeya, H. and Uehara, S. 1980, Experimental study about the sedimentcontrol of slit sabo dams. J. of the Japan Erosion Control Engineering
Society, Vol. 114,.pp. 37-44. (in Japanese)
Innes, J. L. 1983, Lichenometric dating of debris-flow deposition in
the Scotish highlands. Earth Surface Processes and landforms, Vol. 8, pp.
579-588.

14
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Johnson, P. A., and Richard, H. M. 1989, Slit dam design for debris
flow mitigation. Journal of Hydraulic Engineering, ASCE, Vol. 115, No. 9,
pp. 1293-1296.
Lien, H. P. and Tsai, F. W. 1999, Volumetric sediment concentrationin debris Flow. International Journal of Sediment Research.Vol.14, No.3,
Sep., pp. 23-31.
Lien, H. P and Tsai, F. W. 2000, Debris flow control by using slit
dams. International Journal of Sediment Research, Vol. 15, No.4, pp. 391409.
Lin, P. S. and Lin, J.Y. 1999, The impact force and countermeasure
structures of debris flow. Sino-Geotechnics, No.74, .pp. 67-80 (in Chinese).
Melis, T. S., Webb, R. H. and Griffiths, P. G. 1997, Debris flows inGrand Canyon national peak: peak discharge, flow transformations, andhydrographs, Proceedings. First International Conference on Debris-Flow
Hazards Mitigation: Mechanics, Prediction, and Assessment: pp. 5727-736,
New York: ASCE.
Mizuyama, T., Suzuki, H., Oikawa, Y. and Morita, A. 1988,
Experimental study on permeable sabo dam. J. of the Japan Erosion Control
Engineering Society, Vol. 41, No. 2, pp. 21-25 (in Japanese).
Mizuyama, T., Kobashi, S. and Mizuno, H. 1995, Control of passing
sediment with grid-type dams. J. of the Japan Erosion Control Engineering
Society, Vol. 47, No. 5, pp. 8-13 (in Japanese).
Schilling, S. P. and Iverson, R. M. 1997, Automated, reproducibledelineation of zones at risk from inundation by large volcanic debris flows.
Proceedings, First International Conference on Debris-Flow Hazards
Mitigation: Mechanics, Prediction, and Assessment: pp. 176-186, New
York: ASCE.
Shih, B. J., Shieh, C. L. and Chen, L. J. 1997, The grading of risk forhazardous debris-flow zones. Proceedings, First International Conference on
Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment:
pp. 219-228, New York: ASCE.
Suwa, H., Yamakoshi, T. and Sato, K. 2000, Relationship between
debris-flow discharge and ground vibration. Proceedings, Second
International Conference on Debris-Flow Hazards Mitigation: Mechanics,
Prediction, and Assessment: pp. 311-318, Taipei, Taiwan: ASCE.
International Journal of Sediment Research, Vol. 18, No. 1, 2003, pp.
74-87 - 85 –Takahashi, T. 1991, Debris flow. Monograph Series of IAHR, A. A.
Balkema, Rotterdam, The Netherlands, pp. 32-69.
Takahashi, T. 1997, Engineering problems in crossing potential
debris flow ravines by bridges. Workshop Series on Hazard Mitigation for
Civil Infrastructures-Bridge Engineering, Taiwan.
Tera L Curry 2007, A Landslide Study in Redwood Creek Basin,
Northwestern California: Effect of the 1997 Storm, Master Thesis of
Science in Environmental System: Geology, Humboldt State University:
USA
Watanbe, M., Mizuyama, T, and Uehara, S. 1980, Review of debris
flow countermeasure facilities. J. of the Japan Erosion Control Engineering
Society, Vol. 115, pp. 40-45 (in Japanese)

Flood andFlood
and debris
debris flow
flow disasterdisastermanagement
managementof
ofMae-Ngon
Mae-Ngonbasin
basinFang
FangDistrict
DistrictChiangmai
ChiangmaiProvince
Province15387

October 2011, Chiang Mai, Thailand

388

New Technologies for Urban Safety of Mega Cities in Asia

Development of 3D viewer of flood
disaster risk to enhance evacuation
capacity of residents
Kohei MAKINODAN1, Miho OHARA2 and Kimiro MEGURO3
1
Master Student, Department of Civil Engineering,
The University of Tokyo, Japanmakinodan@risk-mg.iis.u-tokyo.ac.jp
2
Associate Professor, Interfaculty Initiative in Information Studies/ Institute of Industrial Science,
The University of Tokyo, Japan
3
Professor, Interfaculty Initiative in Information Studies,/ Institute of Industrial Science,
The University of Tokyo, Japan
ABSTRACT
Eastern part of the Tokyo Metropolitan area has high risk of large-scaleurban flood. Especially, Koto Delta Area whose elevation is lower than sea
level is surrounded by rivers and expected to face severe problems of humanevacuation in the future flood disaster. In order to reduce casualties due tothe future flood disaster, it is important to encourage resident’s awarenessof the flood disaster risk and enhance their imagination capability of proper
evacuation from their home to evacuation centers.
In this research, 3D viewer of flood disaster risk was developed as an
educational tool for enhancing evacuation capacity of residents. This viewer
can show 3 dimensional images of geography, building and estimated waterlevel of the flood. Prototype system was developed using the data in Koto
Delta Area. Residents can check the location of evacuation centers anddifficulty in access to each evacuation center in the 3D view. In order todiscuss the difficulty in evacuation, proper understanding of varying waterlevel, its velocity and hydrodynamic force in the time-history is necessary.
In this viewer, dynamic changing of flood water is shown in 3D spaces andit can contribute to the real imagination of difficulties during evacuation.
Finally, the viewer aims that residents can image appropriate action of
emergent evacuation during flood disaster.
Keywords: urban flood, risk analysis, evacuation, 3D viewer
1. INTRODUCTION
Eastern part of the Tokyo Metropolitan area has high risk of large-scaleurban flood. Especially, Koto Delta Area whose elevation is lower than sea
level is surrounded by rivers and expected to face the severe problems of3891

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human evacuation in the future flood disaster. In case flood risk increases,
local municipalities are usually responsible to issue evacuation counsel or
evacuation order to the residents in the dangerous area. However, casualties
due to inappropriate evacuation during flood are reported every year inJapan. In order to reduce casualties due to the future flood disaster, it isimportant to encourage resident’s awareness of the flood disaster risk andenhance their imagination capability of proper evacuation from their home
to evacuation centers. In this research, considering whole Koto Delta as astudy area, 3D viewer of flood disaster risk was developed as an educational
tool for enhancing evacuation capacity of residents.

2. IMPACT OF LARGE-SCALE FLOOD ON KOTO DELTA AREA
According to the Cabinet Office in Japan, the maximum predicted numberof death is approximately 3,500 and that of isolated people is approximately
720,000 in case the bank of Arakawa river collapsed as a consequence ofincrease water due to extreme heavy rain. This is an estimation whendrainage pump station, drainage pump vehicle and water gate areunavailable. Figure 1 shows location of Koto Delta Area and point of dikebreak in this simulation.
N

30km

Saitama
Tokyo

Chiba

Kanagawa

Koto Delta Area：point of dike break

Figure 1: Location of Koto Delta Area
According to past research (makinodan,2010), detail flood risk
analysis of the area was conducted using GIS in a 125m-mesh with flood
data from Cabinet Office and additional information such as population

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distribution and building inventory. Figure 2 shows inundation depth andinundated area. In most of Koto Delta Area, inundation depth comes up 2mand the number of buildings in this area is 49,449 among total 114,646
buildings.
昼��� /population
��Daytime������
Depth(m)a) 1 hour later

-

0

5.
0

.0
-2

1.
0

-5
.

.0
-1

2.
0

.5
00

0.
5

084
3
84
421
41
21
42
-4
02
40
4
25
-7
1
71
97
98
-1
47
66

原点Z

b) 6 hours laterc) 24 hours later
Figure 2: Alteration of inundated depth

3. CONCEPT OF A NEW EDUCATIONAL TOOL FOR
ENHANCING IMAGINATION CAPABILITY
As an educational tool for flood disaster, a hazard map which shows
inundation depth in each area is most popular in Japan. This map is preparedby municipalities and obligated to make under Flood Control Act. Also thismap shows information about flood prevention and location of evacuation
centers. Figure3 shows a hazard map in SUMIDA ward in Tokyo Prefecture,
Japan.
However a hazard map has following problems.
• Alteration of flood with time history is not shown.
• It is difficult to understand real inundation depth.
• It is difficult to understand time to start evacuation and route toevacuation center.
• Suitable evacuation according to types of housing such as a singlefamily house or a collective housing is not properly instructed
separately.
In order to solve these problems, 3D viewer of flood disaster risk wasdeveloped using VR space. Users can watch flooding condition varied with
time-history from both bird’s eye views and from views on ground level.
Therefore, users can experience flood disaster with close realistic situation.
Also, this system can help to understand difficulty in evacuation realistically.
This function leads proper evacuation for residents. Figure 4 shows the
proposed functions to be developed in the 3D viewer for solving current

Development ofDevelopmentof 3D
3D viewerviewer ofof flood
flood disasterdisaster risk
risktotoenhanceenhanceevacuation
evacuationcapacity
capacityofofresidents
residents

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problems of a hazard map.

Figure 3: Hazard map in SUMIDA ward
Problem of a hazard map

Proposed solution

・ Alteration of flood with time history is notshown.

・animation display(flood varied with time-history)

・It is difficult to understand real inundation
depth.

・3D display,
Display of difficulty in evacuation

・It is difficult to understand timing to startevacuation and route to evacuation center.

・3D display, walk-through,animation display, bird’s eye views

・Some types of evacuation is not shown
depending on types of housing such as singlefamily house or collective housing.

・walk-through, animation display,
3D display

Figure 4: Proposed functions to be developed in the 3D viewer
4. DEVELOPMENT OF 3D VIEWER OF FLOOD DISASTER RISK
4.1 Used data in 3D viewer
As base data of system, 3D urban space data, digital cartographic datasuch as railway and park and flooding simulation data were used. As 3D
urban space data, Map Cube (published by CAD CENTER CO.,Ltd), which
was built up with high-accuracy laser ranging data constructed by PASCO
Co.,Ltd and 2D map provided by INCREMENT P Co.,Ltd, was used.

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Figure5 shows formation of Map Cube and Figure 6 shows VRML data ofrailway, station and surface of water in Koto Delta.
high-accuracy laser ranging data

3D urban space data

2D mapFigure 5: Formation of Map-Cube

Figure 6 : VRML data of railway, station and surface of water in Koto
Delta
Ministry of land, Infrastructure, Transport and Tourism performed
flood simulation in Arakawa-river. In this simulation, amount of rainfall
which might occur once in 200 years was assumed. This simulation dataconsists of inundation depth, velocity and hydrodynamic power and meshsize is 125 meter. Although urban space data and digital cartographic data
are static data, flood simulation data varied with time-history is a dynamic
data.

Development ofDevelopmentof 3D
3D viewerviewer ofof flood
flood disasterdisaster risk
risktotoenhanceenhanceevacuation
evacuationcapacity
capacityofofresidents
residents

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4.2 Methodology
4.2.1 Difficulty in evacuation at the flood disaster
Although inundation depth, velocity and hydrodynamic power areimportant to understand flood risk, it is difficult to judge whether people canevacuate during inundation or not. In this research, difficulty in evacuation
was determined by comparing inundation depth to maximum depth forwalking calculated by equation (1). Figure 8 shows the area where adultmale can’t walk after flood occurs.
(1)h L = 0.7 × (1－u/2.5)
h L : maximum depth for walking (m)，u：velocity(m/s)
maximum depth
depth forfor walking(m)walking(m)maximum

11

The
The areaarea where
where people
people can’t
can’t walk
walk

0.9
0.9
0.8
0.8

Velocity (m/s)

0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
00
00

0.5
0.5

11

1.5
1.5

22

2.5
2.5

Velocity(m)Velocity(m)Figure 7: Relationship between maximum depth for walking and velocity(adult male)

084
3
84
421
41
21
42
-4
02
40
4
25
-7
1
71
97
98
-1
47
66

昼
��
�/ ��
Day
population

Whether people can walkor not

歩行可能��
possible
歩
行可能
impossible
歩行不可能a) 1 hour laterb) 6 hours laterc) 24 hours later
Figure 8: The area where it is impossible to walk (adult male)

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4.2.2 Import of used data to 3D system
In order to combine all the data in 3D spaces, all data were needed tobe converted to VRML (Virtual Reality Modeling Language) format andthen imported to 3D spaces developed by “Omega Space” which is software
by Solid Ray Corporation. VRML is a standard file format for representing
3D interactive vector graphics. Both dynamic and static data were layered in
3D spaces. 3D viewer system can show these VRML data according to time
history. Figure 9 shows formation of system.
3D urban space data
(static data)

Digital cartographic data suchas railway and park (static data)

Flooding simulation
data (dynamic data)

Layering these 3 types datain same space

Overhead view

Regional walk-throughFigure 9: Formation of system
5. EXAMPLE OF SCREEN IMAGES BY 3D VIEWER
Figure 11 and Figure 12 show inundation depth on the 3D viewer. Theses
3D images can be projected on the screen. People can experience 3D
simulation images with special glasses. In this research, compact 3D
projector “Sight3D” (Figure 10) was used for projection. This projector has
some merits that it can project 3D images without a special screen and it isportable as well. Figure 11 is a view without building images. Legend ofinundation depth is shown on the lower right corner of screen and speed ofplaying and elapsed time are shown on the upper right corner. Part of aquaon the upper side of screen shows surface of river. As shown in figures 11
and 12, people can view the city from bird’s eye location and can watch
flooded condition varied with time-history. By watching the flooding
situation, user can know which buildings will be inundated. Figures 13 and
14 are views on the ground level. By using walk-through function on thisscreen, people can know inundation condition to the nearest evacuation
center and change in inundation depth with time history.

Figure 10 : 3D projector and eyeglasess

Development ofDevelopmentof 3D
3D viewerviewer ofof flood
flood disasterdisaster risk
risktotoenhanceenhanceevacuation
evacuationcapacity
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Figure 11: Inundation depth (without buildings)

Figure 12: Inundation depth (with buildings)

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Figure 13: View from ground level (before flood)

Figure 14: View from ground level (after flood)
6. CONCLUSIONSIn this research, 3D viewer of flood disaster risk was developed using VR
space to fulfill deficiencies in current flood hazard maps. In addition to thecurrent functions, several new functions which lead proper evacuation by
resident are required to be imported in this system. In the future study, effectof the system should be evaluated through workshop with residents,.

Development ofDevelopmentof 3D
3D viewerviewer ofof flood
flood disasterdisaster risk
risktotoenhanceenhanceevacuation
evacuationcapacity
capacityofofresidents
residents

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REFERENCES

2.pdf,

Cabinet Office, Japan,
http://www.bousai.go.jp/jishin/chubou/suigai/100402/100402_shiryo_

2010, 4, 39-41.
Bureau of Urban Development Tokyo Metropolitan Government,
Survey on Land Use in Tokyo Metropolitan Area.
Kyozo SUGA，Preliminary Study on Feasible Safe Evacuation in
Flood Disaster, Annual Journal of Hydraulic Engineering, 1995, 2, 879-882

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NewSukhothai flood analysis and its response
under climate changes
Patinya HANITTINAN1, Anurak SRIARIYAWAT2,
and Sucharit KOONTANAKULVONG3
1
Graduate Student, 2 Instructor, 3 Associate Professor,
Department of Water Resources Engineering, Faculty of Engineering,
Chulalongkorn University, Thailand
Anurak.s@eng.chula.ac.th
ABSTRACTYom Basin is one of four main tributaries of Chao Phraya River where is amain rice bowl for Thailand food and export production. Besides, the Yom
Basin is the only basin which has no large scale dam that can regulate thewater flow during whole year. Therefore, flood and drought phenomena arecommon for this basin and cause regular damages to the farmers andcommunities. During year 2010, Sukhothai Province had suffered bothdrought and flooding events in the same year and caused the insecured
situation for local authorities. Although, the authorities concerned hadstudied and set up flood mitigation schemes for the area, the impact ofclimate change may cause changes in flow patterns, quantities andintensities in the area. These proposed schemes may not be adequate totackle the flooding.
In this study, the Sukhothai flood in Yom Basin is reviewed and simulatedwith calibration and verification from the past events. Future climate
scenarios are setup using downscaled and bias corrected MRI-GCM, andthen flooding phenomena in near and far future are simulated to see theimpact of climate change towards runoff, water level and flooding duration.
The present flood mitigation schemes will be assessed by simulation andflood damage in the past. Moreover, the field questionnaires are conducted
to investigate the perception and adaptation opinions from farmers,
municipal citizen, and concerned authorities. The information from fieldsurvey will be used for simulation to investigation the proper adaptationsuggestions for future.
Keywords: Sukhothai flood, climate change, adaptation, perception
1. INTRODUCTION
Thailand is located in the southeastern region of Asia, where now is facing
challenge from climate change including rising sea level, shifts of weather
pattern and occurrence of extreme event such as floods and droughts. The
range of temperature variation from climate model projected that mean
temperature; precipitation and runoff in year 2100 for this part of the world3991

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are found to be 1.0 to 4.5 °C, -20 to +20 %, and -10 to +30%, respectively(IPCC, 2007). This kind of change on climate characteristics will directly
affect to hydrologic system, reservoir operation and water management inbasin scale. The rainfall and runoff tend to increase and decrease in someareas. Changing rainfall pattern of upper watershed has so many effects; forinstance, rules of reservoir operation must change in order to practically
response to the climate change. Consequently, water demand for eachactivity in the downstream also faces considerable uncertainties in the future
and availability of water supply, particularly in the irrigation system.
Furthermore, flood management in wet season has to be changed.
Obviously, reservoir operation in the future will be more difficult to manage
due to the risk of natural disaster, climate uncertainty and complexity ofsocial and economic benefits.
Sukhothai, a province in lower part of the northern Thailand, is also aflood-prone area due to the characteristics of Yom River and the floodplainarea. Effects of climate change are anticipated to cause more loss anddisaster in this area. Even though the existing flood mitigation system
operated by the Thailand’s Royal Irrigation Department (RID) is already inplace, it might not has a sufficient capacity to response to extreme flood in
the future. The alternative adaptation measures should be consideredaccording to the changed magnitude of flood for the possible event.
This study aims to investigate the effect of climate change to flood
situation and flood management in Sukhothai province. The guidelines offlood mitigation including both structural and non-structural measures undereffects from climate change are suggested in this study in order to be theexamples for adaptation.
2. STUDY AREA
The coverage area of Sukhothai province is about 6,596 square kilometers
where 99.7% locates in the Lower Yom River Basin or 26.9% of the wholearea of the Yom Basin. Sukhothai is located in the valley of the Yom Riveron the lower edge of the northern region as shown in Figure.1. Yom River
Basin has the total catchment area of 23,616 km2, and the main channel runs
down a steep valley before passing through Song, Den Chai, and Sung Men
districts, Phrae province. Then, the river flows westward through the valley
passing Long and Wang Chin districts, and continues southward to a plain
in Si Satchanalai district, Sukhothai province. The average annual income ofpeople living in Sukhothai province is the lowest province in the northern
region of Thailand. It was lower than the median income of USD 500 with
40.3% of 602,813 provincial populations.

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3. FLOOD IN SUKHOTHAI
3.1 Cause of flood
The Royal Irrigation Department of Thailand (RID) reported that in2006 the total flooding area was 1,189.55 km2. More than 30 days
inundation areas were found in Kong Krailat district, Muang Sukhothai
district, and Sri Samrong district, and the total loss is more than 5 million
Dollars (RID, 2006). In general, cause of flood in the Yom river basin
comes from many reasons that are heavy rainfall in the basin andexacerbated by deforestation, inadequate water storage for flooding
retention in the upper watershed, ineffective drainage capacity due toshallow river bed and small cross section, and land-use changes. Moreover,the shape of the river itself cause some flood problems, because the crosssection of Yom river at the upstream of Sukhothai border with Phrae
province in Srisatchanalai and Sawankhalok districts is larger than that at
the main stream in Srisamrong and Muang Sukhothai districts and that at
downstream border of Phitsanulok province in Kongkrailart district. Thiskind of “bottleneck” leads to drainage problem during the extreme flood.
Flooding in the basin usually takes place in Sri Samrong, Sri Satchanalai,
Muang Sukhothai and Kong Krailat districts during the South-western
monsoon season, from July to September, leading to huge losses inagricultural and residential areas along the Yom River.

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Figure 1: Sukhothai province and Yom river basin
3.2 Present flood mitigation in Sukhothai province
In the present day, RID plans and implement the flood mitigation
measures based on recorded hydrological data. The components of thesestructural measures are Thung Taleluang and Bung Yai retention ponds,
Yom-Nan diversion canal, Klong Hok Baht canal, and levees along Yom
River. The core principle of these measures is mainly for protection of highdensity business and residential area in Sukhothai municipality in order toreduce flood volume and level as much as possible before it reaches the city,
by bypassing the flow of water to both sides of the Yom River as shown theschematic in Figure 2.
Current practice of flood management is largely considered in an
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lacks of non-structural measures and does not taken the effect of flood
volume to lower Chao Praya basin into account. Therefore, the important
issue is an assessment of the mitigation capacity that could response to theclimate change in the future.
Yom River is the only main river system in Thailand that still has nolarge reservoir in the upstream section. However many feasibility studies ofthe large dam, Kang Seu Ten dam, for mitigation flood had been conductedso many times since the 1970s by many organizations such as RID,
Electricity Generating Authority of Thailand (EGAT), Howard Humphreys
and Sons consultancy, the project is still put on hold because of the
difficulty of negotiations between government and stakeholders.
RID (2001) focused on the response of Kang Seu Ten dam to 1995
flood (1st August – 31st October 1995) and found that Kang Seu Ten dam isable to reduce flood level and duration in upper Yom river basin, and theefficiency of dam is gradually decreased by the distance. The maximum
discharge would be reduced by 1,452 CMS or 74.19%, and the maximum
water level would be decreased by 5.7 m; whereas, the maximum discharge
and water level at Y.17 station, Sam Ngam district at Phichit province,
would not have any significant changes. Taesombat (2001) analyzed theflood mitigation potential of Kang Seu Ten reservoir and found that it would
reduce the peak discharge on the downstream by 20.68 – 94.55% forrecurrence interval range 2 – 10,000 years.
Thiramanus (2004) conducted a study about effectiveness on flood
mitigation of Kang Seu Yen reservoir, using a river analysis simulation by
HEC-RAS model from dam site to Pho Talae district at Phichit province.
This study conducted in six different alternatives, no reservoir, reservoir
capacity at 400, 800, 1,200, and 1600 MCM, and a very large reservoir(without releasing water). The results showed that, Kang Seu Ten reservoir
has a capacity to decisively alleviate flooding from downstream of dam site
to Muang Prae district and also quite effective for reducing flood at
Sukhothai province, if very large reservoir scenario is implemented, it will
help reduce a frequency of occurrence of flooding from 2 times in 3 years to
1 time in 6 years. At the downstream section, the effect of reservoir isdisappeared. Moreover, this study found that the flood return period at
Sawan Kalok district in Sukhothai will increase from 1.7 to 3.6 years and 10
to 12.5 years at Sam Ngam district in Phichit, when Kang Seu Ten reservoir
had 1,200 MCM capacities (same size as RID study).

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Figure 2: Schematic of existing flood mitigation measures in Sukhothai
4. METHODOLOGYThis study starts from the past investigation (year 2002 and 2006) by using
river analysis model, HEC-RAS v4.1. The 2006 flood is chosen for model
calibration and used as representation of a natural case of Yom River during
wet period, while that of 2002 is used for validation. The daily streamflow
data at Y.16 and Y.6 stations from 1st August to 31st October is used insimulations. Furthermore, this study also simulated 2011 flood from 26 June
to 30 June 2011 by using hourly stream flow data provided by RID of
Sukhothai province to investigate the effect of present structural measures.
The second part of this study aimed to simulate future flood conditions inyear 2019 and 2022 by using data from Japanese MRI rainfall model. At thesame time, the field questionnaires are conducted to investigate theperception and adaptation opinions from farmers, municipal citizen andconcerned authorities towards future flood adaptation. The present flood
mitigation schemes are generated from the past flood simulation. The

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information from field survey will be simulated to illustrate proper
adaptations in the future.
5. MODEL SIMULATION
5.1 Calibration and Validation
In this study, Manning’s n roughness coefficient is a main parameterfor calibration. This parameter depended on many factors that are surface
roughness of the river bed, effect of vegetation, channel irregularity, channelalignment, silting and scouring, obstruction, size and shape of channel, stage
and discharge (Chow, 1958). It is a major parameter that determines
discharge of flow in natural channel; therefore, trial and error method ischosen to perform this task.
The calibration and validation results are evaluated from twoparameters; i.e. normalized root mean square error (NRMSE) andcoefficient of determination (R2). From the calibration case (2006 flood
event) as shown in Figure 3, there are NRMSE = 0.096, 0.081 and R2 =0.887, 0.850 for Y.16 and Y.6 station respectively. For the validation caseof year 2002, it shows the value of NRMSE = 0.062, 0.074 and R2 = 0.860,
0.875 for Y.16 and Y.6 station respectively. These results are very good
agreement with the observed data; therefore, it could be implied that theroughness coefficient in main channel, left overbank and right overbank,which are used in model (n varied between 0.032 – 0.041), could be
represented the behavior of flood in this study area.
5.2 Recent flood cases without flood mitigation measures
In the past, Sukhothai province encountered extreme flood in 1995,
2002, and 2006. Since there are no flood control structures such as Ban
Hatsapanchan gate, Thung Taleluang retention pond and Ban Yangsai sluicegate in the past, Sukhothai province faced with province-wide, month-longand devastating consequences on agricultural area in Sawan Kalok, SriSamrong, Kong Krailat districts, and Muang Sukhothai Municipal area. Not
only the overbank flow from the main Yom River, but the lateral flow fromMae Mok and Mae Rumpan subbasin also caused flood in Sukhothaiprovince. Both sources of water generated flash floods from upstream,
which is notoriously dangerous and hard to manage in an emergency
situation.
Since 2007, RID has already implemented some structural measures
as described in Figure 2. In order to investigate the effectiveness of thesemeasures, the comparison between with and without measures is simulated
by using 2011 flood events. As the results, these flood measures canactually reduce peak discharge at Y.6 and Y.3A station by 5.78% and 3.27%,
respectively as shown in Figure 4.

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a) a)

b) b)

d) d)
c) c)
FigureFigure3: calibration
3: calibration
and andverification
verification
resultresultfromfrom
two tworiverriver
gauge
gauge
stations.
stations.

a) a)

b) b)

FigureFigure4:Effect
4:Effectof mitigationof mitigation
measuresmeasuresto flood
to floodhydrographhydrographat Y.6at andY.6 and
Y.3AY.3A
stations
stations
for 2011
for 2011
floodfloodcase.case.
5.3 Future
5.3 Future
flood
flood
cases:
cases:
concerning
concerning
impactimpactof climateof climatechangechangeFor Forthe future
the futurescenario,
scenario,
MRI-GCM
MRI-GCMrainfallrainfall
model
model
is usedis usedto forecast
to forecast
futurefuturerainfall.
rainfall.
It showed
It showedthat thatrainfallrainfallin Sukhothai
in Sukhothaiareaarea
will will
increaseincreasearoundaround20%20%
and and
39%39%
in 2019
in 2019
and and2022,
2022,
respectively
respectively(Chaowiwat,(Chaowiwat,2010);
2010);
then,then,
the therainfallrainfalldatadata
is usedis usedto calculate
to calculate
the future
the future
floodflood
runoffrunoffby rainfall-runoff
by rainfall-runoff
model
model
(HEC-HMS(HEC-HMS
model).
model).
As theAs results,
the results,
the flood
the flood
volumevolumeat Y.14
at Y.14
and and
Y.33Y.33
stations
stationsin thesein these
two twoyearsyears
will will
increaseincrease
by by
13%13%
and and29.4%
29.4%
respectively
respectively
as shown
as shown
in Tablein Table
1; thus,1; thus,this thiscan canbe impliedbe impliedthat thatflooding
flooding
in in
SukhothaiSukhothaiprovince
provinceis havingis having
an upward
an upward
trendtrend
and andneedneedmoremoremitigation
mitigation
measures.
measures.

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Table 1:
Table
Summary
1: Summaryof futureof flood
futurerunoff
flood runoff
in yearin2019
yearand20192022
and 2022

Station Station
Maximum
Maximum
Maximum
Maximum
Difference
Difference
Maximum
Maximum
Difference
Difference
discharge
discharge
discharge
discharge(%)(%)discharge
discharge(%)(%)
in 2006 in 2006in 2019 in 2019in 2022 in 2022
(CMS) (CMS)(CMS) (CMS)(CMS) (CMS)
Y.14 Y.14
2,044 2,044 2,471 2,471 17.28 17.28 2,567 2,567 20.37 20.37
Y.6
Y.6
2,171 2,171 2,592 2,592 16.24 16.24 2,648 2,648 18.01 18.01
Y.3A Y.3A 1,568 1,568 1,908 1,908 17.82 17.82 1,974 1,974 20.62 20.62
Y.4
555 665665 16.54 16.54 749
749 25.90 25.90
Y.4
555

Although,
Although,
RID hasRID
already
has already
implemented
implemented
some structuralsome structural
measuresmeasuresasas
described
described
in Figurein Figure2, the 2,
whole
the wholeprojectproject
did notdidcompleted.
not completed.
In orderIn toorder toassess assess
the future
the future
situation,
situation,
this study
this does
study two
doestypes
two oftypes
simulationof simulation– no – nostructural
structural
measuresmeasuresand completionand completionof RIDof whole
RID wholeplannedplannedmeasuresmeasuresincludingincludingwith Ban
withHat
BanSapanchan
Hat Sapanchan
gate andgateThungand ThungTaleluang
Taleluang
2 retention
2 retention
pond. pond.
From Fromthe simulation
the simulation
using using
river analysis
river analysis
model model(HEC-RAS),(HEC-RAS),
the themaximum
maximum
discharge
discharge
at Y.6 atand
Y.6Y.3A
and stations
Y.3A stations
are projected
are projected
to increase
to increasebyby
5.77% 5.77%
and 1.37%,
and 1.37%,
respectively,
respectively,
for thefor2022
the flood2022 casefloodofcase
onlyofclimate
only climatechangechange
effect effect(no structural(no structural
measures).
measures).
For anotherFor anothercase ofcase2022
of flood
2022 flood
scenario,
scenario,
the whole
the wholesystemsystemof structuralof structural
measuresmeasurescan reduce
can reduce
the peakthe peakdischarge
discharge
by 4.67%
by 4.67%
and 4.32%,
and 4.32%,
respectively
respectively
as illustrate
as illustrate
in Figurein Figure
5.
5.

a)
a)
b)
FigureFigure
5: effect
5:of
effectmitigationof mitigation
measuresmeasuresto floodtohydrographflood hydrographat Y.6 andat Y.6
Y.3A
and Y.3A
stationsstationsfor 2022
forflood
2022case
flood case
6. FIELD
6. FIELDQUESTIONNAIRESQUESTIONNAIRESIn thisInstudy,
this study,
120 field
120questionnaires
field questionnaires
were conducted
were conducted
at fouratplaces;
four places;
i.e. i.e.
Kong Krajong
Kong Krajong– Sawan– Sawan
Kalok Kalok
district,district,
PakpraPakpra– Muang– Muang
SukhothaiSukhothai
district,district,municipal
municipal
area ofarea
Muang
of Muang
SukhothaiSukhothai
districtdistrict
and KraiandNai
Krai– Nai
Kong– Krailat
Kong Krailat
district.district.
This helps
This thehelps
researchers
the researchers
to know
to aboutknow people’s
about people’s
perceptions
perceptions
and andtheir opinions
their opinionsof floodof adaptation
flood adaptation
for future
for future
extremeextremeevent due
event
to dueeffectto ofeffect ofclimateclimatechange.change.
ResultsResultsfrom questionnaires
from questionnaires
showedshowedthat thethatpeople
the people
requestrequest
the thegovernment
government
to tackle
to tackle
a problem
a problemof deforestation,of deforestation,
to construct
to construct
the Kang
the Seu
Kang Seu
Ten damTenanddamsmalland damsmallalong
dam along
the Yom
the River,
Yom River,and toandperform
to perform
channelchannel
dredging
dredging
in terms
in termsof floodof mitigation.
flood mitigation.
For flood
For adaptation
flood adaptationside, mostside, mostpeoplepeople
still embraces
still embraces
the idea
theofidea“top-downof “top-down
approach”,
approach”,
which which
relies mostly
relies mostly

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from government projects, such as construction more levees, dikes,
retention ponds, and new drainage canals (floodways). Nevertheless, thelocal people also adapt themselves to flood mitigation by using sandbags toheighten the levees, changing cropping pattern, and reducing an erosion ofriver bank by planting vegetation.
7. CONCLUSION
Climate change is going to increase an amount of flood volume in Yom
River at Sukhothai province in the future. Results from simulation also
carried out and showed that it can reduce maximum runoff at the Yom rivergauge stations Y.3A and Y.6, when whole structural measures are alreadyconstructed. However only the structural measures are not completely
sufficient for solving flood problems, non-structural measures are stillrequired as recommended from the field survey results. Therefore, this study
suggests the flood adaptation measures, both structural and non-structural
measures, should be implemented as followed:
1) Fully construct and operate Thung Taleluang 1 & 2 retention
ponds (with fully-functioned drainage canal and gate).
2) Construct new drainage facilities to accelerate flood inside
Sukhothai municipal.
3) Assign the right side of Yom River as “flood-plain” area.
4) Construct and maintain levees, dikes and gabions, which protect
the city from overbank flow.
5) Promote concept of “living with flood” to Sukhothai people –design a sensible system of flood compensation, such as flood
insurance, if possible.
6) Reform land-use and flood zoning regulations.
7) Develop more sophisticate and responsive flood warning system,and strengthen cooperation between central and local
government officers during crisis period.
ACKNOWLEDGEMENT
The study cannot be conducted without the data provided from various
agencies, e.g., Royal Irrigation Department, Department of Disaster
Prevention and Mitigation, etc. This project, CC522A, has been supported
in part with National Research Universities fund from Office of Higher
Education Commission (OHEC), Ministry of Education and theassistantship for researcher of the study was funded by UNU-ISP. The
researchers would like to gratefully thank to Miss Mada Iaumsupanimit,
Research Assistant at Water Resources System Research Unit
(CU_WRSRU) for her tireless work that helps us so much.

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REFERENCES
Chaowiwat, W. 2010. The Adaptation Response for FloodManagement, Case Study in Sukhothai Province in Thailand, conference
paper of UNU CSDS-IACC project.
Chow, V. T., 1958. Open Channel Hydraulics, McGraw-Hill College,
Singapore
Hanittinan, P., 2011. Flood Analysis and mitigation measures in
Sukhothai province, UNU seminar on National workshop: Comparative
Studies on Strategies to adapt for the Natural Disasters Due to Climate
Change in Thailand, Khon-Kaen University, Khon-Kaen.
IPCC, 2007. Summary for Policymakers. In: Climate Change 2007:
The Physical Science Basis. Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on Climate Change[Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt,
M.Tignor and H.L. Miller (eds.)]. Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA
Kalonsri, P. 2011. Research about Kang Seu ten project (Thatpolitician doesn’t want to know), Bangkok
Koontanakulvong, S., 2010. Thai Climate Change and its Impacts
towards Water Sector, Water Resources Research System Research Unit,
Bangkok.
Koontanakulvong, S., et.al., 2010. The corrected MRI-GCM data for
Thailand, Technical Report, Chulalongkorn University, December.
RID, 2001. Feasibility study report of Kang Sei Ten project Prae
Province, Vol.2, Bangkok.
Sriariyawat, A., 2011. Ensuring Flood Security in Sukhothai province,
UNU seminar on National workshop: Comparative Studies on Strategies toadapt for the Natural Disasters Due to Climate Change in Thailand,
Chulalongkorn University, Bangkok.
Sriariyawat, A., 2011. Social Responses and and Flood Adaptation in
Sukhothai Province, UNU seminar on National workshop: Comparative
Studies on Strategies to adapt for the Natural Disasters Due to Climate
Change in Thailand, Khon-Kaen University, Khon-Kaen
Taesombat, V., 2001. Flood mitigation potential in upper Chaopraya
river basin of large and medium-sized reservoir. Final report, Bangkok.
Thiramanus, R. 2004. Effectiveness on Flood Mitigation of Kaeng
Sua Ten Reservoir, Faculty of Engineering, Chulalongkorn University,
Bangkok

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Preparing water supply master plan
for a newly declared city lacking land use
guidelines and demographic information
Mustafa T. HASAN1 and Mahmud R. AMIN2
Junior Engineer, Institute of Water Modelling, Bangladesh
mth@iwmbd.org
2
Junior Engineer, Institute of Water Modelling, Bangladesh
1

ABSTRACT
Urbanization proceeds gradually in developing countries with thecommencement of industrialization, most likely without proper land use
master plan. An adequate land use master plan provides required guidelines
and specifications for the preparation of additional master plans regarding
urban utilities. Preparing a water supply master plan for a growing city
without proper land use master plan is a complex task for the engineers andplanners. Particularly, assessment of water demand and computation of
nodal demand is very difficult for a newly declared city enclosed by anadministrative boundary different from the former judicial urban growthcentre boundary because of insufficient primary & secondary data andunavailable land use guidelines. This paper presents a simple methodology
to assess the demand for such an area where no primary demand data isavailable and thus demand has been assessed based on secondary data andconsequently the nodal demand for the Water Distribution System (WDS)
has been computed. Alamdanga Paurashava of Chuadanga district ofBangladesh has been taken as the case study area where no piped watersupply exists currently. The demand assessment has been made analyzing
the demographic data with the help of land use map using ArcGIS toolkit.
For the population projection, census report data has been used. From the
GIS land use map, build up area has been assessed and projected for future.
By using these analysis results, demand with future projection has been
determined. Thus this paper actually presents a methodology for preparing
a WDS master plan of a newly declared city lacking sufficient land use planand data support.
Keywords: master plan, water supply, water demand, population projection,
GIS
1. INTRODUCTION
Being one of the most densely populated agriculture based rural dominating
country; Bangladesh has vast scope of urban growth. Over the last 3 decades,
due to the increment of population and increasing demand for improved life
style, rural areas are being diminished rapidly and transferred to urban areas.
This extensive urbanization is creating demand for various urban facilities.

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Among those, safe water supply thorough pipe network is a priority issue in
urban areas of Bangladesh. Presently about 28% of the urban population
still do not have access to safe water.
Under the above circumstances, Dept. of Public Health Engineering(DPHE) has taken up the project in hand, titled “Groundwater Management
and TPP for Survey, Investigation, and Feasibility Study in Upazila and
Growth Center level Paurashavas having no Piped Water Supply System”.
The project is very much relevant to The National Policy for Safe Water
Supply & Sanitation 1998 of the Government of Bangladesh. Institute of
Water Modelling (IWM) has been employed in the project for“Mathematical Modelling for Safe Drinking Water Source Identification”.
While performing the project activities, a unique method has beendeveloped for preparation of a water supply master plan in a city or small
town lacking adequate primary and secondary data such as proper land use
policy and demographic information. Since, the traditional population basedor modern land use based demand calculation approach is insufficient, acombined population and land use based demand calculation approach has
been adopted. The authors are directly involved in the project and haveillustrated a further modified computation technique in this paper.
2. STUDY AREA
Alamdanga Paurashava is the only municipal area of Alamdanga Upazila of
Chuadanga District. It is located in 23°45' N latitude and 88°56' E longitude.
The smallest administrative unit of a Paurashava is a ward and presently,
Alamdanga Paurashava is divided into 9 wards. The Paurashava has goodroad connections to Dhaka (capital of Bangladesh) and other neighbor
districts and regional centers. Activities related to trade and commerce are
increasing day by day and now it is emerged as one of the few A classmunicipal areas of Bangladesh. Though Alamdanga is a Class A
municipality, till the initiation of the aforesaid project, there was no pipedwater supply scheme in this Paurashava. According to the projectrequirements, the whole municipal area has been modeled for pipe watersupply network coverage for the year 2040. The proposed master plan will
be implemented in three phases commencing from the years 2010, 2020 and
2030, considering water demand for the years 2020, 2030 and 2040
respectively.
3. METHODOLOGY
3.1 Data collection
Two types of data are required for the preparation of a WDS masterplan- spatial and non spatial data. Spatial data consists of the following GIS
based maps of the Paurashava under consideration:

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i. Topographic map,
ii. Physical map, andiii. Road network map.
Topographic survey was conducted in the baseline year 2010 byInstitute of Water Modelling (IWM). All the survey data were processed
and analyzed with the help of ArcGIS toolkit and corresponding maps statedabove were produced. Digital format of the maps have been utilized in thisassignment in the form of shape files (.shp extension).
Demographic data is the only non spatial data input here. Population
data of the years 1981, 1991 and 2001 have been collected from the
population census report of Bangladesh Bureau of Statistics (BBS).
Population census data of 2011 is not published yet. Therefore, population
for the baseline year 2010 has been collected from the Social Impact
Assessment (SIA) Survey, 2010 conducted by Farhat Consultants to fulfill
the project requirement.
3.2 Population projection
Conventional population projection methods require past population
data for forecasting of future population. The administrative boundary of the
Paurashava under interest needs to be constant throughout the census years
under consideration. But for a newly established Paurashava it is very
complex task to extract the previous year’s population data while the town’s
administrative boundary didn’t exist at all. In Bangladesh population census
reports, the smallest unit of area for which the population data is available is“mouza”. Therefore, the mouzas contributing to the whole Paurashava area
have been identified at first. Then the population data of respective mouza issummed up to build up the Paurashava population for each census year.
Thus the population data of the Paurashava for each census year are
extracted.
Alamdanga Paurashava was established in 1985. So the population
census data of 1981 is unavailable for the Paurashava area. The procedurestated above is applied to extract the population of Alamdanga in 1981.
‘Geometric progression method” or ‘compound rate of growth method’,
proposed by Hardenberg is adopted for population projection; since it is themost commonly used and efficient method for growing cities and areas
which have vast scope for extension (Ahmed and Rahman, 2003).
Pf = Pp (1+r) n(1)

where Pf = future population; Pp= present population; r = rate of yearly
population growth and n = number of years to be considered.
nP�� � 2� �
P1

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where P1 and P2 are the population data of two dates of n number ofyears apart.
Obviously the annual population growth rate r is not constantthroughout the years under consideration. For computation purpose, theauthors have assumed that the annual growth rate is constant over anindividual census decade. Growth rates for census decade 1981-1991 and1991-2001 are 2.72 and 2.63 respectively. Adopting SIA survey of 2010,
growth rate for 2001-2010 has been calculated as 2.19. According to theassumption of constant annual growth rate in a census decade, growth rateof 2001-2011 can be adopted as the same as growth rate of 2001-2010(Table 1).
Table 1: Growth rate calculation for census decades

Year
PopulationGR
1971-1981
15,941
1981-1991
20,858
2.72
1991-2001
27,0402.63
2001-2010
32,858
2.19
2001-2011
33577*
2.19*projected population adopting same growth rate as of 2001-2010

Next step is to find out the projected growth rates for 2011-2021,
2021-2031 and 2031-2041. Various methods are available for growth rate
projection such as Exponential (Y = a ebX), Logarithmic (Y = a + b log X),
Semi-log (log Y = a + bX), Reciprocal (1/Y = a + bX), Power (Y = aXb)functions etc. The best equation can be identified on the basis of statistical
criterion like mean square error, mean absolute error, coefficient ofdetermination (R2), standard error of the estimate and significance of theregression coefficients. Here, we shall restrict ourselves to the straight line
method popularly known as ‘method of least squares’ or ‘line of the best fit’.
The method can be used independently when detailed information is notavailable (Mehta, 2004).
The general form of the equation of least square method is:
Y = a + bX

(3)

where Y= required variable to be projected (here, annual growthrate), X= no. of years, a = constant and b = slope of the regression line.
To compute the values of the constants of equation (3), the following
equations are used:∑X = Na + b.∑X

(4)

∑XY = a.∑X + b.∑X2(5)

where:
ΣX = the sum of all observations of X,
ΣY = the corresponding sum of all the Y observations,

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ΣXY = the sum of all the products of X and Y,
ΣX2 = the sum of all the squares of X and
N = total number of observations
Table 2: Growth rate projection based on ‘method of least squares’

Year

(1)
1981-1991
1991-2001
2001-2011
Total

Rate of Growth (%)
(Y)
(2)
2.72
2.63
2.19
(ΣY) 7.54

Sr. No. of Col. 1
(X)
(3)
1
2
3
(ΣX) 6

Square of
‘X’
(4)
1
4
9
(ΣX2) 14

X.Y

(5)
2.72
5.26
6.57
(ΣXY) 14.55

Replacing the above values in equation (4) and equation (5), andsolving for a, b; we have got the required growth rate projection equation:
Y= 3.05 – 0.27X(6)Using equation (6), the projected annual growth rate for 2011-2021,
2021-2031 and 2031-2041 are found as 1.98, 1.71 and 1.44 respectively.
These rates have been assumed constant for a decade; therefore can be
adopted as the same for the years 2010-2020, 2020-2030 and 2030-2040
respectively with no considerable deviation in population projection.
Projected population of the Paurashava for the years 2020, 2030 and 2040
are calculated using these growth rates and equation (1).
Paurashava has potential of future extension and it should be taken
into account in population projection by considering the migration of
populace from rural to extended urban areas. No government planning or
policy is available on extension of Paurashava boundary. The authors haveadopted the urbanization rates in Bangladesh from World Urbanization
Prospects: The2007 Revision by United Nations. The urbanization rates areprovided in the report for every 5 years. For computation purpose,
consecutive growth rates are averaged to find out the rates for every 10
years. Extension area is computed by applying these rates into the baseline
year Paurashava area. Assuming the same population density in theextended area as of the Paurashava area, population in the extended area iscalculated and added to the projected population of the Paurashava (Table 3).
For 2001-2010, ward wise population growth rate is calculated basedon ward wise population for the years of 2001 and 2010. These ward wise
growth rates are extended further for 2020, 2030 and 2040 by multiplying
each with a factor so that summation of ward wise population equals withthe projected Pourashava population of the years under consideration. The
multiplying factors should be selected based on baseline population density
in each ward, road network in baseline year, infrastructure development
plan of the government, potential of improvement of living standard in an
individual ward etc. The factored growth rates are then used in ward wise
population projection (Table 4).

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Table 3: Population augmentation for future urbanization

Rate of change of percentage urban (%) 2010-2020(1.86+1.91)/2= 1.89
Paurashava Area (km2)
9.59
Paurashava Population
39,970Population Density (person/km2)(39,970/9.59)=4,168
Extension area (km2)
0.18
Cumulative Extension Area (km2)
0.18
Population in extension area
0.18*4168=755
Total Population(39,970+755)= 40,725

Locality

2010

2020-2030 2030-2040
1.92
1.71
9.59
9.59
47,35854,651
4,938
5,699
0.18
0.16
0.37
0.53
1,804
3,017
49,162
57,667

Table 4: Population projection
2020

2030

2040

GR Population GR Population GR Population GR Population
(%)
(%)
(%)
(%)
Paurashava 2.19 32,858
1.98
40,725
1.71
49,162
1.44
57,667
Ward No. 1 2.19

3,875

2.16

4,797

1.88

5,780

1.59

6,765

Ward No. 2 1.75

3,973

1.68

4,694

1.45

5,423

1.21

6,117

Ward No. 3 1.75

3,399

1.68

4,016

1.45

4,640

1.21

5,233

Ward No. 4 1.75

4,070

1.68

4,809

1.45

5,555

1.21

6,267

Ward No. 5 2.46

4,308

2.37

5,447

2.07

6,686

1.74

7,941

Ward No. 6 2.46

4,456

2.37

5,634

2.07

6,916

1.75

8,222

Ward No. 7 2.85

2,989

2.97

4,007

2.57

5,162

2.15

6,385

Ward No. 8 1.75

2,601

1.66

3,067

1.44

3,537

1.21

3,990

Ward No. 9 2.84

3,187

2.93

4,254

2.53

5,463

2.13

6,746

3.3 Land use classification
Five types of land use categories are considered (Figure 1) andcorresponding per capita water demand are assigned (Table 5) as describedby Ahmed and Rahman (2003).

Figure 1: Adopted land use category

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Table
Table
5: 5:
Land
Land
useusecategory
category
andandcorresponding
corresponding
perpercapitacapitawater
water
demanddemandLandLanduseuseCategory
Category

2 2
Area
Area
(km
(km
) )
2010
2010 2020
2020

Residential
Residential

2.43
2.43 2.43+6.64*20%
2.43+6.64*20%
=3.76
=3.76
0.24
0.24 0.24
0.24
0.25
0.25 0.25
0.25
0.04
0.04 0.04
0.04
6.64
6.64 6.64-6.64*20%
6.64-6.64*20%
=5.31
=5.31

Commercial
Commercial
Public/Institutional
Public/Institutional
Industrial
Industrial
Agricultural
Agricultural

Average
Average
Consumption
2030
2030 2040
2040 Consumption(lpcd)(lpcd)
4.75
4.75 5.75
5.75 100100

0.24
0.24
0.25
0.25
0.04
0.04
4.32
4.32

0.24
0.24
0.25
0.25
0.04
0.04
3.32
3.32

40 40
25 25
1201200 0

It Itis ismore
morejustified
justifiedto toinclude
includethetheagricultural
agriculturalwater
waterdemand
demandinto
intoirrigation
irrigationscheme
schemerather
ratherthan
thanpiped
pipedwater
watersupply
supplyscheme.
scheme.Therefore,
Therefore,perper
capitacapitademand
demandis isnilnilunder
underthisthiscategory.
category.However,
However,forforfuture
futurelandlanddevelopment,
development,
20%
20%
35%
35%
andand
50%
50%
of of
thetheagricultural
agricultural
area
area
areareassumedassumedto tobebetransformed
transformed
into
into
residential
residential
area
area
forforeffective
effectivearea
area
calculation
calculation
of ofthethe
years
years
2020,
2020,
2030
2030
andand2040
2040
respectively.
respectively.
This
This
is is
a conservativea conservative
assumption
assumption
andandyieldsyieldsmore
more
factorfactorof ofsafetysafetyin indemanddemandcalculation
calculation
as asresidential
residential
category
categoryhashasgotgotconsiderable
considerableamountamountof ofperpercapita
capitademand.
demand.The
Theremaining
remaining
agricultural
agriculturalarea
areais isnotnotconsidered
consideredwhen
whencomputing
computingpopulation
populationdensity.
density.
FigureFigure2 2represents
representsactual
actualpopulation
populationdensity
densityvs.vs.population
populationdensity
densityin inbuildupbuilduparea
area
forfordesigndesignyears.
years.

FigureFigure2: 2:
ActualActualpopulation
population
densitydensityvs.vs.
population
population
densitydensity
in inbuildupbuilduparea.
area.
3.43.4Computation
Computation
of of
nodal
nodal
demanddemandTotal
Total852
852nodesnodesareareidentified
identifiedafter
afterdigitization
digitizationof ofthetheproposed
proposedpipe
pipe
network.
network.Commanding
Commandingarea
areaof ofeach
eachnodenodeis isdemarcateddemarcatedbybycreating
creating‘Thiessen‘Thiessen
polygon’polygon’
using
using
ArcGISArcGIS
software.
software.
The
The
approachapproach
of of
using
using
ThiessenThiessenpolygonpolygonforfornodal
nodalarea
areademarcation
demarcationis issimilar
similarto tothetheapproach
approachgiven
givenbyby
LanceyLanceyandandMays
Mays(1989).
(1989).Thereafter,
Thereafter,union
unionof ofward
wardboundary,boundary,Thiessen
Thiessenpolygonpolygonandandland
land
useusecategory
category
is is
done.
done.
This
This
assigns
assigns
ward
ward
wise
wise
population
population
densitydensityandandperpercapitacapitawater
water
demanddemand
of of
each
each
land
land
class
class
into
into
thetheThiessenThiessen
area.
area.
Thus
Thus
a databasea databaseis iscreatedcreatedin inthethe
form
form
of of
shape
shape
filefile
comprising
comprisingof ofallallnecessarynecessary
information
information
forfornodal
nodal
demanddemandcomputation.
computation.

Preparinga water
supplymasterplan
a newlydeclaredlackingland
guidelines
Preparinga water
supplymasterplan
forfora newlydeclared
citycitylackinglanduseuseguidelines
andandPreparing water supply master plan for a newly declared city lacking land use guidelines
demographic
information
demographic
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Figure 3: (a) Nodal area demarcation using Thiessen polygon and(b) Union of Thiessen polygon, ward boundary and land use classes
After union has been done, each Thiessen area segregates into several
undividable segments. Each segment is a part of a distinct ward and denotes
a specific land class. Water demand in such a segment is computed by thefollowing equation:
dsi = Ai × PDi × LPCDi

and
class

(7)

where:
dsi = Water demand in segment i,
Ai = Area of the segment i,
PDi = Population density of the corresponding ward in design year
LPCDi =Liter per capita water demand of the corresponding land
Nodal demand is calculated then using the following equation:ndnj � � dsi
���

(8)

where:
dnj = Nodal demand of node j andn = No. of segments in node j
For each node, percentage of unaccounted for water (UFW) is added.
Since no metered data is available, the required UFW is assumed from trendof other existing water supply utilities in Bangladesh. According to
Bangladesh Water Utilities Data Book, 2008, the minimum UFW isestimated at Chuadanga Paurashava (2.7%) and maximum is estimated at
Gazipur Paurashava (52%). The average UFW in 11 water utilities is 22.5%.
In addition, UFW is expected to increase with aging of pipe network due to8418

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high water loss. Therefore, UFW for Alamdanga Paurashava is assumed
15%, 22% and 25% for design years 2020, 2030 and 2040 respectively.
3.5 Long range water supply facilities planning
The proposed pipe network master plan is to be implemented in 3
phases. For each phase, corresponding nodal demands are summed up tocomprise the total water demand. During 1st two phases, water supply
coverage is proposed to be limited in high density areas only. Water supply
coverage is assumed 65%, 90% and 100% for 1st, 2nd and 3rd phaserespectively. Figure 4 shows projected water demand and demandconsidering supply coverage vs. proposed water supply capability for thementioned phases.

Figure 4: Projected water demand vs. water production capacity
Master plan of water supply facilities of Alamdanga Paurashava isdone for the final phase using modeling software. Then the pipe network is
truncated and tested for former two phases.
4. CONCLUSIONS
Computation of nodal and total water demand is the prerequisite forpreparation of a long range water supply master plan. Combination of
traditional population based and modern land use based approach is used forwater demand projection. This method can predict population of a growing
town despite the movement of the administrative boundary. Future
urbanization prospect of the town is also considered and a feasible
calculation approach is presented. Inclusion of factored growth rate indifferent portions of the town (wards, in case of Paurashava) yields more
control over population density distribution.
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GIS application for land use classification and nodal demand
computation has made the calculation more accurate. Considering buildup
area instead of actual area for population density distribution also
accommodates the future land use transformation accurately.
The methodology described in this paper is very relevant to othergrowing small town or cities lacking land use guidelines and demographic
information. The whole methodology can be programmed in MS Excel and
ArcGIS interface and hence, easily can be updated based on the future
development plan of the town or city.
ACKNOWLEDGEMENTS
The authors would like to particularly acknowledge the continuous guidance
and assistance of Mr. A.K.M Abdus Satter, Senior Pipe Network Modeler,
Comp-I, Mathematical Modelling for safe Drinking Water Source
Identification, DPHE. Mr. Monowar Ali, Project Direcor, Ground Water
Management Project, DPHE is also appreciated for his kind consent to theauthors for this publication .The invaluable support of Mr. Emaduddin
Ahmad, Team Leader, Comp-I, Mathematical Modelling for safe Drinking
Water Source Identification, DPHE and Mr. S M Mahbubur Rahman,
Director, Water Resources Planning Division, IWM will be rememberedwith gratitude. The authors are also thankful to Ms. Tanjia Akter Amy,
Junior Engineer, IWM for her contribution in this particular assignment.
REFERENCES
Ahmed, M. F., and Rahman, M. M., 2003. Water Supply & Sanitation,
Rural and Low Income Urban Communities, ITN-Bangladesh, BUET,
Dhaka.
Mehta, A. C., 2003. Projection of Population, Enrolment and Teacherswith Focus on Elementary Education, NIEPA, New Delhi.
World Urbanization Prospects: The 2007 Revision, United Nations,
New York, 2008.
Lansey, K., Mays, L., 1989. Optimization Model for Water
Distribution System Design. Journal of Hydraulic Engineering, ASCE,
115(10), p. 1401-1419.
Bangladesh Water Utilities Data Book, Ministry of LGRD, GOB andWorld Bank Dhaka Office, 2008

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The major research plan ‘study
on unconventional emergency
management’ in China
Wenguo WENG 1, Hong HUANG2 and Weicheng FAN3
Associate Professor, Institute of Public Safety Research (IPSR),
Tsinghua University, Beijing, China
wgweng@tsinghua.edu.cn
2
Professor, IPSR, Tsinghua University, Beijing, China
3
Professor, Director, IPSR, Tsinghua University, Beijing, China

1

ABSTRACTIn recent years, more and more unconventional incidents were reported allover the world. Unconventional incident is the incident that has no
precursor along with obvious complex characteristics, secondary disasters
and great damages. It is difficult to respond the incident by the conventional
management methods. In order to improve Chinese government’s
emergency management ability, and promote the development of Chineseemergency management science, the National Natural Science Foundationof China (NSFC) launched the Major Research Plan ‘Study on
Unconventional Emergency Management’ in 2008. The research plan aims
to deeply understand the mechanism and provide the approach for the core
parts in the emergency management - warning and response - by integrating
the multidisciplinary observations, experiments and theories; establish theunconventional emergency management theory based on the ‘scenarioresponse’ approach; promote the scientificalness of emergency plan andplatform and establish the multidisciplinary education framework for
emergency management. In this paper, the practical requirements andscience backgrounds of the Major Research Plan are analyzed, the researchtargets and topics are introduced, and some important issues in theimplementation are discussed. The Major Research Plan will provide more
effective and scientific supports for Chinese emergency management.
Keywords: major research plan, unconventional incident, emergency
management, scenario-response, emergency management platform
1. INTRODUCTION
The frequencies and scales of incidents are increasing and enlarging alongwith the development of the society and environmental change all over theworld. Such as, 2011 Japan great earthquake, 2008 Wenchuan earthquake,2005 Hurricane Katrina, 2004 Indian Ocean Tsunami, 2001 USA 911, etc.
They all caused great damages to the society. Many incidents, which arecalled unconventional incidents here, have no precursor along with obvious4211

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complex characteristics, secondary disasters and great damages. It isdifficult to respond the incident by the conventional management methods.
In order to improve Chinese government’s emergency management ability,and promote the development of Chinese emergency management science,
the National Natural Science Foundation of China (NSFC) launched the
Major Research Plan ‘Study On Unconventional Emergency Management’in 2008. In this paper, the practical requirements and science backgroundsof the Major Research Plan are analyzed, the research targets and topics are
introduced, and some important issues in the implementation are discussed.
2. SOCIETY REQUIREMENTS(1) The vulnerability of modern society needs emergency management
Modern society is a coupled system consisting of human and nature. It
has typical characteristics of complex systems. In recent years, thevulnerability of actual society’s system faces serious challenges because of
frequent unconventional incidents. Such incidents are the most urgent
problems of all nations, such as “9•11” in USA, the Tsunami in Indian
Ocean, the massive earthquake in Wenchuan of China and in East-North ofJapan. The enormous damages influenced social and economic development
and even changed the regional political structure and strategy. To improve
emergency management to those unconventional emergencies is a common
demand of all nations including China (Cauchemez, 2008; Ferguson, 2006).
(2) It is necessary to improve the emergency management capability forincreasing government’s capability and building service-oriented
government.
With the rapid development of the economy, Chinese government is
improving economic regulation and market supervision levels, andreinforcing the capability of social management and public service.
Improving the emergency management capability is an urgent demand andan important guarantee to enhance our country’s governance capability andbuild service-oriented government.
Facing to the serious situation of the new type’s incidents, Chinese
government takes improving emergency management policy and responding
various risks effectively as one of the most important tasks for building
harmonious society. In March 2008, Prime Minister Wen Jiabao pointed out
in governmental work report that we should improve the emergency
management system, the capability of emergency prevention and response,
the research of disaster’s characteristics and mechanisms, and the capabilityof disaster prevention and reduction.

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3. SCIENTIFIC BACKGROUND(1) The development of emergency management science needs creative
fundamental research
Emergency management science belongs to risk management science
which has many study foundations. A “prediction-response” managementmode and a “prediction-warning-response-recovery” process have been built.
However, because the evolving mechanism of unconventional incidents islittle known, and the incident situation, possibility and damage degree arelittle recognized, it is difficult to prevent ahead. Therefore, a new or creative
emergency management approach is desired to solve the problem.
The scientific issues of unconventional emergencies management
obviously show multidisciplinary characteristics including decision-making
science, information science, psychology, etc. At the same time, these issues
have the special study boundary conditions. The research of related
disciplines must be built on the foundation of creative academic ideas(Britton, 2000; Gonzalex, 2008; Kossinets, 2006). Developing thefundamental research of unconventional emergency management will
broaden the science thinking of emergency management and form the new
emergency management theories and approaches.
(2) Emergency management science is very important for the developmentof Chinese management science.
• Research of emergency management has been paid extensive
attention since 2003 “SARS” crisis in China.
• Public safety research is taken as one of the 11 most important
areas of Chinese technology development in “Chinese mid-longterm scientific and technology development plan outline”(20062020).
• In “The 11th Five-Year Plan of the National Natural Science
Foundation of China (NSFC)”, public safety is regarded as apriority development field.
Compared to the research in China, international emergency
management research emphasizes more multidisciplinary intersection andderivation-coupling of incidents, especially the relevance between theincidents caused by nature and human (Gerstenberger, 2005; Harraid, 2007;
Topper, 2005). It also emphasizes the influence of the national
characteristics on emergency management.
In brief, to strengthen emergency management researches, innovating
emergency management approaches and increasing the scientificalness of
emergency management works are urgent to all nations. The researches of
unconventional emergencies management are necessary for creatively
developing Chinese emergency management science.

The major
Themajor researchresearch plan
plan ‘study‘study on
on unconventional
unconventional emergency
emergency management’management’ inin China
China

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4. KEY SCIENTIFIC ISSUES AND PURPOSES
4.1 The key scientific issues“Study on Unconventional Emergencies Management” aims to study
on the following three key scientific issues, the framework is shown in
Figure 1.

Application
Issue
Engineering
Issue

Unconventional Emergency Management
Warning

Response

Technology
Issue

Information
SupportCommand

Behavior
response

Scientific
Issue

Information
processing
and modeling

Emergency
Decision‐makingIndividual/group
behavior

Figure 1: Framework of the key scientific issues(1)
Information processing and model
evolutionary mechanism of unconventional incidents

developmentofTowards the massive, heterogeneous and real-time data of
unconventional incidents during the event's possible precursors andevolvement, the following studies are needed:① Studies on the scientific issues of the information processingof these data including collection, data analysis, transmission,visualization and sharing, etc,
② Studies on the theory and method on non-traditional (forexample, data driven and computational experiments) complex
modeling of unconventional incidents' evolution mechanisms.
The major research contents of this issue include:① The information processing of unconventional incidents.
② Modeling of unconventional incidents' evolution mechanisms.
(2)
incidents

The emergency decision-making theory of unconventional

The studies include:
The whole-process dynamic assessment, decision-making theories andmethods of the on-site decision-making of unconventional incidents; Thetheories and methods of emergency preparation system, decision-making
command system, rescuing/administration system and the organization’s

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design,design,operation
operationandandevaluation
evaluationof ofresource
resourceallocation
allocationsystem;
system;TheThetheoreticaltheoreticaldesigndesignof ofemergency
emergency
platform,
platform,compilationcompilation
andanddrilling
drilling
methods
methods
of ofpre-planpre-plansystem;system;
TheTheintegrated
integrated
decision-making
decision-making
theories
theories
andandmethods
methods
facingfacingto multiple
to multiple
disasters
disasters
andandscenario-built,
scenario-built,
andandthethesoft-hardware
soft-hardware
systemsystemintegration.
integration.
TheThemajor
major
research
research
contents
contentsof thisof thisissue
issue
include:include:①The①The
theories
theories
andandmethods
methods
of ofemergency
emergency
evaluation,
evaluation,
analysisanalysis
andanddecision-making;decision-making;
②The
②The
organization
organization
designdesignandandoperation
operation
optimization
optimizationof ofemergency
emergency
commandcommandsystem;system;③Emergency③Emergency
decision-making
decision-making
supportsupportplatform
platform
system.
system.
(3)(3) TheThe
behavior
behavior
andandpsychologicalpsychologicalresponse
responsemechanismmechanism
of of
an an
individual
individual
andanda groupa groupin emergency
in emergency
conditions.
conditions.
It is
It necessary
is necessary
forfor
us us
to to
study
study
thethemechanisms
mechanisms
of ofcognition,
cognition,
mood,
mood,
attitude,attitude,andandrequirement
requirement
of ofthethemajor
major
participants
participants
includingincludingmanagers,
managers,
rescuers
rescuers
andandpopulaces
populaces
when
when
they
they
face
face
emergency
emergency
andandpressure.
pressure.
Also,
Also,
thethegroup’sgroup’s
behavior
behavior
mechanisms
mechanisms
andandstructural
structuralfeaturesfeaturesshouldshouldbe bestudied.
studied.
TheThemajor
major
research
research
contents
contentsof thisof thisproblemprobleminclude:include:①①
TheThemechanism
mechanismof ofindividual
individualpsychology
psychologyunder
undera apressured
pressuredcondition;
condition;
TheThegroup’sgroup’s
actionactionin emergency.
in emergency.
In In
thisthis
study
study
plan,
plan,
three
three
keykeyproblems
problems
includingincluding
seven
seven
major
major
topics
topicsandandtheir
theirlogicallogicalrelationsrelationsareareshown
shown
in Figs.2
in Figs.2
andand3, respectively.
3, respectively.

Information
Information
processing
processing
andandmodeling
modeling①Information①Information
processing
processing
of ofunconventional
unconventional
incident
incident②Modeling②Modelingof of
evolutionary
evolutionary
mechanismmechanism
of ofunconventional
unconventional
incident
incident③Theories③Theories
andandmethods
methods
of ofemergency
emergency
response
response
evaluation,
evaluation,
analysisanalysisandanddecision‐making
decision‐making

Emergency
Emergency
Decision‐
Decision‐makingmaking④The④The
designdesignandandoperation
operation
optimization
optimizationof ofemergency
emergency
commandcommandsystemsystem⑤⑤
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methods
of ofemergency
emergency
decision‐making
decision‐making
supportsupportIndividual/
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group
behavior
behavior
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mechanismmechanism
of ofindividual
individual
psychology
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under
under
pressurepressureconditions
conditions⑦Group⑦Groupbehavior
behavior
under
under
emergency
emergency
FigureFigure2: Main
2: Mainresearch
research
contents
contents

TheThemajor
research
plan‘studyon onunconventional
emergency
management’in ChinaThe
major
research
plan‘studyemergency
management’inmajor
research
plan‘studyon unconventional
unconventional
emergency
management’in China
China

5 5
425

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Information processing（research content 1）

individual psychology（research content 6）

Modeling construction（research content 2）

Group behavior（research content 7）

Evaluation and analysis（research content 3）
Organization design（research content 4）
Decision‐making support（research content 5）

New scientific intentions for emergency management
Figure 3: The logical relationship between the research contents
4.2 Research purposes
The main purposes of “Study on Unconventional Emergency
Management” are as follows:(1) To form a profound scientific cognition of objective laws in thecore steps (warning and decision-making) of unconventional emergencies
management through observation, experiment, innovation of theory andintegration of the relating multiple disciplines in the specially restrictive
condition of unconventional incidents.
(2) To build a “scenario-response” theoretical system of
unconventional emergencies management and to improve innovation abilityof emergency management science.
(3) To provide a scientific, efficient and ordered decision-making
reference to respond unconventional incidents through improving thescientific level of nation’s emergency management system including
emergency platform and pre-plan system.
(4) To develop emergency management interdiscipline and to train
innovative emergency management experts.
The detailed purposes are as follows:• To propose a series of key regulars and methods forunconventional emergencies management which include
information processing methods and evolutionary mechanisms of
unconventional incidents and the behavior and psychological

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•

•

•

•

response regular of an individual and a group under emergency
conditions.
To integrate the key regulars and methods above and to get a
general description of unconventional incidents; To form a
profound scientific cognition of warning and response inemergency management combined with emergency decisionmaking theory of unconventional incidents, and provide scientificmethods; To develop a “scenario-response” theoretical system of
unconventional emergencies management.
To provide a compilation and a revised manual of emergency preplan system; To apply scientific achievements into emergency
platform system and to provide a platform of theory andexperimental verification of emergency decision-making; To
provide scientific measure and basis to improve emergency
management level and to provide a scientific, efficient andordered decision-making reference to respond unconventional
incidents.
To apply the achievements of the study plan to finally develop
three integrated platforms which include simulation system of
unconventional incidents, the fundamental platforms ofemergency platform and emergency pre-plan system.
To form a new interdisciplinary direction which jumps fromseparated to systematic and interdisciplinary researches for the
purpose of “Emergency decision-making”. It also helps to lay thefoundation of developing emergency management interdiscipline.

5. THE GENERALIMPLEMENTATIONARRANGEMENT

OF

STUDY

PLAN

According to the actual demand features of emergency works, thestudy periods of the study plan are set to be 6 years. The study plan will
support a series of study projects. The executing periods of the supported
projects are set to be 3-4 years. The series of study projects include 3 key
scientific issues covering the 7 major study topics. Each topic contains 8-9
cultivated projects which will be 3 years and 3-4 key projects which will be
3-4 years. According to integrated purpose, the study plan has 3 integration
projects in different scales which will be 3-4 years.
The settings of the projects are mainly proceeded in the first 3 years.
The study plan will set up the fundamental exploration and the application
research projects based on the objective demand as soon as possible. Afterthe mid-term, the study plan will choose the research directions which canplay key role to reach the overall objectives and launch “integration
projects” to carry out the important integrated innovative researches on thebasis of all types of project achievements in the first stage. In the last three
years of the study plan, it will emphasize on the integration and innovationof the achievements in the relating projects. The first stage assessment
intends to be arranged in the third year of the study plan implementation.

The major
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plan ‘study‘study on
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emergency management’management’ inin China
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According to the results of the stage assessment, it will put forwards anadjusted scheme to the study plan and to establish the foundation of“integration projects” in the last stage.
6. EXPECTED OUTCOMES
The expected outcomes of this research plan include:(1) Through the complex system model construction methods (such as,society calculations, complex network, etc.) and communication technology
of computer and internet, the general description of unconventional incident
will be obtained. In the academic aspect, this platform can be treated as a
special “experimental” tool in study process. In the applied aspect, thisplatform combing with emergency decision-making of unconventional
incidents can be treated as an important technology reference of emergency
decision-making.
(2) After getting the support of the various relating directions, theemergency platform system will become a theoretical and validatedexperiment platform for providing emergency decision-making and will
form scientific and powerful national emergency platform and an
emergency pre-plan system. Also, it can improve the service efficiency ofnational emergency management funding.
Through this research plan, great development on China’s emergency
management science will be obtained in two aspects:(1) To acquire the results with important international impact. Chinesescientists can contribute greatly and originally in this field and can develop
Chinese emergency management fundamental theory with importantinternational impact.
(2) To accelerate the formation of emergency management
disciplinary direction.
7. CONCLUSIONSIn order to improve Chinese government’s emergency management ability,and promote the development of Chinese emergency management science,
the National Natural Science Foundation of China (NSFC) launched the
Major Research Plan ‘Study on Unconventional Emergency Management’in 2008. The research plan aims to deeply understand the mechanism andprovide the approach for the core parts in the emergency management warning and response - by integrating the multidisciplinary observations,experiments and theories; establish the unconventional emergency
management theory based on the ‘scenario-response’ approach; promote thescientificalness of emergency plan and platform and establish themultidisciplinary education framework for emergency management. The
Major Research Plan will provide more effective and scientific supports for
Chinese emergency management.

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ACKNOWLEDGEMENT
This work was supported by Ministry of Science and Technology of thePeople´s Republic of China under Grant No. 2011BAK07B02 and No.
2011BAK07B03.
REFERENCES
Britton, N. R., Clark, G. J., 2000. From response to resilience;
Emergency management reform in New Zealand. Natural Hazard Rev. 1(3),145-150.
Cauchemez, S., et al., 2008. Estimating the impact of school closure
on influenza transmission from sentinel data. Nature 452, 750-754.
Ferguson, N. M., et al., 2006. Strategies for mitigating an influenza
pandemic. Nature 442, 448-452.
Gerstenberger, M. C., Wiemer, S., Jones, L. M., Reasenberg, P. A.,
2005. Real-time forecasts of tomorrow’s earthquakes in California. Nature
435, 328-331.
Gonzalex, M. C., Hidalgo, C. A., Barabasi, A. L., 2008.
Understanding individual human mobility patterns. Nature 453, 779-782.
Kossinets, G., Watts, D. J., 2006. Empirical analysis of an evolvingsocial network. Science 311, 88-90.
Harraid, J., Jefferson, T., 2007. Shared situation awareness inemergency management mitigation and response. System Sciences, 23-23.
Topper, G. J., Worsley, P. M., 2000. The use of remote sensing and
GIS technologies by New South Wales agriculture for emergency
management. Geosciences and remote sensing symposium 4, 1489-1491

The major
Themajor researchresearch plan
plan ‘study‘study on
on unconventional
unconventional emergency
emergency management’management’ inin China
China

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New Technologies for Urban Safety of Mega Cities in Asia

Effects of environmental condition
on corrosion of structural steel
in marine environment of Thailand
Prasong PERMSUWAN1, Pakawat SANCHAROEN2,
Somnuk TANGTERMSIRIKUL3, Paiboon SREEARUNATHAI4,
Ekkarut VIYANIT5 and Wanida PONGSAKSAWAD5
1

Graduate student, School of Civil Engineering and Technology, Sirindhorn
International Institute of Technology, Thammasat University, Thailand
Prasong_civilnu@hotmail.com
2
Researcher, Construction and Maintenance Technology Research Center,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
3
Professor, School of Civil Engineering and Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
4
Lecturer, School of Bio-Chemical Engineering and Technology (BCET),
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
5
Researcher, National Metal and Materials Technology Center (MTEC),
114 Thailand Science Park, Thailand

ABSTRACT
Structural steels which are hot-rolled steel grade SS400 according to JIS
G3101, hot-rolled steel grade SM490YA according to JIS G3106 and hotrolled atmospheric corrosion resisting steel grade SMA490A according to
JIS G3114 were exposed from January 2010 until January 2011 to marine
and industrial environment at Maptaphut industrial estate, Rayong,Thailand. The specimens were exposed in two conditions that were
atmospheric and tidal zone. The corrosion behaviors of specimens werestudied by means of weight loss measurement according to ISO8407,
compositions of rust layers by XRD analysis and characteristic of rust layer
by SEM analysis. Also, environmental conditions such as temperature,
relative humidity, and deposition rate of chloride were monitored monthly.
The corrosion rates of specimens were also measured by potentiodynamic
polarization in laboratory. The results showed that corrosion rate at 12
months of carbon steel was higher than that of weathering steel.
Furthermore, specimen in tidal zone showed higher corrosion rate thanatmospheric zone obviously due to effects of biofouling and wet-dry
condition. The result can be used for material selection and designing
service life of steel structure in Thailand.
Keyword: corrosion, marine, atmospheric, tidal, carbon steel, weathering
steel, chloride

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1. INTRODUCTION
Structural design of both reinforced concrete and steel structures consider
mainly the strength of members. But durability design or service life design,
which also affects the safety of structure, is rarely concerned. Particularly,
the steel can be deteriorated rapidly when it is subjected to corrosive
environmental condition. Carbon steel and weathering steel are used in steel
structure including high-rise building, bridge, offshore platform, sheet piling,steel pile and coastal facilities. Normally, steel structures in marine
environment are deteriorated by atmospheric corrosion. Also, some part ofthose steel structures such as steel piles or sheet piles are immersed in thesea water. So the area between the lowest sea level and the highest sea levelis influenced by tidal zone corrosion.
Atmospheric corrosion is an electrochemical reaction occurring on
metal surface in a presence of thin film electrolyte. In case of atmosphericcorrosion, structural steel in marine environment deteriorates primarily byclimatic factors such as temperature, relative humidity, and the presence ofchloride and SO2. Normally, rust formed on surface of carbon steel isporous with poor adherent, and cracked at the outer part (Castano et al.,2010). This phenomena causes oxygen, water, Cl- and SO2 from outside topenetrate to the steel substrate easily (Yuantai et al, 2009). For corrosion
resisting steel, at the early stage, the rust is formed similarly to the carbon
steel. But as the exposure time increased, the rust layer becomes morecompact, denser, and tighter (Renato, et al., 2003). For this reason, the rustlayer acts as the barrier to inhibit corrosive species and then the rate ofcorrosion is decreased.
The compositions of rust layer have been observed by several
researchers. Mainly, the compositions of rust found in marine environment
are composed of lepidocrocite (γ-FeOOH), goethite (α-FeOOH), akaganeite(β-FeOOH) and magnetite (Fe3O4). The γ-FeOOH is usually formed in theearly stage and transformed to α-FeOOH and Fe3O4. This α-FeOOH isimportant key to reduce corrosion because its compact and dense structure
prevent penetration of water, oxygen and corrosive species from theenvironment. However, area with presence of chloride is often observed βFeOOH which has porous and loose structure.
In Thailand, environmental conditions are different from othercountries. There is no sufficient data of atmospheric corrosion to model orpredict steel corrosion in order to design service life of steel structures inThailand. Also, there is limit information on atmospheric and tidal corrosion.
In addition, the standard currently used to design steel structures in Thailand
was adopted from other countries. It is essential to study the corrosion
behavior of structural steel in Thailand. The aim of this paper was toinvestigate the corrosion behavior of SS400, SM490YA and SMA490A
steels in the marine environment of Thailand.

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2. EXPERIMENTAL
2. EXPERIMENTAL
PROGRAMPROGRAM
2.1 Specimen
2.1 preparation
Specimen preparation
The materials
Thetestedmaterials
in thistestedstudy
in arethisthreestudykinds
are threeof structural
kinds ofsteel;structural
1) steel; 1)
hot-rolled steels
hot-rolled
for generalsteels forstructuregeneralgrade
structure
SS400
grade
according
SS400 toaccording
JIS G3101,
to JIS G3101,
2) hot-rolled
2) steels
hot-rolled
for weldedsteels forstructure
weldedgrade
structure
SM490YA
grade SM490YA
according toaccordingJIS
to JIS
G3106, andG3106,
3) hot-rolled
and 3) atmospheric
hot-rolled atmosphericcorrosion resisting
corrosionsteels
resistingfor weldedsteels for welded
structure grade
structure
SMA490A
grade SMA490A
according according
to JIS G3114.
to JISTheir
G3114.
chemical
Their chemicalcompositions
compositions
determineddeterminedby spark emission
by spark spectrometeremission spectrometerare shown are
in shown in
Table 1 together
Table 1with
togetherthe specified
with the values
specifiedin values
the standard.
in the ISO
standard.
8565 ISO 8565
standard specification
standard specificationsuggests thesuggests
following
the following
procedures proceduresfor specimen
for specimen
preparationpreparation
before exposure
beforetest.
exposure
Specimens
test. Specimens
were cut fromwerethecutsteelfromplate
the tosteel plate to
the size of the
150×70×3
size of 150×70×3
mm for SS400
mm forand SS400
SM490YA
and SM490YA
steels, and steels,
150×70×5
and 150×70×5
mm for SMA490A
mm for SMA490A
steel. The millsteel.scale
Theon
mill
thescalesurfaceon theof thesurfacespecimensof the specimenswaswasmechanicallymechanicallyremoved byremoved
sand blastingby sandandblasting
then wet-polishedand then wet-polishedby 600 gradeby 600 grade
sand paper sandon allpaper
surfaces.
on allFinally,
surfaces.
theFinally,
specimens
the specimens
were rinsedwere
withrinsed
distilledwith distilledwater and ethyl
wateralcohol,and ethyl
driedalcohol,by blower,
dried byweightedblower,andweighted
immediately
and immediately
placedplacedin desiccators
in desiccators
before the test.
before the test.
Table 1: Chemical
Table 1:compositions
Chemical compositionsof differentof
types
differentof steeltypes of steel

Chemical composition
Chemical(% bycompositionwt)(% by wt)
Steel types
C
Si C Mn Si P Mn S P Cr S Ni Cr Cu Ni Al Cu Mo Al≤ 0.20Standard JIS G3106Standard
JIS G3106≤ 0.55≤ 0.20≤ 1.65≤ 0.55≤ 0.035≤ 1.65≤ 0.035≤ 0.035 - ≤ 0.035 - - - - - - - SM490YA
SM490YA
0.070
0.218 0.070 0.352 0.218 0.009 0.352 0.016 0.009 0.031 0.016 0.073 0.031 0.154 0.073 0.013 0.154 0.015 0.013
Standard JIS G3101Standard -JIS G3101 - - - - ≤ 0.05 - ≤ 0.05≤ 0.05 - ≤ 0.05 - - - - - - - SS400
SS400 0.047
0.174 0.047 1.039 0.174 0.010 1.039 0.006 0.010 0.026 0.006 - 0.026 - - - - - ≤ 0.18
≤ 0.035≤ 1.4≤ 0.035≤ 0.035≤ 0.035
0.15-0.65≤ 0.18 ≤ 1.40.15-0.65
0.45-0.75
0.05-0.30
0.45-0.75
0.30-0.50
0.05-0.30 - 0.30-0.50 - Standard JIS G3114Standard
JIS G3114
SMA490A
SMA490A
0.115
0.396 0.115 0.368 0.396 0.076 0.368 0.005 0.076 0.681 0.005 0.16 0.681 0.368 0.16 0.021 0.368 0.003 0.021
Steel types

2.2 Exposure
2.2 test
Exposure test
Exposure site
Exposure
is locatedsite isat locatedMaptaphut
at Maptaphut
industrial estate,industrial
Rayong,estate, Rayong,Thailand asThailand
shown inasFigureshown1.inThe
Figureposition
1. Thecoordinates
position coordinatesof this locationof thisis location is
12° 39’ northern
12° 39’latitude
northernand
latitude101° 10’and eastern
101° 10’longitude.
eastern longitude.
Even though,Even though,environment
environmentof exposureofsite
exposure
is marine
siteenvironment
is marine environment
but this areabutisthisalsoarea
an is also anindustrial estateindustrial
with estatecoal- powerwith coalplant,
power
oil refinery,plant, oilchemicalrefinery,industry,
chemicaletc.
industry, etc.
The experiment
The experiment
was conducted
was conductedfrom January
from2010
January
to January2010 to2011.
January
The 2011. The
exposure test
exposure
was conducted
test was inconducted
two conditions
in two conditions
which werewhichatmospheric
were atmosphericandandtidal zone exposure.
tidal zone exposure.

Effects of environmental condition on corrosion of structural steel
Effects of environmental
condition oncondition
corrosiononofcorrosion
structuralofsteel
in marineof Thailand of Thailand
Effects of environmental
structuralsteelenvironment
in marine environment
3
in marine environment of Thailand

4333

Mo
0.015
0.003

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,
Marine and industrial environment at
Maptapud Industrial Estate, Rayong, Thailand

A

B
Rack No. 2
Highest level of sea waterN

Rack No. 1

Platform No.12A

Lowest level of sea water

Platform No.4

Figure 1: Details of the exposure site:(A) atmospheric exposure and (B) tidal exposure
For atmospheric exposure, two exposure racks according to ISO 8565
were set on the high voltage transmission tower platform No. 4 only. Rack
No.1 faced to the East and rack No.2 faced to the North directions with therack slope of 45° to the horizontal as shown in Figures 1 and 2.
For tidal exposure, sample was placed in the plastic box and installed
under the transmission tower platform number 4 and 12A of which water
quality are different. The position of the boxes was set in the middle
between the highest and the lowest sea water level in order to simulate wetdry condition as shown in Figures 1 and 2. Environmental conditions suchas temperature and relative humidity were monitored monthly by sensors
connected to a data logger near the rack No.1. The results are shown in
Table 2.

Figure 2: The exposure rack of atmospheric zone
(left) and tidal zone (right)
Chloride deposition rate was measured monthly by using the wet
candle method according to ISO 9225, and surface of wet candle exposed toatmosphere is 100 cm2. Also, the wet plate modified from standard wet
candle method was installed in 4 directions in order to measure effect ofwind directions on chloride deposition rate. The results are shown in Table 2.
The sea water properties, mainly chloride and sulfate concentration, were
measured by Ion-chromatography. The results are shown in Table 2.
The compositions of corrosion products were characterized by X-ray
diffraction (XRD) method using X-ray diffractometer (Rigaku TTRAX III
50 kV 300mA) with Cu target. The scan is performed at a speed of 10°/min,

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a scan step of 0.02 at 2θ and range from 10° to 70° at 2θ. The characteristicof rust layer was observed by SEM analysis using JEOL model JSM-6301F.
After 1, 3, 6 and 12 months, exposed specimens and monitored data
were collected for analysis. Corrosion products were removed chemicallyby HCl acid etching according to ISO 8407. After corrosion products had
been removed completely, the specimens were rinsed with ethanol, dried
with blower and weighted to measure weight loss.
Table 2: Atmospheric conditions and sea water properties

Atmospheric conditions
Sea water properties
Chloride (ppm)
Sulfate (ppm)Monthly average Monthly averageMonthly averagetemperature (°C) relative humidity (%) Cl-deposition (mg/(m2.day)) Tower4 Tower12A Tower4 Tower12A
30.6
61.3
22.5
19586
18821
3147
3041

Table 3: Chloride deposition rate of each direction
Wet-plate Direction faced to
Chloride deposition rate2

(mg/(m .day))

East

North

West

South

27.75

27.39

27.94

39.43

3. RESULTS AND DISCUSSION
3.1 Environmental characteristics at exposure site
The environmental characteristics measured at the exposure sites areshown in Table 2. According to ISO 9223, environmental conditions areclassified in term of chloride deposition rate (class S) and sulfur dioxide
deposition rate (class P). Also, Time of wetness (TOW) (classτ), the periodof time when relative humidity is greater than 80% and temperature isgreater than 0ºC, is also used for the classification. Environmental conditionof exposure site is classified as S1 because chloride deposition rate is 22.47
mg/m2.day which is between 3-60 mg/m2.day. Environmental condition isclassified as class τ3 because TOW is 9.1% which is between 3 < τ ≤ 30 %.
Also, the corrosive categories of the exposure site can be classified as C2(low) to C4 (high) class by S1 and τ3 depending on classification of sulfur
dioxide. As shown in Table 3, the result of the wet plate shows that chloride
deposition of rack No. 2 facing north is higher than that of rack No. 1 facing
east because of the wind direction.
3.2 Thickness loss
Figure 4 shows examples of the surface appearance of SS400 steel
after 12 months exposure at atmospheric and tidal zone. In atmosphericzone, dark-brown rust product uniformly covered the entire surface while
uneven surface was observed in specimens exposed to tidal zone and werecovered with tightly attached biofouling. Other types of steel showed similar
appearance after 12 months exposure.

Effects of environmental condition on corrosion of structural steel
Effects of environmental condition on corrosion of structural steel in marine environment of Thailand
in marine environment of Thailand

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October 2011, Chiang
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Chiangmai,

Generally, the corrosion rate of steel exposed to real environment wascalculated in term of thickness loss. The equation used to calculate thickness
loss is shown in Eq.1
C =W × 104
ρA(1)

where C is the thickness loss (µm), w is the weight loss (g) of
specimen after being exposed, ρ is the density of the steel (7.86 g/cm3) and
A is the exposed surface area of the specimen (both sides) (cm2).
Figures 5a and 5b show thickness loss of SS400, SM490YA andSMA490A steels exposed to atmospheric zone for 12 months on rack No.1
and rack No.2, respectively. In both exposure racks, the thickness loss ofSS400, SM490YA and SMA490A steels continuously increased from the
beginning to 12 months but the rate of corrosion decreased with increasing
time. Especially, corrosion rate of SMA490A steel obviously decreased at
the long term because rust layer was more compact and denser.
The thickness loss of SS400, SM490YA and SMA490A steels exposed totidal zone after 12 months under platform No.4 and 12A are shown in
Figures 6a and 6b. In tidal zone, the thickness loss of specimens is very high(greater than- 200 µm) after 12 months of exposure. Both platforms,
thickness loss of SMA490A was the lowest because of its alloying
composition. Particularly, rate of corrosion of specimens under platform
No.4 shows almost constant increasing without effect of protective rustlayer. As the results, the thickness loss of specimens under platform No.4 issignificantly higher than those under platform No.12A. This is because
different water quality such as higher O2 and higher Cl- concentration
content which causes fast growing of biofouling as well as accelerates steel
corrosion was observed under platform No.4.

(a)
(b)
(c)
Figure 4: Appearance of SS400 steel: (a) before exposure, (b) after 12months of exposure in atmospheric condition and (c) after 12 months of
exposure in tidal condition

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ICUS Report 56x
30

SS400

25

SMA490A
20
15
10

SS400
SMA490A

20
15
10
5

5
0

SM490YA

25

Thickness loss (µm)

Thickness loss (µm)

30SM490YA

0

3

6

9

12

0

15

0

3

6

9

12

15

Exposure time (months)

Exposure time (months)(a)(b)
Figure 5: Thickness loss of specimens versus exposure time at atmosphericzone on; (a) rack No.1 and (b) rack No. 2
500

500

SS400

SS400

400

SMA490A

Thickness loss (µm)

Thickness loss (µm)

400
300
200
100
0

SM490YA

SM490YA

SMA490A
300
200
100

0

3

6

9

12

Exposure time (months)

15

0

0

3

6

9

12

15

Exposure time (months)(a)(b)
Figure 6: Thickness loss of specimens versus exposure time at tidal zone
under; (a) platform No.4 and (b) platform No.12A
3.3 Corrosion product analysis
3.3.1 Cross section of rust layer
The cross section analysis of steel exposed to atmospheric zone for
12 months showed irregular layer of corrosion product with thickness about
25-70 µm. And rust layers were less compact as shown in Figure 7a. This
layer showed some sites with localized corrosion, which probably act as
anodes in the first steps of atmospheric corrosion (Castano et al., 2010). In
tidal zone, the cross section showed thicker layer of corrosion products thanthat found in atmospheric zone as well as some site with deep localized
corrosion as shown in Figure 7b. The thickness of the layer of corrosion
products was approximately 25–200 µm. The deeper localized corrosion
may be contributed by biofouling. It attached on part of steel surface andcaused severe local corrosion. This can be the weak point of structures.

Effects of environmental condition on corrosion of structural steel
Effects of environmental condition on corrosion of structural steel in marine environment of Thailand
in marine environment of Thailand

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Chiangmai,

resin

resin

steel

steel

Local corrosion(a)(b)
Figure 7: Rust layers on the SM490YA steel exposed for 12 months as;(a) atmospheric zone and (b) tidal zone
3.3.2 Composition of rust layer
The main phases of the rust layers formed on the steels exposed toatmospheric zone for 12 months were γ-FeOOH, followed by β-FeOOH andα-FeOOH as shown in Figure 8a. It can be seen that the main phaseobserved on SM490YA, SS400 and SMA490A was γ-FeOOH. It normallyoccurred at the beginning of corrosion. Then with the interaction of oxygen
and water, γ-FeOOH partly or entirely transformed to more stable α-FeOOH(Zise et al., 2007). As the result, there was low amount of α-FeOOH thatrecently formed on the steels. Generally, β-FeOOH was only found in highchloride containing environment. As many researchers, investigated theeffect of chloride ion on the transformation of rust formed on the carbon
steel and observed that the content of β-FeOOH increased with theconcentration of Cl ions in the environment. Kamimura et al. (2006) also
reported that β-FeOOH was electrochemically active and the existence of βFeOOH influenced the corrosion behavior of weathering steel exposed atmarine site.
For tidal zone, the phases of rust layer formed on the steel exposed for
12 months in both locations was mainly Fe3O4 followed by γ-FeOOH, αFeOOH and β-FeOOH, respectively as shown in Figure 8b. Peaks of Fe3O4
phases had high intensity with a small intensity of other phases. For
occurring of Fe3O4, many researchers reported that γ-FeOOH formed on thesteel surface did not only reacts with the oxygen and water and become αFeOOH, but also reacts with Fe2+ dissolved from the iron and forms Fe3O4.
As the results, there was Fe3O4 in rust layers only in tidal zone. There weremany phases with high intensity because in severely corrosive sea water,rust layers formed very fast and rapidly transform to another phases.
Anyway, rust layers in tidal zone did not act as efficiently protective rustlayers like that of atmospheric zone because rust layers formed in this zone
cannot inhibit corrosive species penetrated to surface of steel. For calcite
phase, it was composition of biofouling shell attaching on the corrosion
products.

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ICUS Report 56x(a)γ-FeOOH
β-FeOOH
α-FeOOH(b)Fe3O4
γ-FeOOH
β-FeOOH
α-FeOOH
CalciteFigure 8: XRD spectra of corrosion products obtained from SM490YA for
12 months as; (a) atmospheric zone and (b) tidal zone
3.4 Corrosion rate
The prediction of corrosion rate of steel exposed to atmosphericcondition was proposed by several researchers as a bi-logarithmic equation
as shown in Eq.2. This equation usually fits well with corrosion behavior
over time.
C = AtB(2)

where C is the thickness loss (µm), t is the exposure time (month), andA, B are constants. The constants A and B can be determined by plot in loglog coordinate between steel thickness loss and exposure time. The
regression analysis was conducted in log-log coordinate to determine valuesof constants A and B value.
For corrosion rate prediction equation, several researchers considered
the B value as the growth law of corrosion product: parabolic or linear. If
the B value is in the range of 0.5 to 1, the corrosion products do notsignificantly protect the steel surface from corrosion and is called a linear
growth. On the other hand, if the B value is lower than 0.5, it indicates aparabolic growth by formation of protective rust layers to reduce rate ofcorrosion in the long term.
The corrosion rates per year and the values of A and B constant in all
exposure zones of SS400, SM490YA and SMA490A steels were calculated
from the bilogarithimic equation and shown in Table 4.
Effects of environmental condition on corrosion of structural steel
Effects of environmental condition on corrosion of structural steel in marine environment of Thailand
in marine environment of Thailand

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For atmospheric zone, the corrosion rate of rolled steel (SS400 and
SM490YA) is higher than corrosion resisting steel (SMA490A) in bothracks because B value of SS400 and SM490YA are higher than 0.5 whichindicate high rate of corrosion. The key factor causing the difference ofcorrosion rate is the chemical composition of the steel. The corrosion rate of
SMA490A is the lowest because the corrosion resisting steel contains somealloy elements such as Cu, Cr, and Ni that improve the corrosion resistanceas shown in Table 1. Q.C. Zhang et al have studied the distribution ofalloying elements during formation of rust layers. They reported that thepresence of Cu restrains the supply of oxygen, retards the anodic dissolution
and reduces the electronic conductivity of rust layers. For this reason, thecorrosion rate of SMA490A steel is reduced. The corrosion rate of rackNo.2 is higher than that of rack No.1 for all types of steel because rack No.2
is affected by the wind direction making higher Cl- deposition rate on thespecimen surface from the results of wet-plate. This shows the importanceof the effect of local environmental conditions on steel corrosion. From theresult, the corrosive category of environment at exposure site can be defined
as class C3 (medium) based on ISO 9223.
In case of tidal zone corrosion, the corrosion rate of tidal zone issignificantly more aggressive than atmospheric zone. The corrosion rates oftidal zone and atmospheric zone show the difference of more than 10 times.
The high Cl- concentration and wetting in tidal exposure accelerated
corrosion process by formation of β-FeOOH. Although the α-FeOOH phase
was formed on both carbon steel and weathering steel but the rust layers
were not act as the protective barrier causing the high B value. Because, the
α-FeOOH phase was not uniformly formed on the surface of steel and thenrust layers cannot sufficiently protect the Cl- penetration. Also, the effect of
biofouling increased corrosion rate significantly. Biofouling is considered amajor factor to control the corrosion behavior since the biofouling attachedto the surface of steel tightly. Biofouling consumes oxygen, while supplies
acid due to its excretion. As a result, steel subjects to extra corrosion due toacid (Coetser, 2005). Eventually, the corrosion affecting from biofouling islocal corrosion which is more severe and difficult for predicting the rate. In
term of location, corrosion of specimens under platform No.4 is more severe
than that of the specimens under platform No.12A because the differencesin Cl-, sulfate and oxygen concentration. Moreover, specimens under
platform No.12A is located in calm sea water and low water quality that has
low oxygen concentration causing slow activity and slow growing of
biofouling.

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Table 4: Corrosion rate and constant values of steels
Steel type

Condition
AtmosphericSM490YA
Tidal
Atmospheric
SS400
Tidal
Atmospheric
SMA490A
Tidal

LocationCorrosion rate (µm/year)

A

B

Rack 1

22.68

5.25 0.59

Rack 2

25.86

6.59 0.55

Under 4461.4254.45 0.86

Under 12A

218.6391.62 0.35

Rack 1

22.21

4.83 0.61

Rack 226.50

6.81 0.55

Under 4480.2965.46 0.80

Under 12A

238.6068.71 0.50

Rack 1

19.93

4.63 0.59

Rack 2

23.53

7.93 0.44

Under 4398.5361.66 0.75

Under 12A

196.1848.31 0.56

The typical rates of corrosion for structural steel suggested by BS
6349-1 standard are shown in Table 5. BS 6349-1 standard recommends the
corrosion rate for steel structure design in various exposure zones. The
results of this study show that average corrosion rate of the steels in
atmospheric zone are approximately 23.45 µm/year. So the standard is
acceptable to be used to design steel structures in atmospheric zone in
Thailand. On the other hands, the results of average corrosion rates of thesteels in tidal zone in this study are approximately 332.27 µm/year. The
standard recommends maximum limit of 100 µm/year. Therefore, thestandard is not suitable for steel structure design in tidal zone in Thailand.
Table 5: Typical rates of corrosion for structural steels temperate climates(BS 6349-1)
Corrosion rate μm/year Results of the study μm/year
Exposure zone
Mean Upper limit* SM490YA SS400 SMA490A
Atmospheric zone
40
100
25
26
23
Splah zone
80
170
Tidal zone
40
100
461
480
398
Seawater immersion zone 40
130*The upper limit is the 95% probability values

4. CONCLUSIONS
1. Corrosion resistance of SMA490A steel is the highest in all conditions
because its chemical compositions improve the characteristic of protective
rust layers.
2. Corrosivity of sea water in tidal zone is significantly higher thanatmospheric environment. This phenomenon is contributed by the effects of
biofouling and high chloride concentration. Corroding mechanism of
biofouling must be concerned in tidal zone corrosion and studied in the
future.

Effects of environmental condition on corrosion of structural steel
Effects of environmental condition on corrosion of structural steel in marine environment of Thailand
in marine environment of Thailand

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3. Calculation of corrosion rate specified in the BS 6349-1 standard might
not be suitable for structural steels exposed to Thailand environments
especially for tidal zone corrosion.
ACKNOWLEDGEMENT
The research was funded by the Electricity Generating Authority ofThailand (EGAT).
REFERENCES
Castano J.G., et al, 2010, “Atmospheric corrosion of carbon steel in
Colombia”, Corrosion science, 52, pp. 216-223.
Coetser S. E. and Cloete T. E., “Biofouling and bio corrosion inindustrial water systems”, Critical reviews in microbiology, 31, 2005, pp.
213-232.
Kamimura, T. et al., 2006. “Composition and protective ability of rustlayer formed on weathering steel exposed to various environments”.
Corrosion Science, 48(9), pp.2799-2812.
Renato A.A., et al, 2003, “Characterization of corrosion products
formed on steels in the first months of atmospheric exposure”, Materials
research, 6, pp. 403-408.
Yuantai M., et al, 2009, “Corrosion of low carbon steel inatmospheric environments of different chloride content”, Corrosion science,
51, pp. 997-1006.
Zhang Q.C., et al, 2002, “Corrosion behavior of weathering steel inmarine atmosphere”, Materials Chemistry and physics, 77, pp. 603-608.
Zise W. et al., 2007. “The Morphology, Phase Composition and Effectof Corrosion ProductonSimulated Archaeological Iron”. Chin. J. Chrm. Eng,
15(3), pp.433-438

12
442

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Asia
NewInfluence of temperature on deterioration
process due to chloride attack
Takahiro NISHIDA1, Nobuaki OTSUKI2 and Hiroshi MINAGAWA3
1
Postdoctoral Fellow, Structural Mechanics Division,
Port and Airport Research Institute, Japan, nishida-t@pari.go.jp
2
Professor, Graduate School of International Development Engineering,Tokyo Institute of Technology, Japan
3
Associate Professor, Department of Civil Engineering,Tohoku University, Japan
ABSTRACTIn recent years, maintenance of reinforced concrete has been considered asa major concern all over the world. One of the most serious deterioration
issues is corrosion of reinforcing steel bars embedded in concrete due tochloride attack in marine environment.
On the other hand, it is generally said that the rates of ion diffusion andsteel corrosion will increase with temperature elevation. Consequently,
there is a possibility that the life time of reinforced concrete in warmer
climates becomes comparatively shorter than colder regions. Therefore it isnecessary to make the applicable methods for predicting the life time andmaintenance management system responsive to the deterioration process invarious temperature profiles.
From the backgrounds mentioned above, this paper presents influence oftemperature on deterioration process of reinforced concrete members due tochloride attack. At first, the temperature dependency of deterioration
phenomena in concrete is experimentally examined based on the Arrhenius
theory. Secondly the life time of reinforced concrete are predicted andcompared with the average temperature in each region. As a result of thispaper, it is concluded that the influence of temperature on deterioration due
to chloride attack is explained by the Arrhenius theory. In addition, the life
time of the structures in south Asian cities are estimated relatively short.
Keywords: deterioration process, activation
dependency, life time, diffusion, steel corrosion

energy,temperature

1. INTRODUCTION
The maintenance of reinforced concrete is now becoming a major concern
around the world due to the short supply of materials with the adequate
qualities for construction and limited budget for construction. Chloride
attack is one of the durability issues (Leeming, 1983), (Sørensen, 1982),(Popovics, 1983) especially in the coastal and marine areas. Since thedeterioration of concrete is based on diffusion or chemical reactions, then4431

October 2011, Chiang
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Chiangmai,

the deterioration progress has temperature dependency. It is generally
known that, the rate of material diffusions or the chemical reactions rises up
with the temperature elevation (Ohki, 1994).
The standards for construction materials or construction methods ofreinforced concrete in the developed countries such as USA, EU or JAPAN
have been established based from their studies and experiences under mild
temperature condition (almost 20ºC). These standards are now being used
and followed by some developing countries without enough local
investigations. When performing investigations using the standards
established in another country, temperature becomes one of the mostimportant parameters as well as the materials used.
In above viewpoints, it is necessary to determine the influence oftemperature on the deterioration process of reinforced concrete due tochloride attack and discuss the appropriate predicting or maintenancemethod under several temperature conditions.
2. EXPERIMENTAL PROCEDURE
2.1 Materials used and Environmental Conditions
Ordinary Portland cement (density: 3.16 g/cm3, specific surface area: 3
270 cm2/g) was used as binder. River sand (density(SSD): 2.60 g/cm3, F.M.:
2.59) and crashed stones (density(SSD): 2.64 g/cm3, F.M.: 7.00) were usedas fine and coarse aggregates respectively. Water-reducing and airentraining agents were used as chemical admixtures. The type of steel
embedded in the concrete specimen was SD 345 A (D16, deformed bar).
Water cement ratio of concrete was set at 0.55.
The temperature during the experiments was controlled at 20ºC, 30ºCor 40ºC in an environmental control chamber. Also the relative humidity
was controlled and maintained at 60 %.
2.2 Investigated items
In order to evaluate the temperature effect on Cl- diffusivity of minuteregion in concrete, the minute diffusion test (Otsuki, 2004) was conductedunder three levels of fixed exposure temperatures (20ºC, 30ºC or 40ºC). A
small test piece (5x5x0.5mm) taken from concrete specimen(dia.100x200mm) was placed inside an acrylic cylinder cell as shown in
Figure 1. One side of the cell was filled with NaCl solution (3.0 wt %) andthe other side was filled with saturated Ca(OH)2 solution. To measure thetime-dependent changes of Cl- concentrations in the Ca(OH)2 solution side,
the sample solution was taken every day. The concentration of Cl- was thenmeasured using ion chromatography. The diffusion coefficient wascalculated using the Fick’s law of diffusion as shown in Figure 1.

2
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ICUS Report 56

Also, in order to evaluate the temperature effect on the corrosion rateof steel bars in concrete, a corrosion monitoring test was conducted under
the same tree levels of fixed temperature (20ºC, 30ºC or 40ºC). In this study,
macrocell corrosion and microcell corrosion were separately evaluatedusing divided steel bars. In macrocell corrosion the anode and the cathodeexist non-uniformly, while, in the case of microcell corrosion the anode andthe cathode exist uniformly. The detail of reinforced concrete specimen isshown in Figure 2. The size of the specimen was 1500x 300 x 100 mm. This
specimen was embedded with a divided steel bar, which was composed ofdivided steel elements as shown in Figure 2 for the purpose of making
separate measurements for the rates of macrocell corrosion and microcell
corrosion. The divided steel bars were electrically connected using leadwires soldered on each steel element. The measurement methods ofmicrocell and macrocell corrosion rate are same with literature survey(Otsuki, 2000).
NaCl Solution(3.0wt%)

5 mm

Ca(OH)2 Solution(Saturated)

Epoxy
Resin
Matrix

Test Piece setting in
Epoxy

Rubber Sheet

C (mol/l)

Cl- Concentrationin Ca(OH)2 Solution

Test
Piece

Δ Q = Δ C ΔtV
J = ΔQ cellA
Dcl = Jcl

∂C cl
∂x

Δ
ΔC
Δ
Δt

Time

T(sec)

Figure 1: Outline of minute diffusion cell test
300mm

150mm
Divided Steel Bar

1500mm

Epoxy
Resin

Divided Steel Bar

Upper

3cm

Lead Wiresfor electrical connection
and measurement

MiddleLower

Steel Element

Epoxy Resin

Concrete

Figure 2: Outline of concrete specimen and divided steel bar

Influence ofprocess due
attackInfluenceof temperaturetemperature on
on Deterioration
deterioration process
due toto Chloride
chloride attack

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3. TEMPERATURE DEPENDENCY
CORROSION IN CONCRETE

OF

DIFFUSIVITY

AND

3.1 Theoretical background
Generally, the diffusion of substances and the chemical reactions rise
up with the temperature elevation. Since diffusion and chemical reactions
are the basis by which most cases of concrete deterioration occur, then theincrease in concrete deterioration with the increase in temperature has to beconsidered.
When the influences of temperature on the diffusion of substance or
the chemical reaction are discussed, the activation energy derived from the
Arrhenius equation is the most important value. Therefore in this chapter,the deterioration progress of reinforced concrete is discussed based on theapparent activation energy calculated by Arrhenius equation. In general, theinfluences of temperature on diffusion or chemical reaction are theoreticallyillustrated using the Arrhenius equation as shown below.
⎛ ΔE ⎞
k = a exp⎜ −(1)⎟⎝ RT ⎠

here, k is Rate Constant, a is Frequency Factor (Constant), ΔE is
Activation Energy (cal/mol), R is Ideal Gas Constant [1.99 × 10-3](cal/K/mol) and T is Absolute Temperature (K).
From equation (1), the increase in rate of the diffusion or chemical
reaction with the temperature elevation can be theoretically confirmed.
During the process of chemical reactions, the reactants seem to shift to the
products side through an active state with high energy. The differenceenergy between the active state and the reactant is called as the activationenergy (Ohki, 1994). In the process, where multiple chemical reactions aresequentially generated, the activation energy follows the reaction which
determines the rate of reaction.
On the other hand, by taking the logarithm of the given equation,
equation (1) will be transformed into the following equation.
⎛ − ΔE⎞⎛ 1 ⎞
log k = ⎜⋅ log10 e ⎟⎜ ⎟ + log a⎝ R⎠⎝ T ⎠(2)

From experimental results, the relationship between logarithm of therate constant and the reciprocal of absolute temperature is generally called
the Arrhenius plot.
3.2 Temperature effect on Cl- diffusivity in concrete

The influence of temperature on diffusivity of Cl- in concrete is shownin Figure 3. From these graph, it can be seen that the rate of Cl- diffusion in
concrete rises up with the increase in temperature. Also the Arrhenius plots

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ICUS Report 56of the Cl- diffusivity in concrete are shown in Figure 4. From this, it can beseen that the relationship between logarithms of the diffusivity and thereciprocal of absolute temperature can be linearly distributed. Therefore it
can be concluded that the diffusion of Cl- in concrete follows Arrhenius
theory. Moreover, the apparent activation energies of the Cl- diffusivity inconcrete obtained from Arrhenius plots are shown in Table 1. From thistable, it can be seen that the apparent activation energies obtained in thisstudy are a little high comparing with that obtained in literature survey(Page, 1981). This is because activation energies obtained in the literature
survey are based on the data of cement paste. On the other hand, the Cldiffusivities of minute test pieces taken from concrete containing interfacialtransition zone between aggregate and cement matrix are used in this study.
That is, it is considered that the pore structure of cement matrix, especiallythe property of the interfacial transition zone, influences on the apparent
activation energy and diffusion phenomenon.

Cl- Diffusivity x 10-7 (cm 2/sec)

15.0

Bleeding Ratio
0.18%
0.51%
4.58%

10.0

5.0

0.0
10
0

20

30

40

50

3.3

3.4

3.5

Temperature (℃)

Bleeding Ratio
0.18%

Log (Cl- diffusivity )

-2

0.51%
4.58%

-4

-6

-8

-10
3.1

3.2

1000/Temperature(1/K)

Figure 3: Influence of temperature
on Cl- diffusivity in concrete

Figure 4: Arrhenius plotsof Cl- diffusivity in concrete

Table 1: Apparent activation energies of Cl- diffusivity in concreteobtained from Arrhenius plots
Present study: containing aggregate
Literature survey (Page, 1981): cement paste

Influence ofprocess due
attackInfluenceof temperaturetemperature on
on Deterioration
deterioration process
due toto Chloride
chloride attack

Activation Energy (kcal/mol)
16.8-32.2
7.7-10.04475

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 5 shows the relationship between Cl- diffusivity of concrete
and water cement ratio proposed by JSCE standard specification (JSCE,2001). And the broken lines in the graph show the Cl- diffusivities
considering with ±10ºC difference against JSCE equation using obtained
apparent activation energy. From this graph it is observed that the scatteringof Cl- diffusivity in the literature data seems to be explained by temperatureeffect. Therefore it can be concluded that the temperature profile is one of
the most important factors when we check the diffusion coefficient of Cl- in
design stage.

Diffusion Coefficient (cm 2/year)

1.E+02+10ºC

1.E+01- 10ºC

1.E+00

1.E-01Equation proposed by JSCElog D = -3.9(W/C)2+7.2(W/C)-2.5

1.E-02
0.2

0.3

0.4

0.5

W/C

0.6

0.7

0.8

Figure 5: Relationship between Cl- Diffusion Coefficient and W/C (JSCE,2002) and temperature effect obtained in present study
3.3 Temperature effect on corrosion of steel bar in concrete
The influences of temperature on macrocell and microcell corrosion
rate in concrete are shown in Figure 6. From these graphs, it can be seen thatthe macrocell and microcell corrosion rate in concrete rise up withtemperature elevation. Also the Arrhenius plots of the corrosion rate inconcrete are shown in Figure 7. From these figures, it can be seen that therelationship between the logarithms of corrosion rate and the reciprocal ofabsolute temperature can be linearly distributed. Therefore it can beconcluded that the behavior of steel corrosion in concrete follows Arrhenius
theory. Moreover, the apparent activation energies of macrocell andmicrocell corrosion in concrete obtained from Arrhenius plots are shown in
Figure 8. From these figures, it can be seen that macrocell and microcell
corrosion in concrete has different temperature dependency. That is to say,the apparent activation energy of macrocell corrosion increases with theincrease in specific concrete resistance. On the other hand, the apparent
activation energy of microcell corrosion is constant regardless of thespecific concrete resistance.

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Macrocell Corrosion Rate (mm/year)

ICUS Report 56
0.03

Position of Steel Bar
Upper

Middle
Lower

0.02

0.01

0.00
10

20

30

40

Temperature (℃)

50

Microcell Corrosion Rate (mm/year)(a) Macrocell corrosion rate
0.003

Position of Steel Bar
Upper

Middle
Lower

0.002

0.001

0.000
10

20

30

40

Temperature (℃)

50

Macrocell Corrosion Rate (mm/year)(b) Microcell corrosion rate
Figure 6: Influence of temperature on corrosion rate of steel bars inconcrete
0.0

-1.0
-2.0
-3.0
-4.0
-5.0

Position of Steel Bar
Upper

Middle

3.2

3.3

-6.0
3.1

3.4

1000/Temperature(1/K)

3.5(a) Macrocell corrosion rate

Influence ofprocess due
attackInfluenceof temperaturetemperature on
on Deterioration
deterioration process
due toto Chloride
chloride attack

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Microcell Corrosion Rate (mm/year)

October 2011, Chiang
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Chiangmai,
0.0
-1.0
-2.0
-3.0
-4.0
-5.0

Position of Steel Bar
Upper

Middle

3.2

3.3

Lower

-6.0
3.1

3.4

1000/Temperature(1/K)

3.5(b) Microcell corrosion rate
Figure 7: Arrhenius plots of corrosion rate of steel bars in concrete

Apparent Activation Energy(kcal/mol)25

Macrocell Corrosion
Microcell Corrosion

20

15

10

5

0
0

5

10

15

Specific Concrete Resistance (kΩ・cm)

Figure 8: Apparent activation energy of corrosion rate of steel bar
4. PREDICTION OF DETERIORATION PROCESS CONSIDERINGTEMPERATURE EFFECT
4.1 Life time of reinforced concrete due to steel corrosion
The determination of the life time of reinforced concrete is a difficult
task because it includes many factors such as the importance of structures,part of the member or financial issue. However it is important to discuss thelife time of structures based on several assumptions from the engineering
point of view. In this study, the life time was defined as the sum of the terms
of prediction results of the incubation, propagation and acceleration period,
and the influence of temperature on the life time of reinforced concrete wasdiscussed.
The water cement ratio, water content in mixture proportion andconcrete cover were set at 0.55, 175kg/m3 and 7.0cm respectively. The

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ICUS Report 56

environmental condition considered in this prediction was tidal zone whichis considered as the most severe environment that induces chloride attack.
Also, in this prediction, the data of temperatures for 55 cities around theworld was used.
4.2 Prediction of incubation periods
In order to predict the incubation periods, the rate of Cl- diffusion in
reinforced concrete considering the temperature was investigated using a
numerical analysis. In this numerical analysis, Nernst-Planck equationconsidering with Debye-Hückel equation and electro-neutrality condition
was used. By considering these equation and condition, the influence of coexisting ions in pore solution of concrete could be simulated. The
effectiveness of this numerical analysis was already confirmed in theliterature survey done by authors (Minagawa, 2002). In this study the above
numerical analysis was modified as following equation in order to consider
the effect of the temperature.
⎛
⎜
4 ⎞
⎜
⎛
0.51 ⋅ ZCl⎜⎟
JCl = −⎜ k ⋅ T1 ⋅ BCl ⋅ ⎜ 1 − ln10 × CCl ⋅
2 ⎟⎟
⎜
⎜
(
)
4
⋅
1
+
I
I
⎝
⎠
⎜
⎜
⎝

⎜
⎜
⎜
∂C n
0.51 ⋅ Z n4 ⎟⎟⎜⎟k ⋅ T1 ⋅ ∑ ⎜⎜ Z n ⋅ ⎜⎜1 − ln10 × C n ⋅⎟ ⋅B ⋅
n ∂x
⎜
⎜
⎛
⎞2 ⎟
4 I ⋅ ⎜⎝ 1 + I ⎟⎠ ⎟⎟⎠
n ⎜⎜⎝
⎜⎜
⎝
⎛

− ZCl ⋅ BCl ⋅ CCl ⋅

⎛

⎞

⎛
⎞
⎜ 2
⎟
∑ ⎜⎜ Z n ⋅ Bn ⋅ C n ⎟⎟⎝⎠n⎞∂CCl ⎟⎟⎟ ⎞⎟⎟∂x ⎟⎟ ⎟
⎟⎟
⎠
⎟
⎟
⎟
⎟
⎠

⎛ ΔE ⎛ 1 1 ⎞ ⎞ ∂C× exp⎜⎜ ⎜⎜ − ⎟⎟ ⎟⎟ ⋅ Cl
⎝ R ⎝ T1 T2 ⎠ ⎠ ∂x

(3)

J is Flux of Ions (mol/cm2/sec), I is Ionic Species, k is Boltzman
Number , [=1.38×10-23] (J/K), T1 is Basic Absolute Temperature [=297](K), T2 is Absolute Temperature, B is Absolute Mobility (cm2/sec/V), C is
Concentration of Ions (mol/cm3), x is Distance from Exposure Surface (cm),e is Elementary Electric Charge [=1.60×10-19] (C), Z is Ionic Charge
Number,φ is Electrostatic Potential (V).
The steel bar in concrete starts to corrode after the Cl- concentration
over the certain value (threshold concentration). “Technical Standards andCommentaries for Port and Harbour Facilities in Japan” (MLIT, 2009)
describes that the threshold concentration of Cl- can be set at around 2.0
kg/m3 in port and habour port concrete facilities. In this study, the period
until the Cl- concentration around steel bar reaches to 2.0 kg/m3 is calculated
by numerical analysis as incubation period.
4.3 Prediction of propagation and acceleration periods
In order to predict the propagation and acceleration periods, the rate ofsteel corrosion in concrete considering temperature effect was investigated.
The total quantity of corrosion was calculated by taking the sum of the

Influence ofprocess due
attackInfluenceof temperaturetemperature on
on Deterioration
deterioration process
due toto Chloride
chloride attack

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quantity of corrosion in each period. The method of prediction for steel
corrosion in concrete considering temperature effect is explained in thefollowing.
Considering the influence of temperature on deterioration ofreinforced concrete, the rate of corrosion of steel bar (macrocell andmicrocell) in concrete is different from each period. Especially it was
confirmed that the influence of temperature on macrocell and microcell
corrosion is different in previous chapters. Therefore, in case of predicting
the propagation and acceleration period, it is necessary to consider the
influence of temperature on macrocell and microcell corrosion rate
separately. In this study the quantity of corrosion was calculated byintegration of the rate of macrocell or microcell corrosion. The total quantityof corrosion was then calculated by the sum of the quantities of macrocell
and microcell corrosion.
In the case of predicting the process of corrosion in concrete, it isnecessary to know the basic rate of corrosion at a certain temperature. The
data of corrosion rate at 20 ºC as shown in Table 2 were used as a reference
for the basic rate of steel corrosion in concrete. In the case of corrosion rateof steel bar in concrete before cracking, the experimental results obtained in
the previous section were used. On the other hand in the case of thecorrosion rate after cracking, the experimental results obtained by Otsuki(2000) were used.
Table 2: Data of corrosion rate at 20 ºC
Before cracking
After cracking (Otsuki, 2000)

Corrosion rate at 20 ºC (mm/year)
Macrocell
Microcell
5.5 x 10-3
2.6 x 10-4
-2
2.0 x 10
6.0 x 10-2

The total quantity of corrosion is calculated by taking the sum of thequantity of corrosion rates obtained in each period. Here it is reported thatthe total quantity of corrosion for crack propagation is equal to 10 mg/cm2(JSCE, 2001). Also it is reported that the bending property of reinforced
concrete becomes 70% of the initial property when 15 % of the steel bar
decreases due to corrosion (Miyagawa, 1998). According to this literature
survey the quantity of corrosion at 15 % degradation of strength in case ofsteel bar with 16mm diameter is about 510 mg/cm2. Therefore the quantities
of corrosion at 10 mg/cm2 and 510 mg/cm2 were used in order to determine
the periods of cracking (end of propagation period) and structural
deterioration (end of acceleration period) respectively.
4.4 Predicted results
Figure 9 shows the relationship between the life time of reinforced
concrete and the average temperature. From this figure it can be confirmedthat the period of incubation, propagation and acceleration varied with theregional and seasonal temperature, and the life time of reinforced concrete
exponentially decreased as the average temperature of the city. It is

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therefore necessary to consider temperature effect on the design andmaintenance of reinforced concrete, especially in the key cities of SouthEast Asian countries, where deterioration was most severe as indicated byreinforced concrete having only 70% of the life time compared to othercountries with mild temperature environment (20ºC) Also it can beconsidered that the life time of the reinforced concrete decreases 50% with
10 °C increase of temperature.
120

Japan
Other Asian Countries
U.S.A. Continent
EuropeLife Time (year)

100
80
60

South‐East Asia
40

50%
20

70%

0
0

10

20

Average Temperature(ºC)

30

Figure 9: Predicted results of life time of reinforced concrete using the 55
cities of temperature profile
5. CONCLUSION
In present study, the influence of the temperature on the deterioration
progress of RC due to chloride attack is theoretically and experimentallyinvestigated. From the investigations the following conclusions are
obtained;(1) The influence of temperature on deterioration due to chloride attack is
explained by the Arrhenius theory from the view point of practice.
(2) The life time of structures in several cities in severe marine environment
are estimated. And the life time of the structures in south Asian cities are
estimated relatively short.
REFERENCES
Japan Society of Civil Engineers, 2001. Standard Specification forConcrete, Maintenance, 97-112.
Japan Society of Civil Engineers, 2002. Complementary for Standard
Specifications for Concrete Structures, Concrete Library 108, 55.
Leeming, M. B., 1983. Corrosion of Steel Reinforcement in Off-shore
Concrete Experience from the Concrete-in-the-Oceans Programme,

Influence ofprocess due
attackInfluenceof temperaturetemperature on
on Deterioration
deterioration process
due toto Chloride
chloride attack

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October 2011, Chiang
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Chiangmai,

Corrosion of Reinforcement in Concrete Construction, Edited by. A.P.
Crane. Ellis Horwood Ltd., Chichester, UK, 59-78.
Minagawa, H., Otsuki, N., Miyazato, S., and Nishida, T., 2002.
Establishment of Numerical Analysis Method For the Prediction of
Leaching of Calcium from Concrete Considering Migration of Multiple Ions,
Concrete Library of JSCE, No.40, 253-268.
Miyagawa, T., Takewaka, K., Masuda, Y., and Moriwake, A., 1998.
Report of Research Committee of Rehabilitation of Concrete Structures,
Proceedings of the Japan Concrete Institute, V. 20, No. 1, 39-48.
Ohki, M., Ohsawa, T., Tanaka, M., and Tihara, H., 1994. Chemical
Dictionary, 275.
Otsuki, N., Miyazato, S., Diola, N. B., and Suzuki, H., 2000.
Influences of Bending Crack and Water-Cement Ratio on Chloride-Induced
Corrosion of Main Reinforcing Bars and Stirrups, ACI Materials Journal, V.
97, No. 4, 454-464.
Otsuki, N., Yodsudjai, W., Nishida, T., and Yamane, H., 2004. New
Test Methods for Measuring Strength and Chloride Ion Diffusion
Coefficient of Minute Region in Concrete, ACI Materials Journal, V. 101,
No. 2, 146-153.
Page, C. L., Short, N. R., and Tarras, A. El, “Diffusion of chloride
ions in hardened cement pastes.” Chemical and Concrete Research, 11, 1981,
pp.395-406.
Popovics, S., Simeonov, Y., Boshinov, G., and Barovsky, N., 1983.
Durability of Reinforced Concrete in Sea Water, Corrosion of
Reinforcement in Concrete Construction, Edited by. A.P. Crane. Ellis
Horwood Ltd., Chichester, UK, 19-38.
Ports and Harbours Bureau, Ministry of Land, Infrastructure,
Transport and Tourism (MLIT), National Institute for Land andInfrastructure Management, MLIT, and Port and Airport Research Institute,2009. Technical Standards and Commentaries for Port and Harbour
Facilities in Japan, 370.
Sørensen, B., and Maahn, E., 1982. Penetration Rate of Chloride in
Marine Concrete Structures, Nordic Concrete Research, Publication No.1,
24

12
454

New Technologies
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Asia
NewDurability evaluation of marine structure
based on continuous microstructureof concrete
Hitoshi AKIYAMA1, Tomoya SAGAWA2, Shafiqul Md. ISLAM1
and Toshiharu KISHI3
1
Graduate Student, School of Eng., The University of Tokyo, Japan
hito@iis.u-tokyo.ac.jp
2
Toshiba Plant Systems & Services Corporation
3
Professor, Institute of Industrial Science, The University of Tokyo

ABSTRACTThis study discussed the relationship between chloride ion penetration andmicrostructure of concrete. The concrete cores were collected from themarine structures (the breakwater and launch slope) in the cold region ofJapan. The blast furnace slag cement was used. This study applied themercury step-by-step intrusion prosimetry(MSIP) to the measurement ofporosity. The MSIP repeats the intrusion and extrusion of mercury several
times while gradually increasing the maximum pressure in order toseparately measure connective pores from ink-bottle pores and to detect thethreshold pressure which starts to cause microstructure deformation. As aresult, it turned out the chloride ion penetration was shallow in the case ofhorizontal cores. The apparent chloride ion diffusion coefficient of thehorizontal cores tended to be lower than that of vertical ones. In addition,some cores showed high chloride ion density only near the surface. These
cores had less connective pores near the surface. It suggested the lessconnective pores prevented the chloride ions from penetration into thedeeper layer.
Keywords: marine structure, chloride attack, blast furnace slag cement,
mercury step-by-step intrusion prosimetry
1. INTRODUCTION
Marine structures have the risk of deterioration by chloride attack. Surface
concrete plays a role in protection of inside steel from the chloride attack.
Chloride ion penetration into concrete is a phenomenon related to water
ingress, ion diffusion or chemical adsorption. Blast furnace slag cement or
fly-ash cement are effective to increase the resistance to the chloride ion
penetration.
The objective of this study is to discuss the chloride ion penetration of
blast furnace slag cement concrete. Especially, this study focused on the4551

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relationship between the chloride ion penetration and microstructure
properties of concrete.
2. FIELD WORK AND EXPERIMENTS
2.1 Investigated structureThis study investigated the some marine structures (the breakwaterand launch slope) in the cold region of Japan. Figure 1 shows the length andconstruction period of the breakwater. It was constructed from 1993 to 1998
toward the sea, and the launch slope was built in 1970. The breakwater
constructed in 1998 is located on the edge and its length is only 10m. Table
1 shows the material design of the breakwater. The blast furnace slag
cement was used. The maximum water to cement ratio was 55%. The
launch slope is located at the root of the breakwater. The material design ofthe launch slope is unknown.

268

230

241

94

360

10m

1993

1994

1995

1996

1997

1998

Figure 1: Length and construction period of the breakwater
Table 1: Material design of breakwater

Nominal strength at 28day(N/mm2)
Slump(cm)Air content(%)
Maximum aggregate size(mm)Cement type
Maximum water to cement ratio(％)
Maximum chloride ion content(kg/m3)

21
5
4.5
40
BB
55
0.30

Figure 2 shows the standard cross-section of the breakwater. The eastside is offshore and wave-dissipating blocks are placed. The height of theeast side is 6.7m above the sea level, and the west side is 5.0m. There was aslope 2.2m apart from the east side. Concrete cores were collected from thetop, side or bottom shown in the figure. In addition, there were stripe
patterns at the surface of the side of the breakwater constructed after 1995.
They might be the marks where the water-permeable forms were used. In
the case of the launch slope, the core was collected from the intertidal zone.

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ICUS Report 56
Top
Wave-dissipating blocks

+6.7m
Side

Bottom+5.0m

East(Offshore)

West
H.W.L. +1.5m
L.W.L. ±0.0m
2.2m

11.55m15.1m

Figure 2: Standard cross-section of the breakwater
Table 2: Collected concrete cores
Construction Period
Launch slope

Breakwater

Top

1970
1993
○
1994
1995
1996
○
1997
○
1998
○
◇:Intertidal zone ○: Splash zone

Surface
Side
◇
○
○
○
○
○

Bottom○○

2.2 Measurement of chloride ion density
The collected cores were sliced 10mm intervals to the depth of 70mm
by using the diamond cutter. The total chloride ion density was measured
by the potentiometric titration. The apparent chloride ion diffusion
coefficient(Da(cm2/year)) and surface chloride ion density(C0(kg/m3)) were
calculated by regression calculation based on the Fick’s laws ofdiffusion(equation 1).
⎛

⎛
⎞⎞
x
⎟⎟
⎜ 2 D ⋅t ⎟ ⎟a⎝⎠⎠

C ( x ,t ) = C 0 ⎜1 − erf ⎜
⎜
⎝

where
C：chloride ion density (kg/m3)
x : depth (cm)t: material age (year)
C0: surface chloride ion density(kg/m3)
Da: apparent chloride ion diffusion coefficient(cm2/year)
erf(s)：error function(1)

2.3 Measurement of porosity
The microstructure at 0-10mm and 10-20mm from the surface wasanalyzed respectively by using the mercury intrusion porosimetry. However,the previous studies pointed out that the conventional mercury intrusion
porosimetry has two problems: One is to overestimate the fine pore volume
by the existence of ink-bottle pores. The other is to enlarge original

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Durability
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October 2011, Chiang
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microstructure by the high intrusion pressure of the mercury. Then thisstudy used the mercury step-by-step intrusion porosimetry(MSIP). The
MSIP repeats the intrusion and extrusion of the mercury several times while
gradually increasing the maximum pressure in order to separately measureconnective pores from ink-bottle pores and to detect the threshold pressure
which starts to cause microstructure deformation. The pore diameter isderived from the equation 2.

D =−4γ cos θP

where
D： pore diameter(m)γ：surface tension of mercury(Pa/m)
P：intrusion pressure(Pa)θ：contact angle(°)(2)

Table 3: Pressure hysteresis of the mercury step-by-step intrusion
porosimetry
Intrusion
stage
1
2
3
4
5
6
7
8
9
10
11
12

Pressure(MPa)
Start
End
1.25
0.00365
0.312
4.16
0.312
12.5
0.312
15.6
0.312
20.8
0.312
31.2
0.312
62.4
0.312
125
0.312
178
0.312
250
0.312
416
0.312
416

Pore diameter(nm)
Start
End
342000
1000
4000
300
4000
100
4000
80
4000
60
4000
40
4000
20
4000
10
4000
7
4000
5
4000
3
4000
3

3. RESULTS AND DISCUSSIONS
3.1 Chloride ion density
Figure 3 shows the total chloride ion density. Firstly, the density in thehorizontal direction tended to be lower. The density in 1970 was the highest
among the horizontal cores. It might be because the concrete was located in
the intertidal zone. The second highest was the density in 1995. The point toobserve is that the density in 1994, 1997 and 1998 was high only near thesurface and it sharply decreased at 1.5-2.5cm. Especially, the density at
1.5cm was zero in 1997.
In the case of the vertical concrete, the penetration in 1995 was largest. The
second highest was the density in 1994. The density in 1997 and 1998 wasrelatively low.

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-

3

Cl (kg/m )Cl-(kg/m3)

ICUS Report 56

Depth (cm)（ii）Vertical

Depth(cm)（i）Horizontal

Depth(cm)1997 Side

Depth (cm)1998 Side（i）Horizontal

Cl-(kg/m3)-

3

Cl (kg/m )Cl-(kg/m3)
Depth (cm)1996 SideCl-(kg/m3)

Cl-(kg/m3)

Depth(cm)1995 Side

Depth (cm)1994 Bottom

Depth (cm)1993 Top

Depth (cm)1996 Top

Depth (cm)1995 Bottom

Cl-(kg/m3)

Cl-(kg/m3)

Cl-(kg/m3)

Depth (cm)1994 SideCl-(kg/m3)

Depth(cm)1970 SideCl-(kg/m3)

Cl-(kg/m3)

Cl-(kg/m3)

Figure 3: Chloride ion density

Depth (cm)1998 Top

Depth (cm)1997 Top（ii）VerticalFigure 4: Approximate curves of the chloride ion density distributions(The white marks were ignored.)
3.2 Surface chloride ion density and apparent chloride ion diffusion
coefficient
Figure 4 shows the approximate curves of the chloride ion density
distributions when applying the Fick’s laws of diffusion. The white marks
represent the points which were not taken into account due to relatively low
values as a consequence of washout by rainfall or something. Figure 5
Durability evaluation
Durability
evaluation ofof marine
marine structure
structure based
based ononcontinuous
continuousmicrostructure
microstructureofofconcrete
concrete4595

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Cl-0 (kg/m3)

shows the surface chloride ion density. According to this, the surface
density was around 10 to 30 kg/m3. Figure 6 shows the apparent the chloride
ion diffusion coefficient. The diffusion coefficient of “1995 Bottom” washighest. The diffusion coefficient of “1994 Side”, “1996 Side” and “1997Side” was relatively low.

Da(cm2/√year)

Figure 5: Surface chloride ion density

Figure 6: Apparent chloride ion diffusion coefficient
3.3 Porosity
Figure 7 shows the cumulative pore volume at 0-10mm and figure 8
shows that of 10-20mm. The total porosity and the connective porosity wereshown respectively. The cumulative curves of the total porosity were
described by the mercury volume which was totally intruded into thesamples. The curves of the connective porosity were obtained by subtracting
the volume of inkbottle pores from that of total porosity. The minimum
diameter of the connective porosity was detected by overlapping each
intrusion curve and observing their agreement. The measured minimum
diameter was the 5 or 7nm.

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ICUS Report 56

㧔i㧕Horizontal（i）Horizontal

Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1994 Bottom
1994 Bottom

3

3

Cumulative pore volume(cm /cm ）Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1997 Top
1997 Top

Cumulative pore volume(cm3/cm3㧕

Pore diameter(nm)Pore diameter(nm)1995 Bottom
1995 Bottom

Cumulative pore volume(cm3/cm3㧕

Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1998 Side
1998 Side

Pore diameter(nm)Pore diameter(nm)1993 Top
1993 Top

Cumulative pore volume(cm3/cm3㧕

Cumulative pore volume(cm3/cm3㧕
3

3

Pore diameter(nm)Pore diameter(nm)1996 Side
1996 Side

Cumulative pore volume(cm3/cm3㧕

Pore diameter(nm)Pore diameter(nm)1994 Side
1994 Side

Cumulative pore volume(cm /cm 㧕

Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1997 Side
1997 Side

Cumulative pore volume(cm3/cm3㧕

3
3

Pore diameter(nm)Pore diameter(nm)1995 Side
1995 Side

Cumulative pore volume(cm3/cm3㧕

Cumulative pore volume(cm3/cm3）

Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm /cm ）3

Pore diameter(nm)Pore diameter(nm)1970 Side1970 Side

Cumulative pore volume(cm3/cm3㧕

Cumulative pore volume(cm3/cm3㧕

Total Total
porosity
porosity

Continuous
Continuous
porosity
porosity

3

3

3

Cumulative pore volume(cm /cm 㧕
Cumulative pore volume(cm /cm 㧕In thecasecaseof 1994
andand1995,
the thetotaltotal
porosity
andandconnective
In theof 1994
1995,
porosity
connective
porositywere
not not
so different
while
the thechloride
penetrationin theverticalporositywere
so different
whilechloride
penetrationin theverticaldirection
waswashigher.
It seemed
thatthat
the thesea seawater
waswaslikelyto remainat atdirectionhigher.
It seemedwaterlikelyto remain
the thehorizontal
surfaceandandthe thegravityaccelerated
the thesea seawater
ingress.
horizontal
surfacegravityaccelerated
water
ingress.
TheThetotaltotal
andandconnective
porosityin theverticaldirectionin 1996
werelesslessconnective
porosityin theverticaldirectionin 1996
were
thanthanhorizontal
direction,
but but
the thechlorideion ionpenetration
waswashigher.
It alsohorizontal
direction,
chloride
penetration
higher.
It alsoseemedthe theinfluenceof thesea seawater
ingress.
seemedinfluenceof thewater
ingress.

Pore diameter(nm)Pore diameter(nm)1996 Top
1996 Top

Pore diameter(nm)Pore diameter(nm)1998 Top
1998 Top

㧔ii㧕Vertical（ii）VerticalFigure7: Cumulative
poreporevolume(0-10mm)Figure7: Cumulative
volume(0-10mm)
TheTheconnective
poreporein 1997
waswasclearlylesslesswhile
its penetration
waswasconnective
in 1997
clearlywhile
its penetration
shallowest
among
all allhorizontal
cores.
It might
reducethe thechlorideion ionshallowest
amonghorizontal
cores.
It might
reducechloride
penetration.
penetration.
In thecasecaseof 1998,
the thetotaltotal
andandconnective
porosityin thehorizontal
In theof 1998,
connective
porosityin thehorizontal
direction
werelesslessthanthanthe theverticaldirection,
while
there
waswasa slight
direction
wereverticaldirection,
while
there
a slight
differencein thechlorideion ionpenetration.
It could
be beexplained
by by
the thedifferencein thechloride
penetration.
It could
explainedlocation.
TheTheconcretein 1998
waswason theedgeedgeof thebreakwater
where
the thelocation.
concretein 1998
on theof thebreakwaterwhere
sea seawatersplashed
severely.
TheThesupplyof thesea seawater
might
be morethanthanwatersplashed
severely.
supplyof thewater
might
be morethe theotherplaces.
otherplaces.

Durability
evaluationofstructurebasedonmicrostructure
ofofconcrete
Durability
evaluationof marine
structure
based
on continuous
microstructureof concrete
Durability
evaluationof marine
marinestructurebased
oncontinuous
continuous
microstructure
concrete

4617

October
Chiangmai,
Thailand
October
2011, 2011,
Chiang
Mai,Thailand
Thailand
Chiangmai,（i）Horizontal
㧔i㧕Horizontal

Cumulative pore volume(cm3/cm3）

Cumulative pore volume(cm3/cm3㧕
Cumulative pore volume(cm3/cm3㧕
Cumulative pore volume(cm /cm 㧕Pore diameter(nm)Pore diameter(nm)1997 Top 1997 Top

Pore diameter(nm)Pore diameter(nm)1996 Top 1996 Top

33

Pore diameter(nm)Pore diameter(nm)1995 Bottom
1995 Bottom

Pore diameter(nm)Pore diameter(nm)1994 Bottom
1994 Bottom

3

Cumulative pore volume(cm3/cm3㧕
Cumulative pore volume(cm /cm 㧕

3

Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm3/cm3）

Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1998 Side1998 Side

Cumulative pore volume(cm3/cm3）

Pore diameter(nm)Pore diameter(nm)1997 Side1997 Side

Pore diameter(nm)Pore diameter(nm)1996 Side1996 Side

Pore diameter(nm)Pore diameter(nm)1993 Top 1993 Top

Cumulative pore volume(cm3/cm3㧕

3

3

Pore diameter(nm)Pore diameter(nm)1995 Side1995 Side

Pore diameter(nm)Pore diameter(nm)1994 Side1994 Side

Cumulative pore volume(cm3/cm3）

Cumulative pore volume(cm3/cm3㧕
Cumulative pore volume(cm3/cm3㧕
Cumulative pore volume(cm3/cm3㧕

3

3

Cumulative pore volume(cm /cm ）Cumulative pore volume(cm3/cm3）
Cumulative pore volume(cm /cm ）Cumulative pore volume(cm3/cm3㧕
3
3

Cumulative pore volume(cm /cm 㧕Pore diameter(nm)Pore diameter(nm)1970 Side1970 Side

Cumulative pore volume(cm3/cm3㧕

3

Cumulative pore volume(cm3/cm3）

Total
Total
porosity porosity

Continuous
Continuous
porosity porosity

3

Cumulative pore volume(cm /cm ）Cumulative pore volume(cm3/cm3）

By comparingof horizontal
the horizontal
for 1998,
By comparing
all ofallthe
cores cores
exceptexcept
for 1998,
the theconnective
porosity
in 1997
and 1994
was least
andporosity
the porosity
in 1995
connective
porosity
in 1997
and 1994
was leastand thein 1995
was most.
Similarly,
the apparent
chlorideion diffusion
coefficientin 1997
was most.
Similarly,
the apparent
chlorideion diffusion
coefficientin 1997
and 1994
was lowest
andinthatin 1995
was highest.
It is likelythat there
and 1994
was lowest
and that1995
was highest.
It is likelythat there
was wasa relationshipbetweenthe chloride
ion penetrationand connective
the connective
a relationshipbetweenthe chloride
ion penetrationand theporosity.
the direction
the same,the concreteless connective
porosity.
If theIfdirectionis theissame,the concretewith withless connective
porosity
the surface
prevent
the chloride
penetration.
This oftype ofporosityat theatsurface
mightmight
prevent
the chloride
penetration.
This typeconcretethe high
chlorideion density
the surface
concretemay may
show show
the high
chlorideion density
near near
the surface
and andshallow
chloride
ion penetration.
shallow
chloride
ion penetration.

Pore diameter(nm)Pore diameter(nm)1998 Top 1998 Top

㧔ii㧕Vertical（ii）VerticalFigure8: Cumulative
pore volume(10-20mm)
Figure8: Cumulative
pore volume(10-20mm)
4. CONCLUSIONS
4. CONCLUSIONSThe chloride
ion penetration
is likely
be affectedby continuous
the continuous
The chloride
ion penetration
is likely
to betoaffectedby theporosity.
connective
porosity
can reducethe chloride
porosity.
The Theless lessconnective
porosity
can reducethe chloride
ion ionpenetration.
The concrete
withconnective
less connective
porosity
may show
the high
penetration.
The concretewith lessporosity
may show
the high
chlorideion density
nearsurface
the surface
and shallow
penetration.
The direction
chlorideion density
near theand shallow
penetration.
The directionof penetration
be consideredalso consideredthewatersea water
ingressof penetration
shouldshouldbe alsosince since
the sea
ingressin thein theverticaldirection
be higher
thanhorizontal
the horizontal
direction.
verticaldirection
can becanhigherthan thedirection.

8
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New Technologies
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in Asia
Asiain Asia
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for Urban
of MegaNew
for
Safetyof
CitiesinICUS Report 56

ACKNOLEDGEMENTS
We would like to thank the Hokkaido Development Agency for giving us
the opportunity of the site investigation. Also thanks are due to Dr.Hiroshi
UEDA(Railway Technical Research Institute) and Dr.Isao KURASHIGE(Central Research Institute of Electric Power Industry) for the cooperationon the site.
REFERENCES
Diamond, S., 2000. Mercury porosimetry: An inappropriate method
for the measurement of pore size distributions in cement-based materials,
Cement and Concrete Research, Vol.30, 1517-1525
Yoshida, R. and Kishi, T., 2007. A study on effect of air void anddestruction of the pore structure at high pressure level based on hysteresis
behavior on mercury Intrusion. Cement Science and Concrete Technology,
No.60, 68-75
Yoshida, R. and Kishi, T., 2008. Proposal of a new approach for
determination of pore continuity and suitable intrusion pressure based on
step-by-step mercury intrusion porosimetery test. 1st International
conference on Microstructure Related Durability of Cementitious
Composites, Vol.2, 1455-1464
Yoshida, R., Kishi, T., Nakarai, K., and Li, C., 2009. Effectiveness ofconnective porosity measured by mercury step-by-step intrusion
porosimetry and proposal of its index. Concrete technology series, No.87,
Japan Society of Civil Engineers
Takahashi, Y., Inoue, S., Akiyama, H., and Kishi, T., 2010. Study onchloride penetration into fly-ash concrete of existing structure and influenceof material age. Proceedings of Japan Concrete Institute, Vol.32
Maruya, T., Tangtermsirikul, S., Matsuoka, Y., 1998. Modeling ofchloride ion movement at the surface layer of hardened concrete.
Proceedings of Japan Society of Civil Engineers, No.585
Ishida, T., Prince, O., and Ho, T.,2009. Modeling of chloride
diffusivity coupled with non-linear binding capacity in sound and cracked
concrete, Cement and Concrete Research, Vol.39, 913-923
Prince, O., and Ishida, T.,2009. Modeling of Chloride Transport
Coupled with Enhanced Moisture Conductivity in Concrete Exposed toMarine Environment, Cement and Concrete Research, Vol.39, 329-339
Amino, T., Otsuki, N., Saito, T., and Hanebuchi, T., 2010. Proposal
for estimation method of surface chloride content of RC deck in open-piled
pier considering the structural types and the influence of wave action.
Concrete research and technology, Vol.21, 1-11
Sugiyama, T., Sato, F., Ushijima, S., and Sakai, E., 2010. Relationshipbetween microstructure and chloride ion penetration resistance of low water
to powder ratio concrete with admixtures. Proceedings of Japan Concrete
Institute, Vol.32

Durability evaluation
Durability
evaluation ofof marine
marine structure
structure based
based ononcontinuous
continuousmicrostructure
microstructureofofconcrete
concrete4639

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New Technologies for Urban Safety of Mega Cities in Asia

Defect detection and crack classificationin cementitious materials
by ultrasonic testing with ANN
Saowanee SAECHAI1, Pansaran SARANROM2,
Raktipong SAHAMITMONGKOL3,Waree KONGPRAWECHNON4,
and Somnuk TANGTERMSIRIKUL5
1
Graduate Student, School of Information, Computer,and Communication Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
saowanee.sae@hotmail.com
2
Graduate Student, School of Civil Engineering and Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
3
Researcher, Construction and Maintenance Technology Research Center
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
4
Associate Professor, School of Information,
Computer, and Communication Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
5
Professor, School of Civil Engineering and Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand
ABSTRACTThis paper introduces a newly developed testing system for theclassification of defect and surface crack in the cement-based materials.
With the system, the pattern of ultrasonic waves for each case of medium
can be measured. The machine learning algorithm called back-propagation
artificial neural network (ANN) classifier is employed for classification andverification of the wave patterns obtained from the different samples. By
applying the system, the presence or absence of a defect in mortar can be
identified. Moreover, the system is applied to determine whether crack
depth reaches the reinforcing bar. The methodology is explained and theclassification results are discussed. The effectiveness of the developed
testing system is also performed. The comparison of the classification
results between the time and frequency domain signals with the ANN
classifier is also demonstrated. The system is proved to be beneficial to thestructure inspection.
Keywords: ultrasonic wave, defect detection, surface crack, artificial neuralnetwork, pattern recognition4651

October 2011, Chiang
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Chiangmai,

1. INTRODUCTION
In many constructions, the concrete structures can be degraded due to aging
and, without an appropriate maintenance work, the failure of thedeteriorated structure may occur in many different forms. There may beembedded defects or surface cracks in the structure. In the case of surface
crack, if cracks penetrate through reinforcing bar, moisture and oxygen caneasily reach rebar and drastically accelerate corrosion of rebar and causes
the reduction rebar cross sectional area of rebar as well as spalling of coverconcrete (Gebregziabhier, 2008). The information about cracks such as theirlocations, directions, widths, and depths are very important for conditionassessment and structural evaluation of the cracked structures. While thelocations, widths, and lengths of surface cracks can be measured andrecorded by visual inspection with some basic instruments such as crack
gages or digital camera, the information about depth of crack as well as thedefect inside the material cannot be measured by visual inspection (Bungey,
1996). The inspection and evaluation can be done without any additional
damage of concrete by non-destructive testing (NDT) techniques. One of themost extensively employed technique for defect detection and surface crack
depth measurement is a well-known “ultrasonic pulse velocity (UPV)”
which applies ultrasonic waves.
Ultrasonic waves aremechanical waves that have a frequency above
approximately 20,000 Hz, which exceeds the limit of human hearing
capacity and can be focused in narrow and straight beams (Schickert, 2002).
Ultrasonic wavesrequire a medium to propagate. If the ultrasonic waves
travel from one medium to another different medium, with different acoustic
impedances, they will partially refract if the angle of incidence is not 90
degree because of the change in propagation velocity, and the rest of energy
will be reflected. For the interface between concrete and air, the ultrasonicwaves almost completely reflect at this interface.
Ultrasonic waves are generally used to inspect structures by anapparatus called “Ultrasonic Pulse Velocity (UPV)”. The UPV only
measures the traveling time that ultrasonic waves need to travel through themedium from transmitter to receiver. In other words, the apparatus does notprovide useful data in some cases. According to the limitations of theoriginal testing system (UPV’s system), the developed testing system is
introduced to inspect concrete structures with higher capacity. By using thedeveloped testing system, an ultrasonic wave pattern that travels through a
medium can be obtained, instead of traveling time. Thedifferent wave
patterns are classified by using machine learning called an “Artificial Neural
Network (ANN)”.
The objectives of this study are to develop a new testing system andapply the artificial neural network classifier for detecting defects anddetermining whether crack depth reaches the reinforcing bar. The study isconducted under the conditions that the location, size, shape, and material ofthe defects as well as the location of the surface crack are predetermined.

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2. EXPERIMENTAL
2. EXPERIMENTAL
PROGRAMPROGRAM
In In
thetheexperimental
experimental
program,program,thethedeveloped
developed
testing
testingsystemsystemwithwiththetheANN
ANN
classifierclassifierwas
wasappliedappliedforfordetectingdetectingthethedefectdefectandandclassifying
classifying
thethe
crack
crack
of of
thethemortar.
mortar.
In In
thethecrack
crack
classification,
classification,thethecrack
crack
depthsdepthswere
were
variedvaried
into
into
three
three
cases.
cases.
The
The
directdirectandandindirectindirectmeasurements
measurements
were
were
used
used
in in
thethedefectdefectdetection
detectionbutbutonly
onlythetheindirect
indirectmeasurement
measurementwas
wasusedusedin inthethecrack
crackclassification.
classification.
2.12.1
Original
Original
testing
testingsystemsystemThe
Thesystem
systemconfiguration
configurationof ofthetheoriginal
originaltesting
testingsystemsystem(or(orcommercial
commercialUPV
UPVsystem)
system)is isillustrated
illustratedin inFigure
Figure1(a).
1(a).In Inthisthissystem,
system,ultrasonicultrasonictransducers
transducers
with
with
a meana meanfrequency
frequency
of of
5555
kHz
kHz
(transmitter(transmitter
andandreceiver),receiver),
were
were
used
used
to to
measuremeasurethethetraveling
traveling
time
time
of of
thethemedium.
medium.
Only
Only
thethetraveling
traveling
time
time
of of
ultrasonicultrasonic
waves
waves
from
from
transmittertransmitterto toreceiverreceiveris isobtained.
obtained.
The
The
traveling
travelingtime
time
cancan
be be
used
used
to to
determine
determine
thetheposition
positionthatthat
thethedefectdefect
may
may
be be
present.
present.
More
More
information
information
about
about
defects
defectsor orcrackscrackscannotcannotbe beobtained.
obtained.
AccordingAccordingto tothethelimitations
limitationsof oforiginal
original
testing
testingsystem,system,thethedeveloped
developed
testing
testingsystemsystemis developed
is developed
to toovercome
overcome
thisthisproblem.
problem.
2.22.2Developed
Developed
testing
testingsystemsystemThe
The
systemsystemconfiguration
configuration
of ofthethedeveloped
developed
testing
testingsystemsystemis illustrated
is illustrated
in inFigure
Figure1(b).
1(b).In Inthisthissystem,
system,an anoscilloscope
oscilloscope(TD2012B(TD2012Bmodel)
model)andandcomputercomputerareare
added
added
to to
thetheoriginal
original
UPV
UPV
system.
system.
The
The
oscilloscope
oscilloscopeis usedis usedto tomeasuremeasureandandrecordrecordthetheultrasonicultrasonic
wave
wave
patterns
patterns
which
which
traveltravelthroughthroughthethemedium.
medium.
The
The
NINI
SignalSignalExpress
Express
programprogram
is is
used
used
to to
collect
collect
thethetime
time
andandcorresponding
corresponding
amplitude
amplitude
arrays.
arrays.
Both
Both
time
time
andandamplitudes
amplitudes
arearecollected
collected
as asthetherawraw
data.
data.
In In
addition,
addition,thetheultrasonicultrasonic
responses
responses
in in
different
different
patterns
patterns
cancanbe beobtained
obtained
andandused
used
forforthethefurtherfurtheranalysis.
analysis.

(a)(a)(b)(b)

FigureFigure1: 1:
SystemSystemconfiguration
configurationof of(a)(a)
original
original
testing
testingsystemsystem(b)(b)
developed
developed
testing
testingsystemsystemThe
The
developed
developed
testing
testingsystemsystemis alsois alsocomposedcomposed
of of
an an
artificial
artificial
neuralneuralnetwork
network(ANN)(ANN)
classifier.
classifier.
The
The
patternpatternof ofnormalized
normalized
signals
signalswere
were
classifiedclassified
andandverifiedverified
byby
thetheANN
ANN
classifier.
classifier.
AnAn
artificial
artificial
neuralneuralnetwork
network
(ANN)
(ANN)
is an
is an
information
information
processing
processing
paradigm
paradigm
thatthatis isinspired
inspired
byby
thethebiologicalbiologicalnervousnervoussystems.
systems.It Itis iscomposedcomposedof ofa alarge
largenumber
numberof ofhighly
highlyinterconnectedinterconnected
processing
processing
elements
elements(neurons)(neurons)
workingworking
in inunisonunison
to to
solve
solve
specific
specific
problems.
problems.

Defectdetection
andandcrack
classificationin cementations
materials
by byultrasonic
testingwith
ANN
Defectdetection
crack
classificationinmaterials
testingwith
ANN
Defectdetectionandcrackclassification
incementations
cementitious
materials
by ultrasonicultrasonic
testing
with
ANN

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An ANN is configured for a specific application, such as pattern recognition
or data classification, through a learning process (Aleksander, 1995).

Figure 2: Back-propagated model with several input and hidden neurons
and one output neuron
This study employs the back-propagated model (Figure 2) which is afeed-forward multi-layered ANNs that allow signals to travel one way only;
from input to output. The feed-forward ANNs tend to be straight forward
networks that associate inputs with outputs. The circles represent neurons.
The neurons are arranged in a number of layers (called multi-layered),
generally three. They are input, middle (hidden) and output layers,respectively (Masnata, 1996; Ni Hong-Guang, 2000).
2.3 Sample preparations
In this study, the mortar sample was used for the test. Ordinary
Portland Cement type I, water, and sand were used to produce the mortar
specimens in the proportion of 539, 269, and 1482 kg/m3, respectively.
2.3.1 Defect detection
For defect detection, the cube mortars, with size 150×150×150mm,
were used as the sample for wave propagation. There were two cases of themortar samples (Figure 3(a) and 3(b)) prepared for two classes of defectdetection:
Case I (non-defectivecase): the pure mortar sample without defectCase II (defectivecase): the mortar sample contains the two circleshaped air voids in the diagonal location. Both air voids has the diameter of
25mm.

4
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ICUS Report 56

(a)

(b)

Figure 3: Samples for defect detection(a) non-defective specimen (b) defective specimen
2.3.2 Crack
Crack classification
classification
2.3.2
For crack classification, the 100x100x500 mm mortar prism
concentrically reinforced with 25 mm reinforcing steel bar were preparedwith different crack configuration. The sample forming is shown in Figure4(a). The cover thickness was thus approximately 37.5 mm. The creation of
artificial crack was achieved by installing a 1.5-mm thick acrylic plate ineach mold before the casting of the mortar. The plate was located at the
middle of the specimen perpendicular direction to reinforcing bar. The
width of the plates were 100 mm but the height of acrylic plates were varied
so that the depth of the created artificial cracks could be varied at 25 mm, 50mm, and 75 mm as shown in Figure 4(b). These acrylic plates were removed
from the specimen at 24 hours after casting. In the case of the crack depth of
75 mm, the acrylic plates were split into two portions so that they can beremoved from the specimen without any constraint from rebar. These threedifferent crack depths represented different states of crack depths asfollows:
Case I (crack depth = 25mm): Crack tip is above the reinforcing bar(shallow crack that does not reach the reinforcing bar)
Case II (crack depth = 50 mm): Crack tip is on the same level withthe center of rebar
Case III (crack depth = 75 mm): Crack tip is below the rebar (crack
propagates through the reinforcing bar).

Figure 4: Samples for crack classification(a) Setting of formwork and instruments (b)Plastic acrylic with different
depthsDefect detection
Defectdetection andand crackcrack classification
classificationin
incementations
cementitious materials
materials by
by ultrasonicultrasonictesting
testingwith
withANN
ANN

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2.4 Test Methods
For different situations, the appropriate measurement setting must be
chosen. There are three possible measurement settings in which thetransducers of UPV equipment may be arranged on the medium. There are
direct measurement, semi-direct measurement, and indirect (or surface)measurement (Figure 5(a) through 5(c), respectively).
For defect detection, the direct and indirect measurements were
employed in this work while the positions of transmitter and receiver are
varied. For crack depth estimation, in the real practical case, only theindirect measurement was used while the distance between transmitter andreceiver were varied over the sample surface with different side of crack.

Figure 5: Pulse velocity measurement ways(a) Direct (b) Semi-direct (c) Indirect measurement
3. ULTRASONIC SIGNALS
3.1 Defect detection
In time domain response, each ultrasonic wave contains 1,000 data
points with sampling rate of 2,500 kHz for every case. To obtain thefrequency domain response, the Power Spectral Density (PSD) of the signal
is calculated from Fast Fourier Transform (FFT) calculation with the time
domain response (Rao, 2010).To make adjustment for the effect of thepressure on probe during the measurement, the time domain response andthe corresponding PSD signal are then normalized with its maximal
magnitude to get the normalized signals.
By the direct measurement, the examples of normalized signals intime domain and frequency domain signals for the samples case I (nondefective case) and case II (defective case) are illustrated in Figure 6(a) and
Figure 6(b), respectively. The figures show the examples of signals obtained
from the transducer in different positions.

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ICUS Report 56(a) time(a) domain
time domain
signalssignals(b) frequency(b) frequency
domaindomainsignalssignals
FigureFigure
6: Normalized
6: Normalized
signalssignals
from directfrom direct
measurement
measurementfor defectfor defectdetection
detection
By theByindirect
the indirect
measurement,
measurement,
the examples
the examplesof normalizedof normalized
signalssignals
inintime domain
time domain
and frequency
and frequency
domaindomainsignalssignals
for theforsamples
the samples
case Icase
and Icaseand case
II are II
illustrated
are illustrated
in Figurein Figure7(a) and
7(a)Figure
and Figure7(b), respectively.
7(b), respectively.

(a) domain
time domain(a) time
signalssignals

DefectDefectdetectionand crackin cementations
materials
by ultrasonic
testingtestingwith ANN
Defectdetection
and
crack
in
materials
bywithdetectionand classification
crack classification
classification
incementations
cementitious
materials
by ultrasonicultrasonic
testing
withANN
ANN

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October 2011, Chiang
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Chiangmai,(b) frequency domain signals
Figure 7: Normalized signals from indirect measurement for defectdetection
3.2 Crack classification
In time domain response, each ultrasonic wave contains 1,500 data
points with sampling rate of 1,000 kHz for every case. The processes toobtain the normalized signals in time and frequency domain are similar tothe case of defect detection. By using only indirect measurement, theexamples of normalized signals in time domain and frequency domain
signals for the samples case I (crack depth = 25mm), case II (crack depth =50 mm), and case III (crack depth = 75 mm) are illustrated in Figure 8(a)and Figure 8(b), respectively. The figures also show the examples of signals
obtained from the transducer in different positions.

(a) time domain signals

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ICUS Report 56(b) frequency domain signals
Figure 8: Normalized signals from indirect measurement for crack
classification
4. INPUTS AND PARAMETERS FOR ANN CLASSIFIERThis section explains the selection of the ANN’s input and parameter setting
for the network training. For defect detection, there were totally 200
normalized amplitude arrays of the normalized signals with 1,000 data
points used as the input of the network with 100 arrays for each sample
cases. The ANN’s output can be either 0 or 1which are represented the nondefective and defective case, respectively. The 50 hidden neurons were used.
For crack classification, there were totally 300 normalized amplitude arrayswith 1,500 data points used as the input of the network with 100 arrays foreach sample cases. The ANN’s output which can be either [1 0 0]’, [0 1 0]’
or [0 0 1]’ which represents the mortar with crack depth of 25mm, 50mm,
and 75mm, respectively. The totally 50 layers of hidden neurons were alsoused.
The pattern recognition of the defect can be simulated and analyzed
by the MATLAB Toolboxes. The training, validation, and testing
parameters were set to be 70%, 15%, and 15% of the number of inputs,
respectively. The normalized amplitude arrays in time and frequency
domain were trained individually.
5. CLASSIFICATION RESULTS
After the training process, the confusion tables were obtained and used toanalyze the accuracy of the network. The classification results obtained with

Defect detection
Defectdetection andand crackcrack classification
classification inincementations
cementitious materials
materials by
by ultrasonicultrasonictesting
testingwith
withANN
ANN

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the ANN classifier are presented in the tables which are described below.
The classification rate for each case is the mean classification rate of thefour times network training.
5.1 Defect detection
For the defect detection, the 200 input samples were trained in the
network according to two classes of the samples, so the training and testing
samples are set to be 140 and 30 samples which are 70% and 30% of the
input samples, respectively. Using direct measurement, the classification
results of ANN classifier with the time domain and frequency inputs arepresented in Table 1 and 2, respectively.
Table 1: Classification results using time domain signals from the direct
measurement
Case

Case I
Case II

Training and testing
samples
140 training samples
30 testing samples

Mean classification rate (%)
Case I
Case II
96.75
3.25
3.5
96.5

Table 2: Classification results using frequency domain signals from thedirect measurement
Case

Case I
Case II

Training and testing
samples
140 training samples
30 testing samples

Mean classification rate (%)
Case I
Case II100
0397

According to Table 1, with the time domain inputs, the accuracy rates
are 96.75% and 96.5% for non-defective and defective cases, respectively.
As shown in Table 2, the very high classification results were obtainedusing inputs in frequency domain with the accuracy rate of 100% and 97%
for non-defective and defective cases, respectively.
For indirect measurement, the classification results of ANN classifier
with the time domain and frequency inputs are presented in Table 3 and 4,
respectively.
Table 3: Classification results using time domain signals from the indirect
measurement
Case

Case I
Case II

Training and testing
samples
140 training samples
30 testing samples

Mean classification rate (%)
Case I
Case II
95
5
5.5
94.5

Table 4: Classification results using frequency domain signals from theindirect measurement
Case

Case I
Case II

10474

Training and testing
samples
140 training samples
30 testing samples

Mean classification rate (%)
Case I
Case II
100
0
0
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From Table 3, with the time domain inputs, the accuracy rates are
95% and 94.5% for non-defective and defective cases, respectively. From
Table 4, the very satisfactory classification results were obtained using
inputs in frequency domain with the accuracy rate of 100% for both cases.
5.2Crack classification
For the crack classification, the 300 input samples were trained in the
network according to three classes of the samples. The training and testing
samples were set to be 210 and 45 samples which are 70% and 30% of the
input samples, respectively. The indirect measurement was only employedin this work. The classification results of ANN classifier with the time
domain and frequency inputs are presented in Table 5 and 6, respectively.
Table 5: Crack classification results using time domain signals(indirect measurement)

Case

Case I
Case II
Case III

Training and testing
samples
210 training samples
45 testing samples

Mean classification rate (%)
Case I
Case II
Case III
87
8
5
18
75
7
13
8
79

Table 6: Crack classification results using frequency domain signals(indirect measurement)
Case

Case I
Case II
Case III

Training and testing
samples
210 training samples
45 testing samples

Mean classification rate (%)
Case I
Case II
Case III
96
1
3
0
100
0
2
3
95

According to Table 5, with the time domain inputs, the accuracy rates
are 87%, 75%, and 79% for the crack depth of 25, 50, and 75 mm,
respectively. As shown in Table 6, the very high classification results wereobtained using inputs in frequency domain with the accuracy rate of 96%,
100%, and 95% for crack depth of 25, 50, and 75 mm, respectively.
From the classification results, the accuracy obtained from theclassification in frequency domain signals is, in all cases, better than thoseobtained from the classification with time domain signals. This may be
because the reflection of ultrasonic wave in the structure can easily change
in the frequency response by different configurations of specimens. The
different patterns of the different specimens can thus be well classified. For
defect detection, the results from using direct and indirect measurements areboth highly satisfactory with a small difference in their accuracies.
6. CONCLUSION
The new developed testing system, implemented by the integration of UPV
apparatus, oscilloscope, and ANN algorithm, can give the good recognitionof defects and good evaluation of crack depths whether crack depth reaches
Defect detection
Defectdetection andand crackcrack classification
classification inincementations
cementitious materials
materials by
by ultrasonicultrasonictesting
testingwith
withANN
ANN

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Thailand
Chiangmai,

the reinforcing bar. According to the classification results of defectdetection and crack classification, employing the frequency domain signals
as the ANN’s input gives higher accuracy and better reliability inclassification.
For defect detection, using both direct and indirect measurement cangive the very high accuracy. To use this system for defect detection, theselection of direct or indirect measurements depends on their suitability foreach specific practical work while, for crack classification, the indirect
measurement is generally used.
In summary, the developed system can be proved to be beneficial to
the structure inspection and evaluation since more information of theultrasonic signals is obtained instead of the traveling time. Furthermore, thedeveloped testing system can also classify other types of damage inconstruction.
REFERENCES
Gebregziabhier, T. T., 2008. Durability problems of 20th century
reinforced concrete heritage structures and their restorations, SAHC, pp. 19,42, and 46.
Bungey, J. H. and Millard, S.G., 1996. Testing of concrete in structures(3rd ed), Blackie academic & Professional, 139-141.
Schickert, M., Krause, M. and Muller, W, 2002.Ultrasonic Imaging ofConcrete Elements Using Reconstruction by Synthetic Aperture Focusing
Technique.Journal of Materials in Civil Engineering. 15, 235-246.
Aleksander, I. and Morton, H, 1995. An introduction to NeuralComputing (2nded), Chapman and Hall.
Masnata, A. and Sunseri, M., 1996. Neural network classification offlaws detected by ultrasonic means, Palermo, Italy, April, 87-93.
Ni, H. –G. and Wang, J. –Z, 2000. Prediction of compressive strengthof concrete by neural networks, Hebei, People’s Republic of China, August,
1245-1250.
Rao, K.R., Kim, D.N., and Hwang, J.-J., 2010. Fast Fourier Transform– Algorithms and Application, 1st Edition., XVIII, 340 p.

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NewA study on the proper land useof the hillside urban area
in depopulation tendency-evaluating future scenarios
from the view of disaster mitigationand environmental conservationIyo YONEMASU 1, Takahiro TANAKA 2 and Daisaku NISHINA 3
1
Graduate Student, Graduate School of Engineering,
Hiroshima University, Japani.yonemasu@gmail.com
2
Associate Professor, Hiroshima University, Japan
3
Professor, Hiroshima University, Japan
ABSTRACTIn Japan, after the World War Ⅱ, the population had been increased andurban areas were also formed on hillside areas because of the urban sprawl.
In the hillside urban areas, there are many physical and social problems
such as inadequate infrastructures, high disaster risks and so on. On theother hand, there are many places in which residents can enjoy someecological services such as fresh air and recreation opportunity. Because
the population decreasing and aging are severe there now, it is necessary to
re-design such hillside urban areas. To figure out the ideal future vision,
this study aims at making some future scenarios and evaluating them fromthe view of disaster risks and ecological services. Actually, we use scenario
analysis method to figure out the future vision of urban land use distribution
at the time of 2035. The site is Takatoriyama neighborhood, which is atypical hillside urban area and located in Kobe. Finally, evaluating 16
scenarios by using GIS, from the view of disaster risks such us the slope
disaster, the seismic disaster, the flood disaster and the fire disaster, and theecological services such as the cold air and biodiversity.
Keywords: hillside urban area, GIS, scenario, disaster mitigation,
environment
1. INTRODUCTION
1.1 Background and aims
After World War II, the Japanese population increased in urban areas,
creating urban sprawls that extended to surrounding hillside areas. In suchareas, many problems arose, including inconvenience of life attributable toinadequate infrastructure, with tightly packed old houses, narrows roads,
and paths with stairs. Moreover, such areas present high disaster risks such

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as slope disasters and flood disasters. However, many places exist whereresidents can enjoy some ecological services such as fresh air and recreation
opportunities. Now, populations are decreasing and aging rapidly, and thattrend is expected to continue. Therefore, redesigning such hillside urban
areas is necessary.
This study was undertaken to produce a future vision of hillside urban
areas, including a view of disaster risks, ecological services, and theconvenience of life in the Takatoriyama neighborhood, Nagata area, in
Kobe city. Herein, to ascertain an ideal future vision, the authors produced
some future scenarios and evaluated them from the perspective of disasterrisks and ecological services.

LegendResidential Area
Residential Area
Residential Area
Industrial Area
Commercial Area
Common land
Park, Green space
Mountain forest
Waterway, Lakeside

Agricultural land
Open SpaceRoad site

Figure 1 Takatoriyama neighborhood.
1.2 Previous researches
Some studies have examined the effects of decreasing population by
producing urban future scenarios and evaluating compact cities.

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These studies evaluate the future scenarios of the proper land use fromthe viewpoint of energy use of cars, costs for city facilities maintenances, inthe urban level.
On the other, there are few researches using scenario analysis to
examine depopulation tendency in the district level, which focus on
mitigating heat environments2). Such studies do not evaluate
comprehensively.
2. OUTLINE
2.1 SiteThis study examines the Takatoriyama neighborhood, Nagata area, in
Kobe city. This is a typical hillside urban area formed on the outskirts of
Takatoriyama as a result of urban sprawl. Although natural amenities areavailable there, steep slopes present high disaster risks from hazards such as
slope disaster. Therefore, it is necessary to tackle these problems. In
addition, most buildings were built before urban planning had adopted
appropriate zoning and other regulatory measures. Therefore, the area hastightly packed old houses, narrow roads, and paths with stairs. It is not a
comfortable environment for people, especially elderly people and thosewith disabilities.
2.2 Flow of this researchThis study was assumed to advance according to the following.
1) Future scenarios targeting 2035 (16 types)
2) Evaluating scenarios from the view of disaster risks and ecologicalservices and consideration
For 1), methods and the results are presented in Chapter 3. For 2),
methods and results are explained in Chapters 4, 5 and 6.
3. MAKING FUTURE SCENARIOS
3.1 Composition of future scenarios
The authors produced 16 future scenarios (Table 1) based on site
surveys and hearing research. They are roughly divisible into three patterns.
1) Designs with the compact concept
The scenario represents a collection of urban land use (residential area,industrial area, commercial area, public facility and road site) for the
specific area (Scenario No. 1–10). There are two patterns: arterial highway
area type and lower area type. The authors each produced five futurescenarios incorporating changes of density type and building height type. In
recent years, it is necessary that the urban structure be compact and that themaster plan of this area proceed from that basis.
2) Designs with physical environment
A study on the proper land use of the hillside urban area in depopulation tendency – evaluating future
A study on the proper land use of the hillside urban area in depopulation tendency
scenarios from the view of disaster mitigation and environmental conservation –-evaluating future scenarios from the view of disaster mitigation and environmental conservation-

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Based on the present land use, authors considered physical elements
such as the disaster danger and environmental amenities, what the land has
potentially (Scenario No. 11–14). To produce each scenario, the authors
examined the present land use and referred to relevant maps (slope disasterhazard map, seismic disaster hazard map, flood disaster hazard map, andfire disaster hazard map), and determined places that are likely to revert to anatural state. Four scenarios of this type entailed different degrees ofphysical environmental consideration. Moreover, as a target of comparison,
one scenario in which urban area is located in the places where naturalenvironmental resources are spoiled (Scenario No. 15).
3) Designs with present trends
This scenario includes decreased urban land use areas throughout theneighborhood while maintaining the present building density (Scenario No.
16).
Table 1: Future Scenarios
Con ce pt

Scena ri o N o

1
2
3
4
5
6
7
8
9
1�
11
12
13
14
15
16

Collecting urban land use around thearterial highway"Design with
Conpact
Concept"typeCollecting urban land use in lower area

"Design with
PhysicalEnvironment"
type

Design with Physical Environment
Not Considering about PhysicalEnvironment"Design with Present
trend" typeType ofDen sityType ofbuilding

High
Mideum
Low
High
High
High
Medium
Low
High
High
High
High
High
High

Low
Low
Low
Mideum
High
Low
Low
Low
Mideum
High
Low
Low
Low
Low

High

Low

High

Low

The Present TAKATORIYAMA Area・・・Type of DENSITY is High and type of BUILDING is Low

3.2 Mode of making future scenarios
To produce future scenarios, the process is explained in the following1), 2), and 3). The methods and the results are explained.
1) Predicted population
The predicted population of this site is taken using cohort data of the
Nagata area population in Kobe city (77,389 people in 2035) and the present
population of each area. Figure 2 shows the results. The Takatoriyama area
population in 2010 was 9550, but the predicted population in 2035 is 7398,
as shown in Table 1.

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Population(Persons)Population(Persons)

10000
10000
9000
9000

9550
9550

9201
9201

8000
8000

8795
8795
8347
8347
7874
7874

7000
7000

7398
7398

6000
6000
2010
2010

2015
2015

2020
2020

2025
2025

2030
2030

2035
2035

高取山地区
高取山地区
Population
Population
人口変化
人口変化
Sift
Sift

year
year(the(thedominicaldominicalyear)
year)

FigureFigure2:2:Population
PopulationShift
Shiftininthe
thesite.
site.
2)2)Area
Areasetting
settingfor
foreacheachlandlanduseuse
The
Theurbanurbanland
landuseusearea
areaofofeach
eachscenario
scenarioisisshown
shownininTable
Table22bybyconsidering
consideringthe
thereduction
reductionofofurban
urbanareas
areasandandthetheexpansion
expansionofofgreen
greenspace
space
with
withdecreasing
decreasingpopulation.
population.
The
The rate
rate ofof population
population decrease
decrease waswas multiplied
multiplied byby thethe current
current
population
populationofofeacheacharea,
area,andandthethenecessary
necessaryarea
areaofoflandlanduseusewaswascalculated
calculated(residential(residentialarea,
area,industrial
industrialarea,
area,commercial
commercialarea,
area,andandroadroadsite).
site).Areas
Areasofof
arterial
arterialhighways
highwayswere
wereexempted
exemptedfrom
fromthisthiscalculation.
calculation.
The
Thepresent
presentTakatoriyama
Takatoriyamaneighborhoodneighborhoodhas
hashighhighdensity
densityand
andlowlow
raisedraisedbuildingbuildingtype.
type.Therefore,
Therefore,thetheauthors
authorsproduced
producedlower
lowerdensity
densitytype
type
scenarios
scenarios(Scenario(ScenarioNos.
Nos.2,2,3,3,7,7,8)8)andandmediummediumandandhighhighraised
raisedbuildingbuilding
type
typescenarios
scenarios(Scenario(ScenarioNos.
Nos.4,4,5,5,9,9,10)
10)forforcomparing
comparing(Table(Table1).
1).TheThebuildingbuildingarrangement
arrangementconcept
conceptTable
Tableisisshown
shownininFigure
Figure3.3.The
Thedensity
densityofofthethepremisespremisesisisset
setby
bythe
thetypetypeofofdensity
densityininTable
Table3.3.Scenario
ScenarioNos.
Nos.2,2,3,3,7,7,and
and88
differdifferaccording
accordingtotothe
thedensity
densitycomparison
comparisonwith
withthethepresent
presentisisascertained
ascertained
withwiththethenecessary
necessaryarea
areabasedbasedononTableTable3.3.
AAdesign
designwith
withthethepresent
presenttrend
trendtypetypeisismade
madeusingusingthethepopulation
populationofof
eacheachadministrative
administrativeunit,
unit,andandnecessary
necessaryareas
areaswere
werecalculated
calculatedfrom
fromthem.
them.
Table
Table2:2:Area
Areasettingssettingsfor
forlandlanduseuse(Scenarios(Scenarios1,1,6,6,11,
11,16)
16)
�he�hekinkinddofoflan
landduusese
Mountain
Mountainforest,
forest,Agricultural
Agriculturalland
land

Bare
Barelandland
Industrial
Industrialarea
area
Residential
Residentialarea
area
Commercial
Commercialarea
area
Road
Roadarea
area
Park,
Park,Green
Greenspace
space
PublicPublicFacility
Facility(Ex.School)(Ex.School)
River,
River,Lake
Lake

2 2
Calcu
Calculatin
lating gFormula
Formula�e�ec ec ssar
e ssary yArAr
e a(m
e a(m
))

Calculation
Calculationofofaccessionaccession
Area
AreaofofPresent
PresentCondition
Condition
×× Population
Populationdecreasing
decreasing
rate
rate

Same
SameasasPesent
PesentCondition
Condition

494,125
494,125207
207
21,613
21,613
22,97922,97960,97060,97042,47442,47458,93658,936
1,592
1,592

studyononthe
theproper
properland
landuseuseofofthe
thehillside
hillsideurban
urbanarea
areainindepopulation
depopulationtendency
tendency––evaluating
evaluatingfuture
futureAAstudy
A study on the proper land use of the hillside urban area in depopulation tendency
scenariosfrom
fromthetheview
viewofofdisasterdisastermitigation
mitigationand
andenvironmental
environmentalconservationconservation––
scenarios-evaluating future scenarios from the view of disaster mitigation and environmental conservation-

55
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High

Scenarios 4・5・9・10

Building Height

Scenarios 2・3・7・8

The Present
Takatoriyama area

DensityLowdensity

Figure 3: Conceptual diagram of layout buildings.

Figure 4: Mikuradori 5, 6, 7 Area
Table 3: Setting densityTy�e o� Den sity
High Density
Medium Density
Low Density

�e �e ren �e Are a
Takatoriyama Area
Mikuradori 5・6・7Area�u i�ding Are a � La nd Are a

0.78
0.67
0.56

3) Zone setting
For this study, future scenarios are set up as the conformation of
distribution of the proper urban land use. The area of the proper urban land
use of each future scenario is set as the necessary area. Furthermore, thezone setting was referred from a survey based on the proper land use noted
above.
3.3 Examples of future scenarios
Some examples are shown below. Figure 5 shows the Design with
Compact Concept type. Figure 6 portrays the Design with PhysicalEnvironment type. Figure 7 depicts the Design with Present trend type.
Figure 5 shows scenario No. 6: collecting urban land use in lower area withhigh-density type and low raised building type. Figure 6 presents scenario
No. 11, which incorporates physical elements that the land already has.
Figure 7 shows scenario No. 16: a design based on present trends.

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Scenario

Scenario 6

Figure 5 Scenario 6(Design with Compact Concept Type)

Scenario

Urban Land
Use
既存施設

Urban LandUsein existence

Figure 6 Scenario 11(Design with Physical Environment
Type)

Urban Land
Use

Figure 7 Scenario 16(Design with present trend type)

4. EVALUATING SCENARIOS: DISASTER RISKS
4.1 Mode of evaluation
The main disaster risks of the hillside urban area are slope disasters,
seismic disasters, flood disasters, and fire disasters. Furthermore, from them,
we evaluate future scenarios made in Chapter 3. Particularly to analyze therisk of slope disaster, the seismic disaster and the flood disaster, authors
overlay the map showing each disaster risk (hazard map of the slope disaster,seismic disaster, and flood disaster made in reference 7) and each scenario
on GIS, and calculated the risk area of the urban city area (Fig. 8).
Subsequently, we evaluated scenarios from calculated expectancy ofthe likely number of deaths (degree of risk) by multiplication of the area(m2) by the expected population density (persons/m2). As for future scenario
16, authors used the value multiplication dimensions of the urban land use
hazards of each administrative unit to estimated population density. Firedisaster was calculated by using the evaluation. Then, for that area, theforecast population density was multiplied to produce a forecast of likely
deaths from a disaster (Table 4).

A study on the proper land use of the hillside urban area in depopulation tendency – evaluating future
A study on the proper land use of the hillside urban area in depopulation tendency
scenarios from the view of disaster mitigation and environmental conservation –-evaluating future scenarios from the view of disaster mitigation and environmental conservation-

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LegendLegendThe cliff failure Area
The poor subsoil Area

Urban Land Use

Future Scenario

LegendSlope disaster hazard map

Risk area in urban city area

LegendThe seismic
hazard area

Urban Land Use

Future Scenario

LegendSeismic disaster hazard map

Risk area in urban city area

LegendUrban Land Use

Future Scenario

The flood
hazard area

Flood disaster hazard map

Risk area in urban city area

Figure 8: Way of evaluating disaster risks(Slope disaster, seismic disaster, flood disaster).

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TableTable
4: Evaluation
4: Evaluationof a fireof adisasterfire disaster
Methodology
Methodology ContentContent

1

Unburnable
Unburnablearea ratio(%)=open-spacearea ratio(%)=open-spaceratio+(1-open-spaceratio+(1-open-space
Calculating
Calculating
ratio/100)×fire-retardantratio/100)×fire-retardant
ratio
ratio
1
unburnable
unburnablearea ratioarea※Open-spaceratio ※Open-spaceratio(%)=(Open-spaceratio(%)=(Open-spacearea/Thearea/The
site area)×100
site area)×100※Fire-retardant※Fire-retardantratio(%)=(Fire-retardantratio(%)=(Fire-retardantarea/Buildingarea/Buildingarea)×100area)×100

2

WoodenWoodenbuilding-to-landbuilding-to-landratio(%)=(Wooden
ratio(%)=(Woodenbuilding-to-landbuilding-to-land
Calculating
Calculatingthethearea/Semigurosu
area/Semigurosu
district area)×100
district area)×100
wooden2
woodenbuilding-tobuilding-to※Semigurosu※Semigurosu
district area=The
district area=The
site area-(Thesite area-(Theroad arearoad
morearea
thanmore thanland ratioland ratio15m width、Waterway、Lakeside、big
15m width、Waterway、Lakeside、bigvacant area)
vacant area)3

fire-fighting
operation/Semigurosu
operation/Semigurosu
district area)×100
district area)×100
Calculating
Calculating
the ratiothe
ratio fire-fighting※The hard※The
areahard
to fire-fighting
area to fire-fighting
operationoperation
to3 hard fire-fighting
to hard fire-fighting=Semigurosu=Semigurosu
district area-The
district area-The
easy areaeasy
to fire-fighting
area to fire-fighting
operationoperation
operationoperation

The ratioTheto hardratio fire-fighting
to hard fire-fighting
operation(%)=(Theoperation(%)=(Thehard area
hard
to area to※The easy※Theareaeasy
to fire-fighting
area to fire-fighting
operation=The
operation=The
district area
districtwithinarea within
140m from140m
the from
waterthearea
water area

4

4

Calcurating
Calcurating
arithmeticarithmetic
average average
from ①Unburnablefrom ①Unburnablearea ratio、
area ratio、
Evaluating
Evaluating②The wooden②The woodenbuilding-to-landbuilding-to-landratio、③The
ratio、③The
ratio to hardratio fireto hard firefighting operation.
fighting operation.

4.2 Results
4.2 Resultsof evaluationof evaluation
Evaluation
Evaluation
resultsresults
are presented
are presented
in Figurein Figure
9. Risks
9. Risksof theofdesign
the design
with withthe physicalthe physicalenvironment
environment
type aretypelower
are lower
overalloverallthan thosethan thoseof cityoflandcity useland use
consolidation
consolidation
type whentype when
seen seen
accordingaccordingto thetopattern.
the pattern.
Consequently,
Consequently,
an anurbanurban
land uselandzoneuse zonewill include
will include
disasterdisasterhazardhazard
areas areas
if we ifdesign
we designwith awith acompact
compact
concept
concept
becausebecausesuch areas
such areas
are dispersed
are dispersed
complexly
complexly
throughout
throughout
the theneighborhood.
neighborhood.
The tradeoff
The tradeoff
betweenbetweenthe disasters
the disasters
is regarded
is regarded
as theaslowest
the lowest
risk inrisk
all in all
scenarios
scenarios
whenwhen
the scenario
the scenario
with thewithhighest
the highest
seismic
seismic
risk isrisk
seen
is fromseen fromthe thefire hazard
fire hazard
rating.rating.
2500

2500

2000

2000

1500

1500

1000

1000

500

500

0

1 0 2 31 42 53 64 75 86 97 108 119 1012 11 13 12 1413 15 14 16 15

16

FigureFigure9: Result
9: Resultof evaluationof evaluationin light
in of
light
disasterof disasterrisks. risks.

A on
study
the proper
land
the hillside
in depopulation
tendency– evaluating
A studytheon
properland useofuse
the ofhillside
urbanurban
area inarea
depopulation
tendency– evaluating
futurefuture
A study on the proper land use of the hillside urban area in depopulation tendency
9 4859scenarios
fromtheofviewof disastermitigationand environmental
conservation–
scenarios
from theview
disaster
mitigationand environmental
conservation–-evaluating future scenarios from the view of disaster mitigation and environmental conservation-

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

5. EVALUATING SCENARIOS: ENVIRONMENTALCONSERVATION
5.1 Mode of evaluation
The main environmental services of the hillside urban area to beconserved are cold air and biodiversity. Therefore, authors evaluated eachfuture scenario from the view of them.
As for cold air, authors overlaid wind flow map with each futurescenario for calculating overlapped area and evaluated scenarios by using
the area. On the other, as for biodiversity, authors used ecological network
map. The mode of the evaluation is shown in Figure 10.

LegendUrban Land Use

Future Scenario

LegendThe area ofcold air

The map of the way of wind

The environmental resource
obstruction area by urban land use

Legend例

LegendUrban Land Use

Future Scenario

The area which
has ecologicalresource

The map of the biodiversity

The environmental resource
obstruction area by urban land use

Figure10: Way of evaluating Environment conservation(cold air and biodiversity).
5.2 Result of evaluation
The evaluation result is presented in Figure 11. The area of the
scenario with physical environment consideration is evaluated as good.
Therefore it is said that even high density and low raised building type do
not obstruct ecological services if physical environments are considered.
Generally, because no mutual relation is apparent between ‘wind path’ and‘biodiversity’, they must be considered individually.

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60000

60000

50000

50000

40000

40000

30000

30000

20000

20000

10000

10000

0

1

02

13

24

35

46 5 7

68

79

810

911 1012 1113 1214 1315 1416 15

16

Figure Figure
11: Results
11: Resultsof evaluationof evaluation
relatedrelated
to environmental
to environmental
conservationconservation

6. RESULTS
6. RESULTS
OF THEOFPROSPECTIVE
THE PROSPECTIVESCENARIOSSCENARIOSIn Chapter
In Chapter
4 and Chapter
4 and Chapter
5, authors
5, authors
evaluatedevaluated
future scenarios
future scenarios
from thefrom theperspective
perspectiveof disasterof disasterrisks andriskstheandenvironmental
the environmental
conservation.
conservation.
To
To
considerconsiderfuture scenarios
future scenarios
comprehensively,
comprehensively,
it can be
it cansaidbethat
said
thethatdisasterthe disasterrisks posedrisks byposed
‘Designby ‘Design
with physicalwith physicalenvironment’environment’
type scenario
type scenario
are lower
are lower
than thosethan ofthose‘Designof ‘Design
with compact
with compact
concept’.
concept’.
Urban Urban
land uselandzones
use willzones will
includeinclude
disasterdisasterhazard hazard
areas ifareas
we if
base
wethe
base
scenariothe scenario
design designusing theusing thecompact
compact
conceptconcept
becausebecausesuch areas
suchareareas
dispersed
are dispersed
complexly
complexly
throughout
throughout
thetheneighborhood.
neighborhood.
The tendencies
The tendencies
among amongfour disasterfour disasterrisks andrisksecologicaland ecologicalservicesservices
mutuallymutually
differ. differ.
7. CONCLUSION
7. CONCLUSION
This study
This wasstudy
undertaken
was undertaken
to produce
to produce
some futuresome scenarios
future scenariosand evaluate
and evaluate
them according
them according
to theirtoattendant
their attendantdisasterdisasterrisks andrisks
provisionand provisionof ecologicalof ecologicalservices.
services.
ResultsResults
show that,show
forthat,the forhillside
the hillside
urban area,
urbanit area,
is effectual
it is effectual
to haveto haveland use
land
likeusetheliketypetheoftypedesignof designwith thewithphysicalthe physicalenvironment
environment
in viewinofview ofboth disasterboth disastermitigation
mitigationand environmental
and environmental
conservation.
conservation.
However,
However,as
as
explained
explained
previously,
previously,
to consider
to consider
the future
the offuturehillsideof hillside
urban areas,urbanoneareas,
must
one must
considerconsiderthe convenience
the convenienceof dailyof lifedailyaccording
life according
to the toinhabitants’the inhabitants’evaluation.
evaluation.
Subsequently,
Subsequently,
we willwe
considerwill consider
future scenarios
future scenarios
includingincludingthese theseelements.
elements.
REFERENCESREFERENCES
HORI Yuto,
HORIHOSOMI
Yuto, HOSOMI
Akira, KUROKAWA
Akira, KUROKAWA
Takashi,Takashi,1999. Study
1999. onStudy onthe Effects
the Effects
on Energy
on Energy
Consumption
Consumption
by Vehicle
by Vehicle
Trips inTripsa Compact
in a Compact
City – City –on the land
properusehillsideof the hillsideurban
in depopulation– evaluating
A study Aonstudy
the proper
uselandof theurban area
in area
depopulation
tendencytendency– evaluating
future future
A study on the proper land use of the hillside urban area in depopulation tendency
11
scenariosof disastermitigationand environmental
conservation–
scenarios
from thefrom
viewtheof view
disaster
mitigationand environmental
conservation–-evaluating future scenarios from the view of disaster mitigation and environmental conservation-

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Using the 1975 and 1992 Person Trip Data of Utsunomiya City –, Papers oncity planning, No. 34, pp. 241-246 (in Japanese)
IWAMOTO Shinpei, TANAKA Takahiro, NISHINA Daisaku, 2011.
A study on the urban structure of small town in the depopulation age:
Evaluation from the viewpoint of urban infrastructure development andmaintenance cost, AIJ Journal of Technology and Design, Vol. 17, No. 36,
pp. 661-666 (in Japanese)
HOYANO Akira, ASAWA Takashi, SATO Rihito, KAWAI Eitoku,
NAKAMURA Ben, 2010. Evaluation of Environmental Impact of Vacant
Lot in a Historical Urban District: Analysis of the impact of vacant lot onthermal environment and building heat load in summer using numericalsimulation, Journal of Environmental Engineering, Vol. 75, No. 656, pp.
899-905 (in Japanese)
KANEKO Tadakaru, MINOMOTO Toshitaro, 1985. A study on the
Actual Condition of Existing Wooded Steep Slopes in Kawasaki-City,
Papers on City Planning, No. 20, pp. 367-372 (in Japanese)
TANAKA Takahiro, TAKEDA Maiko, NISHINA Daisaku, 2010.
Application of GIS to produce neighborhood design support system forhillside area: For design addressing environment, disaster mitigation andlivability, Architectural Institute of Japan, D-1, pp. 941-942 (in Japanese

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Asia
NewUrban heat island creating a design tool
for adaptation
Maria B. K. DEWI
Graduate Student, ICUS, IIS, The University of Tokyo, Japan
m.b.k.dewi@gmail.com
ABSTRACT
Urban heat island is a phenomenon of the cities which is indicated byhigher temperature compared to the surroundings. As the Asian megacities
growing, the prediction is in connection to the greater impact of urban heatisland phenomenon. The urban heat comes from solar radiation, building,people, lack of vegetation, and machinery activities. Urban heat islandbrings impact in reducing human comfort, the health problems and the extra
needs of energy to reach the thermal comfort. To combat heat island
problems, there are some ways, such as providing green, water, the properchoice of materials, and configuration to arrange wind pattern.
Cities in Asia also have problem of urban heat. A design tool is made toadapt the urban heat in general, in the scale of building, street, andneighborhood. This design tool is made for designers, such as urban
planners and architects. It contains words for explanations and pictures.
Each scale contains of for category, which are: the green structure, waterand humidity balance, heat and energy balance, and morphology. The tool
explains sort of activities in the effective and less effective way based on theprevious researches.
Keywords: urban heat island; design tool; temperature; building; street;neighborhood; green; wind; water; configuration. the heat/energy balance,materials for outdoor urban space
1. INTRODUCTION
Urban heat island is a phenomenon where cities accumulate heat and areconsequently warmer than their surroundings (Oke, 1982). Urban heatisland is a phenomenon of the warming atmosphere and surface in cities(urban areas) compared to the surroundings (Voogt, 2004). From the Fig. 1,
there is different curve stated the difference of temperature in urban andrural or urbanized area. The city morphology, wind, density, shadow,
various human activities cause the temperature rising, especially in urban
area. The climate change brings impact to the urban heat island’s
temperature. The rising temperature by climate change can make the urban
heat worse. But the urban heat island does not influence the global warming(Voogt, 2004). Temperature increase in the built environment has great
impact on the cities living conditions (Kleerekoper, 2009). It results in the4891

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less human comfort, health problems, and consumption of more energy andneeds more air-conditioning.
City structures have important roles to tackle the urban heat. As thecity is growing larger, the temperature difference between urban and rural
becomes higher. The relation between temperature gap and city size isconsistent that composition of buildings is taken into consideration incooling both sun and wind orientation (Kleerekoper, 2009). Based on the
United Nations report, in 2009 the world population reached 6.8 billion withover half live in the cities. By the 2050, the estimated population of theworld will be 9 billion, with 70 per cent will live in urban (United Nations,2009). As the cities growing, the challenge of urban heat island will increase.
2. URBAN HEAT ISLAND
2.1 Factors of urban heat island
There are lot of factors contribute to urban heat. The urban heat iscaused by the heat of a city comes from building, people, lack of vegetation,and machinery activities (Kleerekoper, 2009). The heat is resulted from thetrapped heat that buildings absorb during the day, is caused by the materials
used rather than vegetation and soils in the countryside. That heat is radiatedback by materials of buildings to the surrounding. Another contributor is thelack amount of trees and vegetation that support the evapotranspiration tocool the air. Machinery activities come from transportation, heating andcooling system, and industrial machinery. The sun has important role forurban heat, while the wind create cooling effect.
City form and city functions give effect for city’s heating up. Urban
heat islands will increase as the city grows and their effects affect thesurface and ambient temperature in the city (EPA, 2008). Building androads have significant role in increasing urban heat, this is regarding to theability of heat absorbing and reflecting (Akbari, 2005).
There are four form of interaction between building and environment
where the heat exchanges: the effective solar exposure of the glazed andopaque elements of the building envelope, the effective solar heat gain of
the building, the rate of conductive and convective heat gain from and loss,
the air, and the natural ventilation and building’s passive cooling (Hien, etal.)
2.2 The impact of urban heat island
The urban heat islands impacts are: increased energy consumption,
elevated emissions of air pollutants and greenhouse gases, and compromised
human health and comfort (EPA, 2009). It also interfere the small water
cycle.

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Related with human health and comfort, the health problems occur,
such as respiratory difficulties, heat cramps and exhaustion, heat stroke, andheat-related mortality (EPA, 2009). Another health problems also arises
such as dehydration, concentration problems, skin problems, fatigue, sleep
problems, and allergies happens as result of urban heat island (Kuypers,
2008). Those effects are higher on vulnerable population: children, oldpeople, and sick people.
In addition, small water cycle will also affected by urban heat island(Kleerekoper, 2009). Urban areas tend to have less evaporation thansurroundings, because buildings cover up the urban areas. The warmer anddry soil of urbanized area accelerates the water run-off (Kravcik et al., 2007;
Kleerekoper, 2009).
The heating up temperature gives comfort in winter, but has negativeside in summer, supports energy saving in winter but negative one insummer. By the study in the UK, in summer the urban heat island (UHI)
will tend to results in an increased cooling load and an increased number ofexcess deaths due to overheating; but in winter, the UHI will tend to result
in reduced heating loads and a reduced number of cold-related excess deaths(Davies, et al., 2008). It is important to adapt the urban heat, especially forsummer, because of the impact that it creates.
2.3 Urban heat island adaptation
Addressing the urban heat problem, there are two efforst to do, which
are mitigation and adaptation. The mitigation works with climate change
and global warming, while it is not directly working with solution of urban
heat island. And the second one is adaptation, which allows the city to adapt
to the changing environment to minimize the effect of urban heat. While
mitigation shows the solution in long term, adaptation can give the result inshort and long term (PCCC, 2007 in Geerdink, 2009).
To adapt heat island problems, there are some ways, such as providing
green, water, the proper choice of materials, and configuration to arrange
wind pattern. This is based on Kleerekoper’s study about the principles toreduce urban heat that can be achieved by arranging vegetation, water, built
form, and albedo or reflectivity (Kleerekoper, 2009). There is another effort
in her study, which is reducing anthropogenic heat. Since it is related tomitigation efforts, it is not included in this research about adaptation effort.
First of all, by evapotranspiration in active way and creating shadow,
vegetation brings the effort of cooling down the environment. Green can be
implemented in four ways, i.e. street trees, greens, and green roofs andfacades, and urban park or forest. Vegetation can cool the temperature in 1
to 4.7°C (Comte, et al., 1981). Through evapotranspiration, the water
vapours into the atmosphere so it provides cooling effect for the airtemperature. Green provides shadow that can reduce the heat caused bysolar radiation which is very high during summer.

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Secondly, water provides cooling effect by absorbing heat, and it
works when water is in the form of large mass of water, or moving on ariver (Kleerekoper, 2009). Dispersed water gives cooling more than stillwater. Then, proper choice of materials related with albedo. Albedo isinfluenced by building materials’ characteristics, colour, and roughness. In
the study of Taha, an increasing city albedo from 25-40% results in 3°C
temperature decreasing (Taha et al., 1988). Another result is by risingbuildings’ albedo from 9-70% can reduce the annual cooling demand in
19%. Reducing both buildings and city albedo resulted in 62% reduction ofcooling energy demand (Taha et al., 1998).
The configuration or arrangement of buildings in the neighbourhood
can influence urban heat. As the city is growing larger, the effect of urban
heat island also increases. Directing wind by the H/W ratio is more effective
than providing larger space around the building to direct the wind
(Rafailidis, 1997).
The effort of urban heat island adaptation is divided into some parts,
which are: the green structure, the water/humidity balance, the heat/energybalance, and the landscape morphology (Future Cities, 2010). The green
structure has good effects for the city’s temperature, air quality, andrainwater storage. Then, the water/humidity balance is related with water
structures, such as ponds, water courses, rivers, and storage water on green
roofs. They give the less temperature rising. The third one, heat/energybalance, gives the balance of heating up of city. Thus, landscape andmorphology as the orientation and location of buildings give influence on
temperature of an area.
2.4 Urban heat island in Asian Cities
The growing population and urbanization in Asia is rapidly increasing.
Tran et al, (2006) explained that Asian cities are the most rapidly growing
regions of the world nowadays and 16 of the world's 24 mega cities (cities
with more than 10 million people) will be located in Asia by the year of
2015. The urban growth is followed by the increasing temperature of thecity. Ichinose et al. (1999) in Tran et.al. (2006) found that in 135 years,
urbanization has created a warm bias of 2.8°C in lowest air temperature in
the climate record of Tokyo, while Boonjawat et al. (2000) in Tran et.al.
(2006) found a increase of 1.23°C in lowest air temperature in the UHI of
Bangkok for the last 50 years.
An increasing temperature in Seoul is 0.55°C, or 0.275 °C per
decade, compared to the rural area in Korea as 0.15 ° C or 0.075 ° C(Chung et al, 2004). While in Shanghai, China, the different of temperature
between urban area of Longhua and suburban Songjiang is 1°C (Chen et al,2003).

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3. THE TOOL
3.1 The needed tool
Coming with the adaptive solution to urban heat island, the design tool
will be used for urban planners, designers and architects. A tool containing
pictures and explanation, preferably with dimensions will be practicallyused. The design tool is a design guidance, it should help the designers, as a
guidance. The design guidance should give stimulation, option, and widen
the view of designers towards a specific theme, in this case is about urban
heat island.
All of the mentioned adaptation efforts in chapter 2.3 are used formaking the tool, combined with the category, which are: the green structure,
water/humidity balance, heat/energy balance, and urban morphology thatwill be explained in the following chapter.
3.2 The categorization of the tool
Measure to enhance and sustain an appreciated and attractive urban
climate can be taken on building level, street level, neighbourhood level,
and ultimately on regional level (Kuypers and de Vries, 2009). In theneighbourhood and regional level, urban morphology have important role inheat emission and cooling opportunities. The design tool in this researchcontains 3 scales, which are:
1. Building scale;
2. Street scale; and3. Neighborhood scale.
Combining Kuypers’s scale and the scale from Murakami, et al.,
(Murakami, et al., 2000; Murakami, 2004; Mochida, et al., 2008) the scaleof area is defined as:
1. The building scale, is defined as each building, at the zone ofapproximately 30m-50m,
2. The street scale, is defined as one row of the street which might
contains buildings or not.
3. The neighborhood scale, is defined as one neighborhood (up to 1
km x 1 km).
The categorization of each scale will be based on the solution that
future cities has for adapting urban heat, which are: green structure,
water/humidity balance, heat/energy balance, and urban morphology (Future
Cities, 2010).
The effort which has been done by future cities is divided into someparts, which are:
1. The green structure, which has good effects for the city’s
temperature, air quality, and rainwater storage.

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2. The water/humidity balance, which is related with water structures,such as ponds, water courses, rivers, and storage water on green
roofs.
3. The heat/energy balance, which gives the balance of heating up ofcity; it can be consist of the choice of colour and materials.
4. The urban morphology, which is related with orientation andlocation of buildings give influence on temperature of an area
(Future Cities, 2010).
3.3 Overview of the tool
The design tool as a guidance will be formed in 3 tables. Each table
represents each scale, so there are 3 tables: in building scale, in street scale,and in neighbourhood scale. Each scale will be categorized into 4categories: the green structure, water/humidity balance, heat/energy balance,and morphology. Each category includes some actions as written below.
And the action will be defined in effective and less effective way. The
actions from each category were got from researches. All of them weregrouped in the suitable categories that are most related with.
1. Building scale, contains:
a.The green structure: green roof and green façade/wall,
garden for building
b.The water/humidity balance : water close to green façade
c.The heat/energy balance: roof and wall materials and coloursd.The building morphology: building shape and its openings
2. Street scale, contains
a.The green structure: street trees
b.The water/humidity balance : nonec.The heat/energy balance: materials for street, pavement
materials for sidewalks, pavements, parking lots
d.The street morphology: street dimension and direction,building shape which influence the street level
3. Neighbourhood scale, contains
a.The green structure: urban forest/parkb.The water/humidity balance : water, dispersed and flwowing waterc.The heat/energy balance: materials for outdoor urban spaced.The urban morphology: size and density of neighbourhood,building configuration, square

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3.4 3.4
TheThetooltool
No No
1

Table
Table
1: The1: Theurban
urban
heatheatislandislandadaptation
adaptation
tooltool

SCALE
SCALE
AND
AND
ACTIONS:ACTIONS:CATEGORY
CATEGORY
1 Building
Building
scale,
scale,
includes:includes:1. Green
1. Greenroofroof
A. TheA. Thegreen
green
1a. Green
1a. Greenroofroof
shouldshouldbe usebe useratherratherthanthanroofroof
without
without
green
green
structure
structure(includes(includes
green
green
roof,roof, 1b. Plant
1b. Plant
thickthickdarkdark
green
green
vegetation
vegetationon theon green
the greenroofroof
green
green
façade/wall,
façade/wall, 1c. For
1c. Forthe morethe morethanthan
15 cm
15 substrate,
cm substrate,
it is itbetteris betterto fullto full
the thegardengardenfor building)for building) surface
surfaceof roofof roofwithwithcombined
combinedplantsplantsPlantPlant
deciduousdeciduous
woody
woody
and andconifers
conifers
combined
combined
withwith
otherotherplantsplants(mosses(mosses
and andferns,
ferns,
bulbs,
bulbs,
annualannualplants,plants,herbaceous
herbaceousperennials,
perennials,
grassesgrasses
and andsedges)sedges)2. Green
2. Greenfaçade/wall
façade/wall
2a. Green
2a. Green
façade/wall
façade/wallshouldshouldbe usebe useratherratherthanthanwallwallwithout
withoutgreen
green
2b. Green
2b. Green
wallwalland andfacades.
facades.
Place
Place
the green
the green
wallwalltowards
towards
the themostmost
solarsolar
radiation
radiation
received,
received,
usuallyusually
the west
the westside.side.
2c. Percentage
2c. Percentage
of greenof greenfaçade/wall
façade/wall
UseUselargelarge
amountamountof coveredof covered
wallwallwithwith
foliage.
foliage.
2d. Based
2d. Basedon theon kinds
the kindsof theof green
the green
façade/wall
façade/wall
UseUseof livingof living
wallwall- grid- gridand andmodular,modular,verticalverticalinterfaceinterfacewithwith
mixed
mixed
substrate.
substrate.
TheTheuse useof livingof living
wallwall– modular– modular
panel,
panel,
verticalverticalinterface,interface,withwith
inorganic
inorganic
substrate.
substrate.
3. Garden
3. Garden
ProvideProvidegardengardenin everyin everybuildingbuilding
Positioning
Positioning
water
water
closeclose
to theto green
the green
façade.
façade.
B. TheB. Thewater/humidity
water/humidity
balancebalance(includes(includes
water
water
close
close
to green
to greenfaçade)façade)1. Roof
C. TheC. Theheat/energy
heat/energy 1. Roofbalancebalance1a. Materials
1a. Materials
for roof
for roof
based
based
on theon reflectivity
the reflectivity(includes(includes
roofroof
and and UseUse
clayclaytilestiles
wallwallmaterials
materials
and and 1b. Material
1b. Material
choicechoicefor sloped
for sloped
roofsroofs
colours)colours)
ChooseChoosethe white
the whitecolourcolourof: clayof: clay
tile (1sttile (1stbest),best),
concreteconcretetile tile(2nd(2ndbest),best),
fiber-cement
fiber-cement
shingleshingle(3rd(3rdbest),best),
white
white
paintedpaintedmetal
metal
shingleshingle(4th(4thbest),best),
composite
compositeasphaltasphalt
shingle,shingle,fiber-glass
fiber-glassasphaltasphalt
shingle,shingle,organicorganic
asphaltasphalt
shingleshingle(5th(5thbest)best)
1c. Materials
1c. Materials
for flatfor flatand andlow-sloped
low-sloped
roofsroofs
ChooseChoosethe white
the whitecolouredcolouredof: of:smoothsmoothsurfacesurfaceroofroof
withwith
White
White
single-ply
single-ply
membranemembrane(1st best),(1st best),nd ndrdbest),best),
white
white
paintedpaintedmetal
metal
roofroof(3rd (3best),best),
white
white
coating
coating(2 (2built-upbuilt-uproofroof
withwith
white
white
gravelgraveland andcementitious
cementitious
coating
coating(4th (4thththbest)best)best),best),
built-upbuilt-uproofroof
withwith
white
white
gravelgravel(5 (51d. Use1d. Usewhite
white
colouredcolouredroofroof
insteadinsteadof othersof others
UseUsewhite
white
colouredcolouredroofroof(1st (1stbest)best)
UseUsegraygraycolouredcolouredroofroof(2nd(2ndbest)best)
1e. Use1e. Usecoolcooland andreflective
reflective
coating
coatingfor roof
for roofmademadeof concreteof concrete

Urban
heatheatislandcreating
a design
tooltoolfor foradaptation
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islandcreating
aa design
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islandcreating
designtool
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October
2011,
Chiangmai,
Thailand2. Wall
2a. The material colour choice for wall
Material colour choice for building envelope, light colouredbuilding than dark one, or white coloured than painted one.
2b. The use of white or light coloured wall towards the sun
exposed side. Place the wall with high albedo (light coloured) toface the solar radiation in the west and east.
2c. The use of hollow block and concrete than brick. Choose thehollow block and concrete for wall.
Building shape:
Openings on the building to allow wind blow. More openings
on the buildings.

2

D. The building
morphology(includes building
shape and its
openings)
Street scale, includes:
1. Street trees
A. The green
1a. Placed the transpiring plants on the side of the street
structure(includes street trees) 1b. Trees planted on both sides of the street
1c. Related with the ability for evapotranspiration, deciduoustrees is better than conifers
1d. Related with the effectiveness for shading, the crown shapeis really significant. Plant street trees which have large crownshape, create large shadow
1e. Related with the shape and size of the leaves. Plant street
trees:
1. Tilia tomentosa
2. Tilia platyphyllos
3. Tilia cordata
B. The heat/energybalance(includes materials
for street, pavement
materials for
sidewalks,pavements, parking
lots)

1. Materials for street
Combination between concrete and asphalt
2. Paving materials for sidewalks, pavements, parking lots
2a. The colour and material. The use of painted roads
2b. Grass-covered pavement

D. The street
morphology(includes street
dimension anddirection, building
shape)

1. Street
1a. Dimension of the street. Street should have less than 0.25
ratio of H/W(widening the street or shortening the buildings’ height)
1b. Dimension of the street with the same amount of trees.
Create a narrow street with the same amount of trees
1c. Street direction. Direct the street to the main direction of thesummer wind
1d. H/W ratio to create mixed air from urban canopy layer andboundary layer. Create the ratio of H/W 0.5 as the best
2. Buildings
2a. Round shape building rather than angular shape for theentrance and end of street canyon
2b. Tall buildings opposite tall buildings
2c. Slanted roofs to increase the ventilation
2d. Altering roofs shape arrangement is better than similar roof
shape
2e. Shading building by plants, materials, and buildings

3

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A. TheA. Thegreen
green
structure
structure(includes(includes
urban
urban
forest/park)
forest/park)

1. Urban
1. Urbanforest/park
forest/park
1a. Create
1a. Create
urban
urban
forest/park
forest/parkand andopenopengrassgrassfieldfield
1b. Larger
1b. Larger
urban
urban
forest/park
forest/park
gives
gives
greatergreater
impactimpactthanthanthe smallthe smallone one1c. Small
1c. Smalland andspreadspreadgreen.
green.
CreateCreatetwo two
small
small
parks
parks
ratherratherthanthanone onelargelarge
park.park.
1d. Based
1d. Basedon theon size
the sizeof theof leavesthe leaves
to theto coolingthe cooling
effect.
effect.
PlantsPlantstrees:
trees:
1.Aesculus
1.Aesculus
hippocastanum
hippocastanum
2.Gleditsia
2.Gleditsia
triacanthos
triacanthos
3.Platanus
3.Platanus
acerifolia
acerifolia

1. Create
1. Create
water
water
squaresquarecloseclose
to theto green
the green
B. TheB. Thewater/humidity
water/humidity
2. Large
2. Large
surfacesurfaceof waterof waterbalancebalance
3. Dispersed
3. Dispersed
water
water
(includes(includes
water,
water,
4. Flowing
4. Flowing
water
water
dispersed
dispersed
and andflowing
flowing
water)
water)
1. Material
for outdoor
for outdoor
urban
urban
space
space
C. TheC. Theheat/energy
heat/energy 1. Material
1a. The1a. Theuse useof coolof coolmaterials
materials
ratherratherthanthanwarm
warm
materials.
materials.
UseUsebalancebalance(includes(includes
materials
materials light-coloured
light-coloured
materials
materials
for outdoor
for outdoor
urban
urban 1b. The
1b. Theuse useof smoothof smoothsurfacesurfacematerials
materials
thanthan
rough
rough
surfacesurfacespace)
space)
materials
materials
1. Size
1. Sizeand anddensitydensityof neighbourhoodof neighbourhood
D. TheD. Theurban
urban
AdjustAdjustthe neighbourhood
the neighbourhood
becomesbecomes
not too
not large.
too large.
Develop
Developa amorphology
morphology(includes(includes
sizesize
and and small
small
and andnot crowded
not crowded
neighbourhood.
neighbourhood.
densitydensityof of
2. Building
2. Building
configuration
configurationneighborhood,neighborhood,
2a.
More
2a.
More
dynamic
dynamic
configuration
configurationof buildings.
of buildings.
Diagonal
Diagonalbuildingbuilding
configurationof buildingsof buildings
ratherratherthanthangridgrid
configuration.
configuration.
configuration,
configuration,
square)square)configuration
2b. Adjacent
2b. Adjacentbuildingbuilding
placement
placement
3. Square
3. Square
Dimension
Dimensionof theof square
the square
which
which
is surroundedis surroundedby buildings
by buildings
SquareSquareshouldshouldhavehaveless lessthanthan0.250.25
ratioratioof H/Wof H/W

4. CONCLUSION
4. CONCLUSION
TheThetooltoolis guidanceis guidance
for fordesign.
design.
It isIt madeis madein 3inscales,
3 scales,
which
which
are:are:buildingbuilding
scale,
scale,
streetstreetscale,
scale,
andandneighborhoodneighborhood
scale.
scale.
Each
Each
scale
scale
contains
contains
4 categories,
4 categories,
which
which
are:are:the thegreen
green
structure,
structure,
water
water
andandhumidity
humiditybalance,balance,heatheatandandenergyenergybalance,balance,andandmorphology.
morphology.
Regarding
Regardingwithwiththe thestreetstreetandandneighborhoodneighborhood
scale,
scale,
thisthistooltoolalsoalso
hashaspossibility
possibility
to be
to be
used
used
by by
planners.
planners.
Being
Being
performed
performed
in intables,tables,the thetooltoolhashas3 parts
3 parts
based
based
on on
the thescale:
scale:
buildingbuilding
scale
scale
table,
table,
streetstreetscale
scale
table,
table,
andandneighbourhoodneighbourhood
scale
scale
table.
table.
In In
each
each
table,
table,
there
there
are are4 4categories
categories
as asmentioned
mentioned
on on
previous
previousparagraph.
paragraph.
Each
Each
of of
the thecategories
categories
contains
contains
some
someactions
actions
equipped
equipped
withwith
explanations.
explanations.
However,
However,furtherfurther
research
research
is needed
is neededin orderin orderto adapt
to adaptthisthistooltoolfor for
specific
specificlocation
location
andandcondition.
condition.
REFERENCESREFERENCES

Urban
heatheatislandcreating
a design
tooltoolfor foradaptation
Urban
islandcreating
aa design
Urban
heat
islandcreating
designtool
for adaptation
adaptation

94979

contains some actions equipped with explanations. However, further
research is needed in order to adapt this tool for specific location andcondition.
October 2011, Chiang Mai, Thailand
October 2011, Chiangmai, Thailand

REFERENCES

Akbari, Hashem. 2005. Energy Saving Potentials and Air Quality
Benefits of Urban Heat Island Mitigation. Heat Island Group, Lawrence
Berkeley National Laboratory.
Chen, L., et al. 2003. Characteristics of the heat island effect inShanghaiits possible
sland creating
a design andtool foradaptationmechanism. Advances in Atmospheric Sciences 9
20: 991-1001.
Chung, U., et al. 2004. Urbanization effect on the observed change inmean monthly temperatures between 1951-1980 and 1971-2000. Climatic
Change 66: 127-136.
Tran, H. et al. 2006. Assessment with satellite data of the urban heatisland effects in Asian mega cities. International Journal of Applied Earth
Observation and Geoinformation Volume: 8, Issue: 1, Pages: 34-48.
Comte, D.M. le, Waren, H.E. 1981. Modelling the Impact of Summer
Temperatures on National Electricity Consumption. Journal of Applied
Meteorology vol. 20, page 1415-1419.
Davies, Mike, Steadman, Philip, Tadj Oreszczyn. 2008. Strategies forthe modification of the urban climate and the consequent impact on building
energy use. Energy Policy 36: 4548-4551.
EPA, 2008 Reducing Urban Heat Islands: Compendium of Strategies.
Environmental Protection Agency’s Office of Atmospheric Programs.
http://www.epa.gov/heatisland/resources/pdf/BasicsCompendium.pdf
Retrieved in 14 May 2010
Environmental Protection Agency (EPA, United States). Heat Island
Impacts (2009). http://www.epa.gov/hiri/impacts/index.htm Retrieved in
March 2010
Future Cities website. http://www.future-cities.eu. Retrieved in
February 2010
Geerdink, Tobias, et al. 2009. Urban Heat Island: kwetsbare groepen
in de stedelijke leefomgeving (vulnerable groups in urban environment).
Saxion University of Applied Sciences.
Hien, Wong Nyuk, Eang, Lee Siew, Li Shuo, Ana nda Ram Bhaskar,
Tan Kok Kwang.Thermal Performance of Façade Materials and Design
and the Impacts on Indoor and Outdoor Environment.
Kleerekoper, Laura. 2009. Urban Heat. Graduation Thesis. Delft
University of Technology.
Kuypers, Vincent, Vries, Barry de. 2008. Groen voor Klimaat.
Oke, T.R. 1982. The energetic basis of the urban heat island. The
quarterly journal of the Royal Meteorological Society Vol 108, page 1-24.
Rafailidis, Stylianos. 1997. Influence of Building Areal Density andRoof Shape on the Wind Characteristics above a Town. Boundary-Layer
Meteorology 85, page 255-271.
Taha, H. Rosenfeld, Akbari, A., J. Huang. 1988. Residential Coolingloads and the urban heat islands-the effect of albedo. Building andEnvironment 23, page 271-283.
United Nations. 2009. Commission on population and development tofocus on population growth in least developed nations, impact on
development, 30 March-3 April.
Voogt, James. A. 2004. Urban Heat Islands: Hotter Cities.
http://www.ActionBiosience.org. (retrieved in March 2010)

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New Technologies for Urban Safety of Mega Cities in Asia

Study on urban air quality risk using
spatial technology and public perception:a case study of Vientiane Capital city, Laos
Soutthanome KEOLA 1, Edsel SAJOR 2
and Vivarad PHONEKEO3
1
PhD candidate, UEM, SERD,
Asian Institute of Technology, Thailand
st104504@ait.ac.th2
Associate Professor, UEM, SERD,
Asian Institute of Technology, Thailand
3
Senior Researcher, GIC, SET,
Asian Institute of Technology, Thailand
ABSTRACT
Vientiane Capital is one of the urbanized cities in Laos that has been
continuously developed since the end of 90s after the Lao government has
issued the open-door policies that introduced the marketing economy todevelop the country. The critically change in the city is the number ofvariety vehicles which have been increasing yearly, traffic congested havebeen appeared in urban center where high density population located. This
main objective of this study is whether this phenomenon could possible to bea source of air pollution that effects to metropolitan’s health. However,
Laos does not have baseline air quality data that is necessary for the study
due to there is no systematic air quality measurement facilities yet.
Therefore, it is necessary to carry a study for better understanding of the air
quality scenario and regularly convey information to concerned stakeholder
for making decision on health and environment prevention. To overcome
this problem, the this study have proposed an alternative way to solve theproblem, by introducing the application of spatial technology which
includes 9 years MODIS aerosol optical thickness product from NASA as atool for PM data acquisition. In the result of the study, the high and low
concentration of PM areas was obtained which can refer to be the risk area
for resident. Public risk perspective from the high risk area and upper
respiratory symptoms from elderly people have obtained. These results
could be informed for public health decision maker to improve and revise
urban planning and regulations.
Keywords: aerosol optical thickness, MODIS, Particulate matter, publicrisk perspective

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October 2011, Chiang
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Thailand
Chiangmai,

1. INTRODUCTION
Economic growth is linked to urbanization, and does not always positively
contribute to improve the human well-being and living condition. If theeconomy grows rapidly, urban areas would expand without proper control
and might lead to unexpected negative impacts such as increasing of urban
environmental pollution. The increasing of economic activities, businessand industries contribute to generate various environmental pollutions, oneof them is urban air pollution which normally rises up silently during thebuilding phase of urbanization (Fenger, 1999), (Wichitrakorn, 2002).
Traditionally, capital city or urban areas is initial area of air pollution which
results from rapid growth of population in urban center and peri-urban area
(Sevilla et al., 2004). Vientiane Capital is a capital city of Laos that faces of
the initial urban air pollution and have certified by following facts: (i) themonitoring of air quality conducted in every three consecutive days per year
in the period of 2002-2004 have found the particulate matter withaerodynamic diameter 10 μm (PM10) over WHO standard (ADB, 2006); (ii)derived Carbon Monoxide from SCIAMACHY imageries is in the highlevel (SCIAMACHY, 2008); (iii) the noise pollution have over the WHO
standard (ADB, 2006); and the increasing of traffic congested area in theurban center.
Mobile source of air pollution is a critical source in Vientiane Capitalthat requires for proper information to support the air quality management.
The increasing of annually road accident is an acute or visible impact oftraffic that being rising up with number of selling vehicles (MCTPC, 2007),
while chronic or silence impact of traffic is still unclear status. In addition,
the important tools of air quality management such as air quality standard,emission standard and related regulations are limited.
Transportation is the most polluted factor for urban area, the level of
air pollution depends on the physical construction and energy consumption
with particular vehicles and it tends to be worst in cities that contain of highpopulation density (Mage et al., 1995). In this case of Vientiane Capital,
there are many associated factors, (i) buying and selling tax is reduced; (ii)unclear quota for imported low cost vehicles or second hand car; (iii) thepurchase capacity of population is increasing; and (iv) the rapid growth of
population in the sub-urban with high demand on vehicle to travel to urban
center. Recently, the growth of car passenger occupied about 17 % annually,
the total number of motorcycles registered in 2009 is 272 thousand or 3.3
times more than number in year 2000 (Vientiane, 2010). Whilst the parking
area is not properly designed in the urban center; some cars are parked on
the roadsides, block the traffic flow which lead to traffic congestion andcause of car’s emission to the urban atmosphere.
Maintaining and controlling in the initial stage of air pollution ispossible to minimize its severities to harm human and environment (CIAAsia and PAMA, 2004), and many countries could not conduct the air
quality monitoring activities, due to unaffordable for instruments (CIA-2500

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Asia, 2010). The efficient air pollution monitoring instruments are mainly

produced by developed countries; one of them is Moderate Resolution
Imaging Spectro Radiometer (MODIS). MODIS is an earth observation
satellite which provides free Aerosol Optical thickness (AOT) for observing
the air quality in the regional and global scale. However, the usage of
MODIS AOT in the local scale have been recognized through the various
studies on the relationship between MODIS AOT and particulate matterwith aerodynamic diameter less than 2.5 μm (PM2.5) and have resulted thereliable correlation, particularly in the urban areas (Mukai S. et al., 2007;
Jeong E et al., 2006; and Hui Li et al., 2009). Thus MODIS AOT might be
one of alternative solutions for air pollution monitoring in area where air
monitoring station not available, but the ground measurement for validationis still needed (Gupta P et al., 2006).

This paper attempts to estimate the PM2.5 derived from MODIS AOT
and status public health in the area of high and low concentration of PM2.5
of Vientiane Capital. The 9 year MODIS AOT data have been applied andthe high concentration of PM2.5 has occurred during February, March andApril. The High and low risk area has been identified by visualized analysis
with Google Earth application. Risk area found in the urban center and sub
urban has great potential to become risk in the future. The extent throughhealth survey in urban center and sub urban area, some health symptoms ofupper respiratory diseases were found in elderly people who live in the highPM2.5 concentrated area.
2. STUDY AREA
The study area locates in the Vientiane Capital which is situated in thesouthwestern part of Laos and on the banks of the Mekong River. It locatesat 17°58' North, 102°36' East. The Vientiane Capital covers mostly plain
and lowland area. The core urban area consists of 100 villages with belongs
to Chanthabouly, Sisattanak and parts of Sikhottabong, Xaysetha andHadxaifong districts where locate main offices, commercial centers, centerof public services, banks, cultural resources, recreation places andeducational centers.

N
Water body

Figure 1: Map of study area
Study on urban air quality risk using spatial technology and public perception: a case study of Vientiane
Study on urban air quality risk using spatial technology and public perception:
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October 2011, Chiang
Mai,Thailand
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Chiangmai,

The built-up area doubled from approximately 3% of total area in
1995 to 6% in 2005. Vientiane Capital has the population of approximately
700 thousands persons in 2005. Approximately 350 thousand people or
50 % of the total population concentrates in the urban area and 50% in the
sub urban area. The urban center has very limited population growth rate
due to no more apace for development, while the suburban area has highpopulation growth rate with plenty of apace for further urbanization. The
population density of the urban center is 36.7 person/ha on an average,
whilst some areas may be more densely inhabited with more than 80
persons/ha (MCTPC, 2007).
The urban center of Vientiane Capital consists of the whole areas of
Chanthabouly, Sinathanak, Sikhottabong, Xaysetthan, Hatxayfong and
Xaythany district and had divided in 36 traffic zones and 234 villages.
3. METHODOLOGY
According to lack of air monitoring station in Lao PDR, the air quality inthe ground is not available for monitoring; this study have applied Aerosol
Optical thickness (AOT) from the Moderate-Resolution Imaging
Spectroradiometer or MODIS AOT to estimate the PM2.5 massconcentration in Vientiane Capital. The process of methodology is
explaining as follow: (i) the MODIS AOT data collection; a set of MODISAOT in the dry season (February, March and April) for 9 years were
downloaded and then the data were geometric corrected and stored as binary
images; (ii) defined a reference table for the deterring the range of PM2.5.
Reviewing studies on relationship between MODIS AOT and PM2.5;
focused on the result from linear regression to determine its relationship.
The reference table has obtained and this study applied this study to be areference for estimate the range of PM2.5 (Table 1); (iii) defining the risk
area by applying the application of Google Earth to conduct the visualized
analysis. Data on MODIS AOT, population density, travelling pattern,congested traffic points, urban infrastructures have used to identify risk
area; and (vi) conduct health survey in high and low risk area. The
questionnaires were also conducted by face to face interview individual
households at high and low risk location. Respondent’s age was between 18
and 65 years old. The flowchart of the methodology is shown in the Figure 2.
All results of this study are described in the next section.

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START

Download MODIS Aerosol
Product (MOD04) (HDF-EOS
Format)Geometric Correction, Scientific
data set extraction

AOT image (binary format) andclassify the AOT according to thedefined range

Define the range and significant ofcorrelation between AOT and
PM2.5 by reviewing the literatures

Conduct visualization analysis
through the Google earth

Population density, travel pattern,traffic congested points and urban
infastructures

High and low risk area

Conduct health survey

Result: The status of urban air
quality and resident’s health

END

Figure 2: The process of methodology
Table 1: The reference range of MODIS AOT index and mass concentrationof PM 2.5

Range of correlation
coefficient between PM2.5
and AOT
0-0.190-29
0.6, 0.96
0.2-0.49
30-69
0.77, 0.96
0.5-0.79
70-1000.77, 0.96
0.8- more than 1
more than 110
0.87
Sources: (i) Keith D. Hutchison, Solar Smith and Shazia J. Faruqui , 2005; (ii) Nuno
Grosso et al.,2008; (iii) Jeong E et al., 2006, Gupta P et al., 2008; Mukai S et al., 2007;
R.B.A. Koelemeijer et al., 2006;
Note: the green, yellow, orange and red represent the value of written number in the table
Range of aerosol optical
thickness (AOT) index

Range of PM2.5(µg m-3)

4. AREA OF HIGH AND LOW PM2.5 CONCENTRATIONThe MODerate resolution Imaging Spectrometer (MODIS) instrument is asensor onboard Terra and Satellites which its mission is for Earthobservation in global scale and multi-temporal time series for global
environmental study. The application of MODIS data is widely used forland, ocean and atmospheric research and study because of the wide-rangeof spectral bands from red to thermal bands which is in total of 36
Study on urban air quality risk using spatial technology and public perception: a case study of Vientiane
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a case study of Vientiane Capital city, Laos

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Chiangmai,

bands. With the launch of Terra and Aqua polar orbiting satellites, the usageof satellite to estimate the PM2.5 has been increased for alleviate some of theuncover ground measurements and several studies have shown that some
information from satellite data could present for ground measurements. The
studies on the comparison between satellite-derived aerosol optical
thickness and PM2.5 mass found a good correlation between column AOT
derived from the MODIS on the Terra/Aqua satellites and fine particulatemass (PM2.5) (Engel Cox et al., 2006; Gupta et al., 2006, 2007, Wang andChristopher, 2004). Some studies have used local meteorological parameters
along with satellite-derived products to form multiple regression equations
that improve overall relationships.
Since the MODIS onboard EOS-Terra satellite was launched into asun-synchronous polar orbit in December 1999 (R.B.A. Koelemeijer et al.,2005), the obtained MODIS AOT data is available from year 2001 onward.
The free AOT MODIS data within 9 years (2001 and 2004-2010) for
Vientiane
Capitalhave
downloaded
from
NASA
website(http://modis.gsfc.nasa.gov/). The aerosol product or MOD04 is one of the
MODIS products which is generated from MODIS data of Level 1B andcontains the aerosol optical depth physical parameter. 13 grids (radius 10 x
10 Km) cover all of Vientiane Capital.
This study used data from 2001, 2004 to 2011 to estimate the potentialof highest level of MODIS AOT. According the some limitation of MODIS,
the cloud free day consists more in dry seasons. The received MODIS AOT
data around 80% in each February and 60% in March and around 45-50% in
April have downloaded, and these data were sufficient to identify the statusof AOT. MODIS AOT data in each month have classified according toreference Table 1, the percentage of good air quality during dry season (Febto April) is less than 23.2% of total MODIS AOT data, but the critical air
quality also not more than 12.5 % and the 64.2% of air quality still in thelevel of consider for sensitive people. The details are listed in Table 2.
Table 2: The percentage of MODIS AOT by year and month
2001
2004
2005
2006
2007
2008
2009
2010
2011

10.0
22.0
12.1
34.0
24.4
25.0
24.3
27.0
22.0

February
20.0
50.0
32.2
40.7
32.8
36.0
43.0
21.2
15.7
42.1
28.3
45.0
41.1
33.3
42.7
22.1
35.4
27.2

20.0
5.1
19.1
1.8
17.8
1.7
1.3
8.2
15.4

17.5
23.0
17.5
25.2
12.9
18.9
13.5
21.2
16.4

March
30.2
12.0
39.1
30.4
12.0
40.7
22.1
48.0
29.1
49.3
52.4
23.0
22.4
45.1
43.2
33.0
34.1
32.0

40.3
7.5
29.8
4.7
8.7
5.7
19.0
2.6
17.5

30.4
30.0
34.5
33.3
17.0
35.6
23.7
28.6
27.2

26.2
42.0
32.1
43.2
33.5
34.2
43.1
11.2
45.2

April
30.4
22.0
26.0
22.0
28.8
20.0
30.0
30.1
7.5

13.0
6.0
7.4
1.5
20.7
10.2
3.2
30.1
20.1

The average of MODIS AOT within 9 years has displayed in the
Figure 2, the green, yellow, orange and red represents the low, middle, highand very high range of PM2.5 respectively. The grid number 8 is the highest
MODIS AOT. To discover more on this area, the map of population density,
travelling pattern, congested traffic points, urban infrastructures haveimported to the Google earth and high and low risk area have obtained.

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The high risk area consists of 8 villages, and the low risk area consistsof 25 villages which cover 1218 households (11189 people) and 3022
households (301156 people) respectively. From the study, it is obviouslythat MODIS AOT data can be used to apply for air quality monitoring in
Vientiane Capital.

Color
Range of AOT
Range of PM2.5(µg m-3)

Green
0-0.190-29

yellow
0.2-0.49
30-69

Orange0.5-0.79
70-100Red
0.8->1> 110

Figure 3: The average of MODIS AOT’s Vientiane Capital
5. HALTH STATUS AND PUBLIC PERCEPTION
Air quality monitoring is the main source of information in assessing theexposure of the population to ambient air pollution. Exposure is determinedby the concentrations people experience in their living environments. Thus,
monitoring should measure the concentrations in places the people live.
Human exposure to air pollutants may result in a variety of health effects
depending on the type of pollutants: the magnitude, duration and frequencyof exposure; and the associated toxicity of the specific pollutant. This study
trends to estimate the population health status, but the measuring of air
pollution is still not accurate yet. Therefore the dose exposure also will not
reliable for predict the risk. Therefore the assessments on risk perception,
annoyance of urban air pollution, and health-related quality of life haveconducted during June to August 2011 to identify the health status ofresident who live in area of high and low PM2.5 concentration derived from
MODIS AOT. The designed population-based questionnaire has covered allof listed three aspects (risk perception, traffic annoyance, health-related
quality of life).
The survey by questionnaires had conducted in 180 households, 100
households in high PM2.5 concentration area and 80 households in low PM2.5
concentration. 75% of responded household live in personal house and mostof them are house owner and live in their own land more than 10 years.

Study on urban air quality risk using spatial technology and public perception: a case study of Vientiane
Study on urban air quality risk using spatial technology and public perception:
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a case study of Vientiane Capital city, Laos

October 2011, Chiang
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Thailand
Chiangmai,

Apart from the visible health impact from road traffic, the record ofmortality and mobility in health center shows that the mitigation measure
for road safety is need to revise and improve. The common reasons such as
high speed, riding after alcohol and drugs consumption still have a dramatic
impact on the frequency and severity of injuries and mortality from roadaccidents (S. Dhondt et al., 2010). The number of injuries from roadaccident keeps rising up annually (Figure 5). However, the invisible healthimpact still is silence and that is the one of the objective of this study.

Figure 5: Number of injuries from road accident
Department of Transport, 2010
In this study find out a current picture of the way that residents think
about the problem of urban air pollution. The most important source of air
pollution is construction, vehicle emission, road dust and Garbage burning(Table 3). Direct, personal experience was clearly formative in each answer,
the urban air quality is generally very good (the respondent have accepted50%), and road traffic have to consider (only 30% of respondents who havepersonal car are strongly accepted, while respondent who drive themotorcycle have responded for neutral and poor) (Table 4). The visible

indicators included physical depositional evidence (dust or dirt)
at the household level help respondent to understand the level ofurban air pollution easily (Karen Bickersta and Gordon Walker,
2001). The perception on the cognitive sources of urban air pollution andexisting air quality in Vientiane Capital from residents have identified thecritical source of urban air pollution and sense to the severity of air pollution.
Table 3: The perception on the cognitive sources of urban air pollution

Source of urban air pollution
in Vientiane Capital

Percentage of respondents*

Vehicle emission
Construction
Garbage burning
Industrial emissions

93
100
40
10

8
506

Agree

Not
agree
40
80

Do not
know
7
10
10

Void
10
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Slash and
Slash
burn
and burn- 90
90 10Road dust
70 20
20 10
Road dust
70
some respondents
identified
more
than
one source
Note*: Note*:some respondents
identified
more thanonesource

10
10

-

-

Table Table
4: The4:percentage
The percentage
of cognitiveof cognitive
perception
perception
on theonexisting
the existing
air quality
air quality
in Vientiane
in Vientiane
CapitalCapital

Air quality
Air quality
inin Very Very
Good Good
NeutralNeutral
Poor Poor
Very VeryDo
DoVoid Void
Vientiane
Vientiane
CapitalCapital
good goodpoor poornotnotknow know
5040
4010
10 -- - GeneralGeneralarea area
50
3030
3020
20 10
10
10 - Road Road30
10

55% 55%percent
percentof residentof resident
have haveagreedagreed
that theythat might
they might
have haverisk fromrisk fromexposure
exposure
to urbanto urban
air pollution
air pollution
while while
45% still
45% dostillnotdoknow
not know
urban urban
air air
pollution.
pollution.
Since Since
air pollution
air pollution
components
components
may bemay
odorless,be odorless,peoplepeople
may react
may reactto the tochemicalthe chemical
substances
substances
as irritants,
as irritants,
to bodily
to bodily
mediated
mediatedreactionsreactionssuch assuch aseye irritations,
eye irritations,coughingcoughing
and allergic
and allergic
responses
responses(R. Klæboe
(R. Klæboe
et al., et2007).
al., 2007).
However,
However,the risk
theperception
risk perception
on urbanon urban
air pollution
air pollution
for resident
for resident
is not isbignot big
issue, issue,
but they
but aretheyworrying
are worrying
the security
the security
risk suchrisk assuch
robber,as robber,gangstergangsteroror
thief, drug
thief,anddrugamphetamine
and amphetamine(80% (80%of respondentof respondent
have emphasized
have emphasizedon theseon theserisks).risks).
Moreover,Moreover,respondent
respondent
did not
didsignificantly
not significantly
emphasizeemphasizeon healthon healthproblems,
problems,
even mosteven ofmostthemof havethem experiences
have experienceswith listedwith listed
healthhealthproblems
problems
and symptoms
and symptoms
in Tablein Table
5, particularly
5, particularly
elderly.
elderly.
“Health“Healthdiseasesdiseasesoror
symptoms
symptoms
from fromexposure
exposure
to airto pollutant
air pollutant
are possible
are possible
to treatto treatwith withmedication,
medication,and itandis notit ismajor
not major
problemproblemhere” here”
is the iscommon
the common
expression
expression
from healthfrom healthperception
perception
survey.survey.
The discussed
The discussed
information
information
has alreadyhas alreadybeen beenshownshownthat thethatdirect
the direct
healthhealthimpacts
impactsof air ofquality
air quality
represent
represent
an important
an importantsourcesourceof localof local
air quality.
air quality.
However,
However,
respondents
respondents
have haveconfirmed
confirmed
the thenegative
negative
healthhealthimpacts
impactsof airofpollution
air pollution
on theiron owntheir healthown healthwith lesswith lesssignificance.
significance.
Table Table
5 shows
5 shows
the results
the resultsof surveyof survey
questionquestion
whichwhich
asked asked
respondents
respondents
whetherwhetherthey were
they aware
were awareof anyofparticular
any particular
healthhealthproblems
problems
they theyor family
or family
members
members
had experienced
had experienced
that theythat linked
they linked
to poorto airpoorquality.
air quality.
AlmostAlmosthalf ofhalfthoseof thosesurveyedsurveyed(45%)(45%)
identified
identified
some someform formof impact,of impact,
mostlymostly
relatedrelated
to breathing,to breathing,allergic
allergic
and irritationand irritation
problems.
problems.
Table Table
5: percentage
5: percentageof respondentof respondent
reportedreportedon healthon healthimpactimpact

Diseases
Diseases% of total% ofrespondent
total respondent
have experience
have experience
ononthese disease
these disease
and symptoms*
and symptoms*
Pneumonia
Pneumonia
20
20
AllergicAllergic
7070
Cardio-vascular
Cardio-vasculardiseasedisease3
3
ChronicChronic
flu
flu
50
50
Lung disease
Lung disease
37
37
AsthmaAsthma
73
73
HealthHealthsymptoms
symptoms
Difficult
Difficultto breathto (sometimes)
breath (sometimes)
82
82
Chest pain
Chest pain
56
56
ChronicChronic
runny noserunny nose
37
37
ChronicChronicsneezingsneezing
55
55
Cough Coughwithoutwithout
clear reason
clear reason
23
23
ChronicChronic
cough without
cough without
clear reason
clear reason
11
11*Some *Some
respondents
respondents
identified
identified
more than
more
one
than
impact.
one impact.

Studyon airurban
air quality
riskspatial
using spatial
technology
and public
perception:
caseofstudyof Vientiane
Study onurban
qualityrisk using
technology
and public
perception:a case astudy
Vientiane
Study on urban air quality risk using spatial technology and public perception:
9 5079city, Laos
capitalcapitalcity, Laosa case study of Vientiane Capital city, Laos

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

7. CONCLUSION AND DISCUSSION
The usage of MODIS AOT for estimate the air quality is not final answer,
the ground monitoring is need to validate. However, this technique has
illustrated a broad view of urban air pollution for the area that needpreliminary assessment and air monitoring station is not available.
In case of Vientiane Capital, the main source of air pollution is line
source. Vehicle fleet in the Vientiane Capital dominances by private vehicle,
particularly motorcycle. In the year 2009, motorcycle cover 70 % of total
vehicles and follows by pick up, light vehicle and others 14,6%, 5% and10.5% respectively. Moreover, the standard of used car still not issued
officially thus the various type of nonstandard car is imported. According to
the EPA studies, 30% of five-year-old cars emit more than they were
designed to emit. Fifty-five percent of seven-year-old cars will continue topollute urban air quality. Base on facts above, the air pollution in Vientiane
Capital exists but not reach to the critical status. Some of resident have
health problem, but generally resident still happily lives in Vientiane Capital.
REFERENCES
Asian Development Bank (2006). Country Synthesis Report on Urban
Air Quality Management Lao PDR. Asian Development Bank, 2006.
CIA-Asia and PAMA, 2004. A Strategic Framework for Air Quality
Management in Asia. Stockholm Environment Institute, 2004
CIA-Asia (2010). Air Quality in Asia: Status and Trends, 2010
Edition. Clean Air Initiative for Asian Cities (CAI-Asia) Center, April 2010
Engel-Cox, J. A., Holloman, C. H., Coutant, B. W., & Hoff, R. M.
(2004). Qualitative and quantitative evaluation of MODIS satellite sensor
data for regional and urban scale air quality. Atmospheric Environment, 38,
2495–2509.
Fenger Jes (1999). Urban air quality. Atmospheric Environment 33 ,4877-4900
Gupta P. Sundar A. Christopher A., Wang J. G. Robert, Yc Lee,
Kumar. (2006), Satellite remote sensing of particulate matter and air quality
assessment over global cities. Atmospheric Environment (40). 5880–5892.
Gupta P, Sundar A. Christopher, Jun Wang, Robert Gehrig, Yc Lee
and Naresh Kumar (2008).
Satellite remote sensing of particulate matter and air quality
assessment over global cities.
Atmospheric Environment. (40), 5880-5892
Hui Li, Fazlay Faruq, Worth Williams, Mohammad Al-Hamdan,
Jeffrey Luvall, William Crosson, Douglas Rickman and Ashutosh Linaye(2009). Optimal temporal scale for the correlation of AOD and groundmeasurements of PM2.5 in a real-time air quality estimation system.
Atmospheric Environment. (43), 4303-4310
Jeong E. Kim, Seong Y. Ryu, Zhuanshi He and Young J. Kim (2006).
Spectral aerosol optical depth variation with different types of Aerosol at

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Gwangju, Korea . Journal of Atmospheric and Solar-Terrestrial Physics(68), 1609-1621
Karen Bickersta and Gordon Walker (2001). Public understandings of
air pollution: the &localization ofenvironmental risk. Global Environmental Change 11 (2001) 133}145
Mage S., Ferraraccio F., Prati M.V., Annunziata S., A. Bianco, A.
Mezzogiorno, G. Liguori, I.F. Angelillo and M. Cazzola. (1995). Urban air
pollution in mega cities of the world. Journal of Atmospheric Environment,(30.) 5.
Ministry of Communication Transport Post and Construction (2007).
The study of master plan on comprehensive urban transport in Vientiane
Capital in Lao PDR. Progress report, Katahira & Engineers international
July, 2007.
Matthias Schmidt and Ralf-Peter Schäfer (1988). An integrated
simulation system for traffic induced air pollution. Environmental
Modelling & Software 13 (1998) 295–303
R.B.A. Koelemeijer, C.D. Homan and J. Matthijsen (2005).
Comparison of spatial and temporal variations of aerosol optical thickness
and particulate matter over Europe. Atmospheric Environment (40) 53045315
R. Klæboe, A.H. Amundsen, A. Fyhri (2007). Annoyance fromvehicular air pollution: A comparison of European exposure–response
relationships. Atmospheric Environment 42 (2008) 7689–7694
Sevilla J., David C., Jaypee S. (2004). The Effect of Health on
Economic Growth: A Production Function Approach. The journal of World
Development 32 (1). 1121-1124.
SCIAMACHY (2008). The monthly concentration of CO fromSCIAMACHY satellite data in Lao PDR.
SCIAMACHY
website,http://www.iup.unibremen.de/sciamachy/NIR_NADIR_WFM_DOAS/, last updated on 2010.
Stijn Dhondt, Quynh Le Xuan, Hieu Vu Van and Luc Hens (2010).
Environmental health impacts of mobility and transport in Hai Phong,Vietnam. Stoch Environ Res Risk Assess. DOI 10.1007/s00477-010-0374-3
S. Mukai, I. Sano, A. Nishimori, M. Sato, Y. Okada and B.N. Holben(2007). A comparison of aerosol properties with air pollutants. Advances inSpace Research 39 (2007) 32-35
Vientiane (2010). Draft of Vientiane Master Plan. Vientiane Urban
Development Administrative Authority 2010.
Wang Jun and Sundar A. Christopher (2004). Intercomparison
between satellite-derived aerosol optical thickness and PM2.5 mass:
Implications for air quality studies. GEOPHYSICAL RESEARCH. 30,
doi:10.1029/2003GL018174, 2003
Wichitrakorn N. (2002). The estimation of mortality and economic
impact of urban air pollution in Bangkok, College of Public Helth, (Master
Thesis No RA 576.6 T5) Chulalongkorn University

Study on urban air quality risk using spatial technology and public perception: a case study of Vientiane
Study on urban air quality risk using spatial technology and public perception:
11
capital city, Laos509
a case study of Vientiane Capital city, Laos

October 2011, Chiang Mai, Thailand

510

New Technologies for Urban Safety of Mega Cities in Asia

Potential greenhouse gas reductionin Samui towards becoming carbon
neutral island
Poon THIENGBURANATHUM1, Pongtip THIENGBURANATHUM2, andChaya VADDHANAPHUTI3
1
Associate Professor, Department of Civil Engineering,
Faculty of Engineering,
Chiang Mai University, Thailand
poon@eng.cmu.ac.th2
Research Assistant, Department of Civil Engineering,
Faculty of Engineering,
Chiang Mai University, Thailand
3
Lecturer, Department of Geography, Faculty of Social Science,
Chiang Mai University, Thailand
ABSTRACTWorldwide is facing the impacts of climate change, in particular along
coastal areas. Samui, one of the most popular tourist destination andbusiness investment is encountering the risk of losing its precious natural
resource due to human activities and climate change. This study explores
the potential for Samui to reduce greenhouse gas (GHG) emission, towards
becoming carbon neutral island by analysing the potential to reduce GHG
emission based on historical and surveyed data and future activities from 4
sectors, namely: (1) solid waste management, (2) mass urban transportation,(3) energy efficiency, and (4) renewable energy. Calculations suggest thatby changing technologies and infrastructures, Samui is able to reduce
emission from solid waste sector, using landfill and methane capturing
technology, between 2,414-21,633 tCO2e/year. In transport sector, much
reduction (up to 68,875 tCO2e/year) comes from changing diesel motorcycle
to electric motorcycle and switching from diesel cars to either electric andhybrid, or ethanol. In energy efficiency sector, the study finds switching tomore efficient lighting and cooling technologies especially in hotels andresidential area to help reducing GHG up to 11,894 tCO2e/year. Lastly, apotential of at least 100 projects of photovoltaic installed in hotels are able
to reduce 255-2,571 tCO2e/year. In total, the entire island can reduce GHG
by 5,990-9,490 tCO2e/year.
Keywords: Climate Change Mitigation, Samui Island, Clean Development
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1. INTRODUCTION
Worldwide is facing the impact of Climate change, while it is important torecognize that the impact is greater along the coastline and especially on
islands. These impacts includes for example: inundation of coastal areas
where the majority of their inhabitants reside, loss of freshwater supplies,
diminution of biodiversity, destruction of critical infrastructure, and possible
increase in the incidence of serious diseases.
Historically Samui's economy has been based around subsistence
agriculture and fishing, with coconuts as the main cash crop. From the
1980s onwards, tourism has become an economic factor and is now thedominant industry. The construction of a stable, high-speed Internet
connection in recent years has also made the island a feasible location for
IT-based enterprises, which are beginning to provide a certain degree of
economic diversity. The island's climate and accessibility make itparticularly attractive for international investors. Samui is attracting more
and more investor and tourists to the island every year. However, with theeconomic shifted from agriculture to tourism, the island had to adapt itself
to larger human footprint. Tourist brings income as well as increases
pressure and requirement on natural resources consumption.
This study explores the potential for Samui to reduce greenhouse gas(GHG) emission, towards becoming carbon neutral island by analysing thepotential to reduce GHG emission based on historical and surveyed data andfuture activities from 4 sectors, namely: (1) solid waste management, (2)mass urban transportation, (3) energy efficiency, and (4) renewable energy.
2. DEVELOPMENT OF TOURISM IN SAMUIIn 1980s East Asia and Southeast Asia experienced the most rapid growth inregional mass tourism in the world, with 9.2 % per annum increase in thenumber of tourists compared to the global average of 4.5% (Hitchcock et al2008 p. 8). This was due to increasing affluence from the Far East,decreasing cost of travelling, increasing tourist availability and diversity,and most importantly, the 1992 “Visit ASEAN” campaign (Hitchcock et al2008). After 2005, the region received $ 43.2 billion as GDP, 7 million jobs
created while tourist demand still increased by 6.2% per annum. Thailand
has always and long been the top 20 in tourist destination.
The study of Green (2005) describes the establishment of tourism in
Samui back in 1980s in a town called Chaweng as “no more than small
beach bungalows and restaurants catering to backpackers owned andoperated by locals as a means of providing additional income to that which
they earned from other sources, such as coconut farming.” Today, not only
Chaweng is famous but also Tambon Angtong, Tambon Maret, Tambon
Boput, Tambon Maenam, and Lamai community.
As the new millennium turns, massive and rapid growth of tourism

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completely changed the socio-economic status of Samui. In 2002, the total
number of tourist was 857,335 with 85.21% as foreigner mostly from
Germany, United Kingdom and Australia, generating 10.4 billion Baht ofcash flow. At the time, the island had 310 service accommodations withapproximately 60% occupation rate. Although in 2003 alone the SARS
situation decreased the growth rate by 6% (Department of Environmental
Quality Promotion: DEQP, 2006), Samui received up to 10 million
international tourists, which generated 10 billion US dollar income or 5.4%of the GDP (Green 2005) The figure for domestic and international tourist is
150,000 and 850,000 per year, respectively, or 2,903 persons per day .,generating between 12-14 million baht of cash flow per year (Samui
Municipality 2010a). Chudintra and Pintukanok (1992, cited in Wong 1998)
calculated that, for the whole island to maintain its identity, the maximum
carrying capacity is put at the maximum 14,200 tourists/day. With suchgrowth in the number of tourist, the population of local people of Samui in2004 and 2010 was 45,493 (DEQP, 2006) and roughly 51000, respectively,
and last updated on 30 April 2009, was 52,935 (Samui Municipality, 2010a).
The unregistered population, mostly from Northeastern part of Thailand andBurma is roughly 200,000 (Samui Municipality 2010a).
In the past, the majority of local people engage in small-scale
agricultural activity. Agricultural land is dominated by coconut plantation(84,310 rai), durian (11,037 rai), langsat (5,725 rai), mangosteen (430 rai),
and rubber (1,185 rai), another sector includes fishing (Samui Municipality
2010a). Green (2005) observed that people from the Thai mainland andWesterns dominate ownership of the town’s resorts, restaurants and bars.
They tend to employ cheap workers, hence an influx of people from themainland and illegal migrants (Burmese).
3. METHODOLOGY
The project boundary is Samui Island, Surrathani Province. The project
analysed the potential to reduce Greenhouse Gas (GHG) emission from 4
sectors namely: (1) solid waste management, (2) mass urban transportation,(3) energy efficiency, and (4) renewable energy. The potential will analyse
based on existing database as well as survey data. The project focused on
historical activities and planned project activities. The methodologies usedwere base on the approved small-scale methodology for Clean Development
Mechanism (CDM): AMS-III.G Landfill Methane Recovery, AMS-III.F.
Avoidance of methane emissions through composting, AMS-III.T. Plant oil
production and use for transportation applications, AMS-III.AK. Biodiesel
production and use for transportation applications, AMS-III.C. Emission
reductions by low- greenhouse gas emitting vehicles, AMS- III.S.
Introduction of low-emission vehicles to commercial vehicle fleets, AMSIII.AA. Transportation Energy Efficiency Activities using Retrofit
Technologies, AMS-I.A. Electricity generation by user, AMS- II.C.
Demand-side energy efficiency activities for specific technologies,
AMS.II.E Energy Efficient and fuel switching measures for buildings, and
AMS -II.J Demand-side activities for efficient lighting technologies. The

Potential greenhouse
Potential
greenhouse gas
gas reduction
reduction in
in Samui
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formulas were used to calculate potential GHG emission reduction for eachtype of project for each sector.
4. CURRENT GREENHOUSE GAS EMISSION
4.1 Greenhouse Gas emission from waste
The estimation of the methane emission potential of a solid waste
disposal site (BECH4,SWDS,y, in tCO2e) was undertaken using the “Tool todetermine methane emissions avoided from dumping waste at a solid waste
disposal site”. The assumption taken in this study was that the amount ofwaste entering the landfill site in 2009 was 45,267 tons, the amount of waste
increase by 5% to 47,530 tons in 2010. The assumptions and detailcalculations are shown in Annex 2. This is conservatively estimated basedon the total amount of waste collected for disposal in 2008. The averagebaseline over the 10 years crediting period is 2,835 tCO2e per year, if thelandfill gas collection and destruction project starts in 2011-2020 (10 years
crediting period). The result of the analysis is illustrated in Figure 11.

Figure 1:Baseline emission from waste collected and disposed at landfillsite (tCO2e/year) during 2009-2010 only (2 years of waste only).
4.2 Greenhouse Gas emission from transportation
Transportation sector in Samui is dominated by motorcycle. This is
the most frequently used mode for both the residents and tourists. The total
GHG emission from this sector was calculated as shown in table 15.
However, the baseline for each project activity are different, depending on
the design of each project. Therefore, the emission reduction will becalculated based on the different baseline. The detail calculation andassumptions are shown in Annex 3.

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VehicleMotorcycle
Truck
Sedan (<7 seats)
Sedan (>7 seats)
Van (> 7 seats)

No.

Table 1: GHG emission from transport sector in Samui Island.

Fuel
Fuel
Fuel
Type of
GHG
Consumption
Consumption
Consumption
Fuelemissionrate (l/km)(l/year/vehicle))(l/year)used(tCO2e/year)
40,616
5.7
1,087.56
44,172,336.96 Gasoline
106,014
4,314
12.26
2,339.208
10,091,343.31
Diesel27,2473,549
10.8
2,060.64
7,313,211.36 Gasoline
17,552342
10.36
1,976.69
676,027.29 Gasoline
1,825
416
7.55
1,440.54
599,264.64
Diesel
1,618
Total GHG emission estimated for Samui Island
154,255
Sources and Assumptions• Number of Vehicles from Office of Transport, Samui Branch• Average distance assume from each vehicle travel a distance of 19,080 km (53km/day multiplied by 360 days). 53km is the distance of the road around Samui
Island.
• Fuel consumption rate, calculated average from http://www.environment.gov.au,and http://www.motorcyclefuelconsumption.com/• GHG Emission for petrol = 0.0024 tCO2e/l. fromhttp://oee.nrcan.gc.ca/publications/transportation/fuel-guide/2009/index.cfm• GHG Emission for diesel = 0.0027 tCO2e/l. from IPCC 2006

4.3 Greenhouse Gas emission from energy sector
Samui’s electricity demand was met by transmitting electricity fromthe national grid electricity via underwater cables from Suratthani Province.
Hence, GHG emission calculation is based on the national grid emission
factor for Thailand, which is 0.5812 tCO2e/MWh (TGO, 2010). In addition
if the renewable energy is generated from solar or wind, the grid emission
factor adopted for the calculation will be 0.598 tCO2e/MWh (TGO, 2010),
in accordance with “Tool to calculate the emission factor for an electricity
system” Version 2.
5.
POTENTIAL
PROJECTSGREENHOUSE GAS EMISSION

THAT

WOULD

REDUCEThe projects that are not feasible as CDM project activity, but are feasible asa CDM project may be develop without CDM but may consider otheralternatives such as verified emission reduction (VERs) under the voluntary
market instead.

Potential greenhouse
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Table 2: Potential emission reductions projects
Feasibility with CDM

Project

Yes

Waste Option 1: Landfill Recovery
9*(flare/electricity generation)
Waste Option 2:Methane Avoidance
9*(compost)
9
Transport Option 1: Replaced diesel fueltransportation vans with plant oil such as
jatropha. By replacing diesel with 10%
plant oil.
9
Transport Option 2: Replaced diesel fueltransportation vans with plant oil such as
jatropha. By replacing diesel with 100%plant oil.
9
Transport Option 3: Replaced diesel fueltransportation vans with 20% waste oil.
Transport Option 4: Replace transportation
van with electric/hybrid
9
Transport Option 5: Replace petrol
motorcycle with electric motorcycle.
Transport Option 6: Replace commercial
taxis with higher efficiency vehicles
Transport Option 7: Retrofit commercial
taxis with energy efficient equipment
Energy Option 1: Renewable energy
9**
power plant with less than 10 MW
installed capacity
Energy Option 2: The installation ofphotovoltaic at a group of hotels to replaceelectricity supply by the national grid.
Energy Option 3: The replacement ofenergy efficient air conditioners at groupof hotels and resorts on Samui Island.
9
Energy Option 4: The replacement ofenergy efficient equipments at a large
buildings on Samui Island. (assumed 15%
saving)
9
Energy Option 5: Adoption of selfballasted compact fluorescent lamps(CFLs) to replace incandescent lamps(ICLs) in residential applications.
* Without CDM project development cost** Electricity generation from renewable biomass

No

Feasibility without
CDM
Yes
No
9
9

9

9

9
9

9
9

9
9

9
9
9**

9

9

9

9
9

9

6. POTENTIAL GREENHOUSE GAS EMISSION REDUCTION
The potential range of greenhouse gas emission reduction is as shown intable 2. The maximum greenhouse gas emission reduction is 104,973
tCO2e/year if all the potential projects are carried out.

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Table 3: Potential Greenhouse Gas emission reduction
SectorSolid Waste
Transport
Renewable Energy
Energy Efficiency
Total

GHG Reduction (tCO2e/year)
2,414-21,633
28-68,875
255-2,571
23-11,894
2,720-104,973

REFERENCES
Department Environmental Quality Promotion (DEQP) 2006, “Green
Activity to promote environment, tourism and community involvement,
Samui Island Municipality, Suratthani Province” prepared by TESCO Co.,Ltd.
Hitchcock, M., King, V.T., Parnwell, M. 2008. Tourism in Southeast
Asia: challenges and new directions. NIAS Press, Copenhagen.
Green, R. 2005. Community perceptions of environmental and socialchange and tourism development on the island of Koh Samui, Thailand.
Journal of Environmental Psychology 25, 37–56
IPCC. 2007. Climate Change 2007: The Physical Science Basis.
Contribution of Working Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change [Solomon, S., D. Qin, M.
Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller(eds.)]. Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA.
PEA Samui office. 2009. Energy database for national energy analysis
and strategic planning, Suratthani province. Provincial Electricity
Generation.
Office of Transport. 2010 Office of Transport, Samui branch, Ministryof Transport.
Provincial Electricity Authority. 2010. Provincial Electricity Authority,
Samui Office.
Samui Municipality. 2010a. Samui Development Plan 2010-2012,
http://www.kohsamuicity.go.th/ [last accessed 24 November 2010]

Potential greenhouse
Potential
greenhouse gas
gas reduction
reduction in
in Samui
Samui towards
towards becoming
becoming carbon
carbonneutral
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Samui Municipality. 2010b. Waste data (primary data collection).
Samui Municipality, Suratthani province.
The Samui Green Island Project. 2010. The Green Island Project, Koh
Samui,
Thailand2010]

http://www.thegreenislandproject.org/ [last accessed 24 November

Wong, P.P. 1998. Coastal tourism development in Southeast Asia:
relevance and lessons for coastal zone management. Ocean & Coastal
Management 38, 89-109
TGO, 2010. The Study of emission factor for an electricity system inThailand 2009, Summary Report

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Using copper slang in cement concrete
Sudhir MISRA1 and Kunwar Krishna BAJPAI2
1
Professor, Department of Civil Engineering
sud@iitk.ac.in
2
Senior Scientific Officer, Department of Civil Engineering
Indian Institute of Technology Kanpur, India

ABSTRACTWith growing scarcity of natural raw materials, use of industrial wastes andby-products as substitutes is being actively investigated to promotesustainable construction. In this study, utilization of copper slag as analternative material for fine aggregates has been explored. Concrete mixes
with a target compressive strength of about 30MPa and slump in the rangeof 50-60 mm were prepared at different levels of replacement of fineaggregates (by copper slag). Properties related to the mechanical behavior
of concrete (compressive/flexural strength) and some others more related tolong term durability in terms of water absorption, and resistance to chloride
ion penetration, have been compared.
It was found that replacement of fine aggregates with copper slag to theextent of 50% does not result in any significant difference in the propertiesof the concrete. It was also found that given that the copper slag was about
40% heavier compared to the normally used fine aggregates, the density ofconcrete increases by about 6% at the level of 50% replacement, and about
15% at 100% replacement level. It was further found that even complete
replacement of fine aggregates does not adversely affect the flexuralstrength and resistance to chloride ion penetration of the concrete, though areduction in the compressive strength was found at replacement levels
higher than 50%.
Keywords: copper slag, density, concrete, compressive strength, flexuralstrength, durability, recycling

1. INTRODUCTION
A number of industrial waste products are produced in huge quantities eachyear, and their accumulation causes environmental problems. Some of theseproducts such as fly ash, ground granulated blast furnace slag, copper slag,
etc. are now being used to produce value added products. On the other hand,with rapid depletion in natural aggregates, the construction industry
worldwide is under pressure to explore the alternatives to the natural
aggregates, river sand, etc. In India about 6-6.5 million tonnes copper slag is
generated every year. Though there is not much evidence of pozzolonicactivity of copper slag, it can be used as partial/full replacement of fineaggregates (FA) as its particle size distribution can be easily matched with

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FA by suitable modification in the grinding process. In review articles(Bipra Gorai, R.K. Jana, and Premchand, 2003, Caijun Shia, et. al., 2008) on
characteristics and utilization of copper slag, it has been reported that
copper slag can be potential alternative to the admixtures used in concreteand mortars. An attempt has been made in this study to understand theeffect of replacement of FA by copper slag on properties of fresh andhardened concrete.

2. MATERIALS USED IN THE STUDY
2.1 Cement, aggregates, coarse sand, and copper slag
Locally available Ordinary Portland Cement (OPC) was used alongwith coarse aggregates and sand. Physical properties of OPC were
determined as per Indian Standard (IS) (IS 4031-1988 Reaffirmed 2005) andfound to be conforming to IS 8112-1989. Similarly properties of aggregatesused (sand and crushed granite aggregate) were found as per IS 2386-1963
Part I & III (Reaffirmed 2007) and found to be conforming to IS 383-1970(Reaffirmed 2002). It may be noted that properties of the copper slag were
determined in a manner similar to that used for fine aggregates, and theresults are compared in Table 1. It can be seen that the copper slag is muchheavier than the FA and has very little water absorption, whereas thefineness modulus is almost similar.
Table.1: Physical properties of fine aggregates and copper slag
Physical Property

Fine aggregates

Copper Slag

Fineness Modulus

2.95

2.87

Specific Gravity

2.61

3.68

Water Absorption (%)

0.42

0.06

2.2 Concrete mix proportions specimens used
Details of concrete mixes used having varying levels of copper slag
replacements (of the FA) are given in Table 2. The mixes were designatedas CS00, CS25, CS50, CS75 and CS100, respectively for 0%, 25%, 50%,
75% and 100% of the FA content replacement (by volume), the mix CS00
being a control mix (i.e. with no copper slag). For all mixes, the w/c ratio,
and the unit water, cement and the coarse aggregate content, were kept at
0.45, 153 kg, and 340 kg, and 1202kgs, respectively. In all mixes a superplasticizer was used to keep the slump in the required range of 40-65 mm(observed values also given in Table 2).

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Table 2: Details of concrete mix proportions
Concrete Mix

Fine
Aggregates

Copper Slag

Slump

Concrete mix
density

kg/m3

kg/m3

l/m3 (~%)

mm

kg/m3

CS 00

751

0

0

60

2452

CS 25

563

295

71.7 (25)

35

2562

CS 50

376

591

143.3 (50)

30

2646

CS 75

188

886

215.0 (75)

20

2707

CS 10001181

286.6 (100)

45

2793

3. EXPERIMENTAL DETAILS AND TEST DATA
3.1 Compressive and flexural strength
Cube specimens (150mm side) for compressive strength tests andbeam specimens (100 mm X 100 mm X 500 mm) for flexural strength tests
were used as per IS 516-1959 (Reaffirmed 2008) and the test data (averageof three specimens) are given in Table 3.
Table 3: Strength, density and water absorption of concrete at 28 days
Concrete
Mix

Compressive
strength(MPa)

Flexuralstrength(MPa)

Density(kg/m3)Water
absorption
(%)

CS 00

41.4

4.7

2305

3.6

CS 25

39.6

4.6

2379

3.2

CS 50

41.0

5.1

2436

3.7

CS 75

36.1

4.0

2566

3.4

CS 100

34.1

5.2

2603

3.0

3.2 Density and water absorption
Density and water absorption of hardened concrete have beenmeasured using cylindrical specimens (diameter: 100 mm; length: 200 mm)
as per ASTM C642-06 and the observed results have been given in Table 3.
3.4 Rapid chloride ion penetrability tests
The ASTM C1202-10 was used to measure the penetrability ofchloride ions using concrete discs of diameter 95 mm and thickness 50 mm,
at about 28 days and the average (of three specimens) values (Coulombs)
are given in Table 4.

Using copper
Using
copper slag
slanginincement
cementconcrete
concrete5213

October
Mai,Thailand
Thailand
October 2011,2011, Chiang
Chiangmai,

Table 4: Chloride Ion Penetrability Test Data (at 28 days)
Concrete
Mix

Total Charge passed in
6 hours (Coulombs)

Chloride Ion
Penetrability

CS 00

1571

Low

CS 25

1602

Low

CS 50

1111

Low

CS 75

1335

Low

CS 100940

Very Low

4. RESULTS AND DISCUSSIONS
4.1 Density of copper slag based concrete mixes
From simply the mix proportions an increase in the mass per cubic meter ofconcrete mix was found to be about 17.5% with respect to control mix on
account of the higher specific gravity of the copper slag (3.68 compared to2.61 of fine aggregates). This data is compared with the density obtained inaccordance with the ASTM C642-06 and plotted in Figure 1. It can be seenthat the observed values also show the expected increase, and the increase isabout 13% in CS 100.

CS 100
CS 75
CS 50
CS 25
CS 00

Figure 1: Density increase with copper slag content
4.2 Compressive and flexural strength
A diagrammatic representation of the variation of the compressive andflexural strengths (28 days) with respect to the replacement level of FA bycopper slag is shown in Figures 2 and 3. As can be seen from Figure 2, the28 days compressive strength of copper slag based concrete having up to
50% replacement is comparable with the control mix, at levels of 75% and100% replacement, a significant decrease (12.8% to 17.6%) in compressive
strength is observed. This suggests that whereas for up to 50% replacement

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of fineof fineaggregatesaggregateswithwithcoppercopperslagslagthe theconcreteconcrete
mixes
mixes
maymaybe bepreparedprepared
withwith‘normal’‘normal’mixmixdesigndesignconsiderations,considerations,higherhigherlevelslevelsof ofreplacement,
replacement,
additional
additional
carecareshouldshouldbe taken.
be taken.
As As
far faras flexural
as flexuralstrength
strength
is concerned,
is concerned,
it wasit wasfound
found
thatthat
replacement
replacement
of FA
of FA
by by
coppercopperslagslageven
even
to theto theextentextentof fullof full
replacement
replacement
doesdoes
not not
adversely
adversely
affectaffectit. Itit.may
It mayalsoalso
be pointed
be pointed
out out
thatthatfor forall concrete
all concrete
mixes,
mixes,
the themeasuredmeasuredvaluesvaluesare arehigherhigherthanthan
those
those
estimated
estimated(3.8(3.8
MPa)
MPa)in accordancein accordance
withwith
IS 456:2000.
IS 456:2000.
In fact,
In fact,
thisthis
level
level
of theof theflexuralflexuralstrength
strengthis alsois alsomarkedmarkedin in
3 forreference.
FigureFigure3 forreference.

3.8 MPa
3.8 MPa

FigureFigure2: Compressive
2: Compressive
Strength
Strength(28(28days)
days)
FigureFigure3: Flexural
3: Flexural
Strength
Strength(28(28days)
days)
4.3 4.3
Water
Water
absorption
absorption
by hardenedby hardened
concreteconcrete
Water
Water
absorption
absorption
by byhardened
hardened
concreteconcretehashas
often
often
been
been
suggestedsuggested
as assimplesimplemeasuremeasureof theof theporosity
porosityof theof thematrixmatrixandandtherefore
therefore
the thedurability
durabilityof ofthe theconcrete.
concrete.
Measurement
Measurementin accordancein accordance
withwith
ASTM
ASTM
C642-06,
C642-06,
shows
shows
thatthat
the theabsorption
absorption
for forthe thecontrol
control
mixmixis 3.6%is 3.6%andandthatthatfor forthe theother
otherconcretes
concretes
variesvariesbetweenbetween
3.0 3.0
andand3.7%
3.7%
for forthe thedifferent
different
levelslevelsof replacement.
of replacement.
TheThedatadata
collected
collected
in thisin thisstudy
study
is notis notsufficientsufficient
to determine
to determine
a definite
a definite
trend
trend
withwith
respect
respect
to theto thereplacement
replacementlevels,levels,it canit canbe stated
be stated
thatthatno increaseno increasein thein theabsorption
absorption
waswas
found
found
upon
upon
replacing
replacing
FA FA
withwithcoppercopper
slag.
slag.
water
water
4.4 4.4
ResistanceResistanceto chloride
to chloride
ionionpenetration
penetration
TheTheRapid
Rapid
Chloride
Chloride
IonIonPenetration
Penetration
ResistanceResistance
TestTest
(ASTM
(ASTM
C1202C120210)10)
is anotheris anothertesttest
for fora quicka quick
evaluation
evaluationof durabilityof durabilityof concrete.
of concrete.
A bar
A bar
graph
graph
showing
showing
the theresults
results
obtained
obtainedis shown
is shown
in Figurein Figure
4. It4.can
It canbe seenbe seenthatthat
the theresistanceresistanceto chloride
to chloride
ion ionpenetration
penetration
for formost
mostof theof theconcreteconcrete
mixes
mixes
fallsfalls
withinwithinthe theLowLow
penetration
penetration
zone.
zone.
A closerA closerexamination
examinationof theof thedatadata
collected
collected
reveals
reveals
thatthatthoughthoughat 25%
at 25%
replacement
replacement
level
level
the the
RCPT
RCPT
value
value
(Coulombs)(Coulombs)
is similar
is similar
to thatto thatof control
of control
furtherfurther
replacement
replacement
clearly
clearly
lowerslowersthe thechloridechloride
penetrability.
penetrability.
More
More
concrete,concrete,
experiments
experiments
are arehowever,
however,required
requiredto toestablish
establish
a morea morequantitative
quantitative
relationshiprelationshipbetweenbetweenthe thelevel
level
of replacementof replacement
andandthe theresistanceresistanceto chloride
to chloride
penetration.
penetration.

Using
copperslagslagin cement
concreteUsing
copperinincement
concreteUsing
copperslang
cementconcrete55235

October
Mai,Thailand
Thailand
October 2011,2011, Chiang
Chiangmai,

Figure 4: Resistance to chloride ion penetration (ASTM 1202)

5. CONCLUDING REMARKS
Based on tests carried out to better understand the effect of replacing
naturally occurring sand (fine aggregates) to different extents by copper slag,
which is by-product of the copper manufacturing process, the following can
be stated as some of the salient findings.
1) Addition of copper slag does not make the concrete ‘unworkable’,and target values of slump can still be achieved with a suitableadjustment in the superplasticizer dosage.
2) The density of concrete is higher on account of the use of theheavier copper slag (replacing FA).
3) The compressive strength observed at 28days shows that the values
are comparable with up to 50% replacement of FA, though somedecrease is seen at higher replacement levels.
4) The flexural strength is not adversely affected by the replacementof FA by copper slag, and all values are found to be higher than theestimated by IS 456 (based on the actual compressive strength).
5) Water absorption of concrete with copper slag is comparable to thatof control concrete and the values tend to be slightly lower at very
high replacements. A similar trend is observed for resistance tochloride ions based on the results of the Rapid Chloride Penetration
Test (where all concretes fall in the ‘LOW’ to ‘VERY LOW’classification as per ASTM 1202.
ACKNOWLEDGEMENT
Funding for carrying out the work and the copper slag used in the present
study was provided by M/s Sterlite Industries (India), Limited, Tuticorin.
Special mention should be made of Mr. Lovish Ahuja, Manager & Head,
Environment, Sterlite Industries (India), Limited for his participation in thework. Help from Mr. Pankaj K. Gupta (Jr. Technical Superintendent) of6
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Structural Engineering Laboratory, Department of Civil Engineering, IIT
Kanpur, in terms of technical support, is also gratefully acknowledged.

REFERENCES
Bipra Gorai, R.K. Jana, and Premchand, 2003, “Characteristics andUtilisation of Copper Slag: A Review” Elsevier J. Resources, Conservation
and Recycling, 39, 299-313.
Caijun Shia, Christian Meyer, and Ali Behnood, 2008, “Review:
Utilization of Copper Slag in Cement and Concrete”, Elsevier J. Resources,
Conservation and Recycling, 52, 1115-1120.
Indian Standard IS 4031-1988 (Reaffirmed 2005), “ Methods ofphysical tests for hydraulic cement”
Indian Standard IS 8112-1989, “Specification for 43 grade ordinary
Portland cement”
Indian Standard IS 2386-1963 Part I & III (Reaffirmed 2007),“Methods of test for aggregates for concrete”
Indian Standard IS 383-1970 (Reaffirmed 2002). “Specification forcoarse and fine aggregates from natural sources for concrete”
Indian Standard IS:516-1959 (Reaffirmed 2004), “Methods of tests
for strength of concrete”
ASTM C-642-06, “Standard Test Methods for density, absorption,and voids in hardened concrete”
ASTM C-1202-10, “Standard test method for electrical indication of
concrete’s ability to resist chloride ion penetration”
Indian Standard IS:456-2000 (Reaffirmed 2005), “Plain andreinforced concrete - Code of practice (Fourth Revision)”

Using copper
Using
copper slag
slanginincement
cementconcrete
concrete

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526

New Technologies for Urban Safety of Mega Cities in Asia

Role of coarse aggregate in a cement-basedmaterial with strain-hardening subjected tostress-field rotation
Kohei NAGAI1, Benny SURYANTO2, and Koichi MAEKAWA3
Associate Professor, ICUS, IIS, The University of Tokyo, Japannagai325@iis.u-tokyo.ac.jp
2
Postdoctoral Fellow, Department of Civil Eng.,The University of Tokyo, Japan
3
Professor, Department of Civil Engineering,
The University of Tokyo, Japan

1

ABSTRACT
Strain Hardening Cementitious Composite (SHCC) is a cement-based
composite that when pulled exhibits multiple-fine cracks and pseudo-strain
hardening response. A new testing method was developed to reproduce
possible rotation of principal stress axes during the material strainhardening. Thus, not only tensile stresses, but also must shear stresses betransmitted across the cracks. Using this proposed testing method, twentythree SHCC plates were tested. Of the twenty-three plates, four plates weremade of plain PVA-ECC (a SHCC available in Japan), while the other 19
plates were constructed by adding coarse aggregate in the volume fractionsof 5% to 20%. From the plates made of plain PVA-ECC, it was observedthat rotation of principal stress lowered the strength and ductility, andalways resulted in an orthogonal cracking pattern. From the plates
containing aggregate, it was observed that, if no stress rotation took place,the plate load capacity decreased by 20% to 40%, while the plate ductility
was reduced to approximately one half. If stress rotation occurred, the load
capacity and ductility were within 80% to 120% of the plates experiencing
no principal stress orientation change. The aggregate addition of 10% to12.5% showed a better ability to control the orientation of secondary cracks.
Keywords: SHCC, principal stress rotation, shear transfer, multiple cracks,
coarse aggregate
1. INTRODUCTION
In reinforced concrete highway bridge deck structures, wheel movement has
been frequently observed to be the primary source of fatigue damage(Maeda and Matsui, 1984, Perdikaris and Beim, 1988). The wheel
movement causes continual changes of concrete principal stress magnitudeand continuous rotation of principal stress field at different locations on thedeck (Maekawa et al, 2006 and Fujiyama et al, 2007). Due to the stress fieldrotation, in particular, cracks once formed at a certain orientation at various

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Mai,Thailand
Thailand
Chiangmai,

locations on the deck will repeatedly open, slip, and close. It is essential toprovide the necessary stress transfer ability to accommodate such repeatedcrack deformations for longer deck serviceability.
To apply SHCC for deck-type structures, it is essential to test thematerial performance to loading histories in which principal stress directions
do rotate. It is, therefore, anticipated that the crack resistance to shear is as
important as its resistance to tension. Nevertheless, cracked SHCC
demonstrated strong anisotropic responses when subjected to principal
stress rotation due to crack opening and slip (Suryanto et al, 2010). To limit
this slip, extra load-carrying mechanism should be provided in addition tofiber bridging that is more effective for resisting crack from further opening.
This study investigates the effectiveness of coarse aggregate as ameans of shear carrying mechanism in SHCC. Coarse aggregate isconsidered since it is widely available and comparatively cheap, although its
addition would also elevate the toughness of the SHCC matrix and hence
lower its ductility. Hence this study attempts to investigate the trade off
between shear transfer improvement and tensile ductility loss. The effect ofdifferent coarse aggregate volume fractions is prompted.
2. EXPERIMENTAL PROGRAM
The experimental program involved the testing of 15 control plates (Plates
PC) and 8 main plates (Plates PM). The dimension of the control plates was
400×250×20 mm, while that of the main plates was 550×420×20 mm. The
main variable in the test program was the amount of coarse aggregate,
ranging from 0% to 20% by volume.
The material properties of each aggregate volume fraction were
determined from three 100×200 mm standard cylinders (Specimen MC),
three 100×100×400 mm prisms (Specimen MP), and five dog-bone
specimens (Specimen MT, but only applicable to the original mixture withno coarse aggregate). Specimen MT had a constant 80-mm long testing zone,
with a width and thickness of 30 mm and 13 mm, respectively. Both MC
cylinders and MT samples were tested at 28 days, while specimens MP were
tested between 28 and 34 days. All tests were performed in accordance with
the JSCE recommendations (JSCE, 2007).

2
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MainMain
Test Test
Specimens
Specimens

Additional
Additional
Test Test
Specimens
Specimens
13

Plate-Control
Plate-Control(PC) Specimen(PC) Specimen

13

100×100×400
100×100×400

85

85

PrismPrism(MP) (MP)Specimen
Specimen

40

40

30 80

80

40

40

85

85

250×400×20
250×400×20

30
200 200

410×550×20
410×550×20

100 100

60

60

CylinderCylinder(MC)(MC)Specimen
SpecimenCoupon Coupon(MT) Specimen(MT) Specimen

Plate-Main
Plate-Main(PM) (PM)Specimen
Specimen

FigureFigure1: Details
1: Detailsof testofspecimens
test specimens
2.1 SHCCC
2.1 SHCCC
Material:
Material:
PVA-ECC
PVA-ECC
The material
The material
investigatedinvestigatedis a mix
is a ofmixPVA-ECC
of PVA-ECC
and typical-crushed
and typical-crushedtype,type,coarsecoarseaggregate
aggregateavailable
available
in Japanesein Japanesemarket.
market.
TableTable
3 lists
3 lists
the mix
the mix
proportion
proportionof theof ECCthe ECCand andthe original
the original
sievesieve
analysisanalysisof theof coarse
the coarse
aggregate.
aggregate.
Considering
Considering
the thickness
the thicknessof testof plates,
test plates,
the aggregate
the aggregate
size larger
size larger
than than
9.5 mm
9.5 wasmm omitted.
was omitted.
PriorPrior
to casting,to casting,the aggregate
the aggregate
was cleaned
was cleaned
and andkept kept
in a saturated
in a saturated
surfacesurfacedry condition.
dry condition.
2.2 Preparation
2.2 Preparationof Testof TestSpecimens
Specimens
The mixing
The mixing
and casting
and castingof theofspecimens
the specimens
werewere
all doneall doneat theatKajima
the Kajima
ResearchResearch
Institute,
Institute,Japan.
Japan.
The Themixingmixingof theof ECCthe ECC
followedfollowed
the JSCE
the JSCE
guideline
guideline(JSCE,(JSCE,
2007).
2007).
AfterAfterthe material
the material
beingbeing
well well
mixed,
mixed,
coarsecoarseaggregate
aggregate
was added
was added
to thetoslurry
the slurry
and they
and they
werewerethen thenremixedremixedfor aboutfor about
two twominutes.
minutes.
TableTable
4 summarizes
4 summarizes
the fresh
the fresh
properties
propertiesof theof ECCthe ECC
beforebeforeand andafter after
addition
additionof coarseof coarse
aggregate.
aggregate.
AfterAftercasting,
casting,
all plates
all plates
werewerecoveredcoveredwith witha plastica plastic
sheetsheet
and anddemoldeddemolded
after after
one day.
one day.
Afterwards,
Afterwards,
the plates
the plates
werewerewrappedwrappedwith with
wet wetburlapburlapand plastic
and plastic
sheets.
sheets.
AfterAftera fewa few
days,days,
they they
wereweredelivereddeliveredto theto theConcrete
Concrete
Laboratory,
Laboratory,
University
Universityof Tokyo,of Tokyo,and stored
and stored
in aninambient
an ambient
roomroomwith with
60% 60%relative
relative
humidity
humidity
and aandtemperaturea temperatureof 20°Cof 20°C
until until
the test
the date.
test date.
The Thesurfacesurfaceof theof plates
the plates
that hadthat been
had beenat theat bottom
the bottom
duringduringcasting
casting
was wasremarkably
remarkablysmoothsmoothand flat,
and whileflat, while
the upper
the upper
finishingfinishingsurfacesurfacewas uneven.
was uneven.
As a As
result,a result,
the thickness
the thicknessof theofplates
the plates
variedvariedin theinorderthe orderof 1 mm.
of 1 mm.
TableTable
1: Specimen
1: Specimen
numbers
numbers
for eachfor each
specimen
specimentype typeSpecimen
Specimen
Type TypeID ID 0
Plate-Control
Plate-Control
PC PC 3
Plate-Main-45deg
Plate-Main-45deg
PM45PM45
1
Material-Prism
Material-Prism
MP MP 3
Material-Cylinder
Material-Cylinder
MC MC 9Material-Coupon
Material-Coupon
MT MT 15

0 5
3 2
1 1
3 3
9 3
15-

Aggregate
Aggregate
VolumeVolumeContent
Content(%) (%)
5 7.5 7.510 1012.5 12.5
15 1520
2 2
2 2
2 2
2 2
2 2
1 1
1 1
1 2
2 1
1 1
3 3
3 3
3 3
3 3
3 3
3 3
3 3
3 3
3 3
3 3
- - - - - -

20
2
1
3
3
-

Role of coarse aggregate in a cement-based material with
Role ofcoarseaggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-fieldrotationRoleof coarse
aggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-fieldrotation
3 5293strain-hardening subjected to stress-field rotation

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table 2: Mix proportion of ECC (JSCE, 2007) and sieve analysis of
aggregate

Coarse Aggregate
Sieve
Cumulative Passing
size
(%)
(mm)
13.2
95
42.2
350
70
2.0
4.75
5.7
Note: W: water, C: ordinary portland cement, FA: fly ash, and S: sand
PVA fibers: diameter 0.04 mm, length 12 mm, tensile strength 1,600 MPa.
W / (C+FA)
(%)

Case
1
2
3
4
5
6
7

PVA-ECCWater
S / (C+FA)
(%)
3
kg/m

Aggregate
volume
(%)
0
5
7.5
10
12.5
15
20

PVA fibers(%), byVol.

Table 3: Fresh property of PVA-ECC

Slump flow
before adding
aggregate(mm×mm)510×495
495×485
500×500
515×505505×505
485×470
480×480

Air
Content
(%)
12.5
11.5
12.0
11.1
11.7
10.6
9.5

Slump flow
after adding
Aggregate(mm×mm)−455×440430×420405×390
380×380
340×330320×310Density

Slump
loss

(kg/m3)
1,804
1,822
1,851
1,881
1,879
1,914
1,966

(mm)
−
−
−
−
−
16.5
16.0

2.3 Testing Procedure
Figure 2(a) shows the layout of test plates, while Figure 2(b) shows
the testing procedure adopted in the experiment. For the control plates, afour-point bending test was performed. For the main plates, pre-cracks werefirst introduced by performing bending test (Step A). The plate was thenunloaded when the strain at the plate soffit reached a value of 40% of εtu.
After fully unloaded, the plate was reversed upside-down (Step B), further
loaded in bending (Step C), and again unloaded (Step D). Steps B to D werecarried out to flatten the plate. The plate was then cut (Step E) in order toalter the angle of the pre-cracks to a certain angle. Finally, the cut plate wasre-tested in four-point bending (Step G).

(a)

(b)

Figure 2: (a) Details of test plates, and (b) Testing Procedure

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2.4 Material
2.4 Material
Test Results
Test Results
TableTable
4 summarizes
4 summarizes
the average
the averagetensiletensileproperties
properties
from fromfive dog-bone
five dog-bone
coupons,
coupons,
whilewhile
FigureFigure3(a) and3(a) (b)andcompare(b) compare
the average
the average
flexuralflexuraltensiletensile
strengths
strengths
and andcompressive
compressive
strength
strengthwith withdifferent
different
aggregate
aggregate
volumevolumefractionsfractionsobtained
obtainedfrom fromthree three
representative
representative
specimens.
specimens.
It appears
It appears
that asthat
theas theaggregate
aggregate
volumevolumefraction
fractionis increased,
is increased,
the tensile
the tensile
strength
strengthdecreases,
decreases,
whilewhile
the compressive
the compressive
strength
strengthincreases.
increases.
TableTable
4: Results
4: Resultsof tensileof tensile
tests tests

Aggregate
Aggregate
VolumeVolume(%) (%)

Ultimate
Ultimate
TensileTensile
StrainStrain(%) (%)
3.26(0.3)
3.26(0.3)

Compressive Strength (MPa)Compressive Strength (MPa)

Flexural Tensile Strength (MPa)

Flexural Tensile Strength (MPa)Age AgeCracking
Cracking
TensileTensileYield Strength
Yield Strength
StressStress (JSCE(JSCE2007) 2007)
Specimen
Specimen(days) (days)(MPa)(MPa) (MPa)(MPa)MT-1-5MT-1-5 28
28 2.16(0.2)
2.16(0.2)2.99(0.3)
2.99(0.3)
Note: Values
Note: Values
in the bracket
in the bracket
are theare
COV
the inCOV% in %

Aggregate
Aggregate
VolumeVolume(%) (%)(a) (a)(b) (b)FigureFigure3: Results
3: Resultsof bendingof bending
and compression
and compression
tests tests

3. EXPERIMENTAL
3. EXPERIMENTAL
RESULTSRESULTS
Test Testhistoryhistory
in terms
in terms
of appliedof applied
load load
versusversus
midspanmidspandeflection
deflectionof theof thecontrol
controland mainand mainplatesplates
are shownare shownin Figures
in Figures
4 and45,andwhile
5, while
FigureFigure
6 shows
6 shows
the normalized
the normalized
plate plateload capacity
load capacityand ductility
and ductility
experiencing
experiencing
principal
principal
stressstressrotationrotationto thetocorresponding
the corresponding
control
control
platesplates
experiencing
experiencing
no principal
no principal
stressstressrotationrotationfor different
for different
aggregate
aggregate
volumevolumefractions.
fractions.
FromFrom
FiguresFigures
4 and46,and
it is6,clear
it is clearthat thethataddition
the additionof coarseof coarse
aggregate
aggregate
alwaysalwaysresulted
resulted
in lowerin lowerplate plateductility.
ductility.
The ductility
The ductilityof control
of control
platesplateswith withcoarsecoarse
aggregate
aggregate
was ofwasapproximatelyof approximately
one half
one ofhalf
theofplates
the plates
mademadeof theof theoriginal
original
mixturemixture(no coarse(no coarse
aggregate)
aggregate)
and appeared
and appeared
to vary
to vary
more more
greatly,greatly,
rangingrangingfrom fromapproximately
approximately
5 mm5 tomm
10tomm.
10 Theremm. There
was nowasclearno cleartendency
tendency
how thehowplate
the plateductility
ductilitychangedchangedwith increasing
with increasing
aggregate
aggregate
volumevolumefractions.
fractions.
This reducedThis reduced
plate plateductility
ductility
was consistently
was consistently
observed
observed
whenwhenprincipal
principal
stressstressdirection
direction
did not
did change.
not change.
On theOn otherthe otherhand,hand,whenwhenrotationrotationof principal
of principal
stressstressoccurredoccurred(see Figures(see Figures
5 and56),
andductility6), ductilityof platesof plateswith nowithaggregatesno aggregatesdecreased
decreasedby approximately
by approximately
20%, 20%,
whilewhileplatesplateswith withaggregate
aggregate
exhibitexhibitcomparable
comparable
ductility
ductility
valuesvalues
to theto corresponding
the corresponding
platesplates
subjected
subjected
to noto nostressstressrotation.
rotation.
Role of coarse aggregate in a cement-based material with
Role ofcoarseaggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-fieldrotationRoleof coarse
aggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-fieldrotation
5 5315strain-hardening subjected to stress-field rotation

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Regarding the plate load capacity, it is observed that the addition ofcoarse aggregate also always resulted in lower plate strength. As can beclearly seen in Fig. 6, the reduction in strength was approximately 20% to40%. The reduction appears to increase as aggregate volume fraction also
increases. These all phenomena occurred when no principal stress rotation
took place. If rotation of principal stress direction occurred (such as in themain plates), the load capacity was within 80% to 125% of thecorresponding control plates, indicating that the presence of coarse
aggregate has a positive effect under such loading conditions. Figures 4 and6(a) explain better this observed phenomenon.

170
PC1
PC2
PC3
PC3

340
without aggregatewith aggregate
PC3

20±1
in mm

PC3

VAgg.: 5%

VAgg.: 7.5%

VAgg.: 10%

PC3

PC3

PC3

VAgg.: 12.5%

VAgg.: 15%

VAgg.: 20%

Figure 4: Response of control plates containing various amounts of coarse
aggregate subjected to a fixed direction of principal stress field

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VAgg.: V
5%
Agg.: 5%

VAgg.: V
7.5%
Agg.: 7.5%

VAgg.: V
10%
Agg.: 10%

VAgg.: V
12.5%
Agg.: 12.5%

15%
VAgg.: V
Agg.: 15%

VAgg.: V
20%
Agg.: 20%

FigureFigure
5: Comparison
5: Comparisonof responsesof responsesof control
of control
plates plates(no stress(no rotation)
stress rotation)
and andmain plates
main plates(principal(principal
stress rotated)
stress rotated)
for PVA-ECC
for PVA-ECC
plates plates
containing
containingcoarsecoarse
aggregate
aggregate
Main plate,
Main
experienced
plate, experienced
45o
45o
rotation ofrotationstress axisof stress axis

Control plate,
Control
experiencing
plate, experiencing
no stress norotationstress rotation

FigureFigure
6: Normalized
6: Normalized
plate load
platecapacity
load capacityand ductility
and ductility
for plates
for plateswith withdifferent
different
volumevolume
fractionsfractionsof coarseof coarse
aggregate
aggregate
FigureFigure
7 shows
7 shows
the comparison
the comparisonof the ofobserved
the observed
cracking
cracking
patternpatternofofselected
selectedmain plates.
main plates.
The cracking
The cracking
patternpatternshownshown
was obtained
was obtained
from thefrom the170-mm
170-mmlong bottom
long bottom
plate surface
plate surface
after testing.
after testing.
In all In
platesall plates
tested,tested,a bi- a bidirectional
directional
cracking
cracking
patternpattern
was observed,
was observed,
consisting
consistingpre- andpre-secondaryand secondary
cracks.cracks.
The pre-cracks
The pre-cracks
formedformed
orthogonal
orthogonal
to principal
to principal
stress stressdirection
direction
duringduring
pre-cracking,pre-cracking,while while
the secondary
the secondary
crackscracks
formedformed
betweenbetweenPlane Plane
NP NP(orthogonal(orthogonal
to the topre-cracks)
the pre-cracks)and Plane
and Plane
P (orthogonal
P (orthogonal
to principal
to principal
stress stressdirection
direction
duringduring
re-testing).
re-testing).
Ideally,Ideally,
secondarysecondarycrackscracks
would would
form parallel
form paralleltotoPlane Plane
P whenP whenthe pre-cracks
the pre-cracks
can transmit
can transmit
sufficientsufficientstressesstressesacross acrosstheir theirplanesplanes
and undergo
and undergo
limitedlimited
crack opening
crack opening
and slip.
and slip.
It appears
It appears
from Figure
from Figure
7 that 7thethatorientation
the orientationof the ofsecondary
the secondary
crackscracks
can becan
relatedbe relatedwith thewith
added
the added
amountamountof coarseof coarse
aggregate.
aggregate.
As theAs
aggregate
the aggregate
volumevolume
fraction
fractionincreases,
increases,
the inclination
the inclinationof the ofsecondary
the secondary
crackscracks
gradually
graduallychangeschangesfrom nearfromorthogonalnear orthogonal
to the pre-crack
to the pre-crack
plane (Plane
plane (PlaneNP) atNP)
aggregate
at aggregate
volumevolume
fraction
fractionof 0%ofto 0%
the tonear
theideal
near orientation
ideal orientation(Plane(PlaneP) at aggregateP) at aggregate
volumevolume
fractionsfractionsof approximatelyof approximately
10% to10%
12.5%.
to 12.5%.
This indicates
This indicates
the thepositive
positive
contribution
contributionof coarseof coarse
aggregate
aggregate
to improveto improve
the resistancethe resistanceof crackof crack
Role of coarse aggregate in a cement-based material with
Role ofRolecoarseaggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-fieldrotationrotationof coarse
aggregate
in a cement-basedmaterial
with strain-hardening
subjected
to stress-field
7 5337strain-hardening subjected to stress-field rotation

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

to transmit stresses across their planes. With increasing aggregate volume
fractions, however, the orientation of secondary cracks gradually returns
back again to Plane NP. This means that further improvement of stresstransfer cannot be expected solely by more aggregate amounts, provided
that sufficient tensile stress resistance must also exist across cracks.
Principal stress direction
during re-testing[see Step G in Fig. 2(b)]a)

Plane NP
Unwanted orientationof secondary crack
Possible orientation of
secondary crack,
depending on stress transfer
across the pre-cracks

Plane P

Preferred secondary crackorientation

Vagg = 0%

Principal stressdirection
during pre-cracking[see Step A in Fig.

c)b)

Vagg = 7.5%

Vagg = 5%d)e)Vagg = 10%f)Pre-crackorthogonal to

Vagg = 12.5%

g)

10%

Vagg = 15%
Figure 7: Cracking pattern of test plates

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4. CONCLUSIONS
1. Cracked PVA-ECC exhibits degraded performance when subjected to arotation of stress field as a result of shear that must develop at cracks in the
ECC. The material exhibited limited shear transfer, as marked by a nearly
orthogonal cracking pattern.
2. When there was no rotation of principal stress field, the addition of coarse
aggregate always resulted in lower plate load capacity and ductility. Whensubjected to stress rotation, however, the aggregate addition resulted incomparable plate strength and ductility, indicating that the stabilizing effectsof the aggregate on the post-cracking performance of the material.
3. The addition of coarse aggregate in the volume fraction of 10% to 12.5%
is more viable to control the orientation of secondary cracks for following
the latest principal tensile stress direction.
REFERENCES
Fujiyama, C., Gebreyouhannes, E., Chijiwa, N., and Maekawa, K.,
2007. Numerical analysis of various factors on fatigue life for slab undermoving load. Proceedings of the Japan Concrete Institute 29(3), 727-732.
(in Japanese)
JSCE, 2007. Recommendations for design and construction of
HPFRCC with multiple fine cracks. Concrete Library 127, 129-135. (inJapanese)
Maekawa, K., Gebreyouhannes, E., Mishima, T., and An, X., 2006.
Three-Dimensional Fatigue Simulation of RC Slabs under Traveling WheelType Loads. Journal of Advanced Concrete Technology 4(3), 445-457.
Maeda, Y., and Matsui, S., 1984. Fatigue of reinforced concrete slabs
under trucking wheel load. Proceeding of Japan Concrete Institute 6, 221224.
Perdikaris, P. C., and Beim, S. R., 1988. RC bridge decks underpulsating and moving load. Journal of Structural Engineering ASCE 114(3),591-607.
Suryanto, B., Nagai, K., and Maekawa, K., 2010. Bidirectional
multiple cracking tests on High Performance Cementitious Composite plates.
ACI Materials Journal 107(5), 450-460.
JSCE, 2007. Recommendations for design and construction of
HPFRCC with multiple fine cracks. Concrete Library 127, 129-135. (inJapanese)

Role of coarse aggregate in a cement-based material with
Role of coarse aggregate in a cement-based material with strain-hardening subjected to stress-field rotation
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536

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Effect of bottom ash and mineraladmixtures on the curing sensitivityof concrete
Kinaanath Hussain1, Pongsak Choktaweekarn2, Warangkana Saengsoy2
Somnuk Tangtermsirikul3
1
Graduate student, School of Civil Engineering Technology, Sirindhorn
International Institute of Technology, Thammasat University, Thailand
2
Researcher, Construction and Maintenance Technology Research Center(CONTEC), Sirindhorn International Institute of Technology (SIIT), Thammasat
University, Thailand
3
Professor, School of Civil Engineering Technology, Sirindhorn International
Institute of Technology (SIIT), Thammasat University, Thailand
Tel. 02-986-9009 ext 3002, Fax 02-986-9009 ext 3001, E-mail:kinaanath@gmail.com

ABSTRACTIn this paper, curing sensitivity of concrete with bottom ash and multiple binders
was studied. Bottom ash was used as an internal curing agent and a partial
substitution of fine aggregate. Curing sensitivity index was calculated byconsidering compressive strength as an indicator. Two series of concrete with waterto binder ratios by weight (w/b) of 0.35 and 0.55 were produced for testing
compressive strength. The specimens were subjected to two curing conditions
which are continuously water-cured and continuously air-cured. The curing
sensitivity of multiple binder concrete with fly ash and limestone powder (LP) as
cement replacing materials, and with bottom ash as sand replacement wasinvestigated. It was found that for the mixes without bottom ash, the use of fly ash
increased curing sensitivity while LP reduced curing sensitivity of concrete. It wasalso found that the use of bottom ash in concrete reduced the curing sensitivity
especially at low w/b ratio. Autogenous shrinkage, total shrinkage and crack widthof cement-only and cement-limestone powder concrete without bottom ash andcement-only concrete with bottom ash were also investigated. It was found thatbottom ash and LP mixtures reduced shrinkage of concrete. It was also found thatbottom ash and LP mixtures reduced crack width of concrete. From the test resultsof compressive strength, curing sensitivity and shrinkage, bottom ash was proved to
be one of the effective internal curing agents.
Key words: internal curing, bottom ash, fly ash, limestone powder, shrinkage
1. INTRODUCTION
In many cities, the development of durable infrastructure system is of great
importance. Concrete is widely used in the construction of concrete structures. Oneof the important problems of concrete is curing. Appropriate curing gives good537

October
2011,
Chiang
Mai,Mai,
Thailand
October
2011,
ChiangThailandstrength development, low shrinkage, no crack and longer service life with a more
durable structure.
In current practice, effective curing of concrete is a difficult task especially in a hot
country like Thailand. Due to inefficient curing, concrete has low strength
development and durability problems. Aitcin et al. (1997) found 17–22% reduction
in compressive strengths of air-cured concrete when compared to the moist-cured
one. Although engineers know the benefits of good curing, however, good curing
practices are not always implemented. For structures having large exposed surfaces
or mass concrete and for high elevation vertical concrete walls, curing process is atremendous task. With poor curing conditions, the problems caused on mechanicaland durability properties especially for shrinkage of concrete cannot be avoided.
Recently, water-retaining materials or specific porous materials such as polymer
and lightweight aggregate have been studied for being used in concrete for internal
curing purpose. Internal curing is the curing of concrete from inside with the helpof an internal curing agent. The water retained in these materials provides
supplementary water in addition to the originally mixing water for the hydration
reaction process. The extra water is gradually consumed in the hydration reaction sothat it prolongs the hydration reaction progress and reduces shrinkage. It wasreported that internal curing helped in avoiding internal micro cracking which mightoccur in low w/b concrete due to autogenous shrinkage (Lura et al. 2007).
Bottom ash is a porous material (see Figure 1) which has high water retainability so
it is possible to be used in concrete as an internal curing material and has highpotential in real practice.
Bottom ash is a waste material from coal power plants. A large amount of the
produced bottom ash is dumped or used as a land-fill material. These practices
cause some expense for disposing and may cause some environmental problems. As
a result, a beneficial way in points of view of economic and environment is toutilize the bottom ash in concrete.
Some previous researches have shown
improvement on compressive strength with bottom ash replacement up to 10% offine aggregate (Kasemchaisiri and Tangtermsirikul, 2007; Kuram and Kaya, 2008;
Kasemchaisiri and Tangtermsirikul, 2008).
Concrete containing cement replacing materials such as fly ash and limestone
powder is popular since the ready-mixed concrete producers can reduce the cost of
the concrete, reduce environmental problem and enhance some performances of theconcrete at the same time. These mineral admixtures require different curing
periods. So to know the curing sensitivity of these mineral admixtures is of greatinterest. To respond to the problem of curing, it is useful to develop a concrete
which is less sensitive to curing. Internal curing method and the use of multiple
binders are some possible ways to develop a minimum curing concrete.
In this research, the curing sensitivity of concrete with multiple binders and withinternal curing process by using bottom ash as an internal curing agent was studied.
2. EXPERIMENTAL PROGRAM
2.1 Materials
Ordinary Portland cement (OPC), fly ash and limestone powder (LP) were used as
cementitious materials. The chemical compositions of the cement, fly ash andlimestone powder are shown in Tables 1. The mean particle size of the LP used in538

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the test was 5 micron. The specific gravity of the cement, fly ash and LP are 3.15,
2.29 and 2.7, respectively. Natural river sand and crushed limestone were used asfine and coarse aggregates, respectively. The mix proportions of the tested concrete
mixtures are shown in Table 3. In this research, mixtures were designed at two w/b;
0.35 and 0.55. Bottom ash passing ASTM sieve no. 4 was used to partially replacefine aggregate. The water retainability of bottom ash was determined according to
the test method proposed by Kasemchaisiri and Tangtermsirikul (2006).
Table 1: Chemical composition of cement, fly ash and LP
Chemical
Fly
Limestone
Cementcompositionash
powder
SiO2 (%)
19.87 36.29
0.42
Al2O3 (%)
4.87
21.26
0.11
Fe2O3 (%)
3.55
13.77
0.08
CaO (%)
65.03 17.50
55.23
MgO (%)
0.73
2.89
0.48
SO3 (%)
2.52
3.67
0.01
Na2O (%)
0.02
1.40
0.01
K2O (%)
0.45
2.10
0.01
LOI (%)
2.26
0.09
44.16

Figure 1: SEM micro graph of bottom ash
2.3 Method
2.3.1 Compressive strength
Mixtures were designed at two w/b ratios; 0.35 and 0.55. Natural river sand waspartially replaced by bottom ash (BA) at 10% and 30% by volume. Details of all
mix proportions are shown in Table 2. Cube specimens with size 100 × 100 × 100
mm were cast for the compressive strength tests. All mixes were exposed to two
different curing conditions which are water-cured (WC) and air-cured (AC) until
testing. Strength tests were carried out at the ages of 28 and 91 days. All air-cured
specimens were kept in the room with temperature and RH of 28 ±1oC and 68 ±2%,respectively. To obtain one data, three specimens were tested for their average.
2.3.2 Autogenous and total shrinkage
For the autogenous and total shrinkage of concrete, the successful mixtures thatshowed outstanding performance in reducing curing sensitivity on compressive
strength of concrete were selected. Two mixtures; BA10% (w35f0LP0BA10) andEffect of bottom ash and mineral admixtures on the curing sensitivity of concrete
Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete539

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October
2011,
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LP10% (w35f0LP10BA0) were selected to compare with their respective control
mixture (w35f0LP0BA0). Prism specimens of size 75x75x285mm were cast for
shrinkage test. Mixtures were designed at w/b ratio of 0.35. Autogenous shrinkage
specimens were wrapped with plastic and aluminum foil sheets to prevent moistureloss from the concrete.
Free shrinkage and restrained shrinkage tests were evaluated for the total shrinkage
specimens. Two curing conditions were applied to the total shrinkage specimens; 7days water-cured and air-cured. Crack widths were measured with a digital
microscope in three areas of the restrained shrinkage specimens. All shrinkage
specimens were kept in a controlled room temperature and RH of 23± oC and
65±5%, respectively. Details of the mixture proportions are shown in Table 2.
Table 2: Mix proportions of the tested concrete.
Ingredients (kg/m3)
Mixing codecf LP wgs
w35f0LP0BA0474 00 166 1055 737
w35f30LP0BA0
315 135 0 157 1055 737
w35f0LP10BA0
423 0 47 164 1055 737
w35f0LP0BA10474 0
0 166 1055 663
w35f0LP0BA30
474 0
0 166 1055 516
w35f0LP10BA10 423 0 47 163 1055 663
w35f0LP10BA30 423 0 47 160 1055 516
w35f30LP0BA10 315 135 0 156 1055 663
w35f30LP0BA30 315 135 0 153 1055 516
w55f0LP0BA0365 00 201 1055 737
w55f30LP0BA0
245 105 0 193 1055 737
w55f0LP10BA0
326 0 36 199 1055 737
w55f0LP0BA10365 0
0 201 1055 663
w55f0LP0BA30
365 0
0 201 1055 516
w55f0LP10BA10 326 0 36 199 1055 663
w55f0LP10BA30 326 0 36 199 1055 516
w55f30LP0BA10 245 105 0 193 1055 663
w55f30LP0BA30 245 105 0 193 1055 516

BA
0
0
0
58
174
58
174
58
174
0
0
0
58
174
58
174
58
174

Remarks: c: cement, f: fly ash, LP: limestone power, w: water, s: fine aggregate, BA: bottom ash and g: coarse
aggregate

3. RESULTS AND DISCUSSIONS
3.1 Compressive strength
The results of 28-day and 91-day compressive strengths of water-cured and aircured concretes with w/b 0.35 and 0.55 are shown in Figures 2 and 3, respectively.
As expected, air-cured concrete showed comparatively low strength whencompared to water-cured concrete. When compared among the mixtures without
BA, in case of water-cured specimens, at the age of 28 days, the highest
compressive strength for w/b= 0.35 was given by w35f0LP0BA0 at 76 MPa, while
w35f30LP0BA0 and w35f0LP10BA0 had compressive strength of 68 MPa and 74
Mpa, respectively.

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100
90
80
70
60
50
40
30
20
10
0

Air‐cured (AC)FA 30%

Water‐cured (WC)LP 10%
Compressive strength (MPa)Compressive strength (MPa)

Water‐cured (WC)
Cement 100%(a):28‐days

100
90
80
70
60
50
40
30
20
10
0

Cement 100%

Air‐cured (AC)FA 30%

LP 10%(b):91‐days

Figure 2: Compressive strength of water-cured and air-cured concrete with
w/b=0.35.
For 91-day compressive strength, the highest compressive strength was observedwith w35f0LP0BA0 at 88 MPa while w35f30LP0BA0 and w35f0LP10BA0 showed
the values of 84 MPa and 81 MPa, respectively.
Interesting results are observed when air-cured concretes are analyzed. For 28-daycompressive strength, w35f30LP0BA0, w35f0LP10BA0, showed the values of 58
MPa and 65 MPa, respectively, while w35f0LP0BA0 showed 65 MPa. With noproper curing the compressive strength of concrete with LP was the same as that of
the control concrete at 28 days. For 91-day compressive strength of air-cured
concretes, w35f30LP0BA0 and w35f0LP10BA0 showed the values of 62 MPa and
67 MPa, respectively, while w35f0LP0BA0 showed 68 MPa.
For water-cured specimens (see Figure 2) with w/b=0.35, it was found that theincrease in BA content resulted in the reduction of compressive strength whencompared to the mix without BA for all types of binder combination. The sametendency was also found in the case of w/b = 0.55.
For air-cured concrete with w/b=0.35, cement-only concrete with BA 10%,(w35f0LP0BA10), had compressive strength improvement of 1.1% and 1.3% at 28
days and 91 days when compared to the mixture without BA (w35f0LP0BA0). The
mix with 10% BA and fly ash 30% (w35f30LP0BA10) showed 0.8% and 1.6%
increase in compressive strength for 28 days and 91 days as compared to fly ash
mix without BA (w35f30LP0BA0). For air-cured concrete specimens with
w/b=0.55, the cement-only concrete with 10% BA (w55f0LP0BA10) had
compressive strength of 35 MPa and 38 Mpa at 28 days and 91 days, respectively,
which are 2.8% and 1.83% below its respective control mix w55f0LP0BA0.
Fly ash improves long term strength with good curing condition. However, even forpoor curing condition, when BA is present, fly ash can still improve long term
strength because BA can supply the additional water required for the hydration andpozzolanic reaction with water.

Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete
Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete541

October
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ChiangThailand60

Air‐cured (AC)FA 30%

Water‐cured (WC)LP 10%
Compressive strength (MPa)Compressive strength (MPa)

Water‐cured (WC)
Cement 100%

50
40
30
20
10
0

60

Cement 100%

Air‐cured (AC)FA 30%

LP 10%

50
40
30
20
10
0

(a):28‐days(b):91‐days

Figure 3: Compressive strength of water-cured and air-cured concrete with w/b 0.55.
So, in air-cured condition, the cement-only concrete with BA had almost the same
compressive strength as the mix without BA, (see Figure 3). For binary binder
mixtures, compressive strength continuously dropped with the increase in BA
content. It can be concluded here that BA is more effective in low w/b concrete.
This is because at high w/b, there is more water inside the concrete for hydration.
The effect of internal curing is therefore not obvious.
In contrast, due to the low w/b, there is not enough water inside the concrete forhydration reaction, so internal curing becomes more effective. At low w/b, concrete
is dense and external curing water cannot penetrate into the inner portion of
concrete, so external curing is not effective. By adding BA, the additional internal
curing is provided. As the relative humidity inside the concrete drops, BA releases
water for subsequent hydration.
The similar behavior was also presented by other researches with other internal
curing agents such as lightweight aggregate, super absorbent polymers, porous
ceramic waste, etc (Cusson and Hoogeveen, 2008; Zhutovsky et al. 2004)

3.2 Curing sensitivity
The curing sensitivity of concrete on compressive strength was evaluated by using
the curing sensitivity index (CSIfc’) which is the percentage difference between
compressive strength of concrete that is continuously water-cured and that of thecontinuously air-cured concrete as shown in Eq. (1). The higher curing sensitivity
index means that the concrete is more sensitive to curing.
 fc ' (WC)  fc ' ( AC )   100
CSIfc '  
fc ' (WC)(1)where CSIfc’ is curing sensitivity index for compressive strength (%). fc' (WC) andfc ' ( AC ) are compressive strength of water-cured and air-cured specimens,
respectively (MPa).

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Curing sensitivities of concrete with w/b = 0.35 and 0.55 are shown in Figure 4. For
w/b=0.35, the mixtures having 30% fly ash replacement (w35f30LP10BA0) had the
maximum CSIfc’. Concrete with 10% limestone powder replacement(w35f0LP10BA0) had the lowest curing sensitivity.
For both w/b= 0.35 and 0.55, it was found that the use of BA reduced the CSIfc’ of
concrete significantly when compared to the mix without BA. LP accelerates thehydration of cement especially at early age (Bonavetti et al. 2000). As a result, alarge portion of cement has reacted at early age and therefore, reduces CSIfc’ of theconcrete. The pozzolanic reaction of fly ash starts at later age, thus it requires alonger curing period. Another reason is that the rate of evaporation of fly ash
concrete is higher than cement-only concrete (Tongaroonsri, 2009), so early water
loss by evaporation in air-cured fly ash concrete results in less water inside theconcrete for pozzolanic reaction. These make fly ash concrete more sensitive tocuring.
Bottom ash reduces CSIfc’ by its internal curing ability. In the air-cured condition
BA supplies the additional water required for hydration making the concrete lesssensitive to curing.
28 days
Cement 100%

91 days
FA 30%

30

LP 10%

25

25

20

20
CSIfc'

CSIfc'

30

15

28 days
Cement 100%

91 days
FA 30%

LP 10%

15

10

10

5

5

0

0

(a)

(b)

Figure 4: Curing sensitivity index (a): w/b=0.35 and (b): w/b=0.55.
3.3 Autogenous shrinkage
The autogenous shrinkage of mixtures with 10% replacement of limestone powder
in binder and 10% bottom ash replacement in sand is shown in Figure 5. The
mixture with 10% replacement of limestone powder had the least autogenous
shrinkage among the three mixtures. Bottom ash reduced the autogenous shrinkage
of concrete when compared to the mixture without bottom ash.
This phenomenon is similar to other types of internal curing materials (Lura et al.
2007; Cusson and Hoogeveen, 2008; Zhutovsky et al. 2004). Thus, it proves that
BA can be used as an effective internal curing agent to reduce autogenous shrinkage.

Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete
Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete543

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2011,
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October
2011,
ChiangThailand

Autogenous shrinkage (micron)W35f0LP0BA0

W35f0LP0BA10

W35f0LP10BA0

0
‐50

0

5

10

15

20

25

‐100
‐150
‐200
‐250

Age (days)

Figure 5: Autgoenous shrinkage of concrete mixtures with LP and BA.
3.4 Total shrinkage
The results of total shrinkage for air-cured and 7-day water –cured conditions areshown in Figure 6, respectively. Bottom ash was effective in reducing total
shrinkage for both water-cured and air-cured conditions. For the water-cured
condition, bottom ash mixture had similar shrinkage values with that of the
mixtures with limestone powder replacement. Mixtures that were water-cured for 7
days had significant reduction in total shrinkage as compared to the air-cured one.
When the concrete is in water, there is no loss of moisture. In fact there is moisturegain which swells the concrete and no total shrinkage inside the concrete. For the
air-cured condition, similar tendency as the autogenous shrinkage of concrete wasobserved. Concrete with limestone powder replacement had the least shrinkage andmixture with bottom ash reduced total shrinkage as compared to the cement-only
mixture without bottom ash. In this study, although bottom ash replacement reduced
total shrinkage, higher replacement of bottom ash would increase the total
shrinkage due to the increased porosity and then increased amount of water
evaporation from the concrete. However, adequate amount of bottom ash
replacement can maintain the same level of total shrinkage or reduce the total
shrinkage a little as compared to the control mixture.
w35f0LP0BA0(AC)w35f0LP0BA10(AC)w35f0LP10BA0(AC)w35f0LP0BA0(WC)w35f0LP0BA10(WC)w35f0LP10BA0(WC)

100
0

50

‐100

‐100

‐200

0

50

100

‐200

‐300

‐300

‐400
‐500

0

100
Total shrinkage(micron)Total shrinkage(micron)

0

‐400

Age (days)

(a)

‐500

Age (days)(b)

Figure 6: Total shrinkage of (a) 7 days water-cured and (b) air-cured concrete
mixtures with LP and BA.

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3.5 Crack width of concrete

w35f0LP0BA0(WC)w35f0LP0BA10(WC)w35f0LP10BA0(WC)

160
140
120
100
80
60
40
20
0

Crack width (micron)

Crack width (micron)

The long term crack widths of concrete mixtures for water-cured and air-cured
conditions are shown in Figure 7, respectively. In the air-cured condition, cementonly mixture had the largest crack widths and 10% limestone powder mixture had
the smallest crack widths. The 10% bottom ash mixture had crack widths inbetween the cement-only mixture and 10% limestone powder mixture. For thewater-cured condition, bottom ash 10% had the smallest crack width. The reason
for bottom ash mixtures to give such small crack widths were due to its porous
nature and shrinkage reduction. With higher porosity, the concrete have lower
internal stresses in the restrained shrinkage test specimen. As a result cracks occur
slower with smaller crack widths. The similar explanation was mentioned in aprevious research, Topçu and Bilir, (2010).

15

65

115

w35f0LP0BA0(AC)w35f0LP0BA10(AC)W35f0LP10BA0(AC)

160
140
120
100
80
60
40
20
0
15

Age (days)

(a)

65

115

Age (days)(b)

Figure 7: Crack width of concrete with (a) water-cured and (b) air-cured conditions

4. CONCLUSIONS
Based on the test results, the following conclusions are obtained.
1. For water-cured specimens, compressive strength of the mixes with BA werelower than the mixes without BA. However, for air-cured specimens, BA improved
the compressive strength slightly for cement-only concrete and fly ash concrete at
w/b= 0.35.
2. The use of 10% limestone powder reduced the curing sensitivity of the concrete.
3. Bottom ash reduced curing sensitivity of concrete significantly, especially at low
w/b.
4. The use of 10% limestone powder in the binder together with 30% bottom ash in
the fine aggregate was the most effective in reducing curing sensitivity.
5. The use of limestone powder and bottom ash reduced the crack width of concrete.
6. The use of limestone powder and bottom ash was effective in reducing
autogenous and total shrinkage of concrete.
7. From results of compressive strength, curing sensitivity, shrinkage and crack
width measurements, it was proved that BA could be used as an internal curing
material.
8. From this study, it was found that limestone powder and bottom ash are usefulmaterials for sloving the problem of curing and to develop a minimum curingconcrete.
Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete
Effect of bottom ash and mineral admixtures on the curing sensitivity of concrete545

October
2011,
Chiang
Mai,Mai,
Thailand
October
2011,
ChiangThailandAcknowledgements
The authors wish to express their gratitude to BLCP power limited and Metal andMaterial Technology Center (MTEC), The National Science and Technology
Development Agency (NSTDA), and Thailand’s National Research universities,
office of the higher Education commission, for their financial support and valuableassistance in carrying out this research

REFERENCE
Aitcin, P.C., Neville, A.M., and Acker, P., 1997. Integrated View of Shrinkage
Deformation, Concrete International 19: 35-41.
Bonavetti, V., Donza, H., Rahhal V., and Irassar, E., 2000. Influence of initial
curing on the properties of concrete containing limestone blended cement, Cement
and Concrete Research 30: 703–708.
Cusson, D., and Hoogeveen, T., 2008. Internal Curing of High-Performance
Concrete with Pre-soaked Fine Lightweight Aggregate for Prevention of
Autogenous Shrinkage Cracking. Cement and Concrete Research 38: 757–765
Kasemchaisiri, R., and Tangtermsirikul, S., 2007. A Method to Determine Water
Retainability of Porous Fine Aggregate for Design and Quality Control of Fresh
Concrete. Construction and Building Materials 21: 1322–1334.
Kasemchaisiri, R., and Tangtermsirikul, S., 2008. Properties of Self-Compacting
Concrete in Corporating Bottom Ash as a Partial Replacement of Fine Aggregate.
Science Asia 34: 087-095.
Lura, P., Jensen, O.M., and Igarashi, S.I., 2007. Experimental Observation ofInternal Water Curing of Concrete. Materials and Structures 40: 211–220.
Tongaroonsri, S., 2009. Prediction of Autogenous Shrinkage, Drying Shrinkage andShrinkage Cracking in Concrete, PhD Thesis, Sirindhorn International Institute ofTechnology and Faculty of Engineering, Thammasat University, Thailand.
Topçu, I.B., and Bilir, T., 2010. Effect of Bottom Ash as Fine Aggregate on
Shrinkage Cracking of Mortars. ACI Materials Journal 107: 48-56.
Zhutovsky, S., Kovler, K., and Bentur, A., 2004. Influence of Cement Paste Matrix
Properties on the Autogenous Curing of High-Performance Concrete. Cement &Concrete Composites 26: 499–507

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2nd dosage of superplasticizer and slump
recovery of concrete using naphthalene
based superplasticizer
Chalermchai WANICHLAMLERT1 and Somnuk TANGTERMSIRIKUL2
Researcher, Construction and Maintenance Technology Research Center,
Sirindhorn International Institute of Technology,
Thammasat University, Thailandchalermchai_w@siit.tu.ac.th2
Professor, School of Civil Engineering and Technology,
Sirindhorn International Institute of Technology,
Thammasat University, Thailand

1

ABSTRACTThis research is aimed to be a preliminary study for developing a concrete
slump control method using additional superplasticizer (SP). Strength class
C25/30 cement-only concrete with initial slumps of 7.5 cm and 10 cm were
investigated. Naphthalene based SP is used for both concrete mixing andmodifying. Volumetric paste to void ratio was designed at 1.1 and 1.2, whilewater to cement ratio and 1st SP dosage were fixed at 0.63 and 0.5%
respectively. Slump before and after adding various 2nd SP dosages wereobserved until 2 hours. The relationship between the 2nd SP dosages neededfor original slump returning and the slump loss before 2nd SP adding were
found out. The setting times and compressive strength were also
investigated. The higher the total SP dosage used, the longer the setting
times were. With 2nd SP addition, the compressive strength reduced for allages, while the percentage of strength reduction decreased for the longer
age. The strength reduction might occur due to the effect of setting timeextension and the existence of water in SP. According to this studied
condition, it is recommended to adjust concrete by 2nd SP addition for
original slump returning within 90 minutes after mixing.
Keywords: compressive
superplasticizer

strength,concrete,settingtime,

slump,

1. INTRODUCTION
Recently, ready-mixed concrete is ordered based on its slump and strengthclass in order to be ensured it has appropriate workability for theconstruction job and be able to achieve the required load-carrying capacity
when it is mature. However, during fresh state the concrete always loses its
workability with elapsed time. Therefore, occasionally the concrete batch
does not meet the job requirement when it reaches the construction site andis discarded.

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As slump loss of concrete mainly depends on the free water content in
concrete and the surface of solid particles. After cementitious material comeinto contact with water in concrete, the free water content gradually reduces
as a result of consumption in hydration reaction and evaporation, while thesurface of solid particles increases with the hydration reaction [1, 2]. Hence,slump loss increases with elapsed time after mixing as the hydration
reaction forming. In hot weather condition, the slump loss becomes more
rapid due to increase in both hydration rate and water evaporation.
The relatively hot climate of Thailand coupled with the traffic
congestion leading to the lower concrete slump than the requirement ofready-mixed concrete upon reaching delivery point.
There are generally four main methods used for slump control:(i) Use of high slump-retaining capability superplasticizers (at plant)(ii) Design of concrete mix which has excess slump initially (at plant)(iii) Adding of water (on site)(iv) Adding of chemical admixtures (on site)
The first 2 methods are needed to be done at concrete plant by using
some means to estimate the slump loss behavior and to design the concretewith excessive initial slump. For (i), it might be a costly method due to thecost of superplasticizer (SP) and, however, the target slump may not be
achieved at site because there are many uncontrollable factors which thedesigners would encounter, such as the time taken for concrete delivery or
the fluctuation of ambient temperature. Similarly, for (ii), it may not easy todesign a concrete mixture based on slump loss behavior to have excessive
initial slump and exactly achieve a target slump when arrive the site. Mostof the times, this excessive initial slump is achieved by overdosing of SP,
because the range of water-cement ratio is already restricted by the required
strength class. Sometimes, this lead to segregation of concrete at concrete
plant which become more difficult for quality control staff to check whether
the batching concrete is as design, mostly found in case of too muchexcessive slump for high slump class concrete.
The other 2 methods are needed to be done onsite, therefore instead ofslump loss estimation the workability check before the mixture modificationis necessary. For (iii), it may be an inappropriate practice way as thisreduces the concrete strength as changing the mix proportion by increasing
the water-cement ratio, which may be fatally harmful to the structure users.
Whereas, (iv) the required amount of additional SP in order to return theconcrete to its designed slump shall be much smaller than the required
additional water in the previous method. This additional SP is still doubted
whether it could meaningfully affect on the mechanical properties ofconcrete such as strength or not. The method to decide how much theadditional SP or 2nd SP shall be used when concrete arrive the site isnecessary.
Moreover, the behavior of concrete after re-dosing of SP needs to beinvestigated in order to clarify that the proposed method to control slump

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loss does not have unacceptable adverse effect on concrete properties. The
setting time of concrete after SP re-dosing has to be checked to ensure that
there won’t be excessive retarding effect on setting time. Compressive
strength development of concrete was also investigated to ensure that the redosing of superplasticizer does not harmfully decrease the compressive
strength of concrete.
2. METHODOLOGY
2.1 Materials
2.1.1

CementOrdinary Portland Cement Type 1, conforming to TIS 15 Part 1-2547,
was used. Chemical compositions and physical properties of cement are
shown in Tables 1.
Table 1: Chemical compositions and physical properties of cement
Chemical compositions (%)
SiO2
Al2O3
Fe2O3
CaO
MgO
SO3
Na2O
K2O
Physical properties
Specific gravity
Loss on ignition (%)

20.29
5.02
3.22
65.05
1.63
2.60
0.11
0.44
3.15
1.68

2.1.2

Aggregates
An aggregate mixture of natural river sand passing sieve no. 4 andcrushed limestone with maximum size of 25mm conformed to ASTM C 33,
were used as fine and coarse aggregates respectively.
2.1.2

Chemical admixtures
A type F admixture, naphthalene based superplasticizer (SP), wasused for this study as it is economical and widely used in Thailand. A
method for determining the water reducing efficiency of admixtures is
described in Meyer and Perenchio (1979). The authors adapted the minislump technique developed by Kantro at the Portland Cement Association totest water reducing efficiency of admixtures [3].
From test results, the water reducing efficiency of naphthalene based
SP used in this research was equal to 22% and 44% at dosage of 0.5% and
1% (sp/c), respectively.

2nd dosage of superplasticizer and slump recovery of concrete using naphthalene
2nd dosage of superplasticizer and slump recovery of concrete using Naphthalene based superplasticizer5493
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2.2 Mix proportion
Details of concrete mix proportions used in this research are shown in
Table 2. Two concrete mixtures designated as SL7.5 and SL10 represent
concrete with initial slump of 7.5cm and 10cm respectively.
All concrete mixes were designed as follows: paste content (γ) of 1.1
and 1.2 for SL7.5 and SL10 respectively, water-cement ratio (w/c) of 0.63
and initial SP dosage of 0.5%. The design is based on the ready-mix
proportions used in Thailand for strength class of C25/30.
Table 2: Mix proportions
Materials
Cement [kg]Water [kg]Sand [kg]Gravel [kg]
SP [kg]

SL7.5
285
175
865
1095
1.425

Mix ID.

SL10
295
185
865
1060
1.475

2.3 Concrete mixing procedure
Concrete mixer used in this research was a drum type mixer which has
a maximum volume of 50 liters. Concrete mixing procedure is described asfollows:
Firstly, cementitious material, fine and coarse aggregate were
weighted and put into mixer and mixed for about 20 seconds. Secondly,
weighted water was poured into the mixer and mixed for about 2 minutes.
Finally, weighted superplasticizer was put into the mixer and mixed together
with aggregates and paste for 2 minutes 40 seconds. The total mixing time
was around 5 minutes.
The mixing process and other subsequent tests were conducted in atemperature controlled environment at 28±2°c.
2.4 Slump loss testing procedure
The slump loss is determined by following steps. Firstly, concrete
mixtures were measured for the slump values immediately after mixing anddefined as initial slump. Then the concrete mixture is kept in a large tray
and sealed with a plastic wrap to prevent loss of water due to evaporation.
At stipulated time, a sample of the batch is tested for slump to determine
slump loss. Slump is tested after the elapsed time of 30, 60, 90 and 120
minutes. Before every test, concrete is remixed for 3 minutes to ensure thehomogeneity.

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2.5 Re-dosing of superplasticizer procedure
For the SP re-dosing of concrete, the sample is similarly kept in alarge tray and sealed with a plastic wrap. At the stipulated time, concrete isput into the mixer, and mixed for 3 minutes. A small sample is then use fortest of slump. Meanwhile, concrete in the mixer is re-dosed with thespecified amount of SP and mixed for another 3 minutes to ensure
homogeneity. A sample is then tested for slump after re-dosing. The rest isthen used for further testing for slump loss. In this study, re-dosing ofsuperplasticizer at elapsed time of 30, 60 and 90 minutes were carried out.
The amount of 2nd SP dosage used for re-dosing procedure is shown in
Table 3.
Table 3: Variation of 2nd SP dosage

Elapsed time
(min)
30

60

90

2nd SP dosage(% by wt. of cement)
0.20
0.40
0.70
0.20
0.50
0.80
1.00
0.30
0.60
0.90
1.20

2.6 Setting time of cement and compressive strength development test
The initial and final setting time of cement with various dosages ofsuperplasticizer was determined in accordance with ASTM C 191-08.
10x10x10 cm concrete cube specimens were used for testing ofcompressive strength development at the age of 1 day, 3 days, 7 days and 14
days. The specimens were sealed with a plastic wrap upon casting anddemolded after 1 day. After demolding, they were cured in water at 25°c
until the time of testing.
3. TEST RESULTS AND DISCUSSIONS
3.1 Effect of SP dosage on setting time of cement
As seen in Figure1, SPs cause the setting time for cement to increase,and this retarding effect was more pronounced with increase in dosage of SP.

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2nd dosage of superplasticizer and slump recovery of concrete using Naphthalene based superplasticizer5515
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Figure 1: Setting time of cement with various dosages of superplasticizer
3.2 Re-dosing of superplasticizer and effect on slump regained
Upon re-dosing of concrete with SP, the slump of the concrete
increased back to a certain percentage of the original slump. Figure 2 shows
how slump was regained after re-dosing at various dosages at 60 minutes forSL10. Figure 3 shows the relationship between the percentage of slump
regained with increase in 2nd dosage at 30, 60 and 90 minutes for SL10.
Interpolation was carried out to determine the required 2nd dosage inorder to regain the original slump value for the two mixes at various times.
It was found that the required 2nd dosage for two mixes with different initial
slump were very close for their respective time of re-dosing, as shown in
Fig 4. This probably suggests that mixes with similar w/c ratio but
difference in amount of paste required roughly similar dosage for re-dosing
in order to regain the original slump. However, future studies which varyvarious values of paste content (γ) and study the effect of w/c ratio needs tobe carried out in order to confirm this behavior.
Moreover, Figure 4 also shows that the required 2nd dosage increases
exponentially with increasing of elapsed time. This is due to the hardeningof the cement paste with the elapsed time, hence, requiring a higher dosage
of superplasticizer for it to effectively push the now larger and heavier
hydration products apart to regain slump. Moreover, the amount of freewater has also reduced and there is more friction between the particles.

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ICUS Report 56+ 0.8%+ 0.5%+ 0.2%

Figure 1: Slump for re-dosing at 60 min for SL10

Figure 2: Effect of SP re-dosing on slump regained for SL10

Figure 3: Required 2nd dosage to regain original slump and elapsed time
However, the re-dosing procedure shall not be based on elapsed timeafter mixing as the slump loss behavior may not be exactly the same due tovarious uncontrollable factors, such as variation in temperature or
2nd dosage of superplasticizer and slump recovery of concrete using naphthalene
2nd dosage of superplasticizer and slump recovery of concrete using Naphthalene based superplasticizer5537
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movement when concrete is transported. It is suggested that the re-dosing
procedure shall be based on the percentage of slump loss before re-dosing,as shown in Figure 5. From this test result, it shows that after concrete
slump loss reaches about 80% of its original slump, the required 2nd SP
dosage to regain its original slump increases dramatically.

Figure 4: Required 2nd dosage to regain original slump and slump loss
percentage before SP re-dosing
3.3 Re-dosing of superplasticizer and effect on compressive strength
development of concrete
The simulated compressive strength values from FACOMP arecompared to those from the real re-dosing test. By assuming that the 2nd SP
dosage becomes the additional water content, then the w/c ratio of the mix
in FACOMP is automatically increased.
FACOMP is computer software developed by Sirindhorn International
Institute of Technology (SIIT), it is able to make accurate predictions forstrength development, and some durability properties of concrete produced
from Thai local materials.
As shown in Figure6, the actual strength of concrete reduces with theincreasing of 2nd SP dosage for all concrete age. The FACOMP simulated
strengths have the same order of strength reduction as those from the real redosing test, therefore it could be claimed that the existing water content in
2nd SP dosage leads to the increase in total water content of concrete thenresulting as strength reduction. The difference between actual strength andFACOMP simulated strength becomes smaller as the concrete age is longer.
This might be explained by the larger difference in early strength resultsfrom the retardation effect of SP, the higher the SP dosage is the longer thesetting times are.
Moreover, the effect of decrease in strength due to re-dosing ofsuperplasticizer was also found to be less pronounced as the concrete ages,
as seen in Figure 7. It is obvious to find that the adjustment of concrete
workability on site by using proposed SP re-dosing method could drop the

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strength
strengthofofmature
matureconcrete
concrete(usually(usuallyreferredreferredtoto2828days
daysageageconcrete)concrete)only
only
less
lessthanthan5%.
5%.

ActualActual FACOMPFACOMPFACOMPFACOMPFACOMP
ActualActual FACOMP

ActualActualNoNo
redoseredose(Actual)(Actual)
0.50%
0.50%
(Actual)(Actual)
0.80%
0.80%
(Actual)(Actual)NoNo
redoseredose(FACOMP)(FACOMP)FACOMP
ActualActual FACOMP

0.50%
0.50%
(FACOMP)(FACOMP)
0.80%
0.80%
(FACOMP)(FACOMP)

FigureFigure6:6:Comparison
Comparisonbetween
betweenFACOMPFACOMPand
andactual
actualresults
resultsforfor14-day
14-daycompressive
compressivestrength
strengthdevelopment
development

FigureFigure7:7:Strength
Strengthreduction
reductionfrom
fromoriginal
originalconcrete
concreteforforvarious
variousdosages
dosagesofof
2nd
2ndSPSP
4.4.CONCLUSIONSCONCLUSIONS
Based
Basedononthe
theexperimental
experimentalresults,
results,thethefollowing
followingconclusions
conclusionscan
canbebedrawn.
drawn.
1.1.If Ifsuperplasticizers
superplasticizersare
aretotobebeused
usedforforre-dosing
re-dosingtotoregain
regainoriginal
original
slump
slumpatatthe
theconstruction
constructionsite,
site,one
oneshould
shouldtake
takenote
notethat
thatthere
therewould
wouldbebeanan
increaseincreaseininthe
thetotal
totalamountamountofofsuperplasticizer
superplasticizerused,
used,thus,
thus,a afurther
furtherincrease
increase
ininbothbothinitial
initialandandfinal
finalsetting
settingtimes.
times.
2nd dosage of superplasticizer and slump recovery of concrete using naphthalene
2nd
dosageofofsuperplasticizer
and
slump
recoveryofof
concrete
using
Naphthalene
based
superplasticizer
2nd
dosagesuperplasticizer
and
slump
recovery
concrete
using
Naphthalene
based
superplasticizer555
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2. For re-dosing of superplasticizer in concrete, the higher the slump
loss is, the higher the amount of 2nd dosage to regain the original slump
required. The 2nd dosage increases exponentially as there is increase inslump loss, especially after slump loss reaches 80% of original slump.
3. For mixes with the same w/c ratio but different amount of paste,they seem to need the same required 2nd superplasticizer dosage to regain
their original slumps regardless of their slump classes.
4. There is a slight decrease in compressive strength when a 2nd
dosage is added. This decrease in strength is great in the early age of theconcrete and become less pronounced as the concrete ages. The initial great
drop in strength was probably due to the retardation effect ofsuperplasticizer on concrete setting time, hence, slowing down initialstrength development of concrete.
5. The concrete strength reduction induced by superplasticizer redoing method decrease with the age of concrete, according to the referenced
mixes the strength drop only less than 5% for mature concrete (28 days aged
concrete) with strength class of C25/30
Future studies on more types of mix proportions should be studied on
the effect of re-dosing, such as variation in w/c ratio, different types of
cementitious materials in use, and other parameters affecting the slump of
concrete. Effects of temperature on the slump loss and effectiveness of redosing of superplasticizer should also be studied as heightened temperatureis regularly experienced in Thailand. Finally, the use of different types ofsuperplasticizer for re-dosing on concrete, and the compatibility with othertypes of chemical admixtures present in concrete (i.e., retarders,
accelerators) should also be studied.
REFERENCESTANGTERMSIRIKUL S. and KITTICHAROENKIAT P., 1999.
Water Retainability and Free Water in Fresh Concrete, Research andDevelopment Journal of the Engineering Institute of Thailand, Vol. 10, No
1, 42-49.
TANGTERMSIRIKULS.,KHUNTHONGKEAWJ.
andKITTICHAROENKIAT P., 2001. A Workability Prediction Model forConcrete and Mortar, JSCE Journal of Materials, Concrete Structures andPavements, No. 676, 149-157.
TANGTERMSIRIKUL S., and KHAYAT K.H., 2000. Fresh Concrete
Properties, Self-Compacting Concrete, State-of-the-Art report of RILEM
Technical Committee 174-SCC, 17-21

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NewEvaluation of induced strain in concretedue to ASR expansion by digital image
correlation
Yuichiro KAWABATA1, Hiroki GODA2, Ema KATO3
and Mitsuyasu IWANAMI4
1
Researcher, Port and Airport Research Institute (PARI), Japan
kawabata-y@pari.go.jp
3
Assistant Professor, Kyushu Institute of Technology, Japan
3
Senior Researcher, PARI, Japan(Researcher, ICUS, IIS, the University of Tokyo, Japan)
4
Head of Structural Mechanics Division, PARI, Japan
ABSTRACTIn recent years, examples of deterioration of concrete structures due toalkali-silica reaction (ASR) have been reported, and methods used todiagnose such structures have become controversial issues. Regarding thediagnosis of ASR-affected structures, it is difficult to evaluate induced
strain/stress of concrete due to ASR expansion. Therefore it is necessary todevelop a method to evaluate the induced strain in reinforced concrete (RC)member. One of the conventional methods is to measure the strain withstrain gauges before and after releasing induced stress by cutting and/or
coring the surface of concrete. This requires, however, the attachment ofmany strain gauges in order to evaluate multidirectional strains since ASR
expansion shows anisotropic behavior. Meanwhile, digital image
correlation (DIC) analysis, a full-field optical measurement, gives strain
distribution of concrete with high resolution. By using this technique, theauthors developed a method to evaluate induced strain in RC member
caused by ASR expansion.
This paper describes the new method to evaluate induced strain by using
DIC analysis. After expansion, deformation of concrete before and after
coring the concrete was measured. The results showed one possibility thatthe new method can evaluate the induced strain in RC member caused by
ASR expansion.
Keywords: alkali-silica reaction (ASR), digital image correlation (DIC),
multi-rosette analysis, induced strain caused by ASR expansion
1. INTRODUCTION
In recent years, examples of deterioration of concrete structures due toalkali-silica reaction (ASR) have been reported, and the rational repair andreinforcement to such structures has become a controversial issue (Japan

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Society of Civil Engineers, 2005). In concrete structures damaged by ASR,
reduction in concrete strength and Young's modulus and spalling of coverconcrete are observed, resulting in degradation of structural performance ofstructural members, such as load carrying capacity and ductility. Moreover,cracks caused by ASR will make it easy for chloride ion, water and oxygento penetrate into concrete. This may initiate corrosion of steel bars
embedded in the concrete, degrading the durability of concrete structures. In
severe cases, fracture of steel bars in structures has occurred, resulting insignificant decrease of structural performance.
Regarding the diagnosis of ASR-affected structures, evaluation of theinduced strain/stress in concrete is necessary in order to assess the damage
in concrete structures because the induced strain may damage the steel bars.
However, it is difficult to evaluate the induced strain/stress of concrete
caused by ASR expansion Therefore it is necessary to develop a method toevaluate the induced strain in reinforced concrete (RC) member. One of theconventional methods is to measure the strain with strain gauges before andafter releasing induced strain by cutting and/or coring the surface ofconcrete. This requires, however, the attachment of many strain gauges inorder to evaluate multidirectional strains since ASR expansion shows
anisotropic behavior.
Meanwhile, digital image correlation (DIC), a full-field opticalmeasurement, has been increasing in popularity in the fields of medical
science and mechanics technology (Uchino, 2003). DIC can give
multidirectional deformation of the object so that it is being applied to civilengineering field (Goda et al., 2011). By using this technique, the authors
developed a method to evaluate strain distribution in RC member caused by
ASR expansion.
This paper described a new method to evaluate induced strain in
concrete caused by ASR expansion by using DIC. Applicability of the
proposed method was discussed in this paper.
2. EVALUATION METHOD OF INDUCED STRAIN IN CONCRETE
CAUSED BY ASR EXPANSION
2.1 Method and procedures
The method to evaluate the induced strain in concrete caused by ASR
expansion is similar to conventional ones, while the measurement isdifferent. Figure 1 shows the procedure for evaluation of induced strain in
concrete caused by ASR expansion. Similar to the conventional method
using strain gauges, concrete coring is carried out. Before coring concrete,some digital photographs are taken using a digital camera. Since a hole isformed by coring concrete, the strain of concrete around the hole is released.
Consequently the concrete around the hole deforms according to restrained
strain. After coring the surface of the concrete, several digital images aretaken for multi-rosette analysis using DIC as explained in the next section.

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By using this technique, the multidirectional strains around the hole can beevaluated.
Before coring

Taking photos

Multi‐rosette analysis
Coring concrete
After coring

Figure 1: Procedures for evaluation of induced strain in concrete
2.2 Strain measurement of concrete
2.2.1 Digital image correlation (DIC)
DIC is a type of full-field strain measurement method. In DIC, digital
photographs of a specimen at different stages of deformation are used. By
tracking the subset, which is a block of pixels with 256 tones ofmonochrome digital image, DIC provides a full-field deformation vector
field. The subset (N × N) can be set to have any required size analyzed.
In order to correlate the subsets, two types of pattern matching: “roughsearch” and “detailed search” are conducted. Rough search can correlate thesubsets to an accuracy of a pixel. In the rough search, the correlation
function CR for rough search can be determined by using the residual
minimization method shown in the following Eq (1).
M

M∑∑I (X + u + i , Y + v + j )- I ( X + i , Y + j )C R (X + u , Y + v ) =

d

(1)

u

i =- M j =- M

where, Iu(X, Y) and Id(X+u, Y+v) are the light intensities before andafter deformation, respectively; X and Y are the center coordinates of asubset; u and v are displacements in the x- and y-directions, respectively;
and N = 2M+1. When the correlation function CR shows the minimum value,
the subset containing this position can be decided to be the nearest location
where the center of the subset shifted.
On the other hand, due to the discrete form of the nature of digital
image, it is necessary to decide deformation of the subset at sub-pixel level.
Several kinds of interpolation formula are used in the previous work. In thisstudy, the discrete brightness pattern of pixels is directly interpolated
numerically to give the maximum correlation function. The correlation
function CD for detailed search at the sub-pixel level can be determined byusing the following Eq (2).
M

(2)

C D ( X + u,Y + v ) =

M

M

M

∑∑I ( X + u + i,Y + v + j )× ∑∑I ( X + i,Y + j )dui =- M j = M
M

i =- M j =- M

M

M

M

∑∑{I ( X + u + i,Y + v + j )} × ∑∑{I ( X + i,Y + j}di =- M j =- M

2

u

2

i =- M j =- M

Evaluation ofimage
correlation
Evaluationof induced
induced strainstrain inin concrete
concrete due
due toto asrASRexpansion
expansionbybydigital
digitalimage
correlation

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Y

Y

δY2

Xb’

δX1
Yb’

Y0

δY1

X

X0

Xa’

δX2

X

(a) Before deformation(b) After deformation
Figure 2: Schematic diagram of deformation of rectangular region
επ/2
επ/4
Shift from 0 to πε0 (32 steps)
Concrete core
StrainAnalysis point

Distance from the center of the hole

Figure 3: Schematic image of multi-rosette analysis
With analyzed data from DIC, the deformation vector field can becalculated. By comparing deformed rectangular regions to initial ones asshown in Figure 2, strains at each position can be calculated as shown in
Eqs. (3)-(5). Major strains (εmax), minor strains (εmin) and maximum shear
strains (γmax) at arbitrary positions can be obtained by rosette analysis.

(X a' －X 0 ) X 0 + (X b' －X 0 ) X 0(3)(Ya'－Y0 ) Y0 + (Yb'－Y0 ) Y0

(4)

(δX1 Ya' + δY1 X a' ) + (δX 2 Yb' + δY2 X b' )

(5)

εx =
εy =

ε xy =

2

2

2

2.2.2 Multi-rosette analysis
By using DIC, a new analytical method proposed by Uchino, multirosette analysis, is applied to evaluate stress distribution of concrete aroundthe hole (Uchino et al., 2010). The principle of multi-rosette analysis isshown in Figure 3. At first, the calculation method on the change ratio of thehole diameter will be explained. As shown in Figure 1, analysis points will
be arranged in a concentric pattern. In this case there are 64 analysis points.
Two analyses points that are in symmetry with respect to the center point of
the hole will be selected. The distance change between two points will becalculated using the images before and after deformation and 32 calculated
data are obtained. In these calculated data, a combination 0, π/4, and π/2 radalong the x-axis will be selected and the maximum and minimum of the
distance change ratios will be obtained using rosette analysis. Then multiple
rosette analysis will be performed as the combination will be changed, and4560

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the average maximum and minimum of the distance change ratios that
reduced the error will be obtained. According to Uchino, the results of stressconcentration around the hole under one dimensional tension corresponded
Steel plate(50×50×6)

Rebar (D13)

Epoxy resin

50

250

250

50

Epoxy resin

250

250

600

600

(a) Type A(b) Type B

Steel plate(50×50×6)

Epoxy resin

50

250

50

Stirrup (Φ6)

Rebar (D13)

50

250

125@4

50

600

(c) Type C
Figure 4: Shape and size of test specimens
Table 1 Expansion after exposure (unit: μ)
Exposurecondition

Type A

Type B

Concrete

Concrete

Lo

La

Lo

Ac

5922

5651

2938

Nt

Type C
ConcreteLa

Mainrebars

Lo

La

9471

1520

2761

8469

1778

1676

3193 4040 1315 3171

1230

1557 3092

1359

1778

Main
rebarsStirrups

with the analytical results by the finite element method.
3. EXPERIMENTS
3.1 Test specimens
Figure 4 shows shape and size of the test specimens. Alkali-reactive
coarse aggregate, and non-reactive limestone fine aggregate were used.
Water-to-cement ratio was 47%. Sodium hydroxide solution was added into
the water so as to control the total Na2Oeq amount in concrete to 6.0 kg/m3.
Deformed steel bars with a diameter of 13mm 6mm were used.
The size of the test specimens were 250×250×600 mm. Type A has
neither rebar nor stirrup so as not to restrict the concrete. Type B has 4
rebars to restrict the concrete along longitudinal direction only. Type C has
both 4 rebars and 5 stirrups to restrict along longitudinal and latitude
direction. Steel plates were welded to both sides of the rebars. Epoxy resin
measuring 2mm in thickness was coated on the surface of the 250×250 mm.
Fifty-six days after the concrete was cast, the test specimens were exposed
to two conditions; seawater wetting/drying test in the controlled outdoor(Nt) and accelerated seawater wetting/drying test at 60 deg C in thelaboratory (Ac). The period of exposure was about 1.5 years. Strain gauges
Evaluation ofimage
correlation
Evaluationof induced
induced strainstrain inin concrete
concrete due
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expansionbybydigital
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correlation

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were used to measure strain in the steel bars and stirrups. After 28 days ofcuring, the demec studs were attached over the concrete surface. The change
in length between the demec studs was periodically measured by a digitalextensometer. The measured data was treated as strain. The average of all
measured longitudinal (Lo) strains is defined as Lo strain for each specimen.
In the same way, the average of all lateral (La) strains is defined as La strain.
After the exposure test, all of the surfaces of test specimens were washed tomake the random patterns for DIC. Hereafter, the name of tested specimen
was described as (Type of specimen)-(Exposure condition).
Table 1 shows the results of the expansion test. Regarding theexposure condition Ac, Type B and Type C show significant decrease in Lo
strain compared to Type A whereas La strains of Type B and Type C werelarger than that of Type A. This effect was attributed to the existence ofrebars. Expansion of test specimens exposed to Nt was smaller than that
exposed to Ac since the chemical reaction of ASR is strongly affected byexposed temperature.
3.2 Induced strain measurement
The proposed method described above was carried out. Outside
diameter of the core for stress release was 52mm. At first, random pattern
was distributed on the surface of the specimens using black, yellow andwhite sprays. Five images were taken with a digital CMOS camera. Pixel
number of the camera was 14 million (4,800×2,800) pixels, and the area
taken by the camera was 280×180mm. The diameter of the core was
890pixels. The length of a pixel shows 0.06mm. After taking the images, thecore was drilled using a concrete coring machine. Depth of the core was
100mm, twice as deep as the diameter of the core. Then, some images of thesurface around the core were taken using the same camera. Conditions fortaking the image were the same before and after coring. Scale of the subset
for DIC analysis was set to 30×30 pixels. In the multi-rosette analysis, thepitch along the normal vector was 5pixels.
4. RESULTS AND DISCUSSIONS
4.1 Strain distribution around the hole
1400

1200

εmax

1200

εmax

1000

εmin

1000

εmin

Strain (μ)

Strain (μ)

1400

800
600
400
200

800
600
400
200

0

0
26

28

30

32

34

36

26

Distance from the center of the core (mm)

28

30

32

34

36

Distance from the center of the core (mm)(a) Type A-Nt(b) Type B-Nt
Figure 5: Relationship between distance from the center of the core and strain

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Figure 5 (a) shows the relationship between the distance from thecenter of the hole and strain evaluated by the proposed method in Type ANt. The major strain near the concrete core showed 700 μ. The strain tended
to decrease significantly with the increase in the distance from the center ofthe core. At 36 mm from the center, major strain and minor strain showedapproximately 200 μ. This tendency was attributed to the release of straincaused by coring the concrete. On the other hand, the test result of Type BNt shown in Figure 5 (b) showed similar tendency to Type A-Nt. The major
strain near the concrete core showed 1200 μ while the strain at 36 mm fromthe center showed 500-650 μ. The difference between Type A-Nt and Type
B-Nt is the existence of rebars embedded in concrete so that the expansion
force due to ASR was accumulated in concrete due to the restraint of rebars.
Consequently the released major strain in Type B-Nt was larger than that in
Type A-Nt. From this result, it can be said that the released strain is affectedby the restraint condition.

(a) Type A-Nt(b) Type B-Nt
Figure 6: Major strain distribution around the concrete core(a) Type A-Nt(b) Type B-Nt
Figure 7: Crack pattern
Table 2 Released strain near the hole after coring (unit: μ)
Test specimen

Exposed condition

Type A

Released strain
Lo

La

370

640

1081

1177

Type C

1106

1274

Type A

654

864

1848

1935

747

1180

Type B

Type B
Type C

Nt

Ac

Evaluation ofimage
correlation
Evaluationof induced
induced strainstrain inin concrete
concrete due
due toto asrASRexpansion
expansionbybydigital
digitalimage
correlation

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0.2Type A‐Nt
Type B‐Nt
Type C‐Nt

Url (N/mm2)0.15Type A‐Ac
Type B‐Ac
Type C‐Ac

0.1

0.05
edge defect
0
0

0.2

0.4

0.6

Urs (N/mm2)

Figure 8: Relationship between Urs and Url
Figure 6 shows the major strain distribution around the hole of the test
specimens. Type A-Nt shows isotropic strain distribution. In Type B-Nt, thestrain in the La-direction was larger than that in the Lo-direction. Figure 7
shows the crack pattern of the concrete surface after exposure. Type A-Nt
shows multi-directional cracks. In Type B-Nt, cracks occurred in the Lodirection so that strain in the Lo-direction was released. These tendencies
are known as characteristics of ASR expansion of restrained concrete. The
major strain distribution obtained from the proposed method agreed with thecrack map of the test specimen. These results indicated that the major strain
distribution around the hole can be evaluated by the proposed method.
4.2 Validity of the proposed method
Table 2 summarizes the results of the proposed method. The released
strain near the hole formed after coring was smaller than the induced strain
as shown in Table 1. This is attributed to the release of strain due to thecracking of the concrete. ASR expansion accompanies cracking of concrete
so that the induced strain will decrease. Especially, most of the induced
strain in covering concrete would be released due to cracking. On the other
hand, concrete surrounded by rebars is restrained so that concrete will show
larger strain after coring. The previous paper reports that the proposed
method is more accurate than the conventional one using strain gauges(Goda et al., 2011).
Here, the relationship between the induced strain and released strain is
discussed from the viewpoint of the conservation of energy. The energy
derived from concrete expansion can be expressed using the following
equation (6).
2
U c = Eε Lo ε La

(6)where, εLo and εLa are longitudinal and lateral strain, respectively; E isYoung’s modulus (= 33.2 kN/mm2). The calculated energy of Type A canbe assumed to be free-expansion energy (Ufree). The difference between theenergy of Type B or Type C and that of Type A is the energy stored in RC

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member by rebars (Urs). In addition, the released energy derived from coring
concrete (Url) can be calculated by the strain obtained from the proposed
method (Table 2). Figure 8 shows the relationship between Urs and Url.
There is a linear relationship between Urs and Url except for Type B-Ac. In
Type B-Ac, the edge defect was observed in the outside of the hole. It isconsidered that this defect affected the measured strain. The absolute valueof Urs was different from that of Url. This can be attributed to the lost energy
derived from cracking, creep, and shrinkage of the concrete. From the test
results, it can be said that the proposed method can evaluate the stored
energy in RC member.
From these results, it is verified that the proposed method can evaluate
the strain distribution around the hole and the stored energy in RC member
derived from restraint of rebars. Though further research is necessary toevaluate the free-expansion energy of concrete, there is a possibility that the
proposed method can evaluate the induced strain in concrete caused by ASR
expansion.
5. CONCLUSIONSThis paper proposes a new method for evaluating the induced strain in
concrete caused by ASR expansion, by using multi-rosette analysis based on
DIC. The following conclusions can be drawn based on the test results:(1) The proposed method can evaluate the strain distribution around thehole.
(2) Based on the conserved energy, the proposed method can evaluate thestored expansion energy in RC member due to restraint of rebars.
ACKNOWLEDGEMENT
A part of this work was financially supported by Grant-in-Aid for Young
Scientist (B) (No.22760335) from the Japan Society for the Promotion of
Science (JSPS).
REFERENCES
Goda, H., Kawabata, Y., Uchino, M., Iwanami, M. and Hibino, M.,
2011. Application of stress release method by digital image correlation
method to concrete units deteriorated by alkali silica reaction, Proceedingsof JSEM 2011 Annual Conference on Experimental Mechanics, Nara, Japan,
175-180 (in Japanese).
Japan Society of Civil Engineers, 2005. State-of-the-art report on the
countermeasures for the damage due to alkali-silica reaction, Concrete
Library 124 (in Japanese).
Uchino, M., 2003. Sub-micron displacement measurement using a
digital image correlation method, Proceedings of ATEM’03, CD_Paper No.
OS01W0200.

Evaluation ofimage
correlation
Evaluationof induced
induced strainstrain inin concrete
concrete due
due toto asrASRexpansion
expansionbybydigital
digitalimage
correlation

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Uchino, M., Okamoto, T., Hida, K., Ito, Y., Sumitoro, P. and Matsuda,
H., 2010. Strain analysis method using multi-rosette analysis by digital
image correlation method, Proceeding of the International Conference on
Bridge Maintenance, Safety and Management, 2564-2569

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NewDevelopment of remote system forsupporting building damage assessment
during large-scale earthquake disaster
1

Makoto FUJIU1, Miho OHARA2 and Kimiro MEGURO3
Ph.D. Candidate, Department of Interdisciplinary Information Studies,
The University of Tokyo, Japanfujiu@iis.u-tokyo.ac.jp
2
Associate Professor, Interfaculty Initiative in Information Studies/ Institute of Industrial Science,
The University of Tokyo, Japan
3
Professor, Interfaculty Initiative in Information Studies,/ Institute of Industrial Science,
The University of Tokyo, Japan

ABSTRACT
Building damage assessment is necessary for governments to issue theVictim Certificates for residents who suffered from housing damages. The
process of assessment needs accuracy, quickness, objectivity and fairness
because the results of assessment are used as criteria for providing public
monetary supports for rebuilding of their livelihood. In Japan, several big
earthquakes are expected to occur in the near future. A lot of structural
damages due to these earthquakes will cause enormous needs for building
damage assessment. However, there is a limit on the number of specialists
with adequate assessment skills who can access the damaged area underbad traffic conditions. Delay in building damage assessment by local
governments can disturb rapid reconstruction of the damaged area.
Considering these problems during large-scale earthquake disaster, thispaper proposed the new system for building damage assessment using
photos of damaged houses taken by residents or volunteer fire corps indamaged area. Specialists outside the damaged area confirm these photos
on the website and assess their damage levels. All the data used for building
damage assessment is managed with GIS database on the management
server located outside the damaged area under cloud condition. This kind ofdigital management system can contribute to enhance the accuracy andefficiency of the procedures for issuing the Victim Certificates for residents.
In this paper, the total system for supporting building damage assessment
was designed and its prototype system was developed. The system for
uploading the photos of damaged houses was developed as mobile
communication service. The remote system for specialists to assess thedamage level was developed as web service.
Keywords: earthquake disaster, building damage assessment, IT system

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1. INTRODUCTION
In Japan, several big earthquakes are expected to occur in the near future. A
lot of structural damages due to these earthquakes will cause enormous
needs for building damage assessment. Building damage assessment isnecessary for governments to issue the Victim Certificates for residents who
suffered housing damages. However, current number of human recourses
who are trained with the procedure of building damage assessment is notenough. It is necessary to develop the new system which can correspond to
next large-scale earthquake disaster. The guidelines of general procedure forinspecting building damage and evaluating loss due to disasters were
published by the Cabinet Office in 1968, 2001 and 2009. However, in pastdisasters, various problems of building damage assessment have been
pointed out such as inaccurate inspection, difficulty in quick inspection andlack of human recourses with sufficient skill of assessment.
In this research, new remote system for building damage assessment
using IT system was proposed and prototype system was developed. Thesesystems have some features that can solve some problems pointed out by
past building damage assessments and execute building damage assessment
quickly after a large scale earthquake disaster. This proposed system has
two sub-systems. First one is photo uploading system used in damaged area.
Second one is assessment system for supporting experts such as registeredarchitects and experienced workers outside the damaged area. Finally, we
report that design and functions of developed system.
2. PROBLEMS OF PAST BUILDING DAMAGE ASSESSMENTS
AND SOLUTIONSThere are 3 inspection stages in building damage assessment such as“Primary Inspection”, “Secondary Inspection” and “Issue of the Victim
Certificates”. Through these stages, damage levels of buildings are decided
by visual inspection. The primary inspection evaluates the damages
appeared on the exterior of a building. The secondary one evaluates not only
the exterior damage but also the interior damage. The purpose of thesecondary inspection is to provide the second opinion for the evaluation
when the owner or resident of a damaged house does not accept the result of
the primary one. Therefore, the primary inspection is carried out for all thedamaged buildings, while the secondary inspection is usually carried out by
request. Finally, Victim Certificates for residents are issued from the local
governments.
The process of assessment needs accuracy, quickness, objectivity andfairness because the results of the assessments are used as criteria forproviding public monetary supports for rebuilding their livelihood. However,various problems have been pointed out for the building damage
assessments after past earthquakes. We reviewed literatures regarding past
several building damage assessments such as Shigekawa (2005) andclassified reported problems as shown in Table 1. As a result, enormous

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problems in each inspection stage were obtained. Our proposals to solve theproblems at each stage were shown in table 1. For example, “primary
inspection” stage has the problems with low inspection accuracy andinsufficient inspectors’ knowledge. In order to solve these problems, we
proposed double check procedures to enhance accuracy of assessments.
Table1: Problems and solutions of building damage assessment after
earthquakes
Flow of Inspection

1995 Hyogoken-Nanbu
Earthquake①Criteria

There is no standard tocarry out the building
damage assessment.
(Murao,1999)②Summon ofInspection

Insufficient number ofassistant staff(Murao,1999)③Training-

Ⅰ-Criteria

Ⅱ-Training of
Inspector

Ⅲ-Screening④Organize

Inspector's knowledge
was insufficient.
(Murao,1999)⑤Screening-⑥Primary
Inspection

Problemconcerninginspection accuracy(Murao,1999)
Difficulty in responding
to residents who havedissatisfactionininspection results(Murao,1999)

Ⅳ-Inspection⑦Secondary
Inspection--⑧Victim Certificate①Use of GIS-

Used by ex post analysis②Use of GPS

Use of electronics
devices③Mobile phone④Digital camera⑤Cloud computing

Not used because oftechnologicaldevelopment

2004 Niigata Chuetsu
2007 Niigata ChuetsuEarthquake
oki Earthquake
There is no standard to carry out the building
damage assessment. Neither examination methods
nor the inspection methods are clearly provided.
Only guidelines were issued by the Cabinet Office.
(Shigekawa, 2005)
Insufficient number of Difficulty in assemble ofassistant staff
inspectors(Shigekawa,2005)(Tanaka,2008)
Becausemethodof assessment is different ineach local government,
training is difficult.
(Horie,2004)
Difficulty in gathering enoughnumberofInspectors and keeping
inspection quality(Shigekawa,2005)

Limit in on-site inspection for lack of inspectors(Shigekawa,2005)

Solution of past
problems in this research
Inspectors who goes inthedamagedarea
becomes unnecessary.
Priortraining
inspectors
canexecuted.

tobe・The owner of damaged
house and the firefighters can become aninvestigator.
・Inspection quality cankeep by doing priortraining and taking a
picture using instruction.
Because of a lot of
support workers exist
outside of damaged area.
So,
a
lot
of
investigations can be
executed.

Difference
betweenstructural
engineer's
aspect and the Cabinet Office guideline(Tanaka,2008)
The assessment result
Inspector's knowledge
keeps accuracy by a
was insufficient.
double check.
(Shigekawa,2005)
Problemconcerning Problem concerning
The assessment result
inspection accuracy
inspection accuracy
keeps accuracy by a
(Shigekawa,2005)(Tanaka,2008) double check.
Difficulty in responding
to residents who havedissatisfactionininspection results(Shigekawa,2005)
Because of a lot of
support workers exist
Difficulty in predicting
outside of damaged area.
number of application
So,
a
lot
of
(Tanaka,2008)
investigations can be
executed.
The assessment result
Needs
for
assistant keeps accuracy by astaff'sforthirdly double check.
inspection
So, number of execution(Tanaka,2008) of third inspection canbe reduced.
The efficiency of work
Because of issue of thewas low, because thevictims certificate wasissue
ofenormous
automated, the amountcertificates was the first
of
work
of
time
for
local
administrative office cangovernments.
be greatly reduced.
(Yoshitomi,2005)
Possible to use GIS byUsed by ex post analysis Used by ex post analysis improving the Web
environment.
Standard equipment in a
Not usedNot used
smart phone.
Theusability
has
Used a little.
Used a little.
improved greatly with asmart phone.
・ Only used for therecordStandard equipment in a
Used a little.
・ Limitindata
smart phone.
processing using PC
for lack of capacity.
Not used because of Not used because of The Cloud computing
technological
technologicalcan be used with a smart
development.
development.
phone.
-Development of remote system for supporting building damage assessment during large-scale earthquake
Development of remote system for supporting building damage assessment during large-scaledisaster
5693
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3. CONCEPT OF NEW REMOTE SYSTEM FOR BUILDINGDAMAGE ASSESSMENT
As a new system for achieving all the solutions for the problems reported at
the past building damage assessments as shown in table 1, we proposed a
new remote system for supporting building damage assessments during
large-scale earthquake disaster. The concept of the system is illustrated infigure 1. The total system consists of two sub-systems. The first one is photo
upload system in damaged area. Photos of a damaged house are taken byresidents or volunteer fire corps in damaged area and those data is uploaded
to the server. The second one is remote assessment system for specialists.
Specialists located outside the damaged area confirm these photos throughthe website, and assess their damage levels and area. All the data used forbuilding damage assessment is managed with GIS database on the
management server located outside the damaged area under cloud condition.
This kind of digital management system can contribute to enhance theaccuracy and efficiency of the procedures for issuing the Victim Certificatesfor residents.
Taking a picture of damaged house in damaged area

Remote building damage assessment by specialist

・Demand of necessary
photograph・Correspond to
inspector's demand.

Instruction oftaking picture

Upload ofphoto

System-１

Area-BArea-A

Interactive condition

Area-C

Area-D

Area-E・GIS information
・Photo information

Input
damagedleverforeach houses

System-２

Photo data・Inspector’s name・GIS information・Monitoring of execution condition etc.

Web・GIS Server
Figure 1: Concept of remote system for building damage assessment

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4. DEVELOPMENT OF PROTOTYPE REMOTE SYSTEM FOR
BUILDING DAMAGE ASSESSMENT
4.1 Development of photo upload system in damaged area
Here, prototype of “Photo upload system in damaged area” wasdeveloped. Photos of a damaged house are taken by residents or volunteer
fire corps in damaged area and those data is uploaded to the server. Thissystem was developed by Android as the mobile phone operating system
which is installed in almost all the smart phones except iPhone. Photo
upload application is installed to each Android smart phone by inspectors
who are residents or volunteer fire corps in damaged area.
Flow of photo upload system is shown in figure 2. Firstly, residents or
volunteer fire corps as inspectors input the basic information such as GPS
information, address and owner name. Secondary, they upload some photos
such as overview of damaged house, incline of damaged house anddamaged point of roofs, walls and fundamentals. Finally, they confirm the
input data and some photos.
Method of completing for photo upload in damaged area using upload
application is as follows. Inspectors take some damaged house photos which
are full views of a damaged house (north side, east side, south side and westside) and closeup views of damaged points.
Transition of input screen

Input and contents of confirmations

basic information screen

Input the GPS information, zip code,
address, owner name,, phone number, etc.

photo upload main screen

Confirm the inspection site, house and GIS
data

overview photo screen
Inclines screen

Upload the photos of damaged house as
north side, east side, west side and southside
Upload the photos of incline

area of roofs screen

Input the area of roofs

photos of roofs screen

Upload the photos of roofs and damaged
point

area of walls screen

Input the length and width of walls in eachside

photos of walls screen

Input the photos of walls in each side anddamaged point

fundamental length screen

Input the length of fundamentals in eachside

photos of fundamentals
screenInput the photos of fundamentals in eachside and damaged point

end screen

Figure 2: Flow of photo upload system in damaged area
Development of remote system for supporting building damage assessment during large-scale earthquake
Development of remote system for supporting building damage assessment during large-scaledisaster
5715
earthquake disasterOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Photo Upload System for Building Damage Assessment
Home

VisualInspection

Incline

Roof

Wall

Base

This is the wall inspection page. Please upload four side
photos of your inspection house.
North side

Select target file

uploadEast side

Select target file

uploadSouth side

Select target file

uploadWest side

Select target file

uploadPlease fill in the situation of around house and etc..

Input Comments
Next

Figure 3: Photo upload system in damaged area (upload page)

Photo Upload System for Building Damage Assessment
Home

VisualInspection

Incline

Roof

Wall

Base

Please relate a photo of wall to damaged point.
Step1

①

②

Please select a photo
which is something
damaged.

Step2
Please selectdamaged point using“pointer (red circle)”.

Please fill in the situation of around house and
etc..

①
②

Input Comments

Next

Figure 4: Photo upload system in damaged area (relationship page)
They select some photos for upload in each factors page, and fill in thecomments about damage level and location of a house etc. as shown infigure 3. Inspectors should take pictures of damaged house concerning threefactors: externals, inclination and building element (roof, exterior wall andfoundation). Furthermore, they have to relate closeup views of damaged
points to full views using touch screen functions as shown in figure
4.Figures 3 and 4 are the prototype images of the system for the primary
inspection. The prototype images of photo upload system were developed
based on the data of totally damaged houses due to the 2011 off the Pacificcoast of Tohoku Earthquake. After taking some pictures, inspectors need to
upload them to an exclusive server in cloud condition using upload
application. Using this application makes it easier to select and upload

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ICUS Report 56

photos which are taken by inspector in damaged area. The reason is thatsmart phone has touch screen functions which are tap, drag, flick and pinch
out/in operations.
4.2 Development of remote assessment system for specialists
Here, prototype of “remote assessment system of photos of damaged
houses was developed. Specialists outside the damaged area confirm thesephotos on the website and assess their damage levels. All the data used forbuilding damage assessment is managed with GIS database on the
management server located outside the damaged area under cloud condition.
Flow of remote assessment system is shown in figure 5. Firstly,
specialists who are registered architects and experienced workers outside thedamaged area confirm the basic information such as shape of damaged
house, location and seismic level on the web system and overview all thephotos of a damaged house. Secondary, they assess the damage level andarea using some photos such as overview of damaged house, incline ofdamaged house and damaged point of roofs, walls and fundamentals.
Finally, specialists confirm the input data and some photos. Then result offirst assessment is passed to the next specialist to carry out double check.
Transition of input screen

Input and contents of confirmations

basic information screen

Confirm the shape of damaged house,location and seismic level

overview screen

Confirm the overview photos

overview assessment screen

assess the “totally collapse” using overview
photo

overview assessment
confirmation screen

confirms the assessment result of theoverview photo again and the assessment isfixed.

incline assessment screen

assess the incline using incline photos ineach side

incline assessment
confirmation screen

confirms the assessment result of the incline
photo again and the assessment is fixedroofs assessment screen

assess the damaged level and area of roofs
using photos in each sideroofs assessment
confirmation screen

confirms the assessment result of thedamaged roofs photo again and theassessment is fixed.

walls assessment screen

assess the damaged level and area of walls
using photos in each sidewalls assessment
confirmation screen

confirms the assessment result of thedamaged roofs photo again and theassessment is fixed.

fundamentals assessment
screenassess the damaged level and points offundamentals using photos in each side

fundamentals assessment
confirmation screen

confirms the assessment result of thedamaged fundamentals photo again and theassessment is fixed.

end screen

Figure 5 Flow of remote assessment system

Development of remote system for supporting building damage assessment during large-scale earthquake
Development of remote system for supporting building damage assessment during large-scaledisaster
5737
earthquake disasterOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Remote System for Building Damage Assessment
Home

VisualInspection

Incline

Roof

Wall

Base

Please select damage level and area of roof.
Damage level and area
Level

Ⅱ

Area

２０

％

Input Comments

Next

Please fill in the situation of around house and etc..

Figure 6: Remote assessment system (roof assessment page)

Remote System for Building Damage Assessment
Home

VisualInspection

Incline

Roof

Wall

Base

Please select damage level and area of wall.
Damage level and area
Level

Ⅳ

Area

３０

％

Input Comments

Please fill in the situation of around house and etc..

Next

Figure 7: Remote assessment system (wall assessment page)
Figures 6 and 7 show the prototype images of the system for primary
inspection. These images were developed based on the data of totally
damaged houses due to the 2011 off the Pacific coast of Tohoku Earthquake.
Total damage level of a house is decided based on damage levels of threefactors: externals, inclination and building element. Assessment for one
damaged house should be conducted by two or three specialists to doublecheck the result and keep accuracy, fairness and objectivity. They can see
close-up photos if necessary. They evaluate the photos and decide its
damage level as shown in figures 6 and 7. Specialists select the damagelevel and area from pull down choice set in each factor page. In addition,
they can request additional photos for accurate assessment to inspectors in

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ICUS Report 56

damaged area through the each assessment page. In final page, fill in thespecial or caution comments of assessed damaged house and pass to thenext specialist. When the assessment ends here, Victim Certificates forresident is issued from local government.
5. CONCLUSIONSIn Japan, several big earthquakes are expected to occur in the near future. It
is necessary to develop the new system which can be corresponds to next
large-scale earthquake disaster. In this research, new remote assessment
system for building damage assessment was proposed.
Some problems of past building damage assessments were analyzed
and applicability of new technologies including new electronics devices
which are GPS, GIS, digital camera and mobile phone (smart phone) was
discussed. Among these problems, this paper focused on “Inspection stage”
and “Assessment stage”, and proposed new remote system for building
damage assessment using both mobile communication service and web
service.
The prototype images of remote building damage assessment systemwere developed based on the data of totally damaged houses due to the 2011
off the Pacific coast of Tohoku Earthquake. In the future, we plan to
improve the functions of the system and examine its effectiveness throughexperiments for specialists.
REFERENCE
Murao, O., Yamazaki, F., 1999, Comparison of Building Damage
Evaluation by Local Governments after the 1995 hyogoken-nanbu
earthquake, Journal of Architecture Planning and Environmental
Engineering, No.515, pp.187-194
Shigekawa, K., Tanaka, S., Horie, K., Hayashi, H., 2005, Some
Regulational Issues on Building Damage Assessment –A Case Study of
Niigata-ken Chuetsu Earthquake- , Journal of social Safety Science No.7,
pp.133-140
Horie, K., Shigekawa, K., Maki, N., Tanaka, S., Hayashi, H., 2005,
Application of Damage Assessment Training (DATS) to Ojiya City following
2004 Niigata-ken Chuetsu Earthquake –Through a Disaster Response
Support Activity for Issuing Victim Certificate- , Journal of social Safety
Science No.7, pp.123-132
Yoshitomi, N., Hayashi, H., Urakawa, G., Shigekawa, K., Tanaka, S.,
Horie, K., Matsuoka, K., 2005, The Development of a Damage Certificate
Issuing Support System –A new disaster response database schema created
for the Niigata Chuetsu Earthquake- , Journal of social Safety Science No.7,
pp.141-150
Tanaka, S., 2008, A Study on the Building Damage Assessment
Processes for the 2007 Niigata Chuetsu Oki Earthquake Disaster :Development of remote system for supporting building damage assessment during large-scale earthquake
Development of remote system for supporting building damage assessment during large-scaledisaster5759
earthquake disasterOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Kashiwazaki Case Study , Proceedings of social Safety Science No.22,
pp.35-38

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Basin water management under land use
and climate changes-Nan Basin as case studySucharit KOONTANAKULVONG1, Kwanchai PAKOKSUNG2
1
Associate Professor, Chulalongkorn University, Thailand
Sucharit.K@chula.ac.th2
Researcher, Chulalongkorn University, Thailand
wrsru_kcp52@yahoo.com n
ABSTRACTIn the last two decades, land use in the upper watershed had changed
drastically due to the rapid upland agricultural invasion. This affected therunoff pattern to the reservoir especially in the dry season and sometimes
caused flash flood to the downstream area. The recent climate change trend
causes additional impact to runoff pattern to the reservoir and make basinwater management becomes more complicated.
Nan Basin is in the northern part of Thailand and provides about 25 % of
the raw water source to the Central Plain of Thailand. The recent
promotion for upland crop agriculture by price guarantee system from thegovernment, i.e., maize, made the change in land use in the upper watershed area. The study on runoff change due to land use change had been
conducted via runoff data at gauge stations in the main stream andprecipitation data in the past 20 years. Besides, the climate change data
derived from the bias corrected MRI-GCM were used to analyze theprojected runoff in the basin and project the change. Both land use andclimate changes will give impacts to the reservoir operation in the basin
and there is a need for new tool to help manage water properly in thischanging environment.
The study investigated the degree of change from the land use in the pastand climate change for the future and a new tool were introduced to better
water management for the basin which will secure water source for thecountry as well.
Keywords: land use, climate change, basin water management, new tool
1. INTRODUCTION
Land use in the upper watershed of Nan Basin had changed dramatically
due to the increasing population and agricultural growth in the past decade.
Forest area changed to agriculture and after that the agricultural area wastransformed to industrial, residential or recreational areas. This change

5771

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

affected the runoff and the use of natural resources which created the impact
to the hydrologic and environmental conditions. The study aimed toinvestigate the degree of change from the land use in the past and climatechange for the future and some new tools were introduced to better water
management for the basin which will secure water source for the country as
well.
The Nan river basin is located in the northern region of Thailand withthe total catchment area of 34,682.04 sq.km. The basin originated from Bor
Klua district, Nan Province and is situated between latitude 15o 42’ 12” tolatitude 19o 37’ 48” N and longitude 99o 51’ 30” to longitude 101o 21’ 48”
E, The basin covers the area of 6 provinces namely Nan, Uttaradit,
Phitsanulok, Pichit, Phetchabun and Nakhonsawan Provinces and can bedivided into 16 sub-river basin as shown in Figure 1 and Table 1.

LegendSUBBASINRIVER
ELEVATION,m.MSL
0 - 5050 - 100
100 - 200
200 - 500
500 - 750
7501 - 1,000
1,000 - 1,250
1,250 - 1,500
1,500 - 1,750
1,750 - 2,000
2,000 - 2,500

Sources: Department of Water Resource

Figure 1 Topographic NAN Basin

Table 1: Catchment area of each sub basin in Nan Basin

2
578

COD
E

SUB BASIN NAME

Area(km2)

0902

UPPER PART OF MAE NAM
NAN

2,222.34

0903

HUAI NAM YAO (1)787.730904

SECOND PART OF MAE NAM
NAN

2,200.39

0905

NAM YAO (2)1,532.190906

NAM SAMUN

598.88

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ICUS Report 56
0907

THIRD PART OF MAE NAM
NAN

589.570908

NAM SA

778.400909

NAM WA

3,375.80

0910

NAM HAENG

1,043.80

0911

FOURTH PART OF MAE NAM
NAN

2,435.02

0912

NAM PAT

992.830913

KHLONG TRON

1,297.540914

MAE NAM KHWAE NOI

4,578.860915

NAM PHAK

2,008.040916

MAE NAM WANG THONG

2,470.50

0917

LOWER PART OF MAE NAM
NAN7,770.16

TOTAL

34,682.04

Sources: Department of Water Resources

Up to now, there were various studies on land use change and runoff
coefficient changes in the NAN Basin. The land use change was mostly
estimated from the satellite data and compared the change of area of eachland use type, though the satellite images available were limited only forsome years. The runoff coefficient indicated water release unit in eachwatershed which was calculated from the ratio of runoff, catchment area andrainfall. The runoff coefficient values in the year 2000 is greater than 2006’s
because the forest area in the year 2006 was less than 2000. In Nan basin,
runoff coefficient changed at the rate of 2.1% per year (Kwanchai P. et. al.,2011). The impact of climate change towards water disaster in Thailand,i.e., drought, flood, landslides was also assessed by using the bias-corrected
MRI-GCM data and there was an indication that Nan Basin will be one of
the hot spot of change (Sucharit K. et.al., 2011).
1.

OBJECTIVES AND METHODOLOGY

The study aimed to find the affect of land use change towards runoff pattern
due to the economical growth in the upper basin. Future climate conditions
are put into the consideration to investigate the water situation of bothpresent and future.
The application of satellite data from TRMM is introduced as a newtool to see the opportunity to better water management from the main dam.
The collected data included rainfall, runoff, land use change (Forest areachange) in each sub basin boundaries in the year 2000 and 2006. The
analyzed runoff coefficients (Kwanchai P. et. al., 2011) were then illustrated
spatially by using GIS technology.
The data used in the study in the main basin and each sub basin of Nanbasin are the land use in the year 2000 and 2006, rainfall and runoff timeseries.
Basin waterBasinwater management
management under
under land
land use
use andand climate
climate changes
changes-Nan-Nanbasin
Basinasascase
casestudystudy-

5793

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

In the study procedure is as follows:1) collect the economical data in the study area such as population,
agricultural product/output etc.
2) prepare the land use map in the year 2000 and 2006,3) classify land use type, i.e., forestry, agriculture, residential,
irrigation, water3) resource and other, in each subbasin,4) simulate the runoff pattern using the previous analysed runoff
coefficient,5) analyze the runoff pattern with the changes in land use (forest
area change),6) analyze the flood and drought with new land use and climate
conditions
7) simulate water condition and analyse water supply volume tocentral plain,
8) apply TRMM data for water control from dam.
2.

RESULTS

The difference of land use change and runoff in NAN basin in the year 2000
and 2006 was analyzed and the results are summarized as follows.
2.1 Economical growth
In 2009, the population in Nan Basin with a majority of the population
lived in non municipality 85%, as shown in Figure 2. Phitsanulok Province
had the highest population and Uttaradit Province had the lower. The socioeconomical index for Nan Basin used in this study was the gross provincial
product (GPP). In 2008, GPP in study area increased 39.76% from the year
1995 and with the value of 151,025 MB as shown in Figure 3. The GPP(including agriculture) increased 80.12% from the year 1995 with the valueof 52,761 MB as shown in Figure 4. Agricultural statistics in the study area
like maize grew at the highest about 73.8%. The summer rice, rainy rice andrubber grew about 47.3%, 7.4% and 7% respectively.
00% 100%100%
90% 90% 90%
80% 80% 80%
462,951845,561
539,4942,311,959
462,951845,561
539,4942,311,959
463,953
462,951
462,951845,561
845,561
539,494
539,4942,311,959
2,311,959
463,953
463,953
463,953
70% 70% 70%
60% 60% 60%
50% 50% 50%
40% 40% 40%
304,929
304,929
304,929
304,929
382,426
382,426
382,426
382,426
1,736,623
1,736,623
1,736,623
1,736,623
30%
664,718
664,718
664,718
664,71830%
30%
384,550
384,550
384,550
384,550
20% 20% 20%
10% 10% 10% 158,022
158,022
158,022
158,022
157,068
157,068
157,068
157,068575,336
575,336575,336575,336
180,843
180,843
180,843
180,843
79,40379,40379,403
79,4030% 0% 0%Nan

Uttaradit Phitsanulok

PichitNan Basin

'�
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�
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%

Sources: National Statistical Office ���$$Figure 2: Population in Nan Basin in the year 2009

4580

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ICUS Report 56

2008
�
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MBMB

0

20,0000
20,00040,00040,000
060,00020,000
60,00080,00040,000
80,000100,000
60,000100,000
120,000
80,000120,000
140,000
100,000
140,000
160,000
120,000
160,000140,000 160,000

���%�$��%�$0 10,00010,00020,000
0 20,000
10,00030,00030,000
20,00040,00040,000
30,00050,00050,000
40,00060,00060,000
50,000Source:Source:National
National
Statistical
Source:Statistical
National
OfficeOffice
Statistical Office

Source:Source:National
National
Statistical
Source:Statistical
National
OfficeOffice
Statistical Office

60,000MB

���%�$

a) a)
Gross
Gross
a)Provincial
Gross
Provincial
Provincial
Product
Product
Product
b) b)
GPP
GPP
(Includingb)(Including
GPP (Including
Agriculture)
Agriculture)
Agriculture)
FigureFigure3:Figure
3:
Economical
Economical
3: Economical
data
data
in in
Nan
data
Nan
Basin
inBasinNan Basin
900,000
900,000
900,000
Maize
Maize
800,000
800,000

800,000

Maize
200,000
200,000
Increased
Increased
73.8%*
Increased
73.8%* 73.8%*

200,000

180,000
180,000

RubberRubber Rubber
180,000

700,000
700,000

700,000

160,000
160,000

160,000

600,000
600,000

600,000

140,000
140,000

140,000

500,000
500,000

500,000

120,000
120,000

120,000

400,000
400,000

400,000

100,000
100,000

100,000

300,000
300,000

300,000

80,00080,00080,000200,000
200,000

200,000

60,00060,00060,00040,00040,00040,000100,000
100,000

100,000

20,00020,00020,000‐‐‐20052005 20062005
2006 20072007
2006 20082008
2007
2548 2548 2549 2549
2548 2550 2550
2549 2551 2551
2550

3,500,000
3,500,000

3,500,000

3,000,000
3,000,000

3,000,000

2,500,000
2,500,000

2,500,000

Rainy
Rainy
RiceRice
Rainy Rice

Increased
Increased
7Increased
*7 *
7*

‐

1,800,000
1,800,000

Decreased
Decreased
7.4%*
Decreased
7.4%* 7.4%*
1,600,000
1,600,000

1,800,000 Increased
Increased
47.3%*
Increased
47.3%* 47.3%*
1,600,000

1,400,000
1,400,000

1,400,000

1,200,000
1,200,000

1,200,000

1,000,000
1,000,000

1,000,000

800,000
800,000

800,000

600,000
600,000

600,000

2,000,000

1,500,000
1,500,000

1,500,000

1,000,000
1,000,000

1,000,000

500,000
500,000

500,000

400,000
400,000

400,000‐

200,000
200,000

200,000‐

2548 2006
2549
2551
25482005
25492006
25482550
25492551
2550
2005
2005
20072550
2006
2008
2007
2007
2008

นNan
าน

อุUttaraditตรดิตอุUttaraditถตรดิตถ
อุUttaraditตรดิตถ

พิPhitsanulokษณุโพิลก
พิPhitsanulokษณุโ ลก
ษณุโ ลก
Phitsanulok‐พิจิตร พิPichit
พิPichit
จิตร
จิตร
2006
2007
2008
2005
20062549
2005
20072550
20062551
2008
2007 Pichit
2008
2548 2549
2551
25482005
25482550
2549
2550
2551
ทัNan
้งลุมน้ํ า้งลุBasinทัNan้งลุมน้ํ า BasinทัNanมน้ํ า Basin
2,000,000
2,000,000 2,000,000
SummerSummerRice
Summer
Rice
Rice

‐
2008
2551

2,000,000
2,000,000‐

นNanาน นNan
าน

‐
‐
‐
2551
2008
2006 20072007
20052005 20062005
2006 20082008
2007
2548 2548 2549 2549
2548 2550 2550
2549 2551 2551
2550

*prepare*preparedata*prepare
data
betweenbetweendata
2005
between2005
andand2008
2005
2008and 2008

2008
2551 88

8

Source:Source:OfficeOfficeofSource:Agricultureof Agriculture
OfficeEconomicsof Agriculture
EconomicsEconomics

FigureFigure4Figure
Cultivated
4 Cultivated
4 Cultivated
area
area
growth
growthareaingrowth
in
Nan
Nan
Basin
inBasinNan Basin
2.22.2
Land
Land
2.2
Use
Land
Use
ChangeChangeUse Change
in in
NAN
NAN
in
Basin
NAN
BasinBasin
The
The
land
land
The
useuse
land
in in
the
use
the
study
in
study
the
area,
study
area,
shown
shown
area,inshownin
FigureFigurein4Figure
and
4 and
Table
4Tableand2,Table
2,
cancanbe2,becan beclassifiedclassifiedclassified
into
into
6 major
6into
major
6groups,majorgroups,i.e.,groups,i.e.,forestry
forestryi.e., forestry
area,
area,
agriculture
agriculturearea, agriculture
area,
area,
irrigation
irrigationarea, irrigation
area,
area,
residential
residentialarea, residential
area,
area,
water
water
area,
resources
water
resources
resources
area
area
and
and
area
other.
other.
and other.
Table
Table
2:Table2:
Distribution
Distribution
2: Distribution
of of
land
land
use
ofuse
land
type
type
use
in in
Nan
type
Nan
Basin
inBasinNan Basin
2000
2000 2000
Type
Type
of LandofType
Land
Use
ofUse
Land UseAreas
Areas
Areas (sq.km)% %(sq.km)(sq.km)Residential
Residential
Residential
Agriculture
Agriculture
Agriculture
Irrigation
Irrigation
Irrigation
Forestry
Forestry
Forestry
Unclassified
Unclassified
Unclassified
Water
Water
Resources
Resources
Water Resources
Total
Total Total

2006
2006 2006%AreasAreas(sq.km)(sq.km)Areas (sq.km)%%%
781.11 781.11 2.26
2.26 2.26 872.32
872.32 872.32 2.65
2.65 2.65
781.11
14,991.73
14,991.73
14,991.7343.33
43.33 43.3316,299.58
16,299.58
16,299.5849.60
49.60 49.60
2,480.72
2,480.72
2,480.72 7.17
7.17 7.17 2,695.00
2,695.00
2,695.00 8.20
8.20 8.20
15,745.15
15,745.15
15,745.1545.51
45.51 45.5113,798.86
13,798.86
13,798.8641.99
41.99 41.99
130.29130.29 130.29 0.38
0.38 0.38 535.10
535.10 535.10 1.63
1.63 1.63
471.12471.12 471.12 1.36
1.36 1.36 399.23
399.23 399.23 1.21
1.21 1.21
34,600.10
34,600.10100100 100
34,600.10
34,600.10
34,600.10 100100 100 34,600.10

Basin
Basin
water
water
management
management
under
under
land
land
useuseandandclimateclimatechanges
-Nan
-Nan
basin
basin
as as
case
case
studystudyBasin
water
under
land
use
and
climatechanges
-Nan
basin
asas
case
Basin
water management
management
under
land
use
andchanges
climatechanges-NanBasincasestudystudy-

5 5 5815

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,
Sources: Land Development Department

Forest area is the top of land use type in Nan basin while water
resource area had the lowest in the year 2000 and 2006 because NAN basin
was less developed but rich in natural resource.
The differential land uses (forest area) by sub basin were shown
Figure 6 and Table 3. In the year 2006, the deforestation was greater thanthe 2000’s because the economic in basin started to grow. The Khwae Noi
sub basin had the highest deforestation rate of 115.7 sq.km/year or 6.2% peryear out of 16 sub basin in NAN basin because Phitsanulok Province, where
the Khae Noi sub basin is located, was highly developed. The Sa sub basin
had lowest rate of 6.5 sq.km/year or 1% per year. In average, forest area in
Nan basin decreased about 386 sq.km/year or 16% per year.
LegendSUBBASIN
LAND USE TYPE
URBANFORESTOTHER
ARGICULTURE
IRRIGATIONWATERa) Land Use 2000b) Land Use 2006

Sources: Land Development Department

Figure 5 Land Use in NAN Basin
2.3 Runoff and hydrograph change

Legend% land use changes
0% - 10%
10% - 20%
20% upb) percentagechanges by subbasin
Sources: Land Development Departmenta) deforestation area

Figure 6 Land Use Change(forest area changes)
in NAN Basin

The annual runoff volume in Nan basin will change with the rainfallchange. The runoff in near future will decrease from the present but therunoff in far future will increase from the present as shown in Figure 7. The
annual runoff volume of Nan basin in upper zone (U) and lower zone (L) innear future will decrease from the present but the runoff in far future will
increase from the present. The middle zone (M)’s runoff will increase inboth near future and far future as shown in Table 4.

6582

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Technologies forfor Urban
Urban Safety
Safety ofof Mega
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New

ICUS Report 56

Table3:
Table3:
Table3:
ForestForestForest
area
area
area
changechangechange
in
inNAN
in
NAN
NAN
Basin.
Basin.
Basin.
2000
2000
2000
22 2
AAFF,km
AF,km
,km
%
%%
0902
0902
1,205.2
1,205.2
54.2
54.2
54.2
0902
1,205.2
0903
420.1
53.3
0903
0903
420.1
420.1
53.3
53.3
0904
770.2
50.3
0904
0904
770.2
770.2
50.3
50.3
0905
329.3
55.0
0905
0905
329.3
329.3
55.0
55.0
0906
364.2
61.8
0906
0906
364.2
364.2
61.8
61.8
0907
2,789.2
78.6
0907
0907
2,789.2
2,789.2
78.6
78.6
0908
630.5
81.0
0908
0908
630.5
630.5
81.0
81.0
0909
1,557.2
70.8
0909
0909
1,557.2
1,557.2
70.8
70.8
0910
615.2
58.9
0910
0910
615.2
615.2
58.9
58.9
0911
549.2
22.2
0911
0911
549.2
549.2
22.2
22.2
0912
1,657.8
68.1
0912
0912
1,657.8
1,657.8
68.1
68.1
0913
1,151.5
88.7
0913
0913
1,151.5
1,151.5
88.7
88.7
0914
1,860.0
40.6
0914
0914
1,860.0
1,860.0
40.6
40.6
0915
838.6
84.5
0915
0915
838.6
838.6
84.5
84.5
0916
932.4
46.4
0916
0916
932.4
932.4
46.4
46.4
0917
823.4
10.6
0917
0917
823.4
823.4
10.6
10.6
47.3
47.3
47.3
Total
16,493.94
Total
Total 16,493.94
16,493.94
Remark:Remark:AAFFisA
isFforest
forestis forest
area
area
area
Remark:
Code
Code
Code

2006
2006
2006
22 2
AAFF,km
,km
AF,km
%
%%
1,012.8
1,012.8
1,012.8
45.6
45.6
45.6
353.2
44.8
353.2
353.2
44.8
44.8
660.9
43.1
660.9
660.9
43.1
43.1
291.9
48.7
291.9
291.9
48.7
48.7
328.3
55.7
328.3
328.3
55.7
55.7
2,571.8
72.5
2,571.8
2,571.8
72.5
72.5
585.0
75.2
585.0
585.0
75.2
75.2
1,424.8
64.8
1,424.8
1,424.8
64.8
64.8
555.5
53.2
555.5
555.5
53.2
53.2
431.2
17.5
431.2
431.2
17.5
17.5
1,481.0
60.8
1,481.0
1,481.0
60.8
60.8
1,059.0
81.6
1,059.0
1,059.0
81.6
81.6
1,049.6
22.9
1,049.6
1,049.6
22.9
22.9
634.5
63.9
634.5
634.5
63.9
63.9
768.9
38.3
768.9
768.9
38.3
38.3
590.6
7.67.6
590.6
590.6
7.6
13,798.86
13,798.86
13,798.86 39.6
39.6
39.6

40,00040,00040,00027,49027,49027,490MCM
MCM/MCM
year/year/year
ANNUAL
ANNUAL
ANNUAL
35,00035,00035,00022,478
22,47822,478MCM
MCM/MCM
year/year/year
WET
WET WET/year
year/ year DRY
24,97824,97824,978MCM
MCM/MCMDRY DRY
30,00030,00030,00025,00025,00025,00020,00020,00020,00022,54522,54522,545MCM
MCM/MCM/year
year/ year 20,704
15,00015,00015,00017,914
20,70420,704MCM
MCM/MCM/year
year/ year
17,914
17,914MCM
MCM/year
MCM
/year
/year
10,00010,00010,000
4,928
4,928
4,928
MCM
MCM
MCM
/ /yearyear/4,274
year4,274/ /yearyear/ year
4,274
MCM
MCM
MCM
5,000
5,0005,000
4,487
4,487
4,487
MCM
MCM
MCM
/ /yearyear/ year00 0

differential
differential
differential
22 2
AAFF,km
,km
AF,km
%
%%
192.4
192.4
192.4
16.0
16.0
16.0
66.8
15.9
66.8
66.8
15.9
15.9
109.4
14.2
109.4
109.4
14.2
14.2
37.4
11.4
37.4
37.4
11.4
11.4
35.9
9.99.9
35.9
35.9
9.9
217.4
7.87.8
217.4
217.4
7.8
45.4
7.27.2
45.4
45.4
7.2
132.5
8.58.5
132.5
132.5
8.5
59.7
9.79.7
59.7
59.7
9.7
118.0
21.5
118.0
118.0
21.5
21.5
176.8
10.7
176.8
176.8
10.7
10.7
92.5
8.08.0
92.5
92.5
8.0
810.4
43.6
810.4
810.4
43.6
43.6
204.1
24.3
204.1
204.1
24.3
24.3
163.5
17.5
163.5
163.5
17.5
17.5
232.9
28.3
232.9
232.9
28.3
28.3
2,695.1
2,695.1
2,695.1
16.3
16.3
16.3

Runoff,MCMปริมาา,, ล้ล้าา น
ปริRunoff,มาณน้าณน้ํํ าาท่ท่MCM
น ลบ.ม.
ลบ.ม.
ปริRunoff,มาณน้ํ าท่MCMา, ล้า น ลบ.ม.

28,76728,767MCM
MCM
MCM/ /yearyear/ year
ANNUAL
ANNUAL
ANNUAL28,767
WET
WET
WET
23,97823,978MCM
MCM
MCM/ /yearyear/ yearDRY
DRY
DRY 23,978
4,789
4,789
4,789
MCM
MCM
MCM
/ /yearyear/ year2525 252520
252025202530
253025302540
254025402550
255025502560
256025602570
257025702580
258025802590
259025902600
260026002610
261026102620
262026202630
263026302640
264026402650
26502650

FigureFigureFigure7:
7:Runoff
7:
Runoff
Runoffchangeschangeschangesininthe
inthethe
past
past
past
and
and
and
futurefuturefuture
The
The
The
hydrographhydrographhydrographchangechangechangewaswas
was
analyzed
analyzed
analyzed
from
from
from
the
thetherainfallrainfallrainfall
time
time
time
seriesseriesseries
and
and
and
the
thethe
land
land
land
use
useuseandandandrecognizedrecognizedrecognized
thethethechange.
change.
change.
The
The
The
analysisanalysisanalysis
in
in in
each
each
each
zone,
zone,
zone,
comparedcomparedcomparedthethetheaverageaverageaverageannualannualannualrunoffrunoffrunoffbetweenbetweenbetween
beforebeforebefore
1993
1993
1993
and
andand
after
after
after
1993,
1993,
1993,
showedshowedshowedthethethehigherhigherhigher
peak
peak
peak
and
and
and
one
one
one
month
month
month
shift
shift
shift
due
due
due
to
to thetothethequickerquickerquicker
rainfallrainfallrainfall
and
and
and
the
thethe
land
land
land
use
useusechangechangechangeasasshown
as
shown
shown
in
inFigurein
FigureFigure
8.
8. 8.
Table
Table
Table
44 Runoff
4Runoff
Runoffchangeschangeschangesinineach
in
each
each
zone
zone
zone
of
ofpresentofpresent
present
andand
and
futurefuturefutureconditions
conditions
conditions
seasonseasonseason zone
zone
zone

Runoff,
Runoff,
Runoff,
MCM
MCM
MCM
%
%different%
different
different
past
past
past
Near
Near
Near
Far
FarFar Near
Near
Near Far
FarFar1979-1993
1979-1993
1979-1993 1994-2008
1994-2008
1994-20082015-2039
2015-2039
2015-2039
2075-2099
2075-2099
2075-2099
past
past
past
AnnualAnnualAnnual UU U
12,498.9
12,498.9
12,498.9 15,438.1
15,438.1
15,438.1 12,467.7
12,467.7
12,467.7 14,430.0
14,430.0
14,430.0 -19.2-19.2-19.2 -6.5
-6.5-6.5
MMM
1,636.1
1,636.1
1,636.1
1,853.3
1,853.3
1,853.3 4,271.5
4,271.5
4,271.5 4,873.9
4,873.9
4,873.9 130.5
130.5
130.5163.0
163.0
163.0
LL L
8,343.2
8,343.2
8,343.2
9,981.8
9,981.8
9,981.8 8,239.2
8,239.2
8,239.2 9,463.2
9,463.2
9,463.2 -17.5-17.5-17.5 -5.2
-5.2-5.2
22,478.2
22,478.2 27,490.4
27,490.4
27,490.4 24,978.4
24,978.4
24,978.4 28,767.2
28,767.2
28,767.2 -9.1
-9.1-9.1 4.6
4.64.6Basin
Basin
Basin 22,478.2
drydrydryUU U
1,666.0
1,666.0
1,666.0
1,830.3
1,830.3
1,830.3 2,140.6
2,140.6
2,140.6 2,410.9
2,410.9
2,410.9 17.0
17.0
17.0 31.7
31.7
31.7

Basin
Basin
water
water
management
management
under
under
land
land
use
useuseandandandclimateclimatechangeschanges
-Nan
-Nan
basin
basin
as
ascasecase
studystudyBasinwatermanagement
under
land
climatechanges
-Nan
basin
as
studyBasinwatermanagement
under
land
use
and
climatechanges-Nan
Basinascasecase
study-

7583
7 7

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Rainy

M
L
Basin
U
M
L
Basin

510.7
2,310.7
4,487.4

522.1
2,575.9
4,928.3

712.1
1,421.5
4,274.3

793.6
1,584.5
4,789.1

36.4
-44.8
-13.3

52.0
-38.5
-2.8

10,807.8
1,119.2
5,987.7
17,914.6

13,599.7
1,548.8
7,396.7
22,545.2

10,327.1
3,559.4
6,817.7
20,704.2

12,019.0
4,080.3
7,878.7
23,978.1

-24.1
129.8
-7.8
-8.2

-11.6
163.4
6.5
6.4

�$

�$

�$

�$

�$

�$

�$

�$

�$

��$$
thn
o ��$$m/M
C ��$$,Mffo
nu ��$$R�����" ' �
'�
��&&
After
1993
Before1993
����" ' ��
��
&&

�

�

�

a)

�0$
�
thn
o
m
/
�0$
M
C
M
,ff
nou �0$
R
�

�

�

�

�

�

�

hydrograph in upper zone����" ' �
'�
��&&
After
1993
Before1993
����" ' ��
��
&&

�

�

�

b)

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�

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�

hydrograph in middle zone����" ' �
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��&&
After
1993
�
�
��" ' ����&&
Before1993thno ��$$m/MCM
ff,o ��$$
nu
R
�
�

�

�

�

�

�

�

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�

c)
hydrograph in lower zone
Figure 8: Hydrograph changes in each zone of Nan Basin

Damage Cost, MB

PichitPhitsanulok
Uttaradit
Nan

1995

1996

1997

1998

1999

2002

2006

Source : DDPM, RID

Figure 9: Flood Damages in each province
2.4 Flood and drought
The effect of land use change and climate change on flood anddrought issue in the study area were assessed by collecting past floodrecords and analyzing water balance in each zone to preject the future
possible drought

8584

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Technologies forfor Urban
Urban Safety
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Cities inin Asia
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New

ICUS Report 56

In In
thethepast,
past,thethedamagedamagecausedcaused
by by
major
major
flood
flood
of of
NanNanbasin
basin
thatthatcoveredcoveredNan,
Nan,
Uttaradit,
Uttaradit,
Phitsanulok
Phitsanulok
andandPichitPichitProvince
Province
were
were
estimated
estimated
in in
each
each
province
province
andand
shown
shown
in in
FigureFigure
9. From
9. Fromthethedata,
data,
it canit can
be be
seen
seen
thatthatdamagedamagein thein the
year
year
1995
1995
waswasthetheworst,
worst,
followedfollowed
by bythethe
year
year
2006
2006
andand2002.
2002.
DamagedDamaged
areas
areas
were
were
mostlymostlyresidential
residential
andandagricultural
agriculturalareas.
areas.
TheThewater
water
deficitdeficitin thein thestudy
study
areaarea
waswasanalyzed
analyzed
to investigate
to investigate
droughtdroughtsituation
situation
from
from
water
water
balancebalanceanalysis,analysis,i.e.,i.e.,
water
water
demanddemandandandwater
water
supply.
supply.
TheThewater
water
deficitdeficit
in in
each
each
subsubbasin
basin
waswas
shown
shown
in in
Table
Table
5. 5.TheThehighesthighestwater
water
deficitdeficitareaareaof present,of present,
near
near
futurefutureandandfar farfuturefutureis inis thein the
lower
lower
zone
zone
where
where
thethelarge
large
irrigation
irrigation
areas
areas
arearelocated.
located.
Table
Table
5 Water
5 Water
deficitdeficitin eachin eachsubsubbasin
basin
andandzone
zone
PastPast
1979-2008
1979-2008
Near
Near
2015-2039
2015-2039
FarFar2075-2099
2075-2099
Code
Code useuse deficit
conditio
conditio useuse deficit
conditio
conditio useuse deficit
conditio
conditio
deficitdeficitdeficit

MCM/
MCM/
MCM/
MCM/ n n MCM/
MCM/
MCM/
MCM/ n n MCM/
MCM/
MCM/
MCM/ n n
95.31 1.6 1.6
r r 80.68
80.68 0.660.66
93.32
93.32 0.290.29
0902
0902 95.31
7.367.36 0.070.07
9.869.86 0.020.02
0903
0903 8.798.79 0.150.15
70.77 1.041.04
64.37
64.37 5.685.68
62.79
62.79 6.356.35
0904
0904 70.77
14.18 0.150.15
19.36 0.090.09
11.33
11.33 0.050.05
ย ย 19.36
0905
0905 14.18
24.66 6.296.29
19.56
19.56 0.290.29
29.18
29.18 0.050.05
0906
0906 24.66
10.53 0.050.05
7.297.29 0.060.06
7.177.17 0.040.04
0907
0907 10.53
22.37 0.810.81
14.42
14.42 0.170.17
13.83
13.83 0.040.04
0908
0908 22.37
15.28
15.28 0.010.01
10.92
10.92 0.020.02
0909
0909 18.318.3 0.460.46
26.97 4.1 4.1
20.24
20.24 0.870.87
18.06
18.06 0.950.95
0910
0910 26.97
795.4650.73
50.73
713.16713.1630.23
30.23
801.28801.2830.77
30.77
0911
0911795.46
94.68 7.417.41
83.22
83.22 3.533.53
87.03
87.03 2.672.67
0912
0912 94.68
48.65 7.887.88
44.03
44.03 3.953.95
47.23
47.23 3.413.41
0913
0913 48.65
450.6136.56
36.56
466.04466.0441.99
41.99
461.82461.8239.73
39.73
0914
0914450.61
24.54 0.010.01
22.56
22.56 0 022.322.3 0 00915
0915 24.54
5.565.56 0.030.03
5.075.07 0 00916
0916 5.695.69 0.050.05
1479.33232.08232.081634.83
1634.83279.24279.241686.41
1686.41270.05270.050917
09171479.33
291.9 14.65
14.65
248.55248.55 7.9 7.9
256.48256.48 7.827.82
upper
upper291.9
938.7866.02
66.02
840.41840.41 37.737.7
935.55935.5536.85
36.85
middlemiddle938.78
1960.16268.7
268.7
2128.992128.99321.27321.272175.592175.59309.79309.79lower
lower1960.16
3190.84349.36349.363217.95
3217.95
366.87366.873367.623367.62354.46354.46
Basin
Basin3190.84

Remark:Remark:highhigh

middlemiddle

lower
lower

none
none

4. TRMM
4. TRMMAPPLICATIONAPPLICATION
In orderIn orderto betterto better
water
water
operation
operationin thein theNanNanBasin,
Basin,
thetheflow
flow
estimate
estimatefromfromungagedungagedsubsubbasinsbasinsis essential
is essential
to help
to help
save
save
water
water
releasereleasefromfromthethe
dam.
dam.
To To
analyze
analyzethisthissidesideflow
flow
of subof subbasin
basin
in middle
in middlezone
zone
of Nanof Nanbasin,
basin,
datadata
duringduringSepSep30 30
to Octto Oct31,31,
2006
2006
were
were
used
used
to testto testthetheapplication
applicationof TRMMof TRMM
data.
data.
TheThe
TRMM
TRMM
data,
data,
used
used
KalmanKalmanfilter,filter,waswasestimated
estimatedin eachin eachgridgrid
andandcomparedcomparedwithwithobserved
observed
datadata
distributed
distributedin eachin eachgridgrid
by bythetheThiessenThiessenmethod.
method.
FigureFigure10 10
showedshowedthethecomparison
comparison
of ofobserved
observed
andandfilteredfiltered
TRMM
TRMM
rainfallrainfalldatadata
withwiththethecorrelation
correlationof 0.8of 0.8andandRMSE
RMSE
of 3.6of 3.6which
which
is acceptable
is acceptable
to be
to be
used
used
forforfurtherfurtherrunoffrunoffanalysis.
analysis.
TheTheestimated
estimated
runoffrunoff
(side
(side
flow,
flow,
FigureFigure11 11b))b))
in inthethestudy
study
areaarea
from
from
TRMM
TRMM
filteredfiltered
datadata
waswascomparedcompared
withwiththetheactualactualdatadata

Basin
water
management
under
landlanduseuseandandclimatechanges-Nanbasin
as casestudyBasinwatermanagement
under
climatechanges-NanbasinasascasestudyBasinwatermanagement
under
land
use
and
climatechanges
-Nan
Basin
case
study-

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October 2011, Chiang
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Thailand
Chiangmai,(Figure 11 a)) and found that the side flow volume from filtered TRMM
gave acceptable side flow volume.
This method showed that the filtered TRMM rainfall pattern can beused to estimate runoff volume in ungage basin and help dam operator tosave water release of both dry and wet season. Such tool can be applied forbetter water management and flood early warning in the future.
3530

y = 0.8x

25
m
m 20
,
M
M15
R
T
10
5
0
0

5

10

15

20

25

30

35

Rain Gage, mmb) Comparisons between rain
gage and TRMM filtered dataa) Locate of TRMM grid and rain
gage stations

Figure 10: TRMM Grid and its correlation
1200
RAINFALL

1000

ReleaseSRKNarasuan_dam

s800
m
c
,
e
gr600
a
h
sci
D400

side_flow

200
0
6
0
/
9
0
/
0
3

6
0
/
0
1
/
5
0

6
0
/
0
1
/
0
1

6
0
/
0
1
/
5
1

6
0
/
0
1
/
0
2

a) actual side flow

6
0
/
0
1
/
5
2

6
0
/
0
1
/
0
3

0

1200

0

20

1000

TRMM_sim

20

40

m
m
,
60 lla
f
in
a
R
80

s800
m
c
,
e
gr600
a
h
sci
D400

side_flow

40

100

200

120

0

m
m
,
60 lla
f
in
a
R
80
100
120

6
/0
9
0
/
0
3

6
/0
0
1
/
5
0

6
/0
0
1
/
0
1

6
/0
0
1
/
5
1

6
/0
0
1
/
0
2

6
/0
0
1
/
5
2

6
/0
0
1
/
0
3

b)side flow estimated from TRMM
data

Figure 11 Side flow pattern estimated from TRMM data
5. CONCLUSIONS AND RECOMMENDATIONThe study concluded that land use change affected runoff volume. Thechange in forests area influenced the runoff change. The deforestation was
effected from the growth of the economic in basin which caused theincrease in the agriculture area. The decreasing forest area in the basin
affected the increase of runoff coefficient and decrease of total runoff as an
impact chain. There is a need to find a balance between cultivated10586

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area and forest area in the upper watershed. The study can be used as a data
to determine the balance of natural resource utilization and socioeconomical development in the more sustainable manner in the future forthe study area.
Runoff had been changed in volume and hydrograph in near future
will decrease while increase in the far future than present. Hydrograph peak,shifted about 1 month quicker when compared between before 1933 andafter 1993, became higher due to the shift of rainfall pattern.
The TRMM data with the Kalman filter algorithm and GIS techniquegave acceptable rainfall data compared with rain gage data and the runoff
from ungage sub basin using TRMM data gave also good correlation withthe observed. The TRMM satellite data and technique gave future potential
as a new tool for water management of both dry and wet season to alleviate
drought and reduce flood.
The present study used monthly hydrological data of each sub basin
for analysis with two year of land use data as available. In future if moreland use data is available, the trend and rate of land use change can be
determined more properly which will make the study more precised.
ACKNOWLEDGEMENT
We would like to thank to the agencies that provided important data
and digital information, e.g., Land Development Department, RID, TMD,JAXA etc. and also to Thailand Research Fund as research funding andChulalongkorn University for research unit funding.
REFERENCES
Chow, V., D. Maidment, and L. Mays, 1988. Applied Hydrology,
McGraw-Hill International Edition, Singapore, 572 p.
Chulalongkorn, 2011, Strategic Water Management Planning in Nan
Basin, Progress Report, submitted to Thailand Research Fund, August.
Singh, V., 1992. Elementary Hydrology, Prentice Hall, New Jersey,
973 p.
Singh, V., 1988. Hydrologic Systems Volume I Rainfall-Runoff
Modeling, Prentice Hall, New Jersey, 480 p.
Singh, V., 1988. Hydrologic Systems Volume II Rainfall-Runoff
Modeling, Prentice Hall, New Jersey, 480 p.
Sucharit K. and Chaiyuth S., 2011, GCM Data Comparison and Its
ApplicationtoFloods/Droughts Adaptation, The Second International Conference on
Sustainability Science in Asia’ (ICSS-Asia2011), 2-4 March, Hanoi, Viet
Nam
Sucharit K. and Kwanchai P., 2011, The Effect of Land Use Change
on Runoff in The Nan Basin, Proc. SSMS2011, Sri Lanka, Sep 14-15.

Basin waterBasinwater management
management under
under land
land use
use andand climate
climate changes
changes-Nan-Nanbasin
Basinasascase
casestudystudy-

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Thailand
Chiangmai,

Tripathi, M., P. Shrivastava, and S. Dwivedi, 2003. HydrologicalModeling of A Small Watershed Using Satellite Data And GIS, Journal of
the Indian Society of Remote Sensing, 32(1):313-329

12
588

New Technologies
Technologies forfor Urban
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Cities inin Asia
Asia
NewRelationship among response, recovery
and development from the view pointof financial resource allocation
Yasuhito JIBIKI
Project Assistant Professor, CIDIR, III, the University of Tokyo, Japanjibiki.yasuhito@iii.u-tokyo.ac.jp
ABSTRACT
Relationship between response, recovery and development is verified fromthe view point of financial resource allocation.
It has been emphasized that development is the highest priority for them andshould not be undermined by response and recovery, thus it is important toprovide sufficient resource to response and recovery activities against
disasters. In addition, the concept of the disaster management circle isconsidered to implicitly assume or anticipate that good response leads good
recovery, and good recovery contributes development. In other words,
certain linkage can be found between response, recovery and development.
Based on the relationship between these three phases, a hypothesis might bereasonable; amount of money disbursed for response, recovery anddevelopment to affected countries has correlation with each other. Affected
countries receive financial assistance, depending on the extent of the loss,
damages and their own vulnerability. A positive correlation could beobservable; the more financial support is demanded for response, the more
aid is required for recovery and development. In order to verify the
hypothesis, financial data from three major funds is employed; the Central
Emergency Response Fund (CERF), the Trust Fund for Human Security(TFHS), and Global Facility for Disaster Reduction and Recovery(GFDRR). CERF mainly provides its resource to response activities. TFHS
and GFDRR distribute their resource to efforts for recovery anddevelopment.
As a result of empirical statistical analysis, only the linkage of response andrecovery is significantly observed.
Keywords: financial resource allocation, development
1. INTRODUCTION: Backgrounds and Purpose
1.1 Backgrounds
This article examines relationship between response, recovery anddevelopment, from the view point of financial resource allocation.

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In the field of global environment, the relationship between resource
allocation and development has been argued for decades. Developing
countries have been insisting that their first priority is development.
Although these countries have shown their understandings to the importanceof global environment, they have been repeatedly emphasizing that their“right to development” should be fully taken into consideration in thecontext of environmental protection (Williams, 1997; Kasa et. al, 2008).
Based on this preoccupation, developing countries have been
demanding additional resource provision from developed countries (Miller,
1995b; Williams, 1997; Streck, 2001; Najam, 2002; Najam, 2004; Roberts
et. al, 2007; Boyd et. Al, 2008). It has been claimed by developing countries
that efforts for the environmental protection should not hamper actions andresource allocation for development. Developing countries have been
concerning that their limited resource is divided and invested both toenvironment issues and development. Without any additional assistance, itis predictable that their limited resource becomes scarce in the end, anddevelopment as their first priority is not achieved.
Similar to the field of global environment, the relationship between
resource allocation and development has also been discussed in the arena of
humanitarian assistance. The United Nations General Assembly Resolution
64/251 in 2009 stressed the significance of “…the timely provision ofhumanitarian assistance through all phases of a disaster, from relief andrecovery to development, including the provision of adequate resources.”
Additionally, the linkage of response, recovery and development was statedin the United Nations General Assembly Resolution 48/192 in 1991, and theresolution reaffirmed that efforts to emergency are required to be recognized“as a step towords long-term development.”
Additionally, a concept of the disaster management circle isconsidered to implicitly assume or anticipate that good response leads good
recovery, and good recovery contributes development. In other words,
certain linkage can be found between response, recovery and development.
1.2 Purpose
Based on discourses of the relationship between resource allocationand development, and the linkage of these three phases, a hypothesis might
be reasonable; amount of money disbursed for response, recovery anddevelopment to affected countries has correlation. It seems that affected
countries receive financial assistance, depending on the extent of the loss,
damages and their own vulnerability. A positive correlation could beobservable and testified; the more financial support is demanded for
response, the more aid is required for recovery and development.
In the following sections, a method for verification of hypothesis isnoted in the section 2. The Section 3 demonstrates results of calculation inline with data described in the Section 2. The Section 4 concludes the results
obtained at the Section 3 and discusses what these results mean.

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Prior to start analyzing, definitions of terms are needed to be clarified.
This inquiry employs a limited definition of the term “resource” andspecifically uses the resource as financial resource. In this article,
humanitarian assistance treats both natural and man-made disasters, since
financial institutions do not separately distinguish these two types ofdisasters.
2. METHOD
2.1 Source of data
In order to examine the hypothesis stated in the Section 1.2, a data setof this paper is prepared. The data set contains eight variables compiled
from sources mentioned below.
The data from financial resource is gathered from three major funds;
the Central Emergency Response Fund (CERF), Global Facility for Disaster
Reduction and Recovery (GFDRR), and the Trust Fund for Human Security(TFHS). CERF and TFHS were managed by the United Nations. GFDRR is
operated and coordinated by Word Bank and the United Nations.
CERF mainly provides its resource to response activities. Based on
the United Nations Resolution 48/192 in 1991, the Central Emergency
Revolving Fund (old CERF) was established. In 2006, the fund wasreformed in the part of Humanitarian Reform, and the name and the types ofprovision of the fund were changed. The grants of new CERF consist bothof Rapid Response and Under Funded Emergency. In this article, the data of
Rapid Response and Under Funded Emergency from CERF is dealt as
financial resource for response.
GFDRR allocates its financial resource both to recovery anddevelopment. GFDRR was established in 2006. GFDRR has several
financial services, but in this article the data of its Track-II and Track-III isadopted. GFDRR Track-II mainstreams disaster risk reduction indevelopment, and GFDRR Track-III provides standby recovery financing
facility for accelerated disaster recovery (GFDRR, 2010). In this paper, thedate of GFDRR Track-III is recognized as financial resource fordevelopment and GFDRR Track-II is coped as recovery resource.
TFHS was founded in 1999. Referring its “Key funding criteria” andthe titles of projects, the fund is considered to tend to disburse its resource toprojects relating with development (MOFA of Japan, 2009). Thus, in thisarticle, the data of TFHS is regarded as financial resource for development
In comparison with these three funds, data of the number of affected people
by disasters is added. From the data base of EM-DAT, the number of theaffected population by natural disaster is organized. In addition, the data ofinternally displaced people (IDP) caused by conflicts and violence is also
consolidated into the data set. The figure of IDP is taken from a data set
managed by Internal Displacement Monitoring Centre and Norwegian
Relationship between response, recovery and development from the view point of financial resource
Relationship among response, recovery and development from the view point
allocationof financial resource allocation

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Refugee Council, since that data set is known as the most comprehensivedata.
2.2 Procedure for developing the data set
A variable “Response” is an accumulated number of CERF grants
from the year of 2006 to 2010. From 2006 to 2010, the provision of the
grants has been reached 79 affected countries.
A variable “Recovery” is a summed number of GFDRR Track-III
from the year of 2006 to 2010. If the resource is allocated to several
countries or to regional level, such a data is not included, since it is notpossible to specify that each country receives accurate amounts of money.
From 2006 to 2010, the provision of the grants has been reached 22 affected
countries.
Variables for “Development” have three types. The first variable is an
accumulated number of GFDRR-II from the year of 2006 to 2010. As is in
the case of GFDRR Track-II, if the resource is allocated to several countries
or to regional level, such a data is not included, since it is not possible tospecify that each country receives accurate amounts of money. 43 countries
received assistance individually from GFDRR Track-II. The second variable
is a summed number of TFHS from the year of 2006 to 2009. The TFHS
data in 2010 is not available. As is in the case of GFDRR Track-II and
Track-III, if the resource is allocated to several countries or to regional level,such a data is excluded, since it is not possible to specify that each country
receives accurate amounts of money. 39 countries received assistanceindividually from TFHS. The number of recipient countries by funds is
described in Table 1 below. Finally, the third variable is aggregated as thesummed number of GFDRR Track-II and TFHS.
Table 1: The number of recipient countries by funds
Countries obtained CERF only
Countries obtained GFDRR Track-III only
Countries obtained GRDRR Track-II only
Countries obtained TFHS only
Countries obtained ALL 4 funds listed above
The total number of recipient countries

The number
countries

ofrecipient
30
1
9
9
5
102

The data of the affected people by natural disasters and IDP by
conflicts and violence are compiled from the year of 2006 to 2010. And, one
variable is set as the accumulation of the data of the affected people bynatural disasters and IDP by conflicts and violence.
All figures are organized by counties in the data set. If counties do notreceive any resource from funds, or do not have the affected population by
natural disasters or IDP by conflicts and violence, a cell of the data set is not
filled by “zero (0),” but treated as a deficient value.

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3. RESULTS
Table 2 in the next page provides summary statistics for eight variables usedin the empirical analysis. The results of mean, median and standard
deviation indicate that the figures in the data set are varied widely.
Therefore, when correlation between variables is estimated, not only
Pearson product-moment correlation coefficient as the parametric method,
but also Spearman's correlation coefficients as the non-parametric method
are calculated.
Table 3 illustrates the two types of the correlation analysis. The resultsof Pearson product-moment correlation analysis reveal that the relationshipbetween the variable “Response” and “Recovery” has positive correlationand it is statistically significant. Also, the correlation between the variable“Recovery” and “Development 2” is statistically significant, but it isnegative relationship.
Table 2: Summary statistics

Variable
Number ofStandard
MeanMedianNameobservation
deviation
1. Response
79
23413201.00
9859577.00
33590169.89(CERF)
2. Recovery
22
432083.95
208807.00
629316.84(GFDRR Track-III)
3. Development 1
431042211.19
730000.00
1154375.95(GFDRR Track-II)
4. Development 2
392682150.92
2399820.00
1507815.94(TFHS)
5. Development 3
692165492.28
1504073.00
1739655.74(Sum of No.3 and No.4)
6. The affected people
98
10931646.51
546547.00
69111688.76
by natural disasters
7. IDP by conflicts and
412719221.95
890000.00
5382081.61
violence
8. Total affected number
100
11827894.58
806489.50
68487649.86(Sum of No.6 and No.7)* The unit of figure for Response, Recovery, Development 1, Development 2 andDevelopment 3 is US$.

Relationship between response, recovery and development from the view point of financial resource
Relationship among response, recovery and development from the view point
allocationof financial resource allocation

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Table 3: Results of correlation analysis
Variables
1. Response
2. Recovery
3. Development 1
4. Development 2
5. Development 3
6. The affected people by natural disasters
7. IDP by conflicts and violence
8. Total affected number*** p <.01** p <.05

Pearson product-moment correlation coefficient
3
4
5
6

1

2

1.00
.46 *
.10
.28
.25
-.01
.39 **
.02

－
1.00
-.04
-.53 *
-.34
.01
.07
.01

1

2

1.00
.46 *
.04
.10
.03
.35 ***.51 ***.54 ***

－
1.00
.14
-.48
-.31
.05
-.20
.04

－
－
1.00
-.10
.64 ***
.04
-.08
.04

－
－
－
1.00
.91 ***
-.04
.11
.07

－
－
－
－
1.00
-.07
-.02
-.07

－
－
－
－
－
1.00
.03
1.00 ***

7

8

－
－
－
－
－
－
1.00
.41 ***

－
－
－
－
－
－
－
1.00

* p< .10

Variables
1. Response
2. Recovery
3. Development 1
4. Development 2
5. Development 3
6. The affected people by natural disasters
7. IDP by conflicts and violence
8. Total affected number*** p <.01** p <.05* p< .10

Spearman's correlation coefficients
3
4
5
6
－
－
1.00
-.09
.62 ***.34 **.14.39 ***－－－
1.00.90 ***
-.11
.06
.06

－
－
－
－
1.00
.02
-.04
.10

－
－
－
－
－
1.00
.34 **.87 ***

7

8

－
－
－
－
－
－
1.00
.70 ***

－
－
－
－
－
－
－
1.00

The results of Spearman's correlation coefficients demonstrate that therelationship between the variable “Response” and “Recovery” has a positive
correlation and it is statistically significant. On the contrary, the correlation
between the variable “Recovery” and “Development 2” is not statisticallysignificant.
In addition with these two types of the correlation analysis, partial
correlation is calculated. In the partial correlation analysis, the variables“The affected people by natural disasters,” “IDP by conflicts and violence”
and “Total affected number” are employed as control variables, since threevariables have significant relationship with “Response.”
The results of the partial correlation analysis shows that the significant andpositive relationship between “Response” and “Recovery.” In the casebetween “Recovery” and “Development 2,” the relation is not observed
statistically significant.
Table 4: Results of partial correlation analysis
Partial correlation
coefficient
by Response
andRecoveryby Recovery andDevelopment 2*** p<,01** p<.05

6594

Control Variables
The affected people by
IDP by conflicts
natural disasters
and violence

Total affected
number

.46*

.53

.46*

.12

-.99

-.54

* p<.10

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4. CONCLUSION AND DISCUSSION
The relationship between resource allocation and development and thelinkage of these three phases in humanitarian assistance is argued in thisarticle. As the results of statistical analysis, only the linkage between
response and recovery is verified. According to the results of Spearman's
correlation coefficients, the variable “Response (CERF)” and “Development1(GFDRR Track-III)” positively correlate with the number of the affected
population by natural disasters, conflicts and violence. However, from theviewpoint of resource allocation, it is concluded that response and recovery
do not significantly relate with development. Thus, it is considered that
financial provision to each disaster phases are recognized as not a continuity
process, but separated.
In order to verify the result of the paper, further inquiries are required
to be done. This article presents a macroscopic trend at national level, but it
is necessary to examine whether each projects or programs in specific sites
have the linkage from response to development at field level.
Additionally, management of the funds is to be studied. In the field ofglobal environment, transparency for management of Global Environmental
Facility (GEF) has been severely discussed (Streck, 2001; Najam, 2005;
Roberts et.al, 2007). Comparing with GEF, the total amount of funds fordisaster is limited. However, it seems important particularly for recipient
countries to investigate the transparency of the funds.
REFERENCES
Boyd, E., Corbera, E., and Estrada, M., 2008, UNFCCC negotiations(pre-Kyoto to COP-9): what the process says about the politics of CDMsinks, International Environment Agreements, Vol.8, 95-112.
GFDRR,
2010,
AnnualReport2010.
http://www.gfdrr.org/gfdrr/sites/gfdrr.org/files/publication/GFDRR_annual_repo
rt_2010.pdf [Accessed on 1st September 2011]
Kasa, S., Gullberg, A.T., and Heggelund, G., 2008, The Group of 77
in the international climate negotiations: recent developments and future
directions, International Environment Agreements, Vol.8, 113-127.
Miller, Marian, A.L., 1995, The Third World in Global Environmental
Politics. Buckingham: Open University Press.
MOFA (Ministry of Foreign Affairs) of Japan, 2009, The Trust Fundfor Humanitarian Security: For the "Human-centered" in 21st century.
http://www.mofa.go.jp/policy/human_secu/t_fund21.pdf [Accessed on 1st
September 2011]
Najam, A., 2005, Developing Countries and Global Environmental
Governance: From Contestation to Participation to Engagement,International Environmental Agreements, Vol.5, 303-321.
Najam, A., 2002. Unravelling of the Rio Bargain, Politics and the Life
Sciences, Vol. 21, No.2, 46-50.
Najam, A., 2004, Dynamics of the Southern Collective: Developing
Relationship between response, recovery and development from the view point of financial resource
Relationship among response, recovery and development from the view point
allocationof financial resource allocation

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Thailand
Chiangmai,

Countries in Desertification Negotiations, Global Environmental Politics,
Vol.4, No.3, 128-154.
Roberts, J. T., and Parks, B. C, 2007, A climate of injustice global
inequity, North-South politics, and climate policy. Mass: MIT Press,
Cambridge.
Streck, C., 2001, The Global Environmenta Facility - a Role Modelfor International Governance?, Global Environmental Politics, Vol.1, No.2,
71-94.
Williams, M., 1997, The Group of 77 and Global Environmental
Politics, Global Environmental Change, Vol.7, No.3, 295-298.

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NewDevelopment and applicationof triage system (TRACY)
Muneyoshi NUMADA1, Yasunori HADA2, Miho OHARA3
and Kimiro MEGURO4
1
Research Associate, ICUS, IIS, The University of Tokyo, Japannuma@iis.u-tokyo.ac.jp
2
Associate Professor, Department of Education Interdisciplinary Graduate
School of Medicine and Engineering, University of Yamanashi, Japan
3
Associate Professor, ICUS, IIS, The University of Tokyo, Japan
4
Professor, ICUS, IIS, The University of Tokyo, Japan
ABSTRACTThis research developed an IT triage system for collecting disaster medical
information in real time and sharing it among related institution in entire
area. FeliCa card and card-reader are used to constitute of this system toobtain the number and condition of patients etc. in real time.
There are advantages by applying FeliCa on the daily basis to the triage.
For example, the database of the personal information such as name, dateof birth and address for the daily service can be applied for the triage torecognize the each patient in the disaster by using FeliCa ID. In this case,the hospital is not required to ask the patient for the personal informationand can be understand the patient personal data who cannot speak due toheavy injury. As there are many people who have the FeliCa for daily
service, therefore hospitals are not necessary to ready the FeliCa card inadvance for all unpredictable large number of patients.
The unique serial number of FeliCa can be considered as the patient ID.
Therefore the hospitals and other related institution can easily share andmanage the patient transfer by using FeliCa ID for the entire region.
FeliCa reader and PC for pass-processing are set at triage zone and eachzone such as Black (deceased), Red (immediate), Yellow (delayed) andGreen (minor), and the department of medicine and radiation. PC and
FeliCa reader at the each point for pass-processing can record the patient’s
zone pass time and location in the database server.
In the case for example, that the symptoms of patient is changed to theworse, the latest triage level can automatically be update in database server
without special work or operation by conducting the usual pass processingin this system. This is same case, even if the symptoms improve.
A disaster drill was held at the Yamanashi University Hospital with 450
participants. TRACY was examined its availability and practicability byusing in this drill. From the result of that, the present system can obtain the5971

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number of patients for each triage level and the accepted number of patientsin each diagnosis and treatment department in real time, including response
for changing triage level and the people looking for their family in hospital.
In the point of the information sharing in the entire area, the patient’s
information can be shared among hospitals, the administration, andresidents in real time.
Keywords: triage, disaster management in hospital, TRACY, real-time
information, information sharing
1. INTRODUCTION
Disaster medical care during accidents and disasters both large and small iscarried out with less medical resources in normal situations.
Disaster medical care consists of triage, transport and treatment. In thecase of a disaster or accident, it is necessary to exert maximum effect withlimited medical resources, but to accomplish these hospitals need toestimate the expected number and condition of patients. The advancementof triage, including understanding and ensuring the capacity of beds,
tracking the status of patients’ visits and transport to other hospitals,
managing the assignment of the appropriate medical staff and the
distribution of medical materials is necessary. On the other hand,
information sharing is important effective acceptance and transportation.
These actions are required across the entire region outside the hospital for
setting up the disaster headquarters, coordinating all tasks with thegovernment and other hospitals, and supporting the patients’ family andmedia.
To advance the triage, it is necessary to obtain patient information,such as the victim’s status and number staying at hospital, discharging from
hospital, and being transported to other hospital, in digital form and in realtime.
Research using a digital pen with triage results can digitize patient
information (Ashida et al. 2008). However, it is difficult to manage patient
status when triage level is changed and to understand the number of patient
in different triage levels. In addition, the usage of RFID tags and mobile
RFID network equipment collection system can collect the patient
information using mobile devices in real time (Sonoda et al. 2007, Kusuda
et al. 2009), but it is necessary to overwrite data when the triage level ischanged so the management is complicated. Furthermore, the flow line ofpatients cannot be confirmed when patients are moved between departments.
For information sharing across an entire region, an information sharing
system has been built to consolidate all kinds of information related todisaster conditions (The Ministry of Health and Welfare Health Policy
Bureau 1996). With this system, staffs are necessary for entering the data inthis system, but it is difficult to assign staff under the limited conditions
during a disaster.

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The purpose of this study is to develop a triage system which cancollect and share the disaster medical information in real-time amonghospitals including emergency medical institution both inside and outside
the disaster area, with residents and with the government. In order toexamine the feasibility and effectiveness of this system, it was applied to alarge-scale disaster drill with 450 participants at the Yamanashi University
Hospital.
Using this system, it is possible to estimate the number of patients indifferent triage levels in real time, to identify the number of patients visiting
each department, to manage the triage level changes in real time and toshare this information with related institutions across an entire region
including people looking for their family in hospitals.
2. PROBLEM SETTING
Traditional triage problems are summarized from the result of the triage drill
held at Yamanashi University Hospital.
2.1 Summary of triage
A triage team normally consists of the triage officer, nurse and support
staff. The team conducts the triage in front of the hospital building. Patientstaken to the triage are transferred to the treatment zones: the mild zone
(green), the moderate zone (yellow), the severe zone (red) and death zone
(black), depending on the level of injury. If the hospital cannot treat thepatient with heavy injuries or due to lack of resources, the patient istransferred to another other hospital.
2.2 Triage problem
The following problems with the current triage method were obtained
from the result of the triage drill at Yamanashi University Hospital.
2.2.1 Real-time information
It takes a certain amount of time for the disaster headquarters to know
the latest patient information such as the number of accepted patients andthe number of patients in the different triage levels because the copy of thecurrent triage tag containing patient information such as name, age, etc. andtriage level is carried by volunteer staff to the headquarters after a certain
amount of information is collected in each zone. Furthermore, it takes time
to copy the information to the patient’s list handwriting one by one. In
addition, patient information is written on a white board in front of thehospital near the triage zone to for people looking for their family in
hospitals.
Therefore, it is difficult to grasp the number of patients in real timeand assign the proper medical staff to the each zone in this triage method.
When there is a change of triage level, the management of its change is very
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difficult to update in real time. Also, some staff needs to work only for the
management of patient’s list. It can be wasted work under the limited
resources of medical staff in the disaster.
2.2.2 Information sharing with other medical institutions
It is necessary to determine that; the patient needs to be transferred toother hospitals by such as the doctor helicopter, because of the heavy statusof patient or the luck of hospital’s resources. However, hospitals which needto transfer the patient cannot make a plan of transference of patient. Because
hospitals don’t know which other hospitals can accept the patient. On theother hand, the accepting hospital management also doesn’t understand thestatus of coming patients.
The information sharing among related medical institutions isnecessary for the effective transport in the entire region.
2.2.3 Information sharing with the family and government
The people look for the location of hospital in which their family is
accepted due to the injury in the disaster. The hospital and the government
asked by the people need to answer the location of hospital and the status of
the family.
However, immediate response is difficult for the hospital in a situationof a huge number of patients. Because they cannot search the patient whom
the family looking for in the paper-based patient’s information and it takes acertain time to obtain the latest information.
In the point of the local government, even if the government needs to findthe family where they are, the local government has to ask the possible
hospitals one by one.
This situation is inefficient for all the relations, the family, the hospitaland the government.
3. IT TRIAGE SYSTEM (TRACY)TRACY has been developed as the triage system to solve the traditional
problems observed in the result of triage drill and the things discuss asmentioned above. The structure and framework of this present system has
been set after several interview and meetings with doctors and nurses inemergency department. This section describes the overview of this system.
3.1 System framework
We discussed the obtaining patient’s information in real time and thesharing it in the whole area as main features. The obtained patient’s
information including the location, triage level and status of patient need to
be updated in real time. It is effective and efficient to share the information
for the patient transference to the other hospital. On the other hand, there aresome advantages in traditional triage tag. When we need to know the

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patient’s information such as name, age and triage level, the current triage
tag can show those by seeing it without special operation. Therefore, bothpresent system and current paper based triage tag are used.
We discussed when the triage level change the information about
triage level also should be changed without special operation of the system
in real time. If there is a change of triage level of the patient such as patientmoves to the new triage zone. When the patient arrive the entrance of the
new zone, we proposed that the change can be recorded by the usual passprocessing used in present system. This method can update the triage levelautomatically without special and/or additional work. This method also canconfirm the movement of the patient correctly.
To respond quickly to the people who are searching for their family
member in the hospital, the staff can search the patient by using the searchfunction of present system in the patient list. In addition, if the list can sharein the whole area, it is beneficial for the government and the family living
far from disaster area.
We discussed that it is important to conduct the effective transportingin the entire region. This could be done by understanding the condition of
accepting patients in other hospital and then to decide whether thetransporting is available. Therefore, the present system is required to show
the condition of all related hospitals to decide the available transportation in
the entire region.
3.2 Discussion of equipment
The following three points in selecting the equipment for this systemwere considered. 1) Using the equipment on a daily basis, because otherthan daily-life equipment does not work in a disaster. 2) Using low-costequipment in order to spread to the lot of hospitals under the current
economic condition for sharing information in entire area. 3) Using simpleoperating equipment that is not required the special training for operation
only for the disaster.
First, we discussed a handheld wireless UHF IC tag reader/writer thatcan write the patient information to the tag. But when the medical staff try
to know the patient’s information in the IC tag, the special operation isrequired. In addition to that, for the sharing information of patient in theentire area, same equipment is necessary to install in all related hospitals. In
the consideration of cost, the writing function of the patient information to
IC tags/cards is not the low-cost option.
Therefore, the concept of this system is to manage the patient’s
information in the server side. Then, the three method, IC tag, bar codes andFeliCa, were discussed how to recognize the patient ID. The IC tag is
expensive, even for the models without the function of a tag writer. For bar
codes, we have to consider the accuracy of reading the bar code, thepreparation of bar codes in advance and the problem of cost. As the result ofDevelopment andDevelopment
and Application
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Chiangmai,these factors, the bar code is actually difficult to apply to the management ofpatient for triage. For FeliCa, USB-friendly FeliCa reader can be purchased
at lower prices. It is available to use the PC, which is used on the daily
treatment in hospitals, for connecting it. In addition, FeliCa cards are usedby a lot of people for the train pass, student ID, and electronic money on adaily basis. Recently, there is also mobile phone with a FeliCa function.
Therefore, FeliCa can be applied on a daily basis to conduct the triage in thedisaster. The operation is simple "waving the card to the reader" and there ispotential to be expanded further spread.
From the above discussions, FeliCa is used as the configuration of theequipment in this system.
3.3 Constitution of "TRACY"
There are advantages by applying FeliCa on the daily basis to thetriage. For example, the database of the personal information such as name,date of birth and address for the daily service can be applied for the triage torecognize the each patient in the disaster by using FeliCa ID. In this case,the hospital is not required to ask the patient for the personal informationand can be understand the patient personal data who cannot speak due toheavy injury. As there are many people who have the FeliCa for daily
service, therefore hospitals are not necessary to ready the FeliCa card inadvance for all unpredictable large number of patients.
The unique serial number of FeliCa can be considered as the patient
ID. Therefore the hospitals and other related institution can easily share andmanage the patient transfer by using FeliCa ID for the entire region.
Figure 1 shows an overview of this system. FeliCa reader and PC forpass processing are set at triage zone and each zone such as Black(deceased), Red (immediate), Yellow (delayed) and Green (minor), and thedepartment of medicine and radiation. PC and FeliCa reader at the eachpoint for pass processing can record the patient’s zone pass time andlocation in the database server.
In the case for example, that the symptoms of patient is changed to theworse, the latest triage level can automatically be update in database server
without special work or operation by conducting the usual pass processingin this system. This is same case, even if the symptoms improve.
3.4 Content of input item
We consider following kinds of information are necessary for triage in
TRACY.

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Hospital
HospitalAA
TriageTriagezone
zone

FeliCaFeliCareaderreaderTabletTablet
PC PC

Mild
Mild
zone
zone
(green)(green)Moderate
Moderatezone
zone(yellow)(yellow)

Pass-processing
Pass-processing

Patient’s
Patient’s
listlist

Bar-chart
Bar-chart

Details
Detailsof ofpatient
patient

SevereSevere
zone
zone
(red)
(red)
Radiation
Radiation
Medicine
Medicine

Other
Other
hospitals
hospitals

DB
DB

FigureFigure1: 1:Overview
Overview
of oftriagetriagesystemsystem“TRACY”“TRACY”
From
Fromthethehospital
hospitalpoint
pointof ofview,
view,patientpatientpersonal
personalinformation
informationandandmedicalmedicalinformation
information
areare
taken
taken
in in
to to
account
account
as aspatient
patient
detail.
detail.
But
But
this
this
triagetriagesystemsystemonly
onlycovers
coversthethepersonal
personalinformation
information(name,(name,gender,
gender,datedateof ofdate,
date,
etc.)
etc.)butbutnotnotmedical
medicalinformation.
information.Because
Becausemisunderstoodmisunderstoodmedical
medicalinformation
information
may
may
lead
lead
to to
medicalmedicalerrorserrorsandandtroubles.
troubles.
AsAsthetheresult,result,
input
input
items
items
of of
personal
personal
information
information
such
such
as as
name,
name,
date
date
of of
birth,
birth,
age,
age,
address,
address,
and
and
free
free
entry
entry
forforthetheremarks
remarks
areare
read
read
with
with
thethetriagetriage
tag.
tag.
One
One
exampleexample
of of
using
using
remarks
remarks
is is
to to
write
write
thethepatient
patient
exterior
exteriorfeaturesfeatures
such
such
as as
thethe
color
color
of of
shirts,shirts,jacket,jacket,
glass
glass
etc.
etc.
to to
identify
identify
anan
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individual
who
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speak
due
due
to to
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heavy
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injured.
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There
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high
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possibility
to to
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stay
or or
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to to
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other
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hospitals
forforthethepatient
patient
withwiththethe
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of of
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Red
(immediate)(immediate)
andandYellow
Yellow(delayed).
(delayed).
In In
case
case
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those,
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room
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of ofstaying
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hospital
name
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can
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this
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system.
The
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interfaceof ofthethepersonal
personalinformation
informationwindow
windowwas
wasmademadeconsidering
considering
easy
easy
to to
bebe
used
used
byby
hospital
hospitalstaffs.
staffs.
3.53.5Visualization
Visualizationof ofpatient
patient
data
data
at at
thetheheadquarters
headquarters
It Itis isimportant
importantforforthetheforward-command-headquarters
forward-command-headquartersdirecting
directingthethe
assignment
assignmentof ofmedical
medicalstaff
staffandandthetheemergency-response-headquarters
emergency-response-headquartersto to
take
take
a propera properactionactionto tomanagemanagethethetriagetriage
work
work
based
based
onon
understanding
understanding
thethesituation
situation
such
such
as as
thethenumbernumberof ofcurrent
current
accepted
acceptedpatients
patients
in in
thethehospital,
hospital,thethenumbernumberin inthethedifferent
different
triagetriagelevel
level
forforeach
each
treatment
treatment
zone
zone
in in
real
real
time.
time.

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andApplicationof oftriagesystem(TRACY)
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We discuss how to show those data in present system. As the result, the barchart showing the patient number in different triage level and the all patient
list are necessary to analyze the condition of hospital for the triage officer atthe both headquarters. The chart and the list can be updated automaticallyevery 5 seconds. When the patient’s information is needed to edit, thedetails window of patient is available from the list of patient.
3.6 Preparation System
When a disaster occurs, the system must quickly starts with aminimum preparation of work as much as possible.
The present system is developed on the CGI (Common Gateway
Interface). This system can work by the PC which can use WEB browser, is
independent of PC type, and doesn’t need any additional installation. The
CGI program that runs on the WWW-server is independent of PC type/ OS
and it can be work by the access form the browser of PC for pass-processing
at the each zone. The result of the working of CGI returns to the browser of
each PC at the zone.
As mentioned above, the digitize the patient information by FeliCa inreal time can achieve not only the advancement of triage such as tracing of
the patient treatment but also the sharing patient’s information such as thetransfer to the other hospitals, quick response to the person who asking of
his/her family’s location and coordination with the administration for theentire region.
4. VERIFICATION OF TRACY BY DEPARTMENT OFYAMANASHI UNIVERSITY HOSPITALThe Yamanashi University Hospital in Yamanashi prefecture has
experienced the triage drill since 2001. This triage drill becomes 10 times intotal. The purpose of this drill is that the hospital staff makes accurate safety,
accept the patient, implement triage and handle the treatment when the big
earthquake occurs in Yamanashi prefecture.
The present triage system, TRACY, was examined its availability andpracticality in the real disaster by applying the triage drill on this hospitalwith enough experience.
4.1 Triage drill of Yamanashi university hospitalIn this triage drill, 48 doctors, 21 medical engineers, 48 nurses, 47
office staffs, 145 patients and support staff, totally approximately 450
people were attended. Participants were not only from this hospital, but also
from the other hospital, the fire station, the government of Yamanashi
Prefecture, the government of Kofu City, the government of Central City
and residents.

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The drill assumes the disaster level that, there is damage in thehospital building, but the lifeline and other medical equipment worknormally. Therefore the triage and treatment are available even for a large
number of visiting patients.
At 9:00 am a big earthquake with the epicenter of the west andsouthern area in Yamanashi prefecture caused a damage of houses, a fire
and a traffic accident around the hospital. Then the staff in the hospitalchecks the status of the building damage and secures the safety of
responsible department based on the disaster manuals and according to the
instruction of the leaders of each department. All staff prepares to accept the
number of patients as soon as possible. The team of triage set the necessary
materials in the front of hospital building and to decide the triage level ofeach patient on the symptoms. After triage, the patient moves to the triage
zone or is transferred to other hospital depending on the triage level.
4.2 Outline of installation of system
The PC set at Triage area in the front of hospital building, each triage
zone, each treatment department and headquarters. Figure 2 shows the PC
and FeliCa reader set at Department of Radiology. FeliCa cards is adhered
to the back of triage tag, and managed to integrate triage tag and FeliCa
cards together. As the reader of FeliCa card, the FeliCa port/ pasori (RCS320) which is compatible with USB was used.
In this triage drill, FeliCa card has not been entered personal
information such as name and date of birth, and assuming a situation inwhich these information was enter at the hospital. As for the timing and theperson who enter the personal information, the patient information is input
at the upstream process of triage to answer the person who asking frompatient family as soon as possible. The special person who only input thepatient data are assigned beside the doctors, nurses, clerks separately. By
this way it can solve the problem that the patient cannot move during theentering their triage result or personal information in present system. In thecase of a large number of patients compared with the number of staff fordata input, even if all the data entering is not completed, the personal data
can be registered on a temporary basis, and then all staff can modify or
update the content of the personal data at the each triage zone or headquarter.
All four triage teams consisted of triage officer (doctor), nurse and support
staff (clerk) at the triage area.
The triage officer and nurse carry out usual triage work same as
traditional triage way. On the other hand, the clerk read the FeliCa card torecognize its ID by Felica reader connected to the mobile PC by USB. Thenclerks give the triage tag to triage officer, when just before triage officer
begin to conduct triage. In this time, the only patient ID is input in the
database.

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After finishing triage, the clerk brings the first piece of triage tag(copy the paper written patient’s information by triage officer) to the datainput-desk. Then the staff at the data-input-desk enters the patient’s
information such as the name, date of birth, age, address, remarks byreading the copy paper in the present system.
On the other hand, the patient who finished the triage moves to theeach treatment zone. When the patient arrives at the zone entrance, theFeliCa card is read by the FeliCa reader to record the location and the time
automatically as the pass-processing. This is same way for the other zone ordepartment where the PC for the present system is set.
Thus, even if there is a change of triage level, it is possible to conduct
the same pass-processing at the new place. The new triage level can be
updated in the present system automatically in this way.
4.3 Result
Time history of the patient changes: Figure 3 shows the time historyof each patient’s triage level, taking the patient in the vertical axis and timein the horizontal axis. The staff in medical institute and the government canunderstand the triage level of all patients from the time when the patients arereceived in hospital to discharge from the hospital by following time history.
The change of triage level also can be understood in this figure.

Figure 2: PC and FeliCa reader set at Department of Radiology

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9:30

10:30

10:30

: Triage: Triagezone zone: Mild zone
: Mild(green)zone (green): Moderate: Moderatezone (yellow)
zone (yellow): Severe: Severezone (red)zone (red): Death: Deathzone (black)zone (black): Change: Changeof triageof level
triage level

FigureFigure
3: Time3: history
Time historyof patientof patient
triagetriage
level level

The forward-command-headquarters
The forward-command-headquarters
directingdirectingthe assignment
the assignmentofof
medicalmedicalstaff could
staff could
take atake
propera properactionaction
to manage
to manage
the triage
the triage
work based
work basedon onunderstanding
understanding
the situation
the situationsuch assuch
theas
numberthe numberof currentof current
accepted
acceptedpatients
patients
in theinhospital,
the hospital,
the number
the numberin theindifferent
the different
triage triage
level levelat eachat treatment
each treatmentzone inzone
realintime
realprovided
time provided
by thebypresent
the present
system.
system.
The family
The familyof patientof patient
visits visits
to the tohospital,
the hospital,
whichwhich
can becanconsidered
be consideredasasthat thethatfamily
the family
stays stays
to look
to forlookpatient
for patient
status status
and location.
and location.
However,
However,
immediate
immediate
response
response
is difficult
is difficult
for theforhospitalthe hospitalin a situation
in a situationof a hugeof a huge
numbernumberof patients.
of patients.
BecauseBecausethey cannot
they cannot
searchsearch
the patient,
the patient,
for whomfor whomthe thefamilyfamily
is looking
is looking
for in for
the inpaper-based
the paper-based
patient’s
patient’s
information.
information.
By using
By using
the thekey-word
key-wordsearchsearchfunctionfunctionin theinpresent
the present
systemsystemin thisindrill,
this thedrill,allthe
staff
all instaff inhospital
hospital
can search
can search
immediately
immediately
the patient
the patientthey arethey
looking
are looking
for. for.
5. CONCLUSION
5. CONCLUSION
This researchThis researchdeveloped
developed
an IT antriageIT triage
systemsystemfor collecting
for collecting
disasterdisastermedicalmedicalinformation
informationin realintime
real andtimesharing
and sharing
it among
it among
relatedrelated
institution
institution
in entirein entirearea. Felicia
area. Felicia
card andcardcard-reader
and card-reader
are used
are toused
constitute
to constituteof thisofsystem
this systemtotoobtainobtainthe number
the number
and conditionand conditionof patientsof patients
etc. inetc.
realintime.
real time.
A disasterA disaster
drill wasdrillheld
was atheldthe atYamanashi
the Yamanashi
University
University
Hospital
Hospitalwith with
450 participants.
450 participants.
TRACY
TRACY
was examined
was examined
its availability
its availability
and practicability
and practicability
by byusing using
in thisindrill.
this Fromdrill. From
the result
the resultof that,
ofthe
that,
present
the present
systemsystem
can obtaincan obtainthe thenumbernumberof patientsof patientsfor each
fortriage
each triage
level andleveltheandaccepted
the accepted
numbernumberof patientsof patientsin eachin diagnosis
each diagnosis
and treatment
and treatment
department
department
in realintime,real including
time, including
response
response
for changing
for changing
triage triage
level andleveltheandpeoplethe people
looking
looking
for their
for family
their family
in hospital.
in hospital.
In theInpoint
the pointof theofinformation
the information
sharing
sharingin theinentire
the entire
area, area,
the patient’s
the patient’s
information
information
can becan
sharedbe shared
amongamonghospitals,
hospitals,
the administration,
the administration,and residents
and residents
in realintime.
real time.

Development
and Applicationof triage
systemsystem(TRACY)
Development
andof(TRACY)
Development
and Application
applicationof triage
triagesystem(TRACY)

11 607
11

10:45

10:44

10:43

time
10:42

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10:40

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time

10:43
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10:41
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10:39
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10:11
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10:07
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Patient ID

10:00
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10:03
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10:01
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10:00
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76
78
3
1
79
80
95
13
4
81
5
6
96
82
14
83
97
7
8
15
84
9
98
16
10
99
85
17
86
12
23
18
100
87
19
20
21
24
77
101
88
25
26
89
22
102
37

10:00
9:40
9:34
9:39
9:33

ID

9:38
9:32
9:37
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9:36
9:30
9:35

9:34

9:33

Patient ID

9:30
9:32

9:31

76
78
3
1
79
80
95
13
4
81
5
6
96
82
14
83
97
7
8
15
84
9
98
16
10
99
85
17
86
12
23
18
100
87
19
20
21
24
77
101
88
25
26
89
22
102
37

9:30

ID

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

The feedback and opinions were widely obtained from the entire
evaluation meeting and the meeting with the mainly triage officer held after
the triage drill.
These discussions are implementing to increase more practical level in
the next drill. We will expand and examine TRACY according to the result
obtained this triage drill.
ACKNOWLEDGEMENTS:
The authors acknowledge complete cooperation from the Department ofMedicine at Yamanashi University hospital. This cooperation makes
possible to develop and examine the present system. Especially, the authors
got the valuable advice about system function and structures from Professor
Kenichi Matsuda and Dr. Shoji Suzuki as a specialist of the emergency
medicine. The authors also acknowledge support from the Japan Ministry of
Education, Culture, Sport, Science, and Technology (MEXT) for
development of present system.
REFERENCES:
Kusuda, J., Kiyama, N., Utiyama, A., Hiromori, A., Umedu, T.,
Yamaguchi, H. and Higashino, T. (2009), “Design and Development ofElectronic Triage System Using Wireless Sensor Networks,” The Instituteof Image Information and Television Engineering Technical Report, Vol.33,
No.36, 33-38.
Ashida, H., Takeshima, S., Wakisaka, H., Ueki, T., Yamamoto, T.,
Karasawa, K., Inaba, T., Tsuji, K., and Komura., T. (2008) , “A data input
system for triage tag information using a digital pen: a training program foracceptance of a massive number of injured people at the Japan Self Defense
Force Central Hospital,” Japanese Journal of Disaster Medicine, 13(1), 5660.
Sonoda, A., Inoue, S., Oka, K., and Fujisaki, S. (2007), “Experimentof Large Scale Triage with RFID Tags,” Transactions of Information
Processing Society of Japan, 48(2), 802-810.
The Ministry of Health and Welfare Health Policy Bureau (1996),“Disaster health care system of the 21st century - Ideal way of medical
treatment offered to disaster, “ Herusu Shuppan, Co. inc., 25-48.
Shimora,H., Matsui, H., Noda, I. (2009), “Cooperation of Disaster
Related Systems on Distributed System Architecture, “Journal of JAEE,
9(2), pp.61-72.
The National Institute of Advanced Industrial Science and Technology(AIST) , “DaRuMa, “ http://sourceforge.jp/projects/daruma/
Yamanashi Prefecture HP ： Base disaster Hospital ，
http://www.pref.yamanashi.jp/ft-hokenf/60475114366.html

12608

New Technologies
Technologies forfor Urban
Urban Safety
Safety ofof Mega
Mega Cities
Cities inin Asia
Asia
NewAlkali-silica reaction in cement mortar
with waste glass as fine aggregates
Kiang Hwee TAN1 and Hongjian DU2Professor, Department of Civil and Environmental Engineering,
National University of Singapore, Singapore
tankh@nus.edu.sg
2
PhD Candidate, Department of Civil and Environmental Engineering,
National University of Singapore, Singapore
1

ABSTRACTThe alkali-silica reaction (ASR) in cement mortar containing waste glass
was investigated using ASTM Standard C 1260. Mortar bars, consisting of
cement, natural sand and waste glass in various proportions, were placed ina concentrated (1 N) sodium hydroxide solution at 80°C and removed forlength measurements at intervals for up to 28 days. Green and brownglasses were studied together with two mitigating methods commonly used
to control ASR in normal concrete. One method was to replace cement withpozzolans, that is, 30% by fly ash, 60% by ground granulated blast furnace
slag (GGBS), or 10% by silica fume, while the other was to restrain the ASR
expansion by the addition of 1.5% by volume of plain short steel fibers, or
1.0% by mass of lithium compounds. For each test parameter, the glasscontent was varied from 0 to 100% of the total aggregate content. Test
results showed that ASR expansion decreased with increasing glass content,
due to the non-swelling nature of the formed ASR gel. All glass mortar
mixes showed ASR expansion less than 0.1% at 14 days, and are therefore
considered as innocuous. Fly ash and GGBS were the most effective infurther mitigating ASR expansion.
Keywords: alkali-silica reaction; cement mortar; fine aggregates;
mitigation methods; waste glass.
1. INTRODUCTION
In recent years, there have been increasing global concerns on thesustainability of building materials, especially in view of the depleting
natural resources and associated environmental issues. Concrete, a building
material, is the second most consumed commodity after water. To ensuresustainable development, the concrete industry has continued to increase theuse of recycled materials, including industrial byproducts, and explore thedevelopment of innovative cements and concrete mixtures.
At the same time, the reuse and recycle of urban waste has drawn
increasing attention due to limited landfill for its disposal. Among the solid
waste, glass is considered suitable for construction use, because of its

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Chiangmai,

physical characteristics and chemical composition. Previous investigations
have indicated that waste glass may be used in concrete provided that thepotential deleterious expansion, caused by alkali-silica reaction (ASR)
between silica in glass and alkali which is produced as a result of hydrationof cement, could be mitigated (Jin et al. 2000; Park & Lee 2004; Park et al.
2004; Shi 2009; Taha & Nounu 2008; Taha & Nounu 2009; Topcu &Canbaz 2004; Topcu et al. 2008).
In this study, the effects of glass color and content on ASR in cement
mortar were investigated and reported. Also, two ASR mitigation methods,that is: (1) by cement replacement by fly ash, GGBS, or silica fume; and (2)by adding discrete steel fibers or lithium compounds; were examined using
both green and brown glass mortar with different sand to glass replacement
ratios, and the results are discussed herein.
2. MATERIALS AND TEST METHODS
2.1 Materials
Type I ordinary Portland cement (OPC), with alkali content of 0.6%
[that is, (Na2O)eq = Na2O + 0.658K2O)], was used. The chemicalcomposition was analyzed according to ASTM C 150 and shown in Table 1.
The waste glass used in this study was crushed from soda-lime glass bottles,
that is, beer bottles, after they were washed with tap water. It was reduced
into smaller particles complying with the requirement of fine aggregates as
per ASTM C 33 using a jaw crusher. Both green and brown glasses wereused. The chemical compositions of the waste glass and natural sand aresummarized in Table 2. For the purpose of testing for ASR in accordancewith ASTM C 1260, both the waste glass and natural sand were preparedwith percentages of 10, 25, 25, 25 and 15% passing/retained on sieve sizes
4.75/2.36, 2.36/1.18, 1.18/0.6, 0.6/0.3 and 0.3/0.15 mm respectively.
Table 1: Chemical compositions of cement, fly ash, GGBS and silica fumeComposition, %CementFly ashGGBS

Silica fume

SiO2
Al2O3
Fe2O3
CaO
MgO
SO3
Na2O
K2O

20.8
4.6
2.8
65.4
1.3
2.2
0.31
0.44

38.9
29.2
19.6
2.5
2.1
0.19
0.26
0.48

32.2
12.9
0.36
40.7
6.05
4.95
0.28
0.51

96.0
0.28
0.32
0.16
0.37
0.18
0.05
0.57

Class F fly ash, GGBS and silica fume were used as ASR suppressors,
at 30%, 60% and 10% of cement by mass, respectively. The chemicalcompositions of these supplementary cementing materials are shown in
Table 1. Plain, smooth steel fibers, with a diameter of 0.16 mm and lengthof 50 mm, was added at 1.5% by volume of mortar as an ASR mitigation

2
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ICUS Report 56

method. Also, solid lithium chloride and lithium carbonate was dissolved inwater and added as chemical admixtures, at the dosage of 1% of cement
content by mass, to act as ASR suppressors.
Table 2: Chemical compositions of waste glass and natural sandComposition, %
SiO2
Al2O3
Fe2O3
CaO
MgO
Na2O
K2O
TiO2
Cr2O3

Green Glass
71.2
1.63
0.32
10.8
1.57
13.1
0.64
0.07
0.22

Brown Glass
72.1
2.19
0.22
10.5
0.72
13.7
0.16
0.10
0.01

Sand
88.5
1.21
0.76
5.33
0.42
0.33
0.31
0.05
—

2.2 Mortar mixtures and test method
The reference mortar comprised cement, natural sand and water mixed
in the ratio of 1: 2.25 : 0.47 by mass, as specified by ASTM C 1260. Other
mixtures with natural sand replaced with green or brown waste glass sand at
0, 25, 50, 75, and 100% were prepared. For each glass mortar mixture, theASR mitigation methods mentioned in section 2.1 were investigated. For
each test parameter, three 25 mm × 25 mm × 285 mm mortar bars wereprepared. They were demolded 24 hours after casting and placed in water at
80 C for the next 24 hours. The initial lengths of the mortar bars were thenrecorded before they were immersed in 1N 80C NaOH solution. The
expanded lengths were subsequently measured after 2, 4, 7, 10, 14, 21 and28 days. According to ASTM C 1260, expansion larger than 0.2% at 14days is considered potentially deleterious while less than 0.1% is innocuous.
However, for mortars with pozzolans such as fly ash, the ASTM C 1567,
which states 0.1% as the threshold value for potentially deleterious
expansion, should be followed.
3. TEST RESULTS AND DISCUSSION
3.1 Effect of glass color and content
Mortars with different glass sand contents showed larger ASR
expansion with time, as shown in Figure 1. Both green and brown glass
mortars exhibited smaller ASR expansion compared to natural sand mortar(i.e., mortars with 0% glass). According to Jin et al. (2000) and Park andLee (2004), green color glass would be the least reactive in ASR due to its
high content of Cr2O3, which is added to give the greenish color. Comparedto green glass, brown glass exhibited similarly small ASR expansion
although it has a smaller content of Cr2O3. The reason might be due to the
Fe2O3 in brown glass which is added to produce the brownish color. Basedon the double-layer theory (Prezzi et al., 1997), the higher valence of Cr3+

Alkali-silica reaction
Alkali-silica
reaction inin cement
cement mortar
mortar with
with waste
wasteglass
glassasasfinefineaggregatesaggregates

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

ions in green glass and Fe3+ ions in brown glass could reduce the doublelayer thickness and the repulsion forces, resulting in much lower ASR
expansion.
0.20

Ref. - Green glass

Ref. - Brown glass
2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.15

0.10

0.05

0.00
0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 1: ASR expansions of glass sand mortars
The reduction in ASR expansion in mortar with higher glass sandcontent was quite apparent, for both green and brown glass. At 14 days, thenatural sand mortar exhibited an expansion of 0.053%, indicative of nonreactive aggregates. The ASR expansions of green and brown glass mortar
were 0.036, 0.022, 0.012, and 0.005%; and 0.032, 0.020, 0.009, and 0.009%,
for glass replacement contents of 25, 50, 75, and 100%, respectively. All
glass mortars showed ASR expansions less than 0.1% at 14 days, and lessthan 0.2% at 28 days. These results indicated that the glass sand may be notreactive in ASR, at least within 28 days, which is also supported by thefindings of Zhu et al. (2009).
3.2 Effect of supplementary cementing materials
The effect of replacing cement with fly ash, GGBS or silica fume on
ASR expansion is discussed.
3.2.1 Cement replacement by fly ash
The results of ASR expansions of glass sand mortars with 30% of
cement content replaced by fly ash are shown in Figure 2. Fly ash could
significantly reduce the ASR expansions at all sand replacement ratios,
regardless of glass color. Moreover, the ASR expansion generally decreased
with increasing glass sand content. All mixes showed expansion less than
0.015% at 14 days. For brown glass mortar in particular, the fly ash
effectively reduced the expansion rate after 14 days. The ASR suppressing
effect of fly ash could be explained by the pozzolanic reaction between fly
ash and cement hydration product, Ca(OH)2. The fly ash would consume
the OH- ions and lower the pH value of the pore fluids in cement paste,
thereby reducing the aggressive reaction with acidic aggregates andresulting in smaller negative charges on the surface of the glass particles[Prezzi et al. 1997]. Furthermore, due to the pozzolanic reaction, the4612

New Technologies
Technologies forfor Urban
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Asia
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ICUS Report 56

microstructure of cement paste, especially the interfacial transition zone
(ITZ) could be enhanced. The ingress of OH- ions, which is necessary for
ASR gel to form and swell, could be reduced due to the decreased porosityand permeability of cement paste.
0.05

Fly Ash - Green glass

Fly Ash - Brown glass
2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.04
0.03
0.02
0.01
0.00
-0.01

0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 2: ASR expansions of glass sand mortars with 30% fly ash
3.2.2 Cement replacement by GGBSAs supplementary cementing materials, the ASR suppressing
mechanism of GGBS is the same as fly ash. The ASR expansions of mortars
with 60% of cement content replaced by GGBS are shown in Figure 3. All
the mortar mixes showed ASR expansion less than 0.02% at 14 days andless than 0.05% at 28 days, indicative of the effectiveness of GGBS as a
suppressor. The ASR expansion generally decreased with increasing glasscontent, regardless of the glass color.
0.05

GGBS - Green glass

GGBS - Brown glass
2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.04
0.03
0.02
0.01
0.00
0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 3: ASR expansions of glass sand mortars with 60% GGBS
3.2.3 Cement replacement by silica fume
The ASR expansion of glass sand mortar with 10% of cement content
replaced by silica fume is shown in Figure 4. The purpose of silica fume innormal concrete is to obtain high strength, since the super fine particle size

Alkali-silica reaction
Alkali-silica
reaction inin cement
cement mortar
mortar with
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October 2011, Chiang
Mai,Thailand
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Chiangmai,

of silica fume could substantially improve the microstructure of concrete at
the ITZ. Due to the same reason, silica fume could be used as an ASR
suppressor in glass mortar and proved to be effective in this study.
Compared with fly ash and GGBS, silica fume showed slightly lesseffectiveness in restraining ASR expansion. All the mortars with silica
fume showed expansions less than 0.04% at 14 days and less than 0.06% at
28 days.

ASR expansion, %0.08

Silica Fume - Green glass Silica Fume - Brown glass
2-day
4-day
7-day
10-day14-day21-day28-day

0.06

0.04

0.02

0.00

0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 4: ASR expansions of glass sand mortars with 10% silica fume
3.3 Effect of additive materials
The effect of adding short, discrete steel fibers and lithium compounds
on ASR expansion is discussed herein.
3.3.1 Addition of steel fibers
To prevent substantial loss in the flow of mortar, smooth steel fibers
were used rather than deformed or hooked steel fibers. The test results forglass mortars with 1.5% of steel fibers are shown in Figure 5. All the mortar
mixes showed expansion less than 0.03% at 14 days and less than 0.09% at
28 days. The steel fibers could prevent the ASR expansion by reducing theinternal pressure caused by swelling ASR gel, and improving the tensile
characteristics of the mortar. The ASR expansion also decreased withhigher content of glass sand.
0.10

Steel Fiber - Green glass Steel Fiber - Brown glass

2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.08
0.06
0.04
0.02
0.00
0

25

50

75

100

0

25

50

75

100

Glass content, %6
614

New Technologies
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ICUS Report 56

Figure 5: ASR expansions of glass mortars with 1.5% by volume of steel
fibers
3.3.2 Addition of lithium chloride and lithium carbonate compounds
The ASR expansions of mortars with added LiCl and Li2CO3
compounds are shown in Figures 6 and 7, respectively. The amount oflithium compounds was 1% by mass of cement content. The restraining
effect of LiCl compound was lesser than that of Li2CO3 compound due tothe smaller ratio of [Li]/[Na], which has been found to be the key factor in
restraining ASR expansion [Lumley 1997]. The [Li]/[Na] ratio for 1% LiCland Li2CO3 compounds is 0.74 and 0.84, respectively.
0.20

LiCl - Brown glass

LiCl - Green glass

2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.15

0.10

0.05

0.00
0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 6: ASR expansions of glass sand mortars with 1% LiCl
0.10

Li2CO3 - Green glass

Li2CO3 - Brown glass
2-day
4-day
7-day
10-day14-day21-day28-dayASR expansion, %

0.08
0.06
0.04
0.02
0.00
0

25

50

75

100

0

25

50

75

100

Glass content, %Figure 7: ASR expansions of glass sand mortars with 1% Li2CO3
At 14 days, brown glass mortars with 1% LiCl showed higher ASR
expansions than the reference natural sand mortars regardless of the glass
sand content, indicative of insufficient amount of lithium compound (alsosee next section). However, at 21 and 28 days, they exhibited slightly lessexpansion than the reference mortars, when the glass content was less than
50%. The ASR suppressing function of LiCl compound in green glass
mortars as well as of Li2CO3 compound in both green and brown glass
mortars was more obvious. The ASR mitigation mechanism of lithiumcompounds is not well established. It is expected that lithium compounds
could change the natural and chemical compositions of the ASR gel andreduce the solubility of the reactive silica. The possibility of dissolved silica

Alkali-silica reaction
Alkali-silica
reaction inin cement
cement mortar
mortar with
with waste
wasteglass
glassasasfinefineaggregatesaggregates

6157

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

to be repolymerised and the expansive ability of ASR gel would be
subsequently reduced [Taha & Nounu 2009].
3.4 Comparison of different ASR mitigation methods
ASR expansions of glass mortars, with different mitigation methods,
at 14, 21 and 28 days, are shown in Figures 8 and 9. For green glass mortar,
all mitigation methods resulted in reduced expansion to a certain extent
except with silica fume in 100% glass sand mortar at 14 and 21 days. For
brown glass sand mortars, slightly larger expansions than the reference
mortars were observed with LiCl compound at 14 days as discussed earlier
and with steel fibers at 28 days for glass content of 75 and 100%.

Figure 8: ASR expansion of green glass mortars with various mitigation
methods

Figure 9: ASR expansion of brown glass mortars with various mitigation
methods
The effectiveness of ASR mitigation methods investigated decreasedin the order of fly ash, GGBS, Li2CO3, silica fume, steel fibers and LiCl for

8616

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Asia
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ICUS Report 56

green sand mortars, and fly ash, GGBS, silica fume, steel fibers, Li2CO3 andLiCl for brown sand mortars.
4. CONCLUSIONS
Based on the study carried out on waste glass mortar, it is concluded thatboth green and brown glass sand mortars did not show potential deleterious
ASR expansions according to the specifications of ASTM C 1260,
regardless of the glass content. In general, use of supplementary cementing
materials such as fly ash, GGBS, and silica fume, was shown to be more
effective in mitigating ASR expansions, while additive materials such as
steel fibers and lithium compounds were less effective. However, morework would be needed to determine the effect of different quantities of theabove ASR suppressing materials.
REFERENCES
ASTM C 33, 2004. Standard specification for concrete aggregate.
ASTM International, Philadelphia.
ASTM C 150, 2005. Standard specification for portland cement.
ASTM International, Philadelphia.
ASTM C 1260, 2007. Standard test method for potential alkali
reactivity of aggregates (mortar-bar method). ASTM International,
Philadelphia.
ASTM C 1567, 2008. Standard test method for determining thepotential alkali-silica reactivity of combinations of cementitious materials
and aggregate (accelerated mortar-bar method). ASTM International,
Philadelphia.
Jin, W., Meyer, C., and Baxter, S., 2000, Glascrete-concrete with glass
aggregate. ACI Materials Journal 2, 208-213.
Lumley, J.S., 1997. ASR suppression by lithium compounds, Cement
and Concrete Research 2, 235-244.
Park, S., and Lee, B., 2004. Studies on expansion properties in mortar
containing with waste glass and fibers. Cement and Concrete Research 7,1145-1152.
Park, S., Lee, B., and Kim, J. H., 2004. Studies on mechanicalproperties of concrete containing waste glass aggregate. Cement andConcrete Research 12, 2181-2189.
Prezzi, M., Monteiro, P. J. M., and Sposito, G., 1997. The alkali-silica
reaction, Part I: use of the double-layer theory to explain the behavior ofreaction-products gels. ACI Materials Journal 1, 10-17.
Shi, C., 2009. Corrosion of glasses and expansion mechanism of
concrete containing waste glasses as aggregate. Journal of Materials in Civil
Engineering 10, 529-534.
Topcu, I. B., Boga, A. R., and Bilir, T., 2008. Alkali-silica reactions ofmortars produced by using waste glass as fine aggregate and admixtures
such as fly ash and Li2CO3. Waste Management 5, 878-884.

Alkali-silica reaction
Alkali-silica
reaction inin cement
cement mortar
mortar with
with waste
wasteglass
glassasasfinefineaggregatesaggregates

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Mai,Thailand
Thailand
Chiangmai,Taha, B., and Nounu, G., 2008. Properties of concrete contains mixed
colour waste recycled glass as sand and cement replacement. Construction
and Building Materials 5, 713-720.
Taha, B., and Nounu, G., 2009. Utilizing waste glass as sand/cement
replacement in concrete. Journal of Materials in Civil Engineering 2, 709721.
Topcu, I. B., and Canbaz, M., 2004. Properties of concrete containing
waste glass. Cement and Concrete Research 2, 267-274.
Zhu, H., Chen, W., and Zhou, W., 2009. Expansion behavior of glass
aggregates in different testing for alkali-silica reactivity. Materials andStructures 4, 485-494.

10
618

New Technologies
Technologies forfor Urban
Urban Safety
Safety ofof Mega
Mega Cities
Cities inin Asia
Asia
NewHealth survey of concrete in urban
infrastructure by non- contact acoustic
imaging method
Noriyuki UTAGAWA1, Ryo AKAMATSU2 and Tsuneyoshi SUGIMOTO3
1
Project Researcher, Satokogyo Engineering Institute, Japanutagawa@satokogyo.co.jp
2
Under graduate student, Faculty of Engineering,Toin Univ. of Yokohama, Japan
3
Professor, Faculty of Engineering, Toin Univ. of Yokohama, Japan
ABSTRACT
To automate the hammering test that can be measured remotely, “Noncontact Acoustic Imaging Method” is developed. Advantage of thistechnology is a device that can move in a tunnel on the road. For example,
the separation or flaking of the tunnel crown is able to be examined. By
using this method, there is no danger in high places and agonizing effort,
and examined possible high frequency. In this paper, both to demonstrate
the principles of measurement, the result indicate a defect in the specimen
was extracted distance 10m.
Keywords: non contact acoustic imaging method, concrete structure,delamination, nondestructive inspection, long range acoustic device
1. INTRODUCTION
To use the urban infrastructures continuously, the operation andmaintenance of the structure becomes important. Up to now, a concrete
structure has been thought for the performance to be maintained whenalmost permanent, but various performances actually has decreased becauseof the concrete deterioration and fatigue, etc. , and the influence has goneout to the performance of structure in a remarkable case. The deteriorationof a concrete structure comes for the urban foundations such as the road, therailway, and the drainage built at the high-growth period of Japan to beshown after 50 years. Moreover, such an urban infrastructure can be updated
if there is economical room. However, it is becoming direction of using it
for a long term without updating the structure because there are neither
economical room in recent years nor spatial room of the city. The impact tothe structure is also large because there are a lot of natural damages such as
earthquakes and typhoons in Japan. Then, the performance of the structure
not only is maintained but also it is needed to improve the performance atthe same time.
An efficient operation and maintenance including the cost of aconcrete structure, is needed in such a situation. When the maintenance6191

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management of the structure is done, the health survey of concrete structure
is investigated first. Making to high accuracy and efficiency improvement ofsuch an investigation technology are requested.
In the investigation diagnosis, the visual inspection from the distance,
the visual inspection adjoining, and hammering test are executed. If it isnecessary, a more detailed inspection is executed as a result. Big defects ofsurface are examined by watching from the distance. Distribution of cracks
is examined by watching adjoining. Cavities and delaminations at surface ofa concrete are examined by hammering test. Therefore, the visual inspection
and hammering test are important inspections for examining the healthsurvey of a concrete structure. The improvement to hasten the inspection
speed of these techniques that man has executed up to now and to improve
the inspection accuracy is done. Instead of the visual inspection adjoining,
efficiency improvement and making to high accuracy are attempted by theuse of the digital device such as CCD cameras and the crack extraction
techniques (image processing technique). Instead of hammering test, Impact
Acoustic method(IA method) have been developed to automaticallydetermine the presence of defects. IA method is recording on the soundgenerated by a microphone with a hammer blow. The sound pressure isrecorded and then analyzed to extract the internal defects of concrete. In
addition to IA method, the infrared rays tomography method is used in theflaking off investigation of the tile of outward walls of a building and theradar method is used about a healthy investigation of the tunnel lining.
However, the hammering test has been executed in the inspection of ageneral tunnel and the bridge.
The hammering test in a common road tunnel and the railway tunnel is
executed by a dangerous, severe working environment. Moreover, there is apossibility that the defect is overlooked by the presence of the experience
because it is a technology that is judged by the sound with a hammer blow,
too.
In this development, it paid attention to “Non contact acoustic
imaging method”. Non contact acoustic imaging method(NCAI method) is atechnique to probe the defects of the concrete surface from a remotelocation. First, using sound waves generated from the speaker, vibrate theconcrete surface. Next, the distribution of vibration is measured using
remotely located vibrometer. The defects of concrete surface are probed
from the measurement result. The authors have so far, using Non contact
acoustic imaging method, has conducted research on technology to detectburied objects such as underground buried objects and landmines. These
results are shown in the references. This method will be searchable ofconcrete health survey from a position away. For instance, concrete lining
can be investigated from the road side by NCAI method in the tunnel.
Moreover, the floor slab can be investigated from the road or the surface of
the water under the bridge.
In this paper, it explains “Non contact acoustic imaging method”, first.
Next, the result of measuring the test pieces that imitates the defect like asdelamination and cavity is shown from a position 10m away by using NCAI

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method. Finally, the possibility of NCAI method and the development in the
future are described.
2. HEALTH SURVEY OF CONCRETE STRUCTURES BY NONCONTACT ACOUSTIC IMAGING METHOD (NCAI METHOD)
2.1 Technical summary
The NCAI method is a technique for vibrate the structure by the soundwave, and detecting the defect position from the distribution of the vibration.
NCAI method and Hammering test are similar technologies. That is, it is atechnology that vibrates the structure by some methods, and the internalsituation of concrete can be presumed from the situation of the vibration.
Hereafter,NCAI method and the hammering test are compared and it
explains the principle.
About the vibratory source, shock with the hammer is used in thehammering test, and, on the other hand, a large sound that the speaker isgenerated is used in NCAI method. Therefore, it becomes the impulsive
vibration of the point vibration about the generated vibration in hammering
test, and it becomes a vibration of the periodicity of excitation on the side in
NCAI method. In hammering test, the amplitude decreases while partingfrom source point though it depends on the range and the size of excitationin the point vibration. Therefore, the range of detection is limited. On theother hand, in NCAI method, because the certain scope is vibrated at thesame time in excitation on the side, the range of detection can be widely
taken. However, because the impact power cannot be given, it is difficult togenerate only the vibration of normal mode such as the vibrations of adefective internally board.
For the measuring method of the vibration, the sound generated by thevibration is heard by the ear in hammering test. It is clear that the surface
oscillation and the sound are equivalent from a past finding. Therefore, it isalso possible to understand the vibration from the sound. On the other hand,vibration at each point is measured in NCAI method with a laser Doppler
vibrometer. However, the vibration caught because of the sound heard by
the ear is information on the expanded domain, and the vibration caught
with a laser Doppler vibrometer is information on the point. Therefore, twodimensional information of the vibration within the range of the area that is
one time in hammering test can be obtained. On the other hand, the scanningis needed to obtain two-dimensional information in NCAI method.
In general, the presence of the defect is distinguished by "Sei-on" and"daku-on" in the hammering test. "Sei-on" shows the health part because of
the shrill sound caused when the metal is beaten. "Daku-on" is bottom partsof the notes, and defective on the surface is shown. On the other hand, thedefect position is detected from distribution of vibration (amplitude,frequency, and phase) in NCAI method. Either method also finds the defect

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part by using the principle with a different vibration in the defect part andvibration in the health part.
2.2 Hardware of NCAI system
Figure 1 shows the composition of the equipment used in NCAI
method. Long range acoustic device (LRAD : LRAD Corp, LRAD-300X) isa sound speaker for the distance, and the loud sound can be propagated far.
Figure-2 shows the acoustic pressure distribution on the axis measured in
outdoor. The measuring frequency is 2kHz. It was confirmed to obtain the
maximum sound pressure of 143dB in the maximum because of theisolation of 0.5m, and to obtain the acoustic pressure of 110dB even at a
position 20m away. Moreover, the sound was made with a function
generator, amplified with the amplifier, and generated from the speaker by
the microphone of LRAD.

Figure1: Basic concept of NCAI method
Scanning laser Doppler vibrometer (SLDV : Polytec corp., PSV400H4) is a device that measures the vibration velocity of the surface of theobject by using the effect of Doppler of the laser beam. In this device, flat
vibration distribution (It is a vertical direction in respect) can be measured
by doing the multipoint in the scanning. In this measurement, the vibrationof 195 points (15*13 points) is measured by taking the measurement time
per point for 2.15 seconds, and doing the scanning. Moreover, the timing of
the scanning beginning in the vibration measurement is corresponding to thegeneration time of the sound wave with a trigger signal from the function
generator. In addition, the measurement is repeated until a good oscillation
data in each point is obtained.

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Figure 2: An example of the acoustic pressure distribution on the axis
measured in outdoor.
2.3 Method of detecting defect area
The method of extracting the defect in the area is described by using
the plane distribution data of the measured vibration velocity. Here, extract
the range of the defect in the entire area on the assumption that information
on one point in the health part and one point in the defect part in the area has
already been obtained. The flow of the defect detection is shown as follows.
• White noise is entered to the test piece, and the vibration at somepoints are measured. The frequency analysis result of the alreadyknown health part is compared with the frequency analysis result of
the already known defect part. Some frequency domains where thevibration of the defect part grows compared with the vibration of thehealth part are extracted.
• The vibration measurement of all points in the attention area is doneby entering the Chirp wave including the frequency domain
extracted by an already-known measurement point.
• It pays attention to the frequency before and behind the extracted
frequency by using the result of a measurement, and a flat vibration
distribution chart is made. It is presumed that the area where thevibration is growing in the vibration distribution chart is a defect part.
• In this processing, when the defect part doesn't appear too muchclearly, the defect position is presumed by the picture processing thatpays attention to the optimum frequency range method and the phasedifference method.
3. DEFECT DETECTION TO CONCRETE TEST PIECES THATIMITATES DELAMINATION AND CAVITY
3.1 Outline of measurement
Figure-3 shows the setup of the experiment. SLDV and LRAD arearranged at a position 10m away from test piece. It is possible to enter into
the test piece of the sound vibration energy of LRAD effectively byHealth survey
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arrangement in front of the test piece of LRAD. SLDV is arranged at a
diagonal position in the LRAD back. The reason of this arrangement is tosuppress the vibration of the laser head of SLDV by the generation sound of
LRAD.

Figure 3: Experimental setup for non contact acoustic imaging method
3.2 Outline of test pieces
The test pieces are five reinforced concrete boards of 2m in width,
1.5m in height, and 0.3m in thickness. The defect of delamination andcavity are imitated by burying the board made of the styrene foam inconcrete.
The size and the depth of laying underground of the board of thestyrene foam have been changed. There are 32 kinds of the defect. Flat
shape of the defect is a square. There is a size from the square whose length
is a near 5cm to the square whose length is a near 70cm. The depth of thedefect (distance from the styrene foam to the surface) is from 2.5 to 15cm.
There is a case where the defect is arranged at the position of the reinforced
bar. Figure 1 shows the examples of test pieces that arranged the styrene
foam before concrete placing and the completed test pieces.

Figure 1: Examples of the concrete test pieces (No.3-No.5).
(a) Under construction, (b) after completion.

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3.3 Result of detection
The defect from a position 10m away was detected. As a result, thedefect of 2.5cm in depth was able to be detected about the case with anarrow plane scale (square of 10cm). Moreover, the defect that existed in
7.5cm in depth was able to be detected about the case with a wide planescale (square of 50cm).
The result of a measurement of the defect of the plane scale 20cm and2.1cm in depth is shown below as one example of the result. The thicknessof the styrene foam board is 2.5cm. The frequency band of the entering
chirp wave is 500-3000Hz, and 640 microseconds in the duration time.
First, measure the vibration of the center point of the defect, comparedwith the vibration of the surroundings. The results for the FFT analysis ofvibration velocity are shown in Figure 4. In the range of 1400-1600Hz
frequency, it is understood that the greater the vibration of the defective part.
To ensure that the natural frequencies of plate vibrations were observed
around the defective parts, another vibration measurement was performedby using impact acoustic method (IA method). Figure 5 shows the results ofvibration measurement by IA method. The results of IA method, the natural
frequency of defective parts are found to be around 1400Hz. In addition, thedefect has arisen for a strong vibration, whereas it was found that the healthof the surrounding almost no vibration occurs.

Vibration velocity(m/sec)

Center part of defecthealth part

4.5E-05
4.0E-05
3.5E-05
3.0E-05
2.5E-05
2.0E-05
1.5E-05
1.0E-05
5.0E-06
0.0E+00
0

500

1000

1500
Frequency(Hz)

2000

2500

3000

Figure 4: Vibration velocity vs. frequency. Blue line shows the velocity on
the center point of defect, Pink line shows the velocity of health part

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Center part of defecthealth partSound Pressure(Pa)

100
75
50
25
0
0

500

1000

1500
2000
Frequency(V)

2500

3000

3500

Figure 5: Sound pressure vs. frequency by IA method
Therefore, the peak position slightly different results though IA
method, focusing on the vibration from 1400Hz to 1600Hz, the distributionof vibration are created. The distribution of vibration in 1495.5Hz is shownin Figure 6. It is clear that the large vibrations caused by the detective part.
This result may be understood that detective parts can be extracted by NCAI
method.

Figure 6: An example of the experimental result. Output wave is chirp (500
- 3000 Hz).
(a) Figuregraph of CCD camera, (b) Vibration velocity image at 1495.5 Hz.
4. CONCLUSIONSIt has been understood to be able to detect the defect in the surface part suchas delamination and cavity of concrete from a position 10m away by NCIA
method. As a result, the defect of 2.5cm in depth was able to be detected
about the case with a narrow plane scale (square of 10cm). Moreover, thedefect that existed in 7.5cm in depth was able to be detected about the casewith a wide plane scale (square of 50cm). Moreover, the defect of theconcrete at surface part can be vibrated from these results by the sound, andit has been understood to be able to measure the vibration from the remote

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place. Therefore, the hammering test can be replaced by NCAI method in
the near future.
Because it was assumption in this experiment that the defect position
etc. understood beforehand, the vibration frequency that vibrated easily wasable to be decided. Some improvements are necessary to make NCAI
method available in the site. Whether the frequency of the vibration of
normal mode is efficiently found (How does it vibrate the defect by using
LRAD?) becomes an important problem because it understands neither
depth nor the area of the defect in the site beforehand. Moreover, it isnecessary not to use the vibration of normal mode, and to examine the probe
algorithm that pays attention to the frequency band of the vibration for
instance.
ACKNOWLEDGEMENT
This work was supported by the Ministry of Land, Infrastructure andTransport, technology of Japan, research development to contribute toimprovement of the quality of the road policy (2010 Feasibility Study),“Research and development about the non-contact acoustic exploration
method for non destructive Inspection”.
REFERENCES
T.Abe and T.Sugimoto, 2009. Extremely Shallow Underground Imagi
ng Using
Scanning Laser Doppler Vibrometer, Jpn. J. Appl. Phys., 48, 07GC07
T.Abe and T.Sugimoto, 2010. Distinguishing Buried Objects in Extre
mely Shallow Underground by Frequency Response Using Scanning Laser
Doppler
Vibrometer, Jpn. J. Appl. Phys., 49, 07HC15
T.Sugimoto and T.Abe, 2011. Buried object detection method using op
timum
frequency range in extremely shallow underground, Jpn. J. Appl. Phys.,
50, 07HC18

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Service life cycle assessment of chloride
attacked concrete structureswith silane treatment considering
environmental impacts
Aruz PETCHERDCHOO
Lecturer, Department of Civil Engineering, Faculty of Engineering,
King Mongkut’s University of Technology North Bangkok, Thailandaruz.rm@gmail.com
ABSTRACTIn this study, the service life cycle of chloride attacked concrete structures
repaired with silane treatment considering environmental impacts is
assessed by predicting the amount of penetrating chloride ions based on the
Fick’s second law of diffusion. The Crank-Nicolson based finite difference
method is used as a tool, because it is suitable for the problem with spacedependent diffusion coefficient due to applying silane treatment to concrete
structures, and with considering time dependency of surface chloride anddiffusion coefficient in computation. Moreover, the environmental impacts
resulting from applying different strategies of silane treatment (the number
of application, the application time, the effect, and the effective duration ofsilane treatment) are considered, and an optimum strategy is determined.
From the study, it is found that the water to cement ratio of original
concrete and the strategies of silane treatment all are related to the service
life. Based on the parameters considered, the water to cement ratio affects
more. And, the target time horizon also affects the optimum strategy to be
selected.
Keywords: service life cycle, assessment, chloride attack, concrete
structures, silane treatment, environmental impacts.
1. INTRODUCTION
The concern on how human activities affect the loss of biodiversity, thethinning of stratospheric ozone, the climate change, and the consumption ofnatural resources, has been increasing, hence the word “sustainable
development” was introduced in the final report of the Brundtland
Commission (World Commission on Environment and Development,
WCED) of 1987 (Arskog et al., 2004).
In the present, sustainable construction is widely mentioned, because
old-fashioned construction to support city expansion due to population
increase was found to be the largest consumer of materials (Ho et al., 2000)
leading to large environmental impacts, in particular, Greenhouse effect6291

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gases, e.g., carbon dioxide (CO2) from the process of cement production.
This issue subsequently led to the Kyoto protocol (Sakai, 2005) which has
been mentioned until now.
Uren et al. (2000) stated that the sustainable construction can beobserved from the environmental criteria included in the project concept,
and in the process of building, maintaining, and demolishing. Metha (2001)
mentioned that the most efficient way for construction to approach theconcept of sustainability is to reuse waste products from other industrial
activities as well as improve the durability of the works to last. Therefore, aproper design for durability and long-term performance of concrete
structures must be achieved, and the activities in life cycle should
consequently be assessed.
The regulation in the ISO-EN-UNE-14.040 standard defines the word
“Life Cycle Assessment (LCA)” as the collection and assessment of the
inputs and outputs of any potential environmental impacts caused by the
production system throughout its life cycle. From this, the activities, e.g.,construction, reuse, and demolition, causing environmental impacts should
be concerned in the life cycle assessment. For structures in operation, theassessment concerning life cycle can be defined as service life cycle
assessment. The key aspects needed to consider are repair and maintenance(Peris Mora, 2007).
In this paper, the service life cycle of concrete structures underchloride attack by diffusion and under several repair strategies by silane
treatment is studied using the finite difference method to predict the amountof penetrating chloride ions through concrete structures. Moreover, theenvironmental impacts resulting from applying silane treatment are
determined, and an optimum strategy is considered.
2. SERVICE LIFE CYCLE ASSESSMENT
There are two main processes in assessing the service life; assessment of theservice life of chloride attacked concrete structures without and with silane
treatment as explained in the following.
2.1 Without silane treatment
Concrete structures under chloride attack by diffusion can be assessed
based on the partial differential equation (PDE) of the Fick’s second law(Crank, 1975) as
∂C ∂
∂C
=
D
∂t ∂x ∂x(1)

where C is the chloride content as a function of a position x and time t, andD is the chloride ion diffusion coefficient. With proper initial and boundary

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conditions,conditions,
equation
equation
1 can1 analytically
can analyticallybe solved
be solved
and used
and usedin theinassessing
the assessing
process
process
whichwhich
can becanfound
be foundelsewhere
elsewhere(e.g.,(e.g.,
SaettaSaetta
et al.,et1993).
al., 1993).
2.2 With
2.2 Withsilanesilane
treatment
treatment
FromFrom
NCHRP-558
NCHRP-558(2006),(2006),
silanesilane
treatment
treatmentis categorizedis categorized
as oneaskindone kindof penetratingof penetrating
sealers
sealers
for hydrophobic
for hydrophobic
treatment
treatment
aimingaimingto slow
to slow
downdown
the thedeterioration
deterioration
rate ofrateconcreteof concrete
structures.
structures.
ThereThere
are twoare main
two mainstepssteps
in thisin thisprocess
process
as follows:
as follows:
2.2.12.2.1
Chloride
Chloride
ion penetration
ion penetrationfrom fromthe outerthe outersurfacesurfacethroughthroughthe original
the original
concrete.
concrete.
For this,
For this,the Crank-Nicholson
the Crank-Nicholson
numerical
numerical
schemeschemecan becanused.
be used.
As As
the diffusion
the diffusion
coefficient
coefficient
D is D
constant
is constantfor thefororiginal
the original
concrete,concrete,the finite
the finite
difference
difference
approximation
approximationfor equationfor equation
1 (von1 (vonRosenberg,
Rosenberg,1969)1969)is writtenis written
as as

(

(

) () ())⎡ cD⎡ 1 i−+1,2j +c1i ,−j +12+ci ,cji+−11,+j +1ci −+1, j +c1i +1+, j −ci +21c, ji ,−j +2cii,−j1,+j c⎤i −1, j ⎤ci , j +1 −ci ,cji+,1j − cDi, ji +1, j +c
= ⎢= ⎢⎥ (2) ⎥ (2)Δt Δt 2 ⎣⎢ 2 ⎣⎢(Δx )2(Δx )2⎦⎥⎦⎥
in is,
a general
in a generalform,form,
the chloride
the chloride
content
content
at a meshat a meshpointpointx at time
x at time
wherewhere
cx,t is,cx,tt. Δt t.andareincremental
the incremental
time time
step andstep theandsizethe ofsizetheofmesh
the meshpoint,point,Δt Δandx are
Δxthe
respectively.
respectively.
2.2.22.2.2
Chloride
Chloride
ion penetration
ion penetration
throughthroughsilanesilane
treatedtreatedconcreteconcreteand original
and original
concreteconcrete(REHABCON,(REHABCON,
2004).
2004).
Let consider
Let consider
FigureFigure1. When
1. Whenthe time
the time
passespassesby, theby,chloride
the chloride
ions penetrateions penetrate
throughthroughconcreteconcrete
structures,
structures,and theandamount
the amountof chlorideof chloride
at concreteat concretesurfacesurfaceincreases
increases
with withtime time
becausebecauseof timeof timedependent
dependent
surfacesurfacechloride.
chloride.

a) Chloride-Deptha) Chloride-Depth
ProfileProfileb) Chloride-Timeb) Chloride-Time
ProfileProfileFigureFigure1: Chloride
1: Chloride
Profile:Profile:With Withand Without
and Without
SilaneSilane
Treatment
Treatment
At theAttimethe timeti, silane
ti, silane
treatment
treatment
is applied
is appliedat theatsurface
the surfaceof concrete,of concrete,
and then
and thensilanessilanes
will react
will reactwith withthe porethe porestructure
structure
withinwithinhardened
hardened
concreteconcreteto create
to createa nonwettablea nonwettableor hydrophobicor hydrophobic
surfacesurfaceas deep
as deep
as theasdistancethe distancexp (orxp (orrepairrepair
depth).
depth).
This This
will will
resultresultin thein problem
the problem
involving
involving
spacespacedependent
dependent
diffusiondiffusioncoefficient,coefficient,or D(x),or D(x),due todue
thetodifference
the differenceof diffusionof diffusion
coefficientscoefficients
betweenbetweenthe original
the original
concreteconcreteand theandsilane
the silane
treatedtreatedconcrete.
concrete.
In addition,
In addition,
it it
is foundis foundthat thethatdiffusion
the diffusion
coefficient
coefficientis timeis timedependent,
dependent,or D(t),or D(t),becausebecausethe thecontinuous
continuous
process
processof cementof cement
hydration
hydration
results
resultsin connection
in connection
and andcondensation
condensationof concreteof concretepore pore
structures.
structures.
Mathematically,
Mathematically,
the thePDE PDE
Servicelife cycle
assessmentof chloride
attackedconcrete
structureswith Silane
treatment
considering
Servicelife cycle
assessmentof chloride
attackedconcrete
structureswith Silane
treatment
considering
Service life cycle assessment of chloride attacked concrete structures
3 6313environmental
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concerning the space and time dependent diffusion coefficients can be
written as∂C∂C ∂D ( x, t )
=
∂x
∂t ∂x

(3)

It is quite complicated to solve for a close-formed solution of equation
3, hence a Crank-Nicolson based numerical scheme is introduced as (Press
et al., 1996)
ci , j +1 − ci , j
Δt=

1 ⎛⎜ [Di +1/ 2 (ci +1 − ci ) − Di −1/ 2 (ci − ci −1 )], j +1 [Di +1/ 2 (ci +1, − ci , ) − Di −1/ 2 (ci , − ci −1, )], j ⎞⎟+⎟2 ⎜⎝(Δx )2(Δx )2⎠(4)

where Di+1/2 = (Di + Di+1)/2 and Di-1/2 = (Di-1 + Di)/2. If the diffusion
coefficients in equations 3 and 4 are constant, these equations are reduced toequations 1 and 2, respectively. In computation, when the original concrete
is treated with silanes, over the depth xp, the diffusion coefficient of silane
treated concrete will be updated as (D0,t )o = (D0,t )REP at concrete surface, and(D ) = (D )Xp ,t oXp ,t REP

at repair depth xp. (DXp ,t )o and (D Xp ,t )REP are the diffusion

coefficients of the original concrete and silane treated concrete, respectively,
at the depth xp and time t.
Figure 1b shows the chloride content at a threshold depth d (see also
Figure 1a) plotted with time. With silane treatment, the increase of chloride
content is retarded resulting in the reduction of penetrating chloride ions,and consequently the reduction of rebar corrosion and concrete structure
deterioration.
2.3 Time dependant surface chloride and diffusion coefficient
The attack of chloride in this study is represented as the timedependent surface chloride proposed by Kassir and Ghosn (2002) as shownin equation 5 and plotted in Figure 2.
(5)
CS (t ) = 5.34(1 − e −0.25t )Figure 2 Time Dependent Surface Chloride and Diffusion Coefficient

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TheThedeterioration
deteriorationof concreteof concrete
structures
structures
is related
is related
to theirto theirresistanceresistanceor or
diffusiondiffusioncoefficient
coefficient
which
which
is foundis found
to be
to be
timetime
dependent,
dependent,
becausebecausethe thecontinuous
continuousprocessprocessof ofcement
cementhydration
hydrationresults
resultsin inconnection
connectionandandcondensation
condensationof ofconcreteconcrete
poreporestructures.
structures.
TheThetimetime
dependent
dependent
diffusiondiffusioncoefficient
coefficientat timeat timet can
t can
be represented
be represented
as (Thomasas (Thomas
andandBentz,
Bentz,
2000)
2000)
0.2

0.2

0.2

0.2

⎛ ⎛ ⎞28 ⎞if t if> t30⎛ 28⎛⎞28 if⎞ t if≤ t30
years;
years;
andandyears(6)years(6)≤ 30> 30⎜ ⎟ ⎟⎟) =w / D
Dw / Dt )/ c=(tD
Dw / cD(tw)/ c=(tD) =w / cD⎜⎜w28⎟c (wc ⎜w / c ⎜⎟/ c ⎜⎟⎝ t ⎝⎠ t ⎠⎝ t lim⎝ ⎠t lim ⎠

where
where
is thediffusiondiffusioncoefficient
coefficientof ofconcreteconcrete
structures
structures
at 28
at 28
Dw /D
c wis
/ c thedays
days
as equal
as equal
to 13.8,
to 13.8,
7.94,
7.94,
andand
4.574.57
for forthe thewater
water
to cement
to cement
ratio
ratio
(w /(cw)/ c )
equal
equal
to 0.3,
to 0.3,
0.4,0.4,
andand
0.5,0.5,
respectively.
respectively.
TheThepower
power
of 0.2of 0.2
represents
represents
the therateratet lim tisis thelimit
limit
timetime
which
which
is equal
is equal
to 30
to 30
of diffusionof diffusion
coefficient
coefficient
decay,
decay,
andandlim theyears
years(10950(10950days).
days).
TheThetimetime
dependent
dependent
diffusiondiffusioncoefficient
coefficientfor forof 0.3,w / cw of/ c 0.3,
0.4,0.4,
andand
0.5 0.5
are areshown
shown
in Figurein Figure
2. 2.
TheThediffusion
diffusioncoefficient
coefficientof ofsilane
silanetreatedtreatedconcrete
concretestructures
structures
cancanbe berelatedrelatedto tothatthatof ofthe theoriginal
original
concreteconcrete[Dw /[cD(tw)]/ REP[Dw /[cD(tw)]/0c (t )as]0 as
c (t )]REP
which
which
n isn ais number
a number
which
which
represents
represents
the theratio
ratio[Dw /[cD(tw)]/ REPn[D= wn/[cD(tw)]/0c (tin)]0 inc (t )]=
REP
betweenbetweenthe thediffusiondiffusioncoefficient
coefficientof theof thesilanesilanetreatedtreatedconcreteconcreteandandthatthatof ofthe theoriginal
original
concrete.
concrete.
In thisIn thisstudy,
study,
n isnselected
is selected
to be
to 0.2
be 0.2andand0.290.29
for forfourfourstrategies
strategies
(SL1
(SL1
to SL4)to SL4)
as denoted
as denotedin Tablein Table
1. These
1. These
twotwovaluesvaluesare arechosenchosen
based
based
on on
the thetesttest
results
resultsof Medeirosof Medeiros
andandHeleneHelene(2009)(2009)
andandShimomura
Shimomura(2005).
(2005).
In addition,
In addition,
Shimomura
Shimomura(2005)(2005)
estimated
estimated
the thesilanesilanetreatedtreated
depth
depth
to to
be 30
be 30
mmmm
as alsoas alsoused
used
in thisin thisstudy
study(see(see
Table
Table
1). 1).
It isItnoted
is noted
thatthatconcreteconcrete
structures
structures
withwith
lower
lower
diffusiondiffusioncoefficient
coefficientare aremore
more
resistantresistantto chloride
to chloride
diffusion.
diffusion.
2.5 2.5
Application
Application
time
time
andandeffective
effective
duration
durationof silaneof silane
treatment
treatment
In thisIn thisstudy,
study,
the theapplication
application
timetimeof silaneof silane
treatment
treatment
is cyclicallyis cyclicallytimetime
based,
based,
andandadoptedadoptedfromfromthe thedatadataof Dentonof Denton(2002)(2002)as shown
as shown
in Tablein Table
1. 1.
CarterCarterandandMcGettigan
McGettigan(2001)(2001)
referredreferredto theto thepaper
paper
of Weyersof Weyers(1993)(1993)
which
which
statedstatedthatthat
the theeffective
effective
duration
durationor theor theserviceservicelifelifeof high-solidof high-solid
silanessilanes
fellfellbetweenbetween
5 and
5 and
10 years.
10 years.
In thisIn thisstudy,
study,
the theeffective
effective
duration
duration
is chosen
is chosen
to be
to be
7.5 7.5or 10
or years
10 years
after
after
previous
previous
application
application
as shown
as shown
in Tablein Table
1. It1.isItobserved
is observed
thatthat
in SL4,in SL4,when
when
the theeffective
effective
duration
durationis terminated,
is terminated,
the thesilanesilanetreatment
treatment
is isimmediately
immediately
reapplied.
reapplied.
Table
Table
1: Diffusion
1: Diffusion
coefficient,coefficient,application
application
timetime
andandduration
durationof SL1of SL1to SL4to SL4
SilaneSilaneTreatment
Treatment
Strategy
Strategy

Diffusion
Diffusion

SilaneSilaneApplication
Application
TimeTime

Effective
Effective

Coefficient
Coefficient Depth
DepthFirstFirst

Subsequent
Subsequent

Duration
Duration(XP)(XP)) 1ST)(t1ST(t(tSUB(t) SUB)(tDUR(t)DUR)

Every
Every
12.512.5
yrs. yrs.

7.5 yrs.
7.5 yrs.

[Dw /[cD(tw)]/ REPc (t )]REP

SL1 SL1

0.2 [D
0.2(tw)]/0c (t )]0 30 mm
30 mm At year
At year
7.5 7.5
w /[cDSL2 SL2

0.2 [D
0.2(tw)]/0c (t )]0
w /[cD

10 yrs.
10 yrs.

Service
cycle
assessmentof chloride
attackedconcrete
structures
Silanetreatment
considering
Servicelife life
cycle
assessmentof chloride
attackedconcrete
structures
withwith
Silanetreatment
considering
Service life cycle assessment of chloride attacked concrete structures
56335
environmental
impacts
environmental
impacts
with silane treatment considering environmental impacts

October
2011,
Chiang
Mai,Thailand
Thailand
October
2011,
Chiangmai,
Chiangmai,
ThailandSL3 SL30.290.29[Dw /[cD(tw)]/0c (t )]0

SL4 SL4

0.290.29[Dw /[cD(tw)]/0c (t )]0

10 yrs.
10 yrs.
Every
Every
10 yrs.
10 yrs.

10 yrs.
10 yrs.

2.6 2.6
CriticalCriticalchloridechloride
content
content
TheThecriticalcriticalchloridechloride
content
content
or theor thechloridechloridethresholdthreshold
level
level
can
ClCritClcan
Crit
be be
used
used
to indicate
to indicate
the thecurrent
currentstate
stateof structures,of structures,e.g.,e.g.,
startstartof corrosion,of corrosion,
startstartof cracking
of cracking
etc.etc.
Schiessl
Schiessl
andandRaupachRaupach(1990)(1990)
statedstatedthatthat
the thecriticalcriticalchloridechloride
content,
content,
could, could
be defined
be definedas theas thecontent
contentof chlorideof chloride
ionsions
thatthat
ClCritCl, Crit
were
were
necessarynecessaryto sustain
to sustain
local
local
passivepassive
filmfilm
breakdown
breakdownat theat the
steel
steel
depth
depth
beforebeforethe theprocess
processof corrosionof corrosion
initiation.
initiation.
JSCE
JSCE
(2002)(2002)
defineddefinedthe thecriticalcritical
3 3
as aasvalue
a value
to initiate
to initiate
reinforcement
reinforcement
corrosion.
corrosion.
Moriwake
Moriwake
value
value
of 1.2of 1.2
kg/m
kg/m
3 3
(1996)(1996)
defineddefinedthe thecriticalcritical
value
value
of 2.0of 2.0kg/m
kg/m
as aasvalue
a value
to initiate
to initiate
concreteconcrete
3 3
cracking.
cracking.
In thisIn thisstudy,
study,
the thecriticalcriticalchloridechloride
content
content
is chosen
is chosen
as 1.2
as 1.2
kg/m
kg/m
3 3
andand
2.0 2.0kg/mkg/m
to denoteto denote
reinforcement
reinforcement
corrosion
corrosion
freefreeandandconcreteconcrete
crack
crack
freefreecontrol
controlplans
plans
for forconcreteconcrete
structures,
structures,
respectively.
respectively.
3. ENVIRONMENTAL
3. ENVIRONMENTAL
IMPACTS
IMPACTSOFOF
SILANESILANE
TREATMENTTREATMENTTheTheenvironmental
environmental
impacts
impactsof silaneof silane
treatment
treatment
were
were
studiedstudiedby Arskog
by Arskog
et al.
et al.
(2004),(2004),
andandcancanbe classified
be classified
intointo
severalseveralcategories.
categories.
In thisIn thisstudy,
study,
onlyonly
UseUseof Energyof Energy
andandGlobalGlobalWarmingWarming
are areconsidered.
considered.
TheTheenvironmental
environmental
impacts
impactsof theseof these
twotwocategories
categories
are arederivedderivedfromfromfourfourprocesses;
processes;
production
productionof silaneof silane
agent,
agent,
surfacesurfacepreparation
preparation
for fortreatment,
treatment,
transportationtransportation
andandtreatment
treatment
process,
process,
andandlong-term
long-term
degradation.
degradation.
TheTheestimation
estimationof theof theenvironmental
environmental
impacts
impacts
perperactionactionfor forthe thefourfourprocesses
processes
is shown
is shown
in Tablein Table
2. 2.
Table
Table
2: Environmental
2: Environmental
Impacts
Impactsof Silaneof Silane
Treatment
Treatment(Per(Per
Action)Action)Processes
Processes
Productionof silane
agent
Productionof silane
agent
Surfacepreparation
Surfacepreparation
Transportation
and andsilaneprocess
Transportationsilaneprocess
Long-term
degradation
Long-term
degradation
Total
Total

ImpactImpactcategory
category
GlobalGlobalWarmingWarming
UseUseof Energyof Energy
2
2
) 2)
(g CO
(g 2CO
eq/m
) 2)
(MJ/m
(MJ/m
2 eq/m47 47
295 295
17 17
10 10
12 12
80 80
- 21712171
76 76
25592559

These
These
twotwocategories
categories
willwillbe considered
be considered
in combinationin combination
withwiththe theserviceservicelifelife
cycle
cycle
assessment
assessment
as shown
as shown
in thein thenumerical
numerical
examplesexamplesin thein thenextnext
section.
section.
4. NUMERICAL
4. NUMERICAL
EXAMPLES
EXAMPLES
Based
Based
on on
the theaforementioned
aforementioned
ideaidea
andanddata,
data,
a Crank-Nicolsona Crank-Nicolson
based
based
finitefinitedifference
difference
programprogramwaswasdeveloped
developed
for forcomputation,
computation,
andandcalledcalled“SA2CR”“SA2CR”
lifelife
Assessmentof Concrete
structures
under
Chloride
attack
withwith(Service(Service
Assessmentof Concrete
structures
under
Chloride
attackRepairs).
In In
computation,
the thesizesizeof ofthe themesh
point,, andthe theRepairs).
computation,meshpoint,
Δx Δ, x andincremental
incremental
timetime
step,
step,
selected
selected
as 1asmm
1 mmandand1 week,1 week,respectively.
respectively.
Δt ,Δaret , are6 6634

NewNew
Technologies
Technologies
for Urban
for
Urban
Urban
SafetySafetyof MegaMegaof Mega
CitiesCitiesin Asia
Asia
in AsiaNew
Technologies
forSafetyof
CitiesinICUS Report 56

And, theAnd,thresholdthe threshold
depth,depth,d, is selectedd, is selected
to be to80 bemm80asmmequal
as equal
to thetocover
the coverdepth depthof concreteof concrete
structures
structuresin the inmarinethe marine
environment
environment(MOCT,(MOCT,
2004).2004).
The chloride
The chloride
profileprofile
for thefororiginal
the original
concreteconcrete
structure
structurehavinghaving
w/c =w/c =0.3 without
0.3 without
and withand silane
with silane
treatment
treatmentof SL3ofcan
SL3becancomputed
be computed
and plottedand plottedwith respectwith respect
to depth
to depth
and time
and astime
shown
as shown
in Figures
in Figures
3a-c and3a-cFigure
and Figure
3d, 3d,respectively.
respectively.
From From
FigureFigure
3a, the3a, chloride
the chloride
ions penetrateions penetrate
throughthroughthe theoriginal
original
concrete,concrete,when when
the time
thepasses
time passesby (yearby 1(year
to year1 to7).
year
At7).
theAt
surface,the surface,
the chloride
the chloride
ion concentration
ion concentration
increases
increases
with timewith because
time becauseof theofeffectthe effectofoftime dependent
time dependentchloridechloride
ion concentration.
ion concentration.
And, And,the rate
the ofrate
chlorideof chloride
ion iondiffusiondiffusionis slower
is slowerwith increasing
with increasing
time, time,
becausebecauseof theofeffectthe effectof timeof timedependent
dependent
diffusiondiffusioncoefficient
coefficientwhichwhich
decaysdecays
with time.
with time.
From From
FigureFigure
3b, silane
3b, silane
treatment
treatmentof SL3ofisSL3
firstisapplied
first applied
to the tooriginal
the original
concreteconcreteat theatyear
the 7.5,
year hence
7.5, hence
the diffusion
the diffusion
coefficient
coefficientof theoforiginal
the originalas(t )]0 as
concreteconcreteis updated
is updated
to thattoofthat
theofsilane
the silane
treatedtreatedconcreteconcreteor 0.2or[Dw0.2/ c (t )[]D
0 w/ cdeep as
deep
30 as
mm
30frommm concrete
from concretesurface.
surface.
At theAtyear
the 17.5
year (1017.5years(10 years
after theafter thefirst treatment),
first treatment),
the effectthe effectof silanesof silanes
vanishes
vanishesdue todue
the toend
theofend
its oflifetime.
its lifetime.
At theAtyear
the 20year(12.5
20 (12.5
years years
after theafterfirst
thetreatment),
first treatment),silanessilanes
are reapplied,
are reapplied,
and its
andeffect
its effectlast forlast10foryears.
10 years.
After After
that, thethat,samethe samesilanesilane
treatment
treatmentisiscyclicallycyclicallyappliedappliedtill thetillend
theofend
theoftarget
the target
time horizon
time horizonof 100ofyears
100 yearsasasshownshownin Figurein Figure3c. If 3c.
the Ifchloride
the chloride
profileprofileat the atyear
the100
yearfor100
theforcase
thewithcase withsilanessilanes
is comparedis comparedto thattowithoutthat withoutsilanes,silanes,
it shows
it shows
that thethatdiffusion
the diffusion
ofofchloridechlorideions thoughions though
the depth
the depthof concreteof concretewith silane
with silane
treatment
treatment
is slower.
is slower.

a) Yeara) 1Yearto 7 1 to 7b) Yearb) 7.5Year
to 7.557.5to 57.5c) Yearc) 57.5
Yearto57.5
100to(w/100SL3(w/andSL3w/o)and w/o)d) At 80d) At
mm80(w/o
mmand(w/ow/andsilanes),
w/ silanes),
FigureFigure
3 Chloride
3 Chloride
ProfileProfile
VersusVersus
DepthDepth
and Time
and Time
for thefor
original
the original
concreteconcretewith w/c=0.3
with w/c=0.3
lifeassessment
cycle assessmentof chloride
attackedconcrete
structureswith Silane
treatment
considering
ServiceService
life cycleof chloride
attackedconcrete
structureswith Silane
treatment
considering
Service life cycle assessment of chloride attacked concrete structures
7 6357
environmental
impacts
environmental
impacts
with silane treatment considering environmental impacts

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 3d represents the profiles of chloride diffusion though theoriginal concrete having w/c of 0.3 without and with silane treatment (SL1to SL4) at the threshold depth of 80 mm. Without silane treatment, thechloride content will increase causing continuous deterioration of theconcrete structure. If the time that the chloride profile crosses the value of
1.2 and 2.0 kg/m3 is defined as the service life of the structure for corrosion
free and crack free control, its service life is about 50 and 93 years,
respectively. However, if SL3 is applied, the service life of the structure will
be extended to 68 years and larger than 100 years prior to the occurrence ofcorrosion and cracking, respectively. And, the service life of the structurewith SL3 is longer than that with SL1 because of longer effective durationof SL3, but shorter than that with SL2 because of lower silane quality of
SL3. It should also be observed that, for the target time horizon of 100 years,
all the four strategies are effective only for crack free control, while only
SL4 is effective for both corrosion and crack free control. And, the effect ofsilanes on the diffusion of chloride ions is obvious after the year 15 asshown by the profiles which start to deviate from the profile without silane
treatment.

Figure 4 Time to start corrosion for w/c= 0.3, 0.4, and 0.5 without and withsilanesFigure 5 Time to start cracking for
w/c = 0.3, 0.4, and 0.5 without andwith silanes

The service life of the original concrete structure having w/c of 0.3,
0.4, and 0.5 without and with silane treatment can be represented in terms oftime to start corrosion and cracking (the time that the chloride profile toreach 1.2 and 2.0 kg/m3, respectively) as shown in Figures 4 and 5,
respectively. It is found that the original concrete structure with lower w/c isbetter. And, the original concrete structure with w/c of 0.4 and 0.5 underSL1, SL2, and SL3 are not effective for controlling both corrosion and crack
for the target time horizon of 100 years, because the time to start corrosion
and cracking is less than the target time horizon.
The environmental impacts resulting from silane treatment for thetarget time horizon of 100 and 65 years are shown in Tables 3 and 4,
respectively.

8636

New Technologies
Technologies forfor Urban
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ICUS Report 56

Table Table
3: Environmental
3: Environmental
Impacts
Impactsof Silaneof Silane
Treatment
Treatment
for 100
foryear
100timeyear time
horizonhorizonEnvironmental
Environmental
Impacts
Impacts
NumberNumberofof
Silane Treatment
Silane Treatment
WarmingWarming2
2 GlobalGlobal
ActionsActionsUse of Energy
Use of Energy(MJ/m(MJ/m))
2Strategy
Strategy) eq/m2)(g CO2(geq/m
CO2
in 100 Yrs.
in 100 Yrs.
Per Action
Per Action
100 Yrs.
100 Yrs.
Per Action
Per Action
100 Yrs.
100 Yrs.
1) SL1 1)
to SL1SL3 to SL3
8
8
76
76
608 608 2559 2559 20472 20472
2) SL4 2) SL4
10
10
76
76
760 760 2559 2559 25590 25590
Ratio ofRatio2) toof
1)2) to 1)
1.25 1.25
11
1.25 1.25
11
1.25 1.25

Table Table
4: Environmental
4: Environmental
Impacts
Impactsof Silaneof Silane
Treatment
Treatmentfor 65foryear
65timeyear time
horizonhorizonEnvironmental
Environmental
Impacts
Impacts
NumberNumberofof
GlobalGlobal
WarmingWarming
Use of Energy
Use of Energy
Strategy
Strategy ActionsActions
22))(g CO2(geq/m
CO2) eq/m2)(MJ/m2(MJ/m
in 75 Yrs.
in 75 Yrs.
Per Action
Per Action
65 Yrs.65 Yrs.
Per Action
Per Action
65 Yrs.65 Yrs.
1) SL1 1)
to SL1SL3 to SL3
5
5
76
76
380 380 2559 2559 12795 12795
2) SL4 2) SL4
6
6
76
76
456 456 2559 2559 15354 15354
Ratio ofRatio2) toof
1)2) to 1)
1.20 1.20
11
1.20 1.20
11
1.20 1.20

Table Table
3 shows
3 shows
that thethat
ratio
theofratio
the ofnumberthe numberof actionsof actions
betweenbetween
SL4 and
SL4 andthe other
the strategies
other strategies(SL1, (SL1,
SL2, SL3)
SL2, isSL3)
equal
is equal
to 1.25,
to hence
1.25, hence
SL4 causes
SL4 causes
25% 25%higherhigher
environmental
environmental
impacts.
impacts.
Although
Although
SL4 causes
SL4 causes
higherhigher
environmental
environmental
impacts,
impacts,
it is more
it is more
effective
effective
in controllingin controlling
corrosion
corrosionand crackand crack
than otherthan otherstrategies
strategies(see Figure(see Figure
4 and4 5).
andConsidering5). Consideringboth thebothservice
the service
life uponlife upon
corrosion
corrosionand crackand crack
free control
free control
and theandenvironmental
the environmental
impacts
impacts
for thefor thetarget target
time horizon
time horizonof 100ofyears,
100 years,
SL4 isSL4
an optimum.
is an optimum.
If the If
targetthe target
is to control
is to control
the structure
the structure
to be only
to befree
onlyoffree
corrosionof corrosion
for forthe lowest
the lowest
environmental
environmental
impacts
impacts
for thefortargetthe target
time horizon
time horizonof 65 years,of 65 years,
the theoriginal
original
concreteconcrete
structure
structurewith w/c
withofw/c
0.3ofunder
0.3 under
SL2 isSL2
an optimum
is an optimum(see (seeFiguresFigures
3d and3d4).and
But4).if But
the target
if the target
is to control
is to control
both corrosion
both corrosion
and cracking
and cracking
without
without
considering
considering
the environmental
the environmental
impacts,
impacts,
the original
the original
concreteconcrete
structure
structurewith w/c
withofw/c
0.3ofunder
0.3 under
SL4 isSL4
an optimum
is an optimum
insteadinstead
becausebecauseof its of its
longestlongest
serviceservice
life (seelifeFigures.
(see Figures.
4 and 45).and 5).

5. CONCLUSION
5. CONCLUSION
In thisInpaper,
this paper,
the service
the service
life cycle
life cycleof chlorideof chloride
attacked
attackedconcreteconcrete
structures
structureswith silane
with silane
treatment
treatment
considering
considering
the time
the dependency
time dependencyof surfaceof surface
chloridechlorideand diffusionand diffusion
coefficient
coefficientis studied
is studied
using using
the finite
the difference
finite difference
method.
method.
And, And,the environmental
the environmental
impacts
impacts
are also
areconsidered,also considered,and anandoptimuman optimum
strategy
strategyininapplying
applying
silane silane
treatment
treatment
is determined.
is determined.
From Fromthe study,
the study,
it can it
becan
concluded
be concluded
that that
1. Not1. only
Not theonlyw/ctheisw/c
important
is important
for theforservice
the service
life, butlife,also
but analso anappropriate
appropriate
plan planof silaneof silane
treatment
treatmentis alsois requiredalso required
for minimum
for minimum
environmental
environmental
impacts.
impacts.
2. The2.target
The target
time horizon
time horizonand control
and control
plan (corrosion
plan (corrosion
and cracking)and cracking)are important,are important,becausebecausedifferent
different
targetstargets
lead tolead
different
to different
optimum
optimum
strategies.
strategies.
lifeassessment
cycle assessmentof chloride
attackedconcrete
structureswith Silane
treatment
considering
ServiceService
life cycleof chloride
attackedconcrete
structureswith Silane
treatment
considering
Service life cycle assessment of chloride attacked concrete structures
9 6379environmental
environmental
impactsimpacts
with silane treatment considering environmental impacts

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

3. The method in this study is useful for selecting suitable original
concrete and silane treatment strategy for design service life upon corrosion
and crack control.
4. The results in this paper are based on available data. It is necessary
to collect more data for updated results. And, a probabilistic study should be
conducted to see the sensitivity of each parameter in various groups of data.
ACKNOWLEDGEMENT
The financial support from the Faculty of Engineering, King Mongkut’s
University of Technology North Bangkok is gratefully acknowledged.
REFERENCES
Arskog, V., Fossdal, S., and Gjorv, O.E., 2004. Life-Cycle Assessmentof Repair and Maintenance Systems for Concrete Structures. Int. Workshop
on Sustainable Development and Concrete Tech. Beijing. China. May 20-21.
193-200.
Ho, D.W.S., Mak, S.L., and Sagoe-Crentsil, K.K., 2000. Clean
Concrete Construction. An Australian Perspective. Proc.of Concrete Tech.
for a Sustainable Development in the 21st Century. E&FN Spon, London
and New York, 236-245.
Sakai, K., 2005. Environmental Design for Concrete Structures.
Journal of Advanced Concrete Technology. 3:1. 17-28.
Uren S., Brown A., and Gooch F., 2000. Sustainable construction inpractice. Proceedings of International Conference on sustainable building.
Ibd.
Metha P.K., 2001. Reducing the environmental impact of concrete.
Concrete can be durable and environmentally friendly. ConcreteInternational. 23(10).
Peris Mora, E., 2007. Life Cycle, Sustainability and the Transcendent
Quality of Building Material, Building and Environment. 42. 1329-1334.
Crank. J. 1975. The mathematics of diffusion. Oxford: The Clarendon
Press (2).
Saetta, V.A., Scotta, V.R., and Vitaliani, V.R. 1993. Analysis ofchloride diffusion into partially saturated concrete. ACI Materials Journal,
90, 441–451.
NCHRP-558, 2006. Manual on Service life of corrosion-damaged
reinforced concrete bridge superstructure elements. Transportation
Research Board.
Von Rosenberg, 1969. Methods for the numerical solution of partial
differential equations. Elsevier Publishing Co.
REHABCON, 2004. Final report on the evaluation of alternative
repair and upgrading options: Strategy for maintenance and rehabilitationin concrete structures. EC Innovation and SME programme project no. IPS2000-0063, Department of Building Materials, LIT, Lund, Sweden.
Press W.H., Teukolsky S.A., Vetterling W.T. and Flannery B.P., 1996.
Numerical recipes in C: the art of scientific computing. Cambridge
University Press. 2nd Ed.

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Kassir M.K. and Ghosn M., 2002. Chloride-induced corrosion ofreinforced concrete bridge decks. Cement and Concrete Research, pp. 139–
43.
Thomas, M.D.A., and Bentz, E.C., 2000. Life-365 manual. Released
with Program by Master Builders.
Medeiros MHF and Helene P., 2009. Surface treatment of reinforced
concrete in marine environment: Influence on chloride diffusion coefficientand capillary water absorption. Construction and Building Materials, pp.
1476-1484.
Shimomura, T., 2005. Evaluation of effectiveness of surface protecting
materials for concrete by numerical analysis. Proceeding of an international
workshop on durability of reinforced concrete under combined mechanicaland climatic loads, Qingdao Technological University, Qingdao, China.
Denton, S., 2002. Data estimates for different maintenance options forreinforced concrete cross-heads. Progress Meeting, Highways Agency,
London, Parsons Brinckerhoff Ltd., Bristol, U.K.
Carter P., and McGettigan, E., 2001. The fundamental of cleaning andcoating concrete. Chapter 8: Coating Materials: Sealer, pp. 149-166.
Weyers, R.E., 1993. Concrete Bridge Protection, Repair, andRehabilitation Relative to Reinforcement Corrosion: A Method Application
Manual. SHRP-S-360, Strategic Highway Research Program: Washington
D.C., pp.59-61.
Schiessl, P. and Raupach, M., 1990. Influence of concrete
composition and microclimate on the critical chloride content in concrete.
Corrosion of Reinforcement in Concrete. Elsevier Applied Science, 49-58.
Japan Society of Civil Engineers (JSCE), 2003. Standard specification
for concrete structures – 2002, Structural Performance, Guidelines forConcrete, 3.
Moriwake, A., 1996. Study on durability and maintenance ofreinforced concrete jetty deck against chloride induced deterioration. PhD.
thesis, Tokyo Institute of Technology, Tokyo, Japan.
Ministry of Construction and Transportation (MOCT), 2004. Standard
specification for concrete structures on durability. Seoul, Korea (in Korean)Service life cycle assessment of chloride attacked concrete structures with Silane treatment considering
Service life cycle assessment of chloride attacked concrete structures11
environmental impacts
639with silane treatment considering environmental impacts

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640

New Technologies for Urban Safety of Mega Cities in Asia

Development of probabilistic structural
performance evaluation method
for port RC structure
Ema KATO1, Yuichiro KAWABATA2, Mitsuyasu IWANAMI3
and Hiroshi YOKOTA4
1
Senior Researcher, Port and Airport Research Institute (PARI), Japan(Researcher, ICUS, IIS, the University of Tokyo, Japan)
katoh-e@pari.go.jp
2Researcher, PARI, Japan
3
Head of Structural Mechanics Division, PARI, Japan
4
Professor, Faculty of Engineering, Hokkaido University, Japan(Visiting Professor, ICUS, IIS, the University of Tokyo, Japan)
ABSTRACTPort and harbor facilities often tend to suffer performance degradation
during their service period due to various reasons including materials
deterioration and damage of structural components. Therefore, the facilities
need to be maintained appropriately so as to keep the performance over therequired level throughout their service period. For this purpose,
performance evaluation of the facilities becomes important to conduct
suitable maintenance work.
The authors have tried to establish the simplified performance evaluation
method for reinforced concrete (RC) members by focusing on therelationship between the deterioration grade and structural performance. In
this paper, the total of 40 RC slabs extracted from existing port structures
was tested in order to evaluate the relationship between visually judged
deterioration grades and load carrying capacities. Wide variations wereobserved in the relationship in each deterioration grade, however, the load
carrying capacity tended to be smaller than the design expectations when
the symptom of deterioration appeared on the surface of concrete members.
Based on the statistical analysis on the relationship between deterioration
grades and load carrying capacities, the probabilistic evaluation method of
the load carrying capacities of RC slabs was proposed as a quantitativeevaluation method of residual structural performance of existing port RC
structures.
Keywords: reinforced concrete, performance evaluation, deterioration
grade, load carrying capacity, Weibull distribution6411

October 2011, Chiang
Mai,Thailand
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Chiangmai,

1. INTRODUCTIONPort facilities generally face severe environmental conditions compared toother infrastructure. They often tend to suffer performance degradation
during their service period due to various reasons including materials
deterioration and damage of structural components. Therefore, the facilities
need to be maintained appropriately so as to keep the performance over therequired level throughout their design service period. To achieve theeffective maintenance of port facilities, the authors have tried to establish
the life-cycle management system for a reinforced concrete (RC) deck of
open-type wharf that is one of the most vulnerable structural types in port
facilities, as shown in Figure 1 (Port and Airport Research Institute, 2007).
The life-cycle management is a series of actions including judgment of thedeterioration grade by periodic inspection, evaluation of the structural
performance, prediction of the future progress of performance degradation,and proposal of alternatives of appropriate countermeasures based on
lifecycle cost minimization or performance maximization under budget
capping.
Preparation of maintenance program
Years elapsed
Status of facility
usage

Inspection
Design conditions
Environmental
conditions

Input orreference

Evaluation & Prediction
Available performance evaluationand future prediction
Pe
rfo
rm
an
ce
Present
Time
Remaining service
period,Facility use plan

Countermeasure(method and timing)

Database
Input orreferencey Inspectiony Predictiony Countermeasure

Input orreference

Life-cycle management system

LCC reduction and rationalization of maintenance work

Figure 1: Life-cycle management system
During inspection of the present conditions of structural members andassessment of performance of structure, in general, appearances of RC
members are visually observed and are more or less subjectively evaluatedas the deterioration grade specified in the Maintenance Manual (Port andAirport Research Institute, 2007). However, it is not clear how thedeterioration grade quantitatively represents the performance of RC
members.
Aiming at the achievement of life-cycle management, the authors have
tried to establish the simplified assessment procedure of performance of RC
deck by focusing on the relationship between the deterioration grade andstructural performance of RC members. Load carrying capacities of RC
slabs extracted from various decks of existing open-type wharves showedlarge variations, even though those tested slabs indicated the same

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deterioration state (Kato et al., 2008). The tested results implied that theprobabilistic approach is required to appropriately evaluate the structural
performance with considering the variations in the existing structure
efficiently.
In this paper, the total of 40 RC slabs extracted from existing port
structures was tested in order to make clear the relationship between
visually judged deterioration grades and load carrying capacities. Then,based on the statistical analysis on the relationship between deterioration
grades and load carrying capacities, the probabilistic evaluation method of
the load carrying capacities of RC slabs was proposed as a quantitativeevaluation method of residual structural performance of existing port RC
structures.
2. DETERIORATION GRADE AND LOAD CARRYING CAPACITYOF TESTED RC SLABS
2.1 Procedure of test and measurement
To evaluate the relationship between visually judged deterioration
grades and load carrying capacities, the total of 40 RC slabs extracted fromthe total of 7 existing port structures was visually inspected andexperimentally load tested.
Table 1 lists the configurations anddeterioration grades of tested RC slabs. Slabs Nos. 1 to 33 were taken out
from RC decks of open-type wharves that have been in service for morethan 30 years, while Nos. 34 to 40 were taken out from RC superstructure ofan access bridge used for 44 years. Figure 2 shows an example of sampling
condition. The structural details of tested slabs are listed in Table 1.
Unfortunately almost all the details of constituent materials and design
calculations were not available to understand the designed conditions of thetested RC slabs.

Figure 2: Sampling of a slab
Those slabs were visually inspected on their surfaces at their loadingspans as listed in Table 1. Visual inspection was carried out by focusing on
cracks and their directions, spalling off of cover concrete, rust stain, andcorrosion appearances. Deterioration grades of all the slabs given in Table 1

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probabilistic structural
structural performance
performance evaluation
evaluationmethod
methodfor
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RCstructure
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Chiangmai,

were judged by the grading system summarized in Table 2 (Port and Airport
Research Institute, 2007). The total numbers of tested slabs are 2 fordeterioration grade d, 17 for grade c, 11 for grade b, and 10 for grade a.
After the visual inspection and judgment, the slabs wereexperimentally load tested as a one-way slab. They were simply supported
at their marginal regions having loading spans as listed in Table 1 and amonotonically-increased three-point (Slabs Nos.1~20) or four-point (Slabs
Nos.21~40) bending load was applied. The supporting areas were repairedby mortar in case that the cover concrete had been already spalled off.
During the test, the applied load and deflection at the supporting points andat the midspan were measured and recorded. Since no strain gauges wereglued on the surface of reinforcement, the first yield load was determinedwhen the midspan deflection showed a sharp increase.
Table 1: Configuration and deterioration grade of tested RC slabs
No. Year
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34

4
644

40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
32
32
32
32
32
41
41
30
30
44

Grade
b
a
b
c
d
a
a
a
b
b
b
c
c
c
d
b
c
c
b
c
b
a
a
a
c
c
c
c
c
c
c
c
b
b

Tensile reinforcing bars

Min.
width
(mm)

Shear
span
(mm)

(Type and diameter, number of reinforcing
bar, ave. effective depth (mm))

Pmax Failure(kN) mode

1490
1500
532
389
575
492
408
585
537
401
599
578
541
508
699
535
798
732
569
812
1940
1987
1984
1964
1560
1500
1370
1540
1385
1518
1508
1010
1010
600

400
400
450
450
450
450
450
450
550
550
550
550
550
550
600
600
600
600
600
600
750
750
750
750
1000
1000
1000
1000
1000
1000
1000
1450
1450
800

D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
φ13
φ13
φ13
φ13
φ13
φ13
D16
D16
D16
D16
D16
D16
D16
D16
D16
D13
D13
D16
D16
φ13

869
498
147
94
159
128
86
105
162
84
128
178
118
141
252
221
196
281
261
212
384
224
267
243
379
403
329
351
361
247
201
139
142
101

Upper
4
4
3
2
3
3
2
3
2
3
3
3
3
3
3
4
3
3
3
3
13
13
13
13
8
7
7
7
7
14
14
2
2
2

190
190
93
91
82
89
77
67
94
92
98
122
97
97
140
140
140
150
150
150
135
135
135
135
86
81
84
75
67
80
73
225
220
89

Lower

D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
D13
φ13
φ13
φ13
φ13
φ13
φ13
D16
D16
D16
D16
D19
D19
D19
D19
D19
D13
D13
D13
D13
φ13

8
8
3
2
3
3
2
3
2
3
3
3
3
3
5
4
6
5
5
6
5
5
5
5
8
8
8
8
8
7
7
5
5
3

290
290
187
187
189
186
185
176
211
197
180
205
203
168
250
250
250
260
260
260
242
222
241
231
181
181
181
185
179
205
180
280
300
161

F
F
F
F
F
S
F
S
F
F
F
S
S
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
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ICUS Report 56
2φ13 85 2 φ1385
3φ13159 3 103
159 103
S
35
4435
44
c
595
c
800
595
800
φ13
2φ13 94 2 φ1394
3φ13159 3 68159
68
F
36
4436
44
a
595
a
980
595
980
φ13
2φ13 83 2 φ1383
3φ13151 3 58151
58
F
37
4437
44
c
590
c
755
590
755
φ13
2φ13 81 2 φ1381
3φ13152 3 45152
45
F
38
4438
44
b
590
b
755
590
755
φ13
2
86
2
86
4
156
4
72
156
72
F
39
4439
44
a
690
a
750
690
750
φ13
φ13
φ13
φ13
2φ13 95 2 φ1395
4φ13163 4 123
163 123
S
40
4440
44
a
685
a
600
685
600
φ13
Note: TypeNote:
D =Typedeformed
D = deformedbar, Typebar,
φ =Typeroundφ bar,= round
Pmax bar,= maximum
Pmax = maximum
bending load
bending(P), load
F = (P), F =flexural failure,
flexuralS=
failure,shear S=
failureshear
after
failureyielding
after yielding

Table 2:Table
Criterion
2: Criterion
for gradingfor grading
RC slabRCof open-typeslab of open-type
wharf from
wharf
thefrom theviewpoint
viewpointof steel ofbarsteelcorrosion
bar corrosion

Deterioration
Deterioration
grade grade Criteria CriteriaaMap (crackinga
Map cracking> 50%) ( > 50%)
Spalling
off concreteof cover concrete
Spalling offof coverHeavy
Heavy ruststain rust stainbb
Map (cracking
Map cracking≦50%)( ≦50%)
Much rustMuch
stain rust stainc
One directionalcrack
or gel extractioncOne directional
crack or gel
extraction
PartialPartial ruststain rust staind
No deformation
and/or damaged
No deformation
and/or damage

To compare
To compare
the loadthe
carrying
load carrying
capacities
capacities
of testedofslabs
testedwith
slabs
variouswith various
structural
structuraldetails, details,
the loads
thewereloadsnormalized
were normalized
by correspondingby corresponding
calculated
calculated
results based
results on
based
the onbeam
thetheory
beam bytheoryusing
bydesigned
using designed
values ofvaluesstrengths,of strengths,
dimensions,dimensions,and theandinitialthe cross-sectional
initial cross-sectional
areas ofareas
reinforcingof reinforcing
bars. The
bars. The
design values
design ofvaluescompressiveof compressive
strengthstrengthand Young’sand Young’s
modulusmodulus
of concreteof concrete2222were assumed
were assumed
at 24N/mm
at 24N/mm
and 25kN/mm
and 25kN/mm
respectively
respectively
with consideringwith consideringthethedesign standards
design standards
for Japanesefor Japaneseport andportharborand facilities
harbor facilities
used more
usedthanmore
30than 30
years ago.
years
Based
ago.onBasedthe tensile
on the tests
tensileof tests
non-corrodedof non-corroded
reinforcing
reinforcing
bars takenbars takenout fromout
somefromtestsomeslabs,
testtheslabs,
designthe values
design ofvaluestensileof strengthtensile strengthand Young’sand Young’s22
22
modulusmodulusof reinforcingof reinforcing
bars were
barsassumed
were assumed
at 345N/mm
at 345N/mm
and 200kN/mm
and 200kN/mm
respectively.
respectively.

1.5

1.5

1.0

1.0

0.5

0.5

Load carrying capacity ratio
Exp. / cal

Load carrying capacity ratio
Exp. / cal

2.2 Experimental
2.2 Experimental
result andresultdiscussion
and discussion

0.0

0d

□: Nos.1~20□: Nos.1~20○: Nos.21~40○: Nos.21~40

0.0

0d

1c
1c
2b
2b
Deterioraion
Deterioraion
grade gradea3

a3

Figure 3:
Figuredeterioration
3: deterioration
grades vs.
gradesnormalized
vs. normalized
maximum
maximumloads loads
Figure 3Figure
shows3theshows
relationships
the relationships
betweenbetween
the deterioration
the deterioration
grades andgrades andnormalized
normalized
maximum
maximumloads ofloads
testedofslabs.
testedIn
slabs.
slabsInjudgedslabs asjudgeddeterioration
as deterioration

Developmentof probabilistic
structural
performance
evaluation
method forport RC
structure
Developmentofstructural
performance
evaluation
methodforDevelopmentof probabilistic
probabilistic
structural
performance
evaluation
methodforportportRC
RCstructure
structure

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October 2011, Chiang
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Thailand
Chiangmai,

grades c, b and a, there were large variations in the load carrying capacities.
There existed the cases of which maximum load ratios were smaller than 1.0
for deterioration grades c, b, and a. In case of deterioration grade a, inparticular, the load carrying capacity dropped to approximately 50 percentof the design calculations. Some of the load carrying capacities of grade cslabs were reduced to the same level as that of deterioration grade a. Fromthe safety evaluation point of view, when deterioration grade was judged as
grades c, b and a, in other words, symptom of deterioration appeared on thesurface of RC members, the load carrying capacity may become smaller
than the design expectation.
Large variations in the load carrying capacities for deterioration
grades c, b and a were considered to be influenced by two factors as
follows: 1) mislead of judgment of the deterioration grades and 2)
deteriorated portion in a tested slab.
1); Delamination of cover concrete was detected by hammering test at
the midspan area of some tested slabs. However, the delamination was notdirectly related to the judgment of the deterioration grades as listed in Table
2. Furthermore, in some tested slabs, many small cracks and honeycomb
existing on the surface layer of concrete disturbed the change in appearance
due to corrosion, which may mislead the healthier deterioration grade. It
was considered that the degree of corrosion of reinforcing bar was notalways contribute to the surface appearance of slab; that is, judgment of thedeterioration grade.
2); One deterioration grade is representatively judged for one slab. In
some slabs, corrosion cracks and delamiation of cover concrete wereobserved in a small part of their surface. According to Table 2, those slabs
were judged as deterioration grade c. However, some of those slabs showed
the different failure mode from the uniformly deteriorated slabs. In therange of this research, not uniformly deteriorated slabs showed a tendency
of loss in load carrying capacity due to the shear crack progress. The
concrete - reinforcing bars stress transmission changes according to the
corrosion cracks, localized corrosion in reinforcing bars, and their parts andstates. The change in stress transmission leads the change in failure modeand ultimate load consequently. As a result, load carrying capacities of RC
slabs extracted from various decks of existing port structures showed large
variations, though those tested slabs were in the same deterioration state.
The tested results implied that the probabilistic approach is required toappropriately evaluate the structural performance with considering thevariation observed in the existing structure efficiently. In this research,based on the statistical analysis on the relationship between deterioration
grades and load carrying capacities, the probabilistic evaluation method ofload carrying capacities of RC slabs for each deterioration grade a, b and c
was proposed as a quantitative evaluation method of residual structural
performance of existing port RC structures.

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3. PROBABILISTIC EVALUATION OF STRUCTURALPERFORMANCE
3.1 Objective of probabilistic performance evaluation
The extreme value theory has been widely applied in reliability
engineering and failure analysis, especially in the evaluation of localized
corrosion of metallic materials, which has probabilistic features essentially.
Tested slabs extracted from existing port structures were mainly deteriorated
by corrosion of reinforcing bars due to chloride ion penetration into concrete.
Hence, the load carrying capacities of the tested slabs can be considered tomainly depend on the corrosion state of reinforcing bars. Progress ofcorrosion of reinforcing bars in concrete shows large variation even if theseare embedded in a structural member. This variation leads the various crosssectional shapes of the reinforcing bars. As a result, it becomes a main causeof the large variation in the load carrying capacity of RC members. Basedon the above discussion, it seemed possible that the extreme value theory
was applied to evaluate the load carrying capacities of RC slabs
probabilistically as well as the corrosion of metallic materials.
The actual load-bearing mechanism of port RC structures and theinfluences of corrosion of reinforcing bars on structural performance of RC
members are not directly considered in the proposed probabilistic evaluation
method of structural performance of RC slabs based on the deterioration
grade judgment. The target of the probabilistic performance evaluation
using the visually judged deterioration grades is to achieve the strategic andefficient maintenance of port RC structure based on the life-cycle
management.
3.2 Probabilistic structural performance evaluation method
When data of the load carrying capacities of RC slabs are discussedwith the extreme value theory, it is necessary to set the lower limit, 0.0, to
the targeted extreme value. Hence, experimental load carrying capacity
ratios for each deterioration grade were applied to Weibull distribution,
Type III asymptotic distribution of extreme values, presented in Equation 1(Ang, et al., 1984).

⎡ ⎛ x − γ ⎞m ⎤⎟⎟ ⎥F− ΙΙΙ ( x) = 1 − exp⎢− ⎜⎜⎢ ⎝ η ⎠ ⎥⎣⎦(1)

Where F-III(x): cumulative distribution function, x: load carrying
capacity ratio, η: scale parameter, and γ : location parameter, and m: shapeparameter.
Experimental data of load carrying capacity ratios of RC slabs in eachdeterioration grade were assumed to be expressed as the cumulative

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October 2011, Chiang
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distribution function Fexp(xi) by the following equation based on the order
statistics.

Fexp ( xi ) =

i
N +1

(2)

Where Fexp(xi): cumulative distribution function of the ith statistics, xi:
experimental data in increasing order, and N: the total number ofexperimental data.
Load carrying capacity ratio x can be assumed to be x ≥ 0.0 , therefore,
γ in Equation (1) can be set as 0.0. Parameters η and m were obtained bytry-and-error calculation based on the least squares method to best fit to the
cumulative distribution Fexp(xi).
3.3 Development of probabilistic performance evaluation method fromdeterioration grade judgment

Figure 4 shows the experimental and calculated cumulative
distributions of load carrying capacity ratios for each deterioration grade.
Parameters and characteristics values of the load carrying capacity ratio foreach deterioration grade are listed in Table 3. Kolmogonov-Smirnov test
reported the approximation of F-III(x) and Fexp(xi) were performed at the 0.05
level of significance.

Cumulative probability

Exp.
Cal.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

0.0

Grade aGrade aGrade bGrade b

0.5
1.0
1.5
Load carrying capacity ratio x

Grade cGrade c2.0

Figure 4: Cumulative distribution of load carrying capacity ratio
Table 3: Parameters and characteristics values
η

m
Mean
Mode
Standard deviation

8
648

c
5.80
1.20
1.11
1.16
0.19

Deterioration grade
b
a
5.39
3.21
1.13
0.88
1.04
0.79
1.09
0.78
0.19
0.25

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ICUS Report 56

Mean and mode of the load carrying capacity ratio become small as
the deterioration grade progresses. In deterioration grade a, mean and mode
were less than 1.0, which indicates the experimental load carrying capacity
is below the design expectation, in addition to the standard deviation of theload carrying capacity ratio was more than those in grades b and c.
By using obtained cumulative distributions of load carrying capacity
ratio, the cumulative probability of the minimum load carrying capacity
ratio x can be estimated; for example, the probability that the minimum load
carrying capacity ratio x becomes 1.5 or less was 100%. The description,
however, would not be suitable to the structural performance evaluation of
RC structures, which should be maintained strategically. Therefore, in
Figure 5, y-axis is shown as 1.0-F(x), which means the cumulative
probability of the minimum load carrying capacity ratio becomes x or more.
In this figure, the upper limit of load carrying capacity ratio was shown as
1.0 with the intention of applying it for the performance evaluation of actual
port RC structures. According to these results, for example, the load
carrying capacity ratio of RC slab becomes 1.0 or more with the probabilityof about 70 % for deterioration grade c, about 60 % for deterioration grade b,
and about 20% for deterioration grade a, respectively. For another example,
the minimum load carrying capacity ratio with the probability of 95% canbe estimated as 0.72 for deterioration grade c, as 0.65 for deterioration gradeb, and as 0.35 for deterioration grade a.
100%
90%

1 - F(x)

80%
70%
60%
50%

Grade aGrade bGrade c

40%
30%
20%

0.0

0.2
0.4
0.6
0.8
Load carrying capacity ratio x

1.0

Figure 5: Cumulative distribution with which the minimum load carrying
capacity ratio becomes x or moreIn this research, the minimum experimental load carrying capacity
ratio was 0.47 for deterioration grade a. Deterioration grade a describes theworst deterioration state; therefore, the extreme load carrying capacity ratio
is considered to be 0.0 by accumulating further experimental data. The
cumulative distribution of load carrying capacity ratio in deterioration gradea has a possibility of becoming a decentralized tendency.
The difference in the cumulative distribution of load carrying capacity
ratios in deterioration grade b and c was not remarkable in this research. It

Development ofDevelopmentof probabilistic
probabilistic structural
structural performance
performance evaluation
evaluationmethod
methodfor
forportportRC
RCstructure
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was considered to be largely influenced by the localization of deteriorationand their state as discussed in 2.2. In addition, cross-sectional loss inreinforcing bars due to corrosion, that has a great influence on the load
carrying capacity, was not apparently considered in the visually
deterioration grading system. Moreover, the deterioration progress of RC
member is greatly different associated with the exposed environmental
condition, mixed material, construction condition, and service years ofstructures, etc.
The proposed structural performance evaluation method wasdeveloped by accumulating data of load carrying capacities anddeterioration grades of RC slabs sampled from existing port RC structures
located all over the country. However, the data used in this research would
not cover the whole conditions related to service and maintenance of port
RC structures in the whole domestic area. Therefore, it is necessary toaccumulate further experimental data of load carrying capacity in eachdeterioration grade. Moreover, the accuracy of the load carrying capacity
evaluation can be improved by considering the localization of deterioration
as much as possible in judgment of the deterioration grades of b and c.
4. CONCLUDING REMARKSThe total of 40 RC slabs extracted from existing port structures was tested inorder to evaluate the relationship between visually judged deterioration
grades and load carrying capacities. Based on the statistical analysis on therelationship between deterioration grades and load carrying capacities, theprobabilistic evaluation method of load carrying capacities of RC slabs was
proposed as a quantitative evaluation method of residual structural
performance of existing port RC structures. The performance index obtainedby the proposed method is expected to become an effective evidence fordecision of countermeasures for the strategic maintenance of large numbersof existing port structures. For this purpose, validities of the proposed
structural performance index and optimization of cumulative distribution
parameters for each deterioration grade, especially in deterioration grade d,have to be verified by accumulating further experimental data. In addition,
the authors will examine the possibility of its application to the port
structural member other than RC decks of open-type wharves and accessbridges in the further research.
REFERENCES
Ang, A. and Tang, W., 1984. Probability Concepts in Engineering
Planning and Design, Volume II Decision, Risk and Reliability, John Wiley& Sons, Inc..
Kato, E., Yokota, H., Iwanami, M., Akira, Y. and Kawabata, Y., 2008.
Simplified Assessment for Structural Performance of Deteriorated RC Deck,
Proc. of Life Cycle Management of Coastal Concrete Structures 2,
Hangzhou, China, 75-80.

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Port and Airport Research Institute, 2007. Manual on Maintenance ofPort and Harbour Facilities, Coastal Development Institute of Technology(in Japanese)

Development ofDevelopmentof probabilistic
probabilistic structural
structural performance
performance evaluation
evaluationmethod
methodfor
forportportRC
RCstructure
structure

11651

October 2011, Chiang Mai, Thailand

652

New Technologies for Urban Safety of Mega Cities in Asia

Calibration of roughness prediction
for asphalt pavement case study:
Thailand’s department of highways’ roads
Siwarak UNSIWILAI1 and Boonchai SANGPETNGAM2
1
Graduate Student, Department of Civil Engineering,
Faculty of Engineering
Chulalongkorn University, Thailand
2
Lecturer, Department of Civil Engineering, Faculty of Engineering
Chulalongkorn University, Thailand
boonchai.sa@chula.ac.th
ABSTRACTThe Department of Highways of Thailand has implemented the Thailand
Pavement Management System (TPMS) to serve as a maintenancemanagement tool that assists the Bureau of Highways MaintenanceManagement and its district authorities to analyze their road network’s
condition, allocate their annual budget and schedule the maintenance works.
The maintenance management process makes a decision based on the roadcondition which is represented by the International Roughness Index (IRI).
The TPMS adopted the RONET equation for predicting IRI changes as afunction of traffic, pavement strength, and pavement age. This paper
presents the method for calibrating the IRI prediction model for flexible
pavement in Thailand. The process is to adjust the factor called Kgp in thepredicting equation so that the prediction resembles to the actual field
condition. The IRI data obtained from the road condition survey throughout
the country during 2008-2010 is selected to cover a wide range of related
variables including geographic, traffic levels and pavement structures. The
expected products of this study is to obtain the Kgp values that are apposite
for each group of roads and help to improve the accuracy in roughness
prediction of flexible pavement in the future.
Keywords: HDM, Pavement Management System, IRI, calibration, flexible
pavement
1. INTRODUCTION
Pavement Management System (PMS) is a system tool for assisting the roadauthorities to efficiently plan and manage the maintenance tasks for theirroad network by ranking the priorities of maintenance works needed for
those road sections based on the road conditions, budget allowance andeffects to road users. The HDM (Highway Development and Management)
is an example of the PMS software that is well known and has been
implemented to the road authorities in many countries. The HDM version 3
was introduced to the Department of Highways (DOH) in Thailand in 1984.

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After that, in 1987 DOH had developed its own PMS called TPMS
(Thailand Pavement Management System) to suit its usage. Since then, theTPMS has been developing continually. The composition of program
modules in the current TPMS is illustrated in Figure 1.
INPUTS
Data of sample vehicle,
Traffic volume, Vehicles
growth rate, Highways
geometry, Pavement
characteristic, unit cost inoperation

MODELSRESULTS

STRATRoad deterioration
model

Increasing of IRI, Rutting,
Cracking and potholes infuture years

Maintenancequality’s effectmodel

Maintenance method,
Quantity of works,
Maintenance cost,
Pavement condition after
maintenance

Highway geometry’s
characteristic, Highways
roughness, Travel speed,
Unit cost in operation

Road user’s effectmodel

Fuel cost, Lubricant cost,
Tire cost, Vehicle cost,
Vehicle’s maintenancecost, Travel cost andothers cost

Road user cost,
Maintenance cost, Unit
cost of others cost,
Discount Rate

Economic
AnalysisEconomic index e.g. B/Cratio, Road maintenancecost and plan

Vehicle resource
consumption e.g. fueltire etc. and vehicle
travel speed

Social andenvironment
model

Initial value of road
distresses: Cracking,Raveling, Potholes,
Rutting, Roughness, Unit
cost in maintenances

Quality of toxic gas
Energy consumption

Figure 1: Composition and flow diagram of major modules in TPMS
International Roughness Index (IRI) is an indicator of the riding
comfort of a standard vehicle traveling on the pavement surface. IRI is
measured by recording the accumulative filtered suspension motion (inmeters) of the standard vehicle and then divided by the distance traveled by
the vehicle during the measurement (km), thus the unit of IRI is meters per
kilometer (m/km) (Watanatada et al., 1987; WSDOT, 2005).

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TPMS has adopted IRI as the principle indicator of the road surface
condition and incorporated it into the road user effect module. As such, theusers’ vehicle operating costs are mainly dependent on the roads’ IRI
values. Additionally, the maintenance work type selection is based on the
IRI criteria. Therefore, predicting the changes of IRI year by year isnecessary for the authority to plan for the future (3-7 years) maintenanceworks. To predict the IRI changes, TPMS has adopted RONET’s IRI
progression model (Archondo-Callao, 2009) since its equation form is quite
simple and is not tied to the road surface distresses such as rutting, cracking
and potholes, etc. The RONET’s IRI progression model is illustrated asfollows.
dIRI = Kgp*(a0*Exp(Kgm*m*AGE3)*[(1 + SNC*a1)]-5 *YE4 +a2*AGE3) + (Kgm*m*RIa)(1)

where:
dIRI
Kgp
Kgm
m
AGE3

=
=
=
=
=

SNC

=

YE4

=

a0
a1

=
=

a2

=

RIa
RIb

=
=

change of IRI during one year
calibration factor of roughness progression (1.0 for default)
factor for environmental coefficient (1.0 for default)
environment coefficient (= 0.025 for Thailand)age of pavement since last reconstruction or last rehabilitationor last overlay (years)
modified AASHTO’s structural number of pavement structure(Watanatada et al., 1987)
annual number of equivalent standard axles (million
ESA/lane/year)
coefficient = 134
0.755, RONET study value to reflect the reduction of strengthof pavement from pavement distress
0.0121, RONET study value to reflect the increase inroughness from distress
IRI at the start of interested year
IRI at the end of interested year, = RIa + dIRIIn the RONET equation (1), it provides the default values for the Kgp
calibration factor of 1.0. However, Archondo-Callao (2009) suggests thatthe road authorities should perform calibration based on their annual IRI
records from the road condition surveys to obtain a more realisticroughness prediction.

Calibration of roughness prediction for asphalt pavement case study: Thailand’s department of highways’
Calibration of roughness prediction for asphalt pavement case study:
roads
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2. OBJECTIVE
The objective of this study is to perform the model calibration to obtain the
new Kgp coefficient for better prediction of the IRI changes of DOH’s road
network.
3. METHODOLOGYThe DOH has routinely conducted IRI survey on its road network for morethan 3,500 routes covering more than 59,000 kilometers using laser profiler
vehicle since 2008. On a 1-kilometer length road section, the laser profiler
measures a number of profile spots from the road surface, they are thenaveraged to obtain the representative IRI value of the road section. Thisvaluable data along with the basic information related to the input variablesin the equation (1) such as pavement structural characteristics fordetermining modified structural number, pavement age (years) after
previous overlay/rehabilitation/reconstruction and traffic volume for
estimating number of standard axles are obtained from DOH. The following
processes are carried out to perform the calibration of Kgp factor based on
the obtained data.
3.1 Selecting Road Sections
Since a lot of IRI data are surveyed by using laser profiler apparatus
since 2008 – 2010. Our objective is to use this data to calibrate thepavement characteristic on the changes of IRI. Therefore, our interest in thedata is focused on the road sections that are free of periodical maintenanceand rehabilitation works. Furthermore, the select road sections must pass thefollowing criteria:• IRI of the selected road section increases every year
• There are at least 5 sections (5 kilometers) available on the sameroute vicinity.
Based on the explained criteria, IRI data from more than 40 routes
covering 450 road sections is obtained and used in the calibration process.
3.2 Procedure for Calibrating Kgp value
The process of calibrating the Kgp factor is based on trial and error
method to find the Kgp that produces minimum error etween prediction andactual change of IRI. First, an initial Kgp is assumed for initial trial. In each
step, the equation (1) is used to calculate dIRI between year 2008-2009 and2009-2010 based on the trial Kgp, they are then compared with the actualdIRI based on the recorded data, the square of error between the prediction
and actual dIRI within the two consecutive years is calculated as shown inequation (2). The square of errors of all road sections between year 20082009 and 2009-2010 are accumulated and is presented as the sum of error
square value for the trial Kgp. In the next trials, the previous Kgp value isadded by an incremental amount step by step. The calculation process is4656

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repeated to obtain the new value of sum of error square. In the end, a
relationship between Kgp and sum of error square can be plotted and thetargeted Kgp that provides the minimum value of sum of error square is
obtained.
The details of calibration steps are summarized as follows:
1. Calculate dIRI of selected road section from actual data by using
IRI of each section between year 2008-2009 and 2009-2010,
called IRIactual.
2. Calculate dIRI from RONET equation (Equation 1) by using
each road section properties and trial Kgp (begin with 0), calleddIRIpredict
3. Calculate error2 of each road section by the following equation:
error2 = (dIRIactual – dIRIpredict)2(2)

4. Calculate sum of error2 by summing error2 values of all roadsections.
5. Add an incremental amount to the previously trialed Kgp andrepeat step 2-3 using the new trial Kgp.
6. Calculate R2 of relationship between IRIactual and IRIpredict
7. Perform paired T-Test to verify that IRIactual and IRIpredict are in
the acceptable range of reliability of statistical meaning.

Calibration of roughness prediction for asphalt pavement case study: Thailand’s department of highways’
Calibration of roughness prediction for asphalt pavement case study:
roads
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Thailand’ s department of highways’ roadsOctober 2011, Chiang
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Figure 2: Flow chart shows calibration sequence
3.3 Grouping Data
The initial assumption is that the pattern of IRI change may vary bygeographic location which may result in different calibration factor Kgp foreach region. Additional data analysis is conducted by grouping the selected
data by its geographic location into four regions of Thailand: northern,
northeastern, central and southern.
Table 1: Summary of road sections allocated by region and traffic volume
Regional

Northern

AADT (vehicles/day)Less than 300
300 – 1000

1001 – 2500

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Regional

AADT (vehicles/day)Number ofsample2501 – 5000
70
5001 – 10000
34
10001 – 20000
NA*
More than 20000
NA*
CentralLess than 300
NA*
300 – 1000
NA*
1001 – 2500
56
2501 – 5000
60
5001 – 10000
70
10001 – 20000
NA*
More than 20000
44
NortheasternLess than 300
NA*
300 – 1000
72
1001 – 2500
54
2501 – 5000
48
5001 – 10000
56
10001 – 20000
54
More than 20000
NA*
SouthernLess than 300
NA*
300 – 1000
NA*
1001 – 2500
46
2501 – 5000
425001 – 10000
40
10001 – 20000
NA*
More than 20000
NA** There is no road section that fall into that particular category.

4. RESULTS AND DISCUSSION
From data of all selected road sections covering 450 kilometers throughout
the country, Figure 3 illustrates the result of calibrating the Kgp factor under
this data. It appears that Kgp value that yields the minimum sum of error
square is 2.6077. Based on this calibrated Kgp, Figure 4 shows that therelationship between IRIactual and IRIpredict is very close to 1:1 with thecorresponding R2 value of 0.89. Finally, the result of testing paired T-Test
at 95 percent confidential level in Table 2 confirms that IRI values from theprediction and from the recorded surveys of the sampled road sections are
not different in statistic meaning.

Calibration of roughness prediction for asphalt pavement case study: Thailand’s department of highways’
Calibration of roughness prediction for asphalt pavement case study:
roads
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Thailand’ s department of highways’ roadsOctober 2011, Chiang
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Figure 3: Result of Sum of error square and trial Kgp(throughout the country)

Figure 4: Predicted IRI and actual IRI (throughout the country)
Table 2: Result of paired T-Test (throughout the country)
Mean
Variance
Observations
Pearson Correlation

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IRI Predict IRI Actual
2.6738666
2.6822765
0.2524546
0.2506143
727
727
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Hypothesized Mean Differencedft StatP(T<=t) two-tail0726-1.3597386
0.1743348

t critical two-tail
95% confidential

1.9632369
pass

Table 3: Results from calibration based on road data of road sections
throughout the country
Throughout
the country

Number ofsample
727

Kgp

R2

Pair T-Test

2.6077

0.890

Pass

For the case of calibrating Kgp factor based on grouping the roadsections by 4 regions, the results of calibrated Kgp with the minimum sumof error square are presented in Table 4 along with the results of paired Ttest at 95 percent confidential level. The results of calibrating the Kgp factor
by region in northern, central and northeastern regions seem acceptable at
R2 values greater than 0.80. The result of calibration for southern region
achieves R2 of 0.743 considerably lower than the other regions. This might
be due to the fact that the road sections of southern regions are absent ofdata from 4 traffic levels as illustrated in Table 1, and results in missing thecomplete range of IRI data.
Table 4: Results from calibration based on road data by allocated regions

Region

Northern
CentralNortheasternSouthern

Number ofsample
171
203
226
128

Kgp

R2

1.80662.37732.96343.8913

0.952
0.885
0.838
0.743

Pair
T-Test
Pass
Pass
Pass
Pass

Sampled sections

see Table 1, some groupof traffic levels are notavailable.

4. CONCLUSIONSThe calibration of the Kgp factor in the IRI progression equation for TPMS
is conducted in this paper. The results of calibration at the country level andregional level reveal that the calibrated Kgp factors are statistically
acceptable based on the overall samples of 450 road sections.
For applying a proper Kgp factor into the TPMS, the Kgp factor of
2.61 is suggested. This means the rate of roughness progression in Thailandis 1.6 times faster than the default RONET prediction.
The results of calibrating Kgp factor by 4 regions indicate that theKgp factor can vary by region: from 1.81 for northern region to 2.38 forcentral region, 2.96 for northeastern regin and 3.89 for southern region.
However, applying only one Kgp throughout the country should still predict
Calibration of roughness prediction for asphalt pavement case study: Thailand’s department of highways’
Calibration of roughness prediction for asphalt pavement case study:
roads
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Thailand’ s department of highways’ roadsOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

the IRI progression reasonably due to the statistically acceptable level ofverification.
In the future, DOH should keep surveying the selected road sections to
obtain the valuable data for a longer timeline. It will improve the quality ofdata for a better calibration.
ACKNOWLADGEMENTS
The authors would like to acknowledge Bureau of Highways
Maintenance Management, Department of Highways and the Stimulus
Package 2 (SP2) of Ministry of Education under the theme of Green
Engineering for Green Society for providing data, assistance and funding inthis study.
REFERENCES
Archondo-Callao, R., 2009. Road Network Evaluation Tools (RONET)
Version 2.0 User’s Guide. SSATP Working Paper No. 89-A, Sub-SaharanAfricaTransport
PolicyProgram,availableon(www.worldbank.org/afr/ssatp)
Center of Engineering Research and Technical Services, Faculty ofEngineering Chulalongkorn University, 2009. Department of Highways’
Project: Central Road Database and Thailand Pavement Management.
Final Report. Bangkok, Thailand.
HDMGlobal., 2007. Highway Development & Management (HDM-4)
Version 2.0. Volume 5 A Guide to Calibration and Adaptation.
HDMGlobal., 2007. Highway Development & Management (HDM-4)
Version 2.0. Volume 6 Modelling Road Deterioration and Works Effects.
Watanatada, T., Harral, C.G., Paterson, W.D.O., Dhareshwar, A.M.,
Bhandari, A. and Tsunokawa, K., 1987. The Highway Design and
Maintenance Standards Model, Volume 1 Description of the HDM-III
Model. The International Bank for Reconstruction and Development/The
World Bank.

10
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NewApplication on spatial information
for the reaction of the huge earthquake-supporting recovering activities
for the 2011 off the pacific coastof Tohoku earthquakeHirotoshi Kishi1, Ryotaro Takeda1, Dai Yamazaki1, Kanya Tokunaga2,
Yoshito Sawada3, Shiro Ochi3, Takahiro Endo4 and Haruo Sawada5
1
Graduated Student, Department of Civil Engineering,
The University of Tokyo, Japan
kisshi@iis.u-tokyo.ac.jp
2
Technical Assistant, Institute of Industrial Science,
The University of Tokyo, Japan
3
Project Researcher, Institute of Industrial Science,
The University of Tokyo, Japan
4
Assistant Professor, ICUS, Institute of Industrial Science,
The University of Tokyo, Japan
5
Proffesor, ICUS, Institute of Industrial Science,
The University of Tokyo, Japan
ABSTRACT
Spatial information products for the response of the 2011 Tohoku
earthquake were developed in this study. Firstly, reasonable information for
the governmental sectors and field investigators in the hazarded area for thereaction of the earthquake were considered by our project members. We
concluded the important points were the applicability and the accessibility
for the spatial information. Secondly, remote sensing dataset such as aerial
photos distributed by Geospatial information authority, Japan and GIS
dataset were processed to share on the Google Earth (GE). In this process,Tsunami inundation line was interpreted and digitized comparing theseaerial photos to satellite images taken before the earthquake on the GE.
Finally, Tsunami line aerial photo map was published to understand thedamaged area for the governmental sectors, field investigators, researchersand volunteers. This map is planned to keep publishing using new aerial
photo taken after few months after the earthquake to support recovering
activities. These all products were distributed through our project website.
Keywords: 2011 Tohoku earthquake, Tsunami, Disaster recovery, Aerial
photo, GIS and Remote sensing.

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1. INTRODUCTION
The 2011 off the pacific coast of Tohoku earthquake brought unprecedented
damages not only for land shaken inland but also Tsunami inundated coast
area. Over 20 thousand people are dead or missed because of thisearthquake (MLIT, 2011) Disaster management cycle is a basic idea against
natural hazards including earth quake, Typhoon, heavy rain. We humans canreact in four stages against natural hazards; Mitigation and Preparedness in
before disaster phase, and Response and Recovery in post disaster phase. Incase of the earthquake, developing hazard maps and earthquake early
warning system are classified as mitigation phase, and aseismic
reinforcement and setting emergency bags are as preparedness phase. Afterthe earthquake occurred, damage estimation and evacuation indication
would be put on a importance firstly, then shifting to recovery planning in
suffering area. Disaster management cycle helps local communities toprepare for the coming natural hazards (JICA, 2003).
Earth environment engineering research group, Institute of Industrial
Science, The University of Tokyo has discussed what we can do at the
response and recovery stage in this hazard driven by the 2011 off the pacificcoast of Tohoku earthquake as spatial information engineers and discussed
our activities considering situations of hazarded area and available resources.
Quick damage estimation in response phase is one of the most importantworks for the rescue and activities for supporting the governments andregional people. Kishi et al., (2011) reported the activities focused on
response stage.
Based on these backgrounds, the objective of this paper is to report the
prepared spatial information and introduce application uses for thegovernmental sectors, volunteers and field investigators to support disaster
response and recovery activities.
2. METHODOLOGY
2.1 Discussion for supporting disaster response and recovery activities
Firstly, our research group members discussed what we should do forsupporting reaction and recovery activities for the governmental sectors,
volunteers and field investigators. The most important information inreaction phase is to estimate the damaged area promptly. Although damaged
area was extremely large in this earthquake, high resolution aerial photos orsatellite images which could distinguish houses were regarded usefulproducts for damage estimation. Secondly, finding Tsunami inundation line
was regarded as important information for damage estimation because
terrible damage was brought by Tsunami. Thirdly, GIS datasets including
evacuation shelters, country borders, population and elevation informationon the map would be useful for governmental sectors and field investigators
to support recovery activities.

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User friendly GIS system would be important for users because all
spatial products should be accessed easily by all people who need them.
Google Earth (GE) was employed as a basic GIS platform in this activity
because it is one of the wide spread GIS systems all over the world, so thateveryone can use it easily and free. It enables users to compare other spatial
information prepared and being preparing by many contributors all over theworld. For example, old information such as satellite and aerial photos, andnear real time information such as traffic conditions, geo tagged picturesand GIS datasets could be modified and updated on the GE. In addition to
web-based information, parpr-based products should be prepared forhazarded area use because internet connection and electric power supply are
unstable or lost in some areas considering field activities. Based on these
discussions, our research group concluded that 4 products should be
prepared; 1) Fine resolution visible images which can distinguish buildings
to understand damaged area, 2) Tsunami inundation line which clearlyshows Tsunami damaged area, 3) GIS system which can refer and edit
spatial information in city boundary to create recovery plans for local
governments, 4) User friendly web and paper based products for delivering.

Figure 1 : Flowchart of this activity
2.2 Development of spatial products
Figure 1 shows flowchart of our activity. Firstly, Aerial photos takenover Tohoku coast area by Geospatial Information Authority, Japan (GSI)iin 1 or 2 days after the Earthquake (About 80cm resolution and 2672 scenes
in totall) are employed. Map projection of this aerial photos is converted
from zone 9 or 10 of the rectangular plane to latitude-longitude coordinate
system (WGS84) to overlay on the GE. Secondly, Tsunami inundation line
was interpreted by group members on the GE comparing converted aerial
photos, old satellite and aerial photos, elevations and reports of governments.
Application of spatial information for the reaction of the huge earthquake -supporting recovering activities
Application on spatial information for the reaction of the huge earthquake -supporting recovering
for the 2011 off the pacific coast of Tohoku earthquake6653
activities for the 2011 off the pacific coast of Tohoku earthquake-October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,Interpretation keys are defined to assure the quality of interpretations; 1)
Interpreted inundation lines were basically following to the inundation line
reported by GSIii. 2)“ Roads including Tsunami affected area ”areinterpreted as a clear inundation line to ensure project members sharequality for interpretation and Tsunami inundation line quality is assured.
Then, Tsunami inundation line another interpreter checked in heavy
damaged area such as coast side urban area. Thirdly, statistical GIS datasets
which would be useful for response and recovering activities were preparedto overlay on the GE. City boundary, population and area from Census in
2005, 5m digital elevation model from National land information, shelter
point data from Google, DMSP night light image from NOAA/NGDC werecollected. Finally, Tsunami line aerial photo map is developed in 1/10,000
scale in A1 print over heavy damaged area where many evacuated people
are left. Shelters, country boundary, Tsunami inundation line are overlaid on
the aerial photo. Maps are presented to local governmental sectors, field
investigators and volunteer workers. Map contents such as shelter
information, aerial photos and Tsunami line are updating to catch up actual
situation to support recovering activities.
3 RESULTS AND DISCUSSIONS
3.1 Prepared products
Details of prepared products are shown below;
Map projected aerial photos. All projected aerial photos overTohoku coast area distributed by GSI are converted to GE format (.kmz
filetype). In this converting process, images are mosaicked before map
projection conversion so that they can be divided into our intended size sothat there are no space between each images; 0.05degree, 1:25,000 Japan
standard map size and distributed size by GSI are prepared.
Fine resolution Tsunami inundation line. Interpreted Tsunami lines
were in public soon after finishing interpretation as digital data formats for
GIS users (.shp and .kml) through our project website shown in Figure 3.
Immediacy is attached grater importance than accuracy to this disaster
response stage. Interpreted Tsunami inundation area by our project group is
about 10% larger than GSI estimationiii in Kesennuma city. Reasons of ouroverestimation are considered; (1) Road networks including Tsunami
affected area are employed as Tsunami lines, (2) Coast side is regarded asinundation area, and (3) Run-up area is sometimes considered different from
GSI. For the future work, cross checking is an important task because bothinterpretations have some missing inundation area.
GIS datasets for supporting damage estimation and recovery
activities. Figure 2 shows Tsunami inundation line and 5m digital elevation
model in Sendai area overlaid on the GE. It is found that elevation is one of
the most important keys to avoiding Tsunami damage. We contributors allover the world can work together because not only our prepared products
but also other GIS datasets can be overlaid on the GE.

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Figure 2: Overlaid Tsunami inundation line and 5m DEM over Sendai areaon the Google Earth.
Tsunami line aerial photo map (1/10,000 scale) Figure 5 shows the
Tsunami line aerial photo map (1/10,000 scale) over Kesennuma area. Paper
based map would be useful for local government, field investigators andvolunteer workers.
These products are distributed through our project webpage shown in
Figure 3 (http://stlab.iis.utokyo. ac.jp/eq data/). Every products can be
downloaded through this website, which is constructed in Japanese andEnglish. There are still few websites of 3.11 constructed in English.

Figure 3 : Project webpage (http://stlab.iis.u-tokyo.ac.jp/eq data/)

Application of spatial information for the reaction of the huge earthquake -supporting recovering activities
Application on spatial information for the reaction of the huge earthquake -supporting recovering
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3.2 Application uses of products
Prepared products are widely used by governments, research instituteand private company for damage estimation and recovery activities throughour website as shown in Figure 3. Figure 4 shows examples of products
application uses. Picture (a) is taken in Katsura-sima in Shiogama-city in
April 2011. Tsunami line aerial photo maps were delivered by one of our
project members to support volunteer works and local government activities.
Katsura-shima had a huge damage because of earthquake and Tsunami sothat many volunteer workers visited there. Paper based maps are useful
information for understanding situations especially for volunteers at the site.
(b) shows exhibition room in a school festival of University of Tokyo in
May, 2011. Some students of Civil Engineering department in University ofTokyo who joined field survey in Tohoku area, employed theinterpreted Tsunami Inundation line data as contents to make a large scale
map for exhibiting their research results. Visitors could easily understandthe Tsunami damages and geographical situations over Tohoku area. (c)shows land terrain elevation and inundation line in Sendai from HokkaidoChizu Inc. Predicted Tsunami inundation line shown by prepared hazard
maps before 3.11 and actual tsunami line interpreted by this project after
3.11 are drawn in one map. It is found that Tsunami prediction didn’t matchfor 3.11 earthquake. (d) shows iPhone/ipad application, ”Chizu burari which
is developed by ART-Promotion Inc. Tsunami line aerial photo maps shownby figure 5 and map projected aerial photos are employed as application
contents. Maps can be checked even in under the offline conditions once
they are downloaded and every user can download these prepared products
in one’s iPhone/iPad with GPS information.

Figure 4 : Products application uses

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Figure 5 : Tsunami line aerial photo map(Kesennuma, 1:10,000 scale original)
3.3 Discussions and suggestions
Several difficulties are found through this project activities. Hereshows the difficulties and suggested solutions for supporting disaster
response and recovery activities. Firstly, establishing an agency that
evaluates spatial information are highly recommended because muchinformation were provided by many institutes, individuals and governments
after the 3.11 EQ but it was not clear which information is suitable for users.
The agency would introduce spatial information for users considering
differences in spatial and temporal resolution, dataset level, accessibility ofthe spatial data. Secondly, satellite observation data application for large
scale disaster should be discussed because aerial photos are of course very
useful for disaster response but it took few weeks to deliver ortho images
because large area were hazarded. Developing a framework of satellite
image application is important for damage estimation soon after anearthquake happens automatically even in large area. If application method
Application of spatial information for the reaction of the huge earthquake -supporting recovering activities
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of satellite images for disaster damage estimation were developed, we could
understand damaged area more quickly. Thirdly, establishing cocontribution framework in spatial information engineers is urgent task
because understanding other communities’ activity was difficult in thedisaster response activities. It was true that many efforts have done but wecouldn’t share ideas with other community contributors. Sharing
information and constructing relationship among spatial informationengineers or institutes are highly expected for the case of emergency.
4 . SUMMARY
Reasonable spatial information products are discussed and developed for the
response to the 3.11 earthquake; aerial photo overlaid on the Google Earth,interpreted Tsunami inundation line, GIS datasets including country
boundary and shelter points, and Tsunami line aerial photo map based onthese products. These all products are distributed through our website andkept updating. Products are widely employed by field workers, researchersand private companies. For the future works, providing information are to
be updated because conditions in suffering area are changing. 1/10,000 scale
map are going to be updated using new aerial photos taken after few months
from 3.11 EQ, which is planning to be distributed from GSI to support
recovery activities.
REFERENCES
Japan International Cooperation Agency. 2003. Disaster prevention
and development - Towards enforcement of social disaster prevention
powerKishi. H., Takeda. R.,Yamazaki. D., Tokunaga. K., Sawada. Y., Ochi.
S., Endo. T.,
Sawada. 2011. Application of spatial information for the reaction of
the huge earthquake -Response for the 2011 off the pacific coast of Tohoku
earthquake- Proceeding of 50th Remote sensing society of Japan. pp83-86.
2011.
Ministry of Land, Infrastructure and Transport, Japan. 86th report for
Tohoku earthquake released on August 15, 2011.

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NewChallenges in preparedness, response andrelief for people with special needsin times of disasters followings
the great East Japan earthquake
Shigeo TATSUKI
Professor, Department of Sociology, Doshisha University, Japan
statsuki@mail.doshisha.ac.jp
ABSTRACT
Three major challenges were identified and their possible solutions were
proposed in preparedness, response and relief measures for People with
Special Needs in times of Disasters (PSND) following the 2011 Great East
Japan Earthquake. First, recent developments in preparedness measuresfor PSND in Japan have been uncritically relying on the assumption thathazard maps represent “correct” estimates of future hazardous events,
which are based on maximum probable event (MPrE) framework. In reality,
however, maximum possible event (MPoE) has occurred in Tohoku regions.
This has tremendous implications for fundamentally re-thinking entire
hazard estimation process from MPrE to MPoE framework. Second,
counter-disaster measures for PSND have focused mainly on warning andneighborhood-based evacuation assistance activities. Needs for shelters
and temporary housing units that are specially designated for PSND arose
following the earthquake. However, their provision was neither systematic
nor universal due to the lack of pre-planning. More detailed guidelines for
specially designated shelter and temporary housing operation need to be
developed in order to address this issue. Third, people with disabilities(PWD) became invisible in shelters and communities or in eyes of local
government administrators. This is due to the fact that majority of PWDs
did not ask for help in evacuation shelters because they felt general shelters
were not “barrier free” and unresponsive to their functional needs.
Furthermore, many local government administrators felt hesitant to release
PSND registry to NGOs and self-help organizations that were eager tocheck where-about and current situations of PWDs. This was due to thefear of breaking Personal Information Protection Bylaw despite the fact thatthe Bylaw provides exceptional conditions, where the onset of disaster isclearly one of these exceptional conditions. Further elaboration andeducation on the use of personal information of PSND during disasterperiod are needed among public and local government administrators.
Keywords: people with special needs in times of disasters (PSND), theGreat East Japan Earthquake, maximum probable event, maximum possible
event, specially designated shelters and temporary housing for PSND,
personal information protection bylaw

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1. INTRODUCTION
1.1 Counter-disaster measures for PSND in Japan
The issue of special needs population gained high attention after 2004 whena series of natural disasters hit the Japanese Archipelago. Those included
July Niigata-Fukushima flood, October typhoon 23 and October Niigata
Chuetsu earthquake disasters, wherein notably more than 60% of the victims
were over the age of 65. As a response to these tragedies, Japan’s Cabinet
Office established a committee on “Communicating Disaster Informationand Evacuation and Sheltering Assistance for the Elderly and Other
Population during Heavy meteorological and Other Disasters.” Thecommittee published the first edition of the “Evacuation/Sheltering
Assistance Guideline for People with Special Needs in Times of Disasters”
in the following March 2005. After the guideline publication, the termsaigaiji-youengosha or People with Special Needs in Times of Disasters(PSND) was popularized in place of saigai-jakusha or Disaster Vulnerable
Population. PSND is defined as “a person who is able to function daily,
whereby living independently given the proper resources and services whennecessary”.
Following another series of heavy rainfall, flood and land slidedisasters in the year 2005, another Cabinet Office committee conducted
field research of the 2005 meteorological disaster sites and revised theevacuation and sheltering assistance guideline in March 2006. The 2006
guideline emphasized 1) establishing a special team in each municipal
government that was in charge of coordinating assistance to the target
population, 2) encouraging the information sharing of special needs
population within the local government and, if possible, with local
community organizations such as neighborhood associations andcommunity emergency and response team, and 3) planning individualized
evacuation and sheltering procedures for each PSND.
In the following fiscal year 2006, the committee on PSND continued
working on more detailed procedures and workflows in order to collect, toshare information on PSND and to make individualized evacuation andsheltering assistance plans. In March 2007, the committee published the“Report on Preparedness Procedures for PSND.” The 2007 reportemphasized the establishment of a system to assist PSND by facilitating
cooperation between the local/municipal government disaster management
department and its health and welfare department. The role of the disastermanagement department is to provide local hazard information, while thehealth and welfare department provides information on potential
vulnerabilities within the target population. The 2007 report encouraged theuse of map where potential vulnerable individuals such as the frail elderly
and people with disabilities (PWD) are projected onto multiple hazard
layers such as flood, landslide and seismicity. The map can help identify
who are at more risk because of their functional needs as well as of theirgeographic locations.

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Since the publication of the 2006 guideline and the 2007 report, theFire and Disaster Management Agency (FDMA) has requested every
municipality in the country to formulate its own master plan that directs
policy formation on PSND assistance, to identify potential target groups, toclarify ways to collect and share their personal information. Based on themaster plan, municipalities have been further encouraged to start projectplanning to assign local resident helpers to each individual PSND in time ofevacuation. According to the survey conducted by FDMA, as of April 1,
2011, 1,262 out of 1622 municipalities (76.8%) finished formulating PSND
assistance master plan and additional 349 municipalities (21.2%) were
expected to finish within one year. Similarly, 864 (52.6%) municipalities
reported that they have finished creating and have been updating the PSND
directory. 684 (41.5%) municipalities said that they were currently in theprocess of making the directories. Municipalities have been working hardeven on assigning local residents/helpers to each PSND for evacuation,much more time consuming process. 361 (22.0%) reported that they havecompleted the assignment, 998 (60.7%) in the process, and 285 (17.3%) not
yet initiated (FDMA, 2011).
1.2 Kobe PSND Mapping Project
Tatsuki and Comafay (2010) reported the 2008 Kobe PSND Mapping
Project, which was characterized by a combined use of GIS and the social
survey in order to assess overall hazard vulnerability of PSNDs. In responseto the FDMA request as explained in the above, 1.5- million-resided Kobecity administration collated separate social service recipient databases,
resulting in an integrated registry involving one hundred and twenty
thousand individuals who were considered being potentially vulnerable intime of disaster. The registry database identified 4,329 people with physicaldisabilities in 107- thousand-resided Hyogo Ward. The 2008 project
geocoded and mapped them on land slide, flood and tsunami hazard layers.
914 individuals were found residing in hazardous areas (see figure 1).

Figure 1: Persons with disabilities living in Kobe’s Hyogo ward (N= 4,411)
Challenges in preparedness, response and relief for people with special needs in times of disasters following
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These 914 individuals were then visited by interviewers and 612 or
67% responded to a structured questionnaire which measured demographics(i.e., age and gender), levels of disability, social isolation, housing fragility,and physical immobility. The 2008 project was based on the person-inenvironment model of vulnerability, which defined hazard vulnerability (V)as a function of hazards (H), person (P), and environment (E) factors or V =f(H, f(P, E) as illustrated by figure 2.

V= ƒ （H, ƒ （ P, E））
Overall Vulnerability Map
Px

EI
nte
rac
En
tio
v ir
nF
onm
act
or
ent
al F
Per
act
son
or
al F
Ha
a
c
zar
t
d L oraye
rFigure 2: Person-in-Environment model of mapping hazard vulnerability
Based on the model, an overall vulnerability score was then calculated
as a function of hazards and the five variables for each respondent. As aresult, 17% of those who responded were found the most vulnerable andrequiring priority assistance in time of disaster (see figure 3).

Figure 3: Overall vulnerability scores mapped on to hazard layers

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Areal Overall Vulnerability

Flood
Landslide
Tsunami17

Figure 4: PSND kernel density estimation weighted by overall vulnerability
index
Furthermore, a social vulnerability weighted kernel density map ofpeople with special needs was created (see figure 4). This map indicatedwhich particular areas require more human resources for assisting a special
needs population for evacuation and sheltering. The project product maps
helped representatives from special needs groups, community emergency
response teams, community social services, and emergency management
centers initiate evacuation and sheltering assistance planning in the project
areas.
The 2008 Kobe PSND mapping project was an attempt that aimed toprovide a standardized method using individual social vulnerability
mapping as analysis tool to identify more comprehensively the risks that
could affect a given community. This could help different stake holders,special needs groups, community emergency response teams, community
social services, and emergency management centers initiate evacuation andsheltering assistance planning in high risk communities.
2. THREE CHALLENGES IN PSND COUNTER-DISASTER
MEASURES AFTER MARCH 11, 2011
Despite the above mentioned nation-wide efforts on PSND counter-disastermeasures in recent years, serious problems confronted municipalities,
communities, PSNDs and their families at the onset of March 11 Great East
Japan Earthquake Disaster. From three reconnaissance missions conductedby the author team in March and April, at least three major challenges wereidentified in preparedness, response and relief measures for PSND. Those
were namely 1) challenges on identifying people at risk by re-thinking“correct” hazard estimates, 2) challenges on pre-planning specially
Challenges in preparedness, response and relief for people with special needs in times of disasters following
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designated shelters for people with special needs, and 3) challenge on
utilizing personal information on PSND. Each challenge is explained in thefollowing sections.
2.1 Challenges on identifying people at risk: Re-think “correct” hazard
estimates
Recent developments in preparedness measures for PSND in Japan
have been uncritically relying on the assumption that hazard maps represent“correct” estimates of future hazardous events. As figure 5 in the below
illustrates, this turned out to be a horribly wrong assumption. Hazard maps
were created according to maximum probable event (MPrE) framework. In
reality, however, maximum possible event (MPoE) has occurred in Tohoku
regions. This has tremendous implications for fundamentally re-thinking
entire hazard estimation process from MPrE to MPoE framework.

A

3000m
700m

Figure 5: Tsunami hazard map and actual inundation east of Rokugo Juniorhigh school, Wakabayashi ward, Sendai city
In the previous section, the person-in-environment model of hazard
vulnerability (V) was introduced as a function of hazard (H), person (P) andenvironment (E) factors or V = f(H, f(P, E)). In practice, hazard factor was
estimated by maximum probable event framework and therefore the model
could be represented as V = f(MPrE, f(P, E)). The challenge here is toreplace maximum probable event hazard estimate with an alternative hazard
estimate by incorporating maximum possible event framework. The
modified person-in-environment model will therefore be represented as V =f(MPoE, f(P, E)).
2.2 Challenges on pre-planning specially designated shelters for people
with special needs
As was described in the introduction, counter-disaster measures for
PSND have been focusing mainly on warning and neighborhood-based

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evacuation
evacuation
assistanceassistanceactivities.
activities.
Needs
Needs
for shelters
for shelters
and andtemporary
temporary
housing
housing
unitsunits
that werethat were
specially
specially
designateddesignatedfor PSND
for PSND
arosearose
following
following
the March
the March
11 11
earthquake.
earthquake.However,
However,
theirtheirprovisions
provisions
werewereneitherneithersystematic
systematic
nor noruniversal
universal
due toduetheto lack
the lackof pre-planning.
of pre-planning.
ThisThis
is partlyis partly
due toduetheto fact
the fact
that thatthe 2006
the 2006
guideline
guidelineor theor 2007the 2007
reportreporthas not
has provided
not provided
detaileddetailed
procedures
procedureson shelteringon sheltering
assistanceassistanceplanning
planning
for PSND.
for PSND.
The Theconcept
conceptof speciallyof speciallydesignateddesignatedsheltershelterfor PSND
for PSNDor fukushi-hinansho
or fukushi-hinansho
emergedemergedin 2004
in 2004
fromfrom
the thediscussions
discussions
by thebycommittee
the committee
on “Communicating
on “Communicating
DisasterDisaster
Information
Information
and and
Evacuation
Evacuation
and and
Sheltering
Sheltering
Assistance
Assistancefor thefor Elderly
the Elderly
and andOther
Other
Population
Population
duringduringHeavy
Heavy
meteorologicalmeteorologicaland and
Other
Other
Disasters.”
Disasters.”
It was
It wasrecognizedrecognizedthat thatgeneralgeneralevacuation
evacuation
shelters
shelters
as shown
as shown
in figuresin figures
6 and6 7andwere
7 werenot capable
not capableof of
responding
responding
to special
to special
or functionalor functional
needs
needs
of PWDof PWDand andthe frail
the frail
elderly.
elderly.
Functional
Functional
needs
needs
includeincludethosethosein “communication,in “communication,
medicalmedicalneeds,
needs,
maintaining
maintaining
functional
functional
independence,
independence,supervision,
supervision,and andtransportation”
transportation”(Kailes(Kailes
and andEnders,Enders,2007,2007,
p.234)
p.234)
that thatarisearisein timesin timesof disaster.
of disaster.
The Thecommittees
committees
on PSND
on PSND
assistance,
assistance,
however,
however,havehave
not spent
not spentenoughenoughtimetime
to toclarifyclarifyrequirements
requirements
for, for,procedures
proceduresor guidelines
or guidelinesof speciallyof speciallydesignateddesignatedshelters.
shelters.
MostMost
hazards
hazards
that that
the PSND
the PSND
committees
committees
havehave
beenbeen
studying
studying
sincesince20042004
havehavemainlymainlybeenbeenmeteorologicalmeteorologicaland therefore
and therefore
sheltering
sheltering
needs
needs
werewere
short-term
short-termand considered
and consideredbeingbeing
less life-threatening
less life-threatening
than thanevacuation
evacuationneeds.
needs.

FigureFigure6: School
6: School
GymGymShelter
Shelterat at Figure
Figure7: Arahama
7: Arahama
Residents
Residentson theon theRokugoRokugojuniorjuniorhighhighschool,school,SendaiSendai
1st Floor
1st Floor
Classroom
Classroom
at Hakken
at Hakken
City City(April(April6, 2011)
6, 2011)juniorjuniorhighhighschoolschool(April(April6, 2011)
6, 2011)
The TheMarch
March
11 earthquake
11 earthquake
disasterdisastercreatedcreateda situationa situation
where
where
a verya verylargelarge
numbernumberof peopleof people
rushedrushedto generalto generalshelters
shelters
and theandlength
the lengthof stayof stay
was wasrelatively
relatively
long,long,creating
creating
highhighfunctional
functional
needs
needs
fromfrom
PSND.
PSND.
ThisThisapparently
apparently
required
requiredalternative
alternative
shelters.
shelters.
DisasterDisasterhit municipalities
hit municipalities
responded
responded
to thisto thissituation
situationin un-uniform
in un-uniform
manners.
manners.
In theIn casethe caseof Sendaiof Sendai
city,city,
the city
the city
administration
administration
had hadalready
alreadymademadepre-planned
pre-plannedarrangements/compacts
arrangements/compacts
for foralternative
alternative
sheltering
sheltering
serviceservicewithwith
52 local
52 localsocialsocialserviceserviceprovidersproviders
priorprior
to to
the theMarch
Marchevent.
event.
Some
Someof thoseof thosecompacted
compacted
shelters
shelters
conducted
conducted
studystudy
seminarsseminars
and andpracticepractice
drillsdrillsin thein theprevious
previous
year.year.Thanks
Thanksto theseto these
preparations,preparations,somesome
responded
responded
to theto city
the city
administration
administration
requestrequestquicklyquickly
and andthe theotherothereveneven
voluntarily
voluntarily
initiated
initiatedsheltering
sheltering
operations.
operations.
In total,
In total,
26 26
shelters
shelters
operated
operatedand served
and served
aboutabout
260 individuals
260 individuals
in Sendai
in Sendai
city (seecity (seefigurefigure8). 8).

Challenges
in preparedness,
response
and relief
for people
specialin timesof disasters
following
Challenges
in preparedness,
response
and relief
for people
with withspecialneedsneedsin timesof disasters
following
Challenges in preparedness, response and relief for people with special needs in times
7 6777the greatJapanearthquake
the great
East EastJapan
earthquakeof disasters followings the great East Japan earthquake

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Figure 8: Specially Designated Shelter
at Miyagino Day Service Center for
PWD, Sendai City (April 5, 2011)

Figure 9: Specially DesignatedShelter at Yugakukan Sport
Center Gym, Ishinomaki City

(http://road.nippon-foundation.or.jp/2011/04/007fcd1.html)

Downtown center of Ishinomaki city was badly damaged by March 11
tsunami forcing more than thirty thousand people or about one fifth of its
population in general shelters at its peak. A medical doctor helping one of alarge general shelters strongly demanded the city administration that analternative shelter be provided for the frail elderly, PWDs and those outpatients that did not require intensive medical care from the tsunami
unaffected Ishinomaki Red Cross hospital. The city temporally designated
Inai junior high school gym and then later moved the 20 to 30 shelter
occupants to Yugakukan sport center gym (see figure 9) on March 29.
Yugakukan gym eventually accepted about 130 people including PSNDs
and their family members. Yugakukan shelter was staffed initially by mostof Ishinomaki Municipal hospital doctors, nurses and social workers wholost their work place due to the tsunami attacks. Volunteer doctors, nurses,
social workers, nursing care workers and public administrators from otherprefectures came to the Yugakukan shelter and assisted the operation fromearly April.
It should be noted that Ishinomaki city was renowned for its city wide
community-based evacuation planning initiatives for PSNDs. The city wasrecognized as one of the ten model municipalities on PSND preparedness
master planning as early as year 2004. By the end of year 2010, 401 out of
421 administrative districts in the city completed individualized evacuation
planning for each PSND in the neighborhood. The city’s master plan for
PSND, however, did not include planning on specially designated shelters.
Inai junior high school and later Yugakukan shelter operations were all
improvised by city hospital doctors and nurses with the support from thecity. The city, however, was not aware of special service provision clausein Disaster Relief Act that qualified additional financial compensations on
top of general service provisions from the national government. It was not
until almost the end of April that the city formally designated Yugakukan as
the specially designated shelter for PSND. To sum up, specially designatedshelters operated in Ishinomaki city but the operation remained lacking
formal logistic support foundation for a prolonged period of time.

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Shunpoen Nursing Home Shelter (April 7, 2011)

Ochiai Nursery School Shelter(http://www.toshinkai.or.jp/image/C8EFBAD2C3CFC7C9B8AFCAF3B9F0.pdf)

Figure 10: Specially Designated Shelters at Shunpoen Special Nursing Home (Top) and Ochiai Nursery
School (Bottom)

Like Ishinomaki, more than twelve thousand or one sixth of
Kesennuma city population rushed to general shelters after the earthquake
and tsunami in March. Until April, the frail elderly, PWDs and smallchildren were all mixed with other evacuees who looked after those in needs
at general shelters. In some shelters, partition cardboards were used toseparate PSNDs from general evacuees in order to provide some privacy.
On April 7, the city administration officially opened the first speciallydesignated shelter for PSND on an unused nursery school site (see figure10). In the following two weeks, additional four specially designatedshelters were opened. Shunpo-en special nursing home for elderly (seefigure 10) was one of those four new specially designated shelters. It wasserving 60 elderly residents as well as more than one hundred generalevacuees and some PSNDs from the neighborhood after the March disaster.
Those PSNDs were taken care by the home staff workers. The director,
however, was afraid of financial burden to run specially designated shelter
for an extended period of time. Later in April, the city administrators
learned that official designation would allow additional care service
provision from Disaster Relief Act. This was on top of the provision ofregular service hours as prescribed by long-term care insurance scheme.
This alleviated tremendous financial burden which the city and/or thedesignated shelters like Shunpo-en home might have had to bear otherwise.
In other words, Kesennum city also lacked pre-planning on speciallydesignated shelters and the administration was not aware of legal framework(i.e. Disaster Relief Act special service provision clause) to operate theseshelters.
In conclusion, municipalities other than Sendai city did not havecompacts on specially designated shelter operations with social service
providers. It took nearly three weeks for Ishinomaki and Kesennuma toformally designate such shelters after the earthquake. It was learned thatthey were hesitant because they believed their facilities would not meet thestandard for specially designated shelters, as outlined in pre-disasterplanning manuals. Additionally, many local officials were unaware of thespecial service provision clause of the Disaster Relief Act covering shelters
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for people with special needs. Nonetheless, these kinds of sheltering
operations did emerge. Had the local municipalities officially declared thatthey were operating special-needs shelters, they would have been eligible
for additional resources at the onset of the even from both the national andprefectural governments. More detailed guidelines for specially designatedshelters and temporary housing operation for PSNDs need to be developedin order to address this issue.
2.3 Challenges on Utilizing Personal Information on People with Special
Needs in Times of Disasters
Among different types of PSNDs, people with disabilities (PWD)
were invisible in shelters and communities or in eyes of local government
administrators. This was due to the fact that majority of PWDs did not ask
for help in general shelters because they felt general shelters were not“barrier free” and unresponsive to their functional needs. Furthermore,
many local government administrators felt hesitant to release PSND registry
to NGOs and self-help organizations that were eager to check where-about
and current situations of PWDs. This was due to the fear of breaking
Personal Information Protection Bylaw despite the fact that the Bylaw
provides exceptional conditions, where the onset of disaster is clearly one ofthese exceptional conditions. In fact, Minamisoma city officials did releasethat information to a local NGO, and in Higashimatsushima, members ofgroups who worked on behalf of disabled persons, such as the Japan
Disability Forum, were allowed to accompany public health nurses on theirhome visits. Other cities might have been using similar approaches, but it
appeared that in most affected areas officials were unaware of the needs ofmentally ill and developmentally disabled persons and had not attempted toinitiate outreach efforts for those populations. As of June 2011, Japan
Disability Forum announced that they were able to meet 1,386 PWDs in
person from their outreach project in Miyagi prefecture. This number(1,386) accounted for only 2.6 % of 53,511 persons who were registered tobe PWD in the affected areas. Researchers and advocates for persons withdisabilities were unable to determine what was happening with large
numbers of survivors with disabilities. Further elaboration and education on
the use of personal information of PSND during disaster period are needed
among public and local government administrators.
CONCLUSION
This paper first introduced recent developments on counter-disastermeasures for PSNDs in Japan. Based on three reconnaissance missions inMarch and April three major challenges and their possible solutions in
preparedness, response and relief measures for PSND were presented. First,
challenges on identifying people at risk were illustrated. This would require
re-thinking from maximum probable event to maximum possible event
framework. Second, challenges on operating specially designated shelters
for people with special needs were identified. Further elaboration of theguideline on sheltering was suggested. Third, challenges on utilizing

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personal information on PSND during disaster were presented. Further
elaboration and education on this matter was recommended.
REFERENCES
Aoki, K. 2011. Report on supporting a specially designated shelter in
Kesennuma city, Miyagi prefecture. West Tokyo City Elderly Center Kirara(http://www.toshinkai.or.jp/image/C8EFBAD2C3CFC7C9B8AFCAF3B9
F0.pdf, October 1, 2011)
Fire and Disaster Management Agency, 2011. A research report onmunicipalities counter-disaster measures for people with special needs intimesofdisaster.
(http://www.fdma.go.jp/neuter/topics/houdou/2307/230708_1houdou/02_ho
udoushiryou.pdf, September 26, 2011)
Kailes, J. I. and Enders, A. 2007. Moving beyond “special needs”: afunction-based framework for emergency management and planning,
Journal of Disability Policy Studies, Vol.17, No.4, 230-237.
Tatsuki, S. and Comafay, N. 2010. Evacuation and sheltering
assistance planning for special needs population: Kobe disadvantaged
population mapping project, Presentation for International Sociological
Association World Congress of Sociology, Gothenburg, Sweden, July 15,
2010.

Challenges in preparedness, response and relief for people with special needs in times of disasters following
Challenges in preparedness, response and relief for people with special needs in times
11
the great East Japan earthquake
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October 2011, Chiang Mai, Thailand

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New Technologies for Urban Safety of Mega Cities in Asia

Simple¿²¼
and×²»¨°»²­·ª»inexpensiveÌ­«²¿³·
tsunamiÜ·­¿­¬»®
disasterÍ·³°´»
mitigation Í§­¬»³
system forÓ·¬·¹¿¬·±²º±® Indian×²¼·¿² Ocean
Ñ½»¿² Rim
Î·³
Regions¾§
byÝ±³¾·²·²¹
combining Ó«´¬·ó°«®°±­»
multi-purpose Ñ½»¿²
ocean
Î»¹·±²­
observationÞ«±§­buoys ¿²¼
and Ð®±°»®´§
properly ß®®¿²¹»¼
arrangedÑ¾­»®ª¿¬·±²
evacuation Ý»²¬»®­
centersÛª¿½«¿¬·±²
usingÎ»´·¹·±«­
religious Ú¿½·´·¬·»­
facilities«­·²¹
KIMIRO MEGURO1), Shiyunichi KOSHIMURA 2)
and Muneyoshi NUMADA 3)1), 3)
International Center for Urban Safety Engineering
Institute of Industrial Science, The University of Tokyo, Japan
2)
Tokoku University, Sendai, Japan

ABSTRACT
Triggered by a M9.0 earthquake that occurred along the Sunda Trench, OffSumatra, at 07:58 (local time), on December 26, 2004, a huge and devastatingtsunami hit the Indian Ocean Rim countries, causing unprecedented disaster withover 300,000 dead and missing persons. The analysis of other potential tsunami
scenarios in the region has revealed that 1.3 million dead and missing people may
be expected, at worst. Therefore, an effective and sustainable framework against
tsunami disaster is indispensable in this region.
Land use control, i.e. preventing people from residing next to the shore, is one
way to mitigate tsunami disaster if people follow it. However, this is not always aproper option in the Indian Ocean Rim region where the economic activities, e.g.
fishing, tourism, take place directly next to the seaside. For this case, a New
Tsunami Disaster Mitigation System by combining a reliable warning system andproper evacuation facilities is proposed. Important characteristics of this system
are its simplicity, economical efficiency and daily-usability.
This paper introduces the New Tsunami Disaster Mitigation System, highlighting.
The New System for the Indian Ocean Rim region combines a reliable warning
system and proper evacuation facilities. The warning system consists of multipurpose observation buoys operated by local organizations such as hotels andbeach associations. The system is not only used for tsunami warning but also tomonitor temperature, current velocity, wave height, moisture, etc., information
which can be used on a daily basis for the economic activities of the region.
The proposed evacuation facilities are designed taking into consideration:
sheltering capacity, location, and structural strength. Location is especially
important to prevent that the structures are washed away by the tsunami and toguaranty an easy access for the evacuees.

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October
2011, Chiang
Mai, Thailand

In order to verify the suitability of the proposed system, tsunami and evacuation
simulations are carried out. The strong points of the proposed system are its
simplicity, economy and daily usability, which makes it a sustainable option for
the region.
.
1. INTRODUCTION
Triggered by the M9.0 Earthquake that occurred along the Sunda Trench, OffSumatra, at 07:58 (local time), on December 26, 2004, a huge and devastatingtsunami hit the Indian Ocean Rim countries, causing unprecedented disaster withover 300,000 dead and missing persons. The tsunami was triggered by one of thepossible earthquake scenarios along the Sunda Trench. Four other potential
earthquake events along the trench have been identified and the expected numberof casualties in case they occur has been estimated. As a result, it was revealed
that 1.3 million dead and missing people are expected, at worst, as shown in
Figure 1. This number is several times larger than the observed in the December
26, 2004 event, showing that an effective and sustainable framework against
tsunami disaster is indispensable in this region.
Ó¿¨ò É¿ª» Ø»·¹¸¬Ü»½òîêôîððì
×²¼·¿² Ñ½»¿²
Û¿®¬¸¯«¿µ» Ì­«²¿³·

Å³Ã
ïçòîè
ðòðð

Ð±°«´¿¬·±² Ü»²­·¬§Å°»®­±²ñµ³îÃïëðôððððÚ¿«´¬ ±º ×²¼·¿² Ñ½»¿²
Û¿®¬¸¯«¿µ»ô Ü»½òîêô îððì
ð

ïôððð

íôððð Åµ³ÃÓ¿¨ò É¿ª» Ø»·¹¸¬

Main shock
After shock

Å³Ã

Í½»²¿®·±

ïîòêï
ðòðð

Plate boundary

Ð±°«´¿¬·±² Ü»²­·¬§Å°»®­±²ñµ³îÃïëðôððð

¾§ Ü®ò Íò Õ±­¸·³«®¿ô ÜÎ×ô Õ±¾»

ø¿÷ Í½»²¿®·± Ú¿«´¬­ ø
0×²¼·¿² Ñ½»¿²
Û¿®¬¸¯«¿µ» ¿²¼Ì­«²¿³· Ü·­¿­¬»®

200

400

ó

ð

÷ ¿´±²¹ ¬¸» Í«²¼¿ Ì®»²½¸
600

800

[Unit:1000 person]
1,000 1,200 1,400øÜ»½òîêô îððì÷

ð

ïôððð

íôððð Åµ³ÃÓ¿¨ò É¿ª» Ø»·¹¸¬Í½»²¿®·±

Í½»²¿®·±

Å³Ã
îèòêï
ðòðð

Ð±°«´¿¬·±² Ü»²­·¬§Í½»²¿®·±

Å°»®­±²ñµ³îÃïëðôððððÍ½»²¿®·±

Í½»²¿®·±

Ì­«²¿³· Í·³«´¿¬·±²æ ¾§ Ü®ò Íò Õ±­¸·³«®¿
Ð±°«´¿¬·±² Ü·­¬®·¾«¬·±²æ ¾§ Ñ¿µ Î·¼¹» Ò¿¬·±²¿´ Ô¿¾±®¿¬±®§ ðïôðððíôððð Åµ³Ã¾§ Ü®­ò Íò Õ±­¸·³«®¿ ¿²¼ Óò Ì¿µ¿­¸·³¿

ø½÷ Û­¬·³¿¬»¼ Ü»¿¬¸ Ì±´´ ¿²¼ Ó·­­·²¹ Ð»®­±²­¼«» ¬± Ü·ºº»®»²¬ Í½»²¿®·± Ú¿«´¬­

ø¾÷ Ð±°«´¿¬·±² Ü·­¬®·¾«¬·±² ¿²¼ Û­¬·³¿¬»¼ Ó¿¨·³«³ É¿ª» Ø»·¹¸¬¾¿­»¼ ±² Ò«³»®·½¿´ Ì­«²¿³· Í·³«´¿¬·±² º±® ¬¸» îððìòïîòîêÛ¿®¬¸¯«¿µ» ¿²¼ Ü·ºº»®»²¬ Û¿®¬¸¯«¿µ» Ú¿«´¬ Í½»²¿®·±­ ø ¿²¼

÷Figure 1: Estimated damage based on numerical tsunami simulation
with possible fault scenarios along the Sunda TrenchSome countries along the Indian Ocean Rim have established a tsunami disastermitigation system based on land use, i.e. prohibiting people inhabiting next to theseaside. Others are planning to adopt similar measures. Land use control is anefficient measure if people follow it. However, this is not always a proper option

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in case activities such as fishing and tourism, which are the pillars of the region
economy, take place directly next to the shore. Under these conditions, it isinapplicable to implement land use control policies.
In the Pacific Ocean Rim region, tsunami disaster mitigation relies on a
sophisticated warning system, which is used not only for disaster mitigation but
also for earth science research. This system is costly in terms of both installationand maintenance. Furthermore, it requires a great deal of knowledge to operate it.
Although it is very useful and appropriate for this area, where countries withfinancial and technological resources such as US and Japan are located, it is notapplicable for the Indian Ocean region (Figure 2).
Taking the above mentioned points into consideration, a New Tsunami Disaster
Mitigation System which combines a warning system suitable for the Indian
Ocean region and proper evacuation facilities in terms of location, strength andsheltering capacity is proposed. With this system there is no need to relocate thepeople living along the seashore; therefore, there is no impact on the local
economies. The proposed system is simple, economically efficient and dailyusable.
Ì­«²¿³· É¿®²·²¹ Í§­¬»³øÌÉÍ÷
Ý±²ª»²¬·±²¿´ÌÉÍÐ®±°±­»¼
Ò»© ÌÉÍÔ±© Ý±­¬ô Í·³°´» ¿²¼ Ü¿·´§ Ë­»¿¾´»

Sophisticated but Expensive and ComplicatedÌ¸» ³·²·³«³ «²·¬ ±º ¬¸» °®±°±­»¼ ­§­¬»³©±«´¼ ¾» ±²» ±® ¬©± ­·³°´» ³«´¬·ó°«®°±­»±¾­»®ª¿¬·±² ¾«±§­ ©·¬¸ ­±´¿® ¾¿¬¬»®§­§­¬»³ ±°»®¿¬»¼ ¾§ ±²» ¾»¿½¸ ­±½·»¬§ô­«½¸ ¿­ ¸±¬»´ ®»­±®¬ ­±½·»¬§ ±® ·¬­ ²»¬©±®µò
temperature, current velocity, wave
height, moisture, etc. on a daily basis

Redundant and easier/cheaper to sustain
Because of more and simpler stations
With daily usability,

Weather forecast, Safety information,
Break unscientific rumor
Prediction of catch of fish, Fish dude ranch, etc.

Useful for earth-science
But, from disaster mitigation
purpose, frequency of use of
the system is very small.
Difficult to maintain the system
Ô±²¹ ®»¬«®² °»®·±¼ ±º Ì­«²¿³·
Limited resources, researchers andbudgetPoor experiences of tsunami disasterFigure 2: Comparison between conventional and newly proposed tsunami
warning systems

Simple and inexpensive tsunami disaster mitigation system for Indian Ocean Rim Regions
and Inexpensive
Tsunami Disaster
Mitigation
System…
by combiningSimple
multi-purpose
ocean observation
buoys andproperly
arranged evacuation
centers using religious facilities

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October
2011, Chiang
Mai, Thailand

Weather
Forecasting
Data Use
TsunamiMonitoring

Leisure Condition
Information

Resource
Evaluation
Environmental Monitoring(a) Concept of TWS using Multi-Purpose Buoy(b) Networked Multi-Purpose Buoy System

Figure 3: Concept of proposed tsunami warning system composed of
networked simple multi-purposes observation buoys installed
locally and internationally
2. PROPOSAL OF THE NEW TSUNAMI DISASTER MITIGATIONSYSTEM
My proposed New Tsunami Disaster Mitigation System combines a reliablewarning system and proper evacuation facilities. As mentioned earlier, a warning
system such as the one available in the Pacific Ocean Rim region is not suitable
for the Indian Ocean region which has fewer technological resources, researchersand experiences of tsunami disasters. For this reason, I am proposing to use
simple multi-purpose observation buoys, which in addition to serve as a tsunami
warning system, would record temperature, current velocity, wave height,
moisture, etc. on a daily basis. This information can be used for weather
forecasting, safety assessment, fish catch prediction, etc. which are useful for the
local businesses (Figure 3(a)). My proposal is to use numerous and simple stations
so that the system is redundant and easier/cheaper to sustain. The minimum unitof the proposed system would be one or two multi-purpose observation buoys
operated and maintained by hotels/resorts or beach societies in the area. Thesebusinesses will benefit from the daily collected information.
It is expected that many beach societies install the system and join the multipurpose observation buoy network beyond the administrative or internationalboundaries (Figure 3(b)). In this way, it may be possible to gather daily maritime
information over a wider area and eventually forecast a transoceanic tsunami. A
system for transferring this information between associations, domestic andforeign, already exists.
The installation of the proposed buoy system could have additional advantages.
After the December 26, 2004 tsunami, the tourism industry has suffered greatly
not only due to direct impact of the tsunami in the infrastructure but also due tothe unscientific rumors. Visitors that used to come to resort facilities in the region
started avoiding these destinations for fear that a new disaster may occur. In orderto recover the tourists’ trust, the information collected by the buoy system can bevery useful. It is also known that buoys may become the center of marine
ecosystems which could be an attraction for scuba divers.

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Proper evacuation facilities in terms of location, strength and sheltering capacity
are also part of the proposed system. In the region, it is common to observe
temples, churches and shrines located along the coastal line. Therefore, I am
proposing to use similar community centers as evacuation facilities. This scheme
has two main advantages. Because worship centers are permanently used by thepeople, their location is well known so that in case an evacuation notice isreleased, everybody can easily access them. Additionally, because the people feelstrong commitment with these facilities, they take active participation in theirbuilding and maintenance.

3. ESTABLISHMENT OF THE PROPOSED TSUNAMI DISASTER
MITIGATION SYSTEM
In order to establish the proposed system, several works are needed as shown in
Figure 4 and the reconnaissance team, which I headed, carried out them.
1) Structural damage survey
2) Tsunami numerical simulation
3) Topographical survey4) Questionnaire/Interview survey5) Evacuation numerical simulation
The first three activities are closely interrelated and their main objective is todesign the configuration and location of evacuation centers. The structural
damage survey is intended to evaluate the tsunami load and corresponding
damage. With this information, the relationship between tsunami wave load andwave height/velocity can be obtained. With tsunami numerical simulations using
potential earthquake scenarios, it is possible to estimate the wave height andvelocity and the tsunami inundation area due to future tsunami hazards. These
data enable us to properly determine location and structural design criteria forevacuation facilities.
In order to guaranty that the evacuation centers are fully functional, their location
should be selected so that when the expected tsunami occurs they will not be
washed away. For this purpose, it is indispensable to carry out a topographicalsurvey. Real-time kinematic GPS and laser total stations are powerful tools forthis purpose.
Questionnaire and interview surveys are useful to gather data necessary for theevacuation behavior simulation. Relationships between human evacuation
velocity and water depth, which are needed for this study, have already been
proposed. The simulation will confirm whether the escape routes and proposed
evacuation centers are suitable. Because the proposed tsunami disaster mitigation
system heavily relies on the participation of regional organizations, the interviews
are also helpful to assess the level of acceptance of the system among the people
involved.

Simple and inexpensive tsunami disaster mitigation system for Indian Ocean Rim Regions
and Inexpensive
Tsunami Disaster
Mitigation
System…
by combiningSimple
multi-purpose
ocean observation
buoys andproperly
arranged evacuation
centers using religious facilities

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October
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Mai, Thailand

Damage Surveyof Structures

Numerical Tsunami
Simulation using
Potential Faults

Topographical
SurveyTsunami Load

Tsunami Heightand Velocity along
the Coastal line

DigitalElevation
Map

Location Selection
and Design of
Evacuation Facility
Structural Designof Tsunami
Evacuation
Facility

TsunamiInundation
Simulation

Evacuation
Behavior

Questionnaireand Interview
SurveyProposal of
New Tsunami
Warning System

Possibility of
Introductionof theProposed
SystemIntroductionof theProposed
SystemDepth and Velocity

Human Evaluation Simulator in Tsunami Disaster

New Tsunami Disaster Mitigation System Suitable for Indian Ocean Rim Countries

Figure 4: Establishment of the proposed tsunami disaster mitigation system
Figure 5 shows some samples of multi-purpose observation buoys that we havedeveloped. With the solar panel system installed on the buoy, the system cancontinue observation permanently and users can get their favorite information
with real-time basis. Initial cost of the system is about 10 to 20 million yen(changing with the equipments that the user wants to install the buoy). As wethink that potential users of the system are resort hotel owners in beach resort asthey can get the biggest benefit, when we calculate the additional cost(yen/room/day) to the normal room rate that is necessary for maintaining thesystem, we can get the numbers shown in Table 1. The numbers in Table 1 are
obtained by assuming that life time of the system is 3 to 5 years, average numberof rooms in each resort beach is 200 to 500 rooms, and average number days ofuse of the room is 100 to 200 days/year. From the numbers in Table 1, we can saythat with reasonably low additional cost, our proposed system can be maintained.

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Ò±òî

Ò±òî
Ò±òí

Ò±òí

Figure 5: Samples of developed systems
Table 1: Cost needed to maintain the system (yen/room/day)Ý±­¬
ø³·´´ò §»²÷ïðîð

Ô·º» ¬·³»
ø§»¿®­÷îðð ®±±³­ñ¾»¿½¸

ëðð ®±±³­ñ¾»¿½¸

ïðð ¼¿§­

îðð ¼¿§­

ïðð ¼¿§­

îðð ¼¿§­

í
ë
í
ë

ïêé
ïðð
ííí
îðð

èí
ëð
ïêé
ïðð

êé
ìð
ïíí
èð

íí
îð
êé
ìð

4. CONCLUDING REMARKSThis paper presents a New Tsunami Disaster Mitigation System for the Indian
Ocean Rim region, which combines a reliable warning system and proper
evacuation facilities. The warning system consists of multi-purpose observation
buoys operated by local organizations such as hotels and beach associations. The
system is not only used for tsunami warning but also to monitor temperature,
current velocity, wave height, moisture, etc., information which can be used on adaily basis for the economic activities of the region.
The proposed evacuation facilities are designed taking into consideration:
sheltering capacity, location, and structural strength. Location is especially
important to prevent that the structures are washed away by the tsunami and toguaranty an easy access for the evacuees.
In order to verify the suitability of the proposed system, tsunami and evacuation
simulations are recommended. Actually, the research team headed by the author
Simple and inexpensive tsunami disaster mitigation system for Indian Ocean Rim Regions
and Inexpensive
Tsunami Disaster
Mitigation
System…
by combiningSimple
multi-purpose
ocean observation
buoys andproperly
arranged evacuation
centers using religious facilities

689

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2011, Chiang
Mai, Thailand
October
2011, Chiang
Mai, Thailand

has already perform this type of study with some selected areas in Japan and Sri
Lanka and proved the system effectiveness. The strong points of the proposedsystem are its simplicity, economy and daily usability, which makes it asustainable option for the region.

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Study on recovery curves
for housing reconstructionin Sri Lanka, Thailand, and Indonesia
after the 2004 Indian Ocean
Tsunami Disaster
Osamu MURAO1, Kazuya SUGIYASU2, and Hideaki NAKAZATO3
1
Assoc. Professor, The Graduate School of Systems and Information
Engineering, The University of Tsukuba, Japanmurao@risk.tsukuba.ac.jp
2
Doctoral Student, The Graduate School of Systems and Information
Engineering, The University of Tsukuba, Japan
3
The Okinawa Electric Power Company Inc., Japan
ABSTRACT
Each damaged country by the 2004 Indian Ocean Tsunami adopted proper
recovery planning strategy respectively according to the situation for the
resettlement of the victims after the event. It is generally important toclarify the relationship between the recovery process and the policy after
disasters in discussions concerning future post-disaster recovery initiatives.
The recovery curve proposed by the authors is a tool to solve the problems;in previous studies, recovery curves were developed to assess recovery fromthe Sumatra Tsunami using the rate of construction of both transitional andpermanent houses in those three countries, Indonesia, Sri Lanka, andThailand, from the viewpoint of urban physical environment. Following
step should be comparison of the curves along with contexts of the recovery
process, so this study aims to clarify differences of the recovery process. In
this paper, differences of the constructed recovery curves of the three
countries are discussed quantitatively. It clarified that the speediest
recovery from the event is made in Sri Lanka and the slowest is in Indonesia.
In order to consider the national recovery differences, it is necessary tofollow the recovery timeline after the devastating event in the next stage.
Keywords: the 2004 Indian Ocean Tsunami, recovery curve, permanenthouses, urban recovery process, probability density functions
1. INTRODUCTION
As of June 2011, six and half years have passed since the 2004 Indian
Ocean Tsunami struck the coastal areas of several Indian Ocean rim
countries. The authors had followed post-tsunami urban recovery processes
in the most devastated three countries by the event for several years:
Indonesia, Sri Lanka, and Thailand. Each country adopted proper recovery

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Chiangmai,

planning strategy respectively according to its situation and background,and most victims settled themselves in permanent houses as a result.
It is generally considered important to clarify the relationship between
the recovery process and policy, after disasters in discussions concerning
future post-disaster recovery initiatives. For example, Haas et al. (1977)
suggest a model of disaster recovery activity after the 1906 San Francisco
Earthquake. However, it is not easy to clarify the relationship because of
several complicated factors such as difficulty of collecting data, or diverse
social background. Murao et al. (2007) propose a recovery curve
construction method for Chi-Chi, one of the damaged areas due to the 1999
Taiwan Earthquake, as a tool to solve the problems. Actually there aremany indicators to understand urban recovery conditions after disasters, but
the authors chose the construction ratio of necessary buildings, such astransitional/temporary houses or permanent houses, in the damaged areas as
an important physical indicator for the victims.
Following the research in Chi-Chi, recovery curves were developed
for Thailand (Murao, Sugiyasu, and Nakazato, 2008), Sri Lanka (Murao andNakazato, 2010), and Indonesia (Sugiyasu and Murao, 2010) to assess thoserecovery processes after the 2004 Sumatra Tsunami using the rate ofconstruction of both transitional and permanent houses from the viewpointof urban physical environment.
Following step should be comparison of the curves. This paper
compares the recovery curves for the three countries in order toquantitatively clarify the national differences of the recovery process.
2. METHOD
The following procedure is employed to construct the post-tsunami recovery
curves and to compare the curves for the three countries.
2.1 Construction of recovery curves
Recovery functions for the three countries were derived from theobtained building construction data of permanent houses given by thegovernments through authors' previous research. The factors of time(months) and completion ratio of building construction were used toconstruct the recovery functions. The time period starts in December 2004,
with January 2005 being regarded as passing month “1”. The time period
extends fifteen to fifty months respectively in each country until the timethat most planned houses are completed. The completion ratio of building
construction for a given time period is calculated based on the total amountof completed buildings.
At the time T when the victims' lives have been sufficiently settled,
for a time period of t (months), the cumulative completion ratio of building
construction R (t) is assumed to have the cumulative normal distribution, as
follows:

2
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R (t) = Φ ((t - λ)/ζ)(1)
where Φ represents the standard normal distribution, and λ and  ζ are
the mean and standard deviation of t, respectively. The two parameters forthe distributions, λ and  ζ, are determined using the least squares method on
probability paper as shown in Figure 1, for the case of Thailand. Then
recovery curves are drawn as shown in the following chapter.
4.00
3.00

Recovery Condition in Thailand

2.00
1.00
0.00
0

5

10

15

20

25

30

-1.00
-2.00
-3.00

y = 0.178 x - 2.482
R² = 0.757-4.00Time Period (months)

Figure 1: Relationship between time and completion ratio of permanenthouse construction in Thailand, as plotted on probability paper
2.2 Comparison of the recovery curves
The constructed recovery curves by the way of the above have two
important parameters, mean (λ) and standard deviation (ζ). Thoseparameters suggest commencement time and average construction time
period of the permanent houses built in each country. Then, thoseparameters are compared to quantitatively understand the national recovery
tendency.
3. RECOVERY CURVES FOR PERMANENT HOUSESThis chapter presents the construction status of permanent houses in thethree countries based on the acquired official data by the governments at
first, and it is followed by the constructed recovery curves respectively.
3.1 Construction status of permanent houses and data source
The number of damaged buildings due to the tsunami rose to 629,316
in the world by the report of WHO (2005). Indonesia, Sri Lanka, andThailand, the focused countries in the research, are the top three mostdevastated countries among the affected areas. Table 1 shows a damage
outline by the tsunami in the countries.

Study on recovery curves for housing reconstruction in Sri Lanka, Thailand, and Indonesia after the 2004
Study on recovery curves for housing reconstruction in Sri Lanka, Thailand,
Indian Ocean Tsunami
6933
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Thailand
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Table 1: Damage outline by the 2004 Indian Ocean Tsunami in three
countries

Affected countries
Sri Lanka
Thailand
Building damage
103,753
4,806
Displaced people
500,668
58,550Deaths30,9595,392Missing
5,644
3,062
Deaths and missing
36,6038,454
Source: Research and International Cooperation Bureau (2006)
Relief Web Map Center (2005)
WHO (2005)

Indonesia
514,150
417,438
114,573
127,749
242,322After the event, each government discussed strategy for urban
recovery according to its damage situation and social context. Througharranging post-tsunami recovery plans, they estimated the number ofnecessary permanent houses for the victims before construction. Table 2
shows the number of planned permanent houses and the completion time of
the first permanent housing site. The data sets of permanent house
information from the governments shown in the table were used for therecovery curves.
Table 2: Construction status of permanent houses in three countries
Sri Lanka1)
29,971Thailand2)
2,251

Indonesia3)
132,928

Planned permanent houses
Completion time of the first permanent
April 2005
March 2005
Dec. 2006
housing site
Source:1) RADA (2006)
2) Provided by Provincial Social Department and Human Security in Feb. 2007
3) BRR (2005), BRR (2007), BRR (2009), and provided data by BRR in Feb. 2008

3.2 Recovery curves for permanent houses in Sri Lanka
Figure 2 shows the recovery curves for Sri Lanka along with observed
recovery ratio constructed by Murao and Nakazato (2010). Although thecurve for the permanent houses was fitted by the cumulative normal
distribution described in 2.1, the curve for the transitional houses was basedon the Gompertz distribution.
Recovery Curves for Sri Lanka

1
0.9

Recovery Ratio

0.8
0.7
0.6
0.5
0.4

Permanent House

0.3

Observed
Transitional House

0.2

Observed

0.1
0

0

5

10

15

Time Period (Months)

Figure 2: Recovery curves for permanent houses and transitional housesin Sri Lanka (Murao and Nakazato, 2010)

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3.3 Recovery curve for permanent houses in Thailand
Figure 3 represents the recovery curve for the permanent houses inThailand along with observed recovery ratio (Murao et al., 2008).
Recovery Curve for Thailand

1
0.9

Recovery Ratio

0.8
0.7
0.6
0.5
0.4
0.3

Permanent House

0.2

Observed

0.1
0

0

5

10

15

20

25

Time Period (Months)

Figure 3: Recovery curve for permanent houses in Thailand(Murao et al., 2008)
3.4 Recovery curves for permanent houses in Indonesia
The recovery curves for permanent houses and transitional houses inIndonesia (Sugiyasu and Murao, 2010) are shown in Figure 4.
Recovery Curves for Indonesia

1
0.9

Recovery Ratio

0.8
0.7
0.6
0.5
0.4

Permanent House

0.3

Observed
Transitional House

0.2

Observed

0.1
0

0

5

10

15

20

25

30

35

40

45

50

Time Period (Months)

Figure 4: Recovery curves for permanent houses and transitional housesin Indonesia (Sugiyasu and Murao, 2010)
4. COMPARISON OF THE RECOVERY CURVES AMONG THE
THREE COUNTRIES
4.1 Viewpoints of the comparative study
Showing the two parameters of the recovery curves, mean (λ) andstandard deviation (ζ), the recovery curves for the permanent houses
Study on recovery curves for housing reconstruction in Sri Lanka, Thailand, and Indonesia after the 2004
Study on recovery curves for housing reconstruction in Sri Lanka, Thailand,
Indian Ocean Tsunami
6955
and Indonesia after the 2004 Indian Ocean Tsunami DisasterOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

indicate how each government dealt with resettlement for the victims.
Table 3 shows the parameters of the curves for the three countries and someconstruction completion time obtained by the curves. Mean (λ) shows thenumber of months whose construction completion ratio of the permanenthouses is 50%, and the value of standard deviation bring out the time periodthat 68.27% of the scheduled buildings are mostly constructed.
Table 3: Comparison of parameters for permanent house construction
Mean (λ)
Standard deviation (ζ)
Coefficient of determination (R2)Time period of most building
construction (2ζ)
Completion time of the 1st permanenthouse site
50% completion time
90% completion time

Sri Lanka
8.2
1.9
0.96

Thailand
14.0
5.6
0.76

Indonesia
28.8
8.2
0.92

3.8

11.3

16.4

April 2005

March 2005

Dec. 2006

Aug. 2005
Oct. 2005

Feb. 2006
Sep. 2006

April 2007
March 2008

4.2 Comparison of the construction processes in the three countries
The recovery curves for permanent houses in the three countries aredemonstrated in Figure 5, and probability density functions are illustrated in
Figure 6. These figures and the above table clarify quantitative differencesof post-tsunami recovery process among the countries in terms of permanenthouse construction.
The speediest recovery from the event is made in Sri Lanka; theslowest is in Indonesia. The first permanent house site in Thailand wasfinished in March 2005, followed by Sri Lanka in April 2005. Comparedwith the two countries, the completion of those in Indonesia was too late, in
December 2006, twenty-one months later from the month of Thailand.
Recovery Curves for the Three Countries
1
0.9

Recovery Ratio

0.8
0.7
0.6
0.5
0.4
Indonesia

0.3
0.2

Thailand

0.1

Sri Lanka

0

0

5

10

15

20

25

30

35

40

45

50

Time Period (Months)

Figure 5: Recovery curves for Sri Lanka, Thailand, and Indonesia

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Probability Density for the Three Countries

Recovery Ratio

0.2
Indonesia
ThailandSri Lanka

0.1

0

0

5

10

15

20

25

30

35

40

45

50

Time Period (Months)

Figure 6: Probability density functions for Sri Lanka, Thailand, andIndonesia
Figure 5 and Figure 6 shows the time of the peak (λ: 50% completiontime) for each country: 8.2 months (August 2005) in Sri Lanka, 14.0 months(February 2006) in Thailand, and 28.8 months (April 2007) in Indonesia.
The gap between Sri Lanka and Indonesia is 20.6 months, more than one
and half years. The 90% completion time is October 2005 in Sri Lanka,
September 2006 in Thailand, and March 2008 in Indonesia. The difference
between Sri Lanka and Indonesia is about thirty months.
Time period that 68.27% of the buildings are mostly constructed (2ζ) is 3.8
months in Sri Lanka, 11.3 months in Thailand, and 16.4 months inIndonesia. The slowest recovery of Indonesia spends four times of the
speediest recovery of Sri Lanka. It means that Sri Lanka could concentrate
the construction effort for shorter period than the others.
5. CONCLUSION
This paper presents the recovery curves for permanent houses constructed in
Sri Lanka, Thailand, and Indonesia after the 2004 Indian Ocean Tsunami toquantitatively evaluate recovery processes. Constructed curves clarified
differences of the recovery process among the three countries: (1) the
speediest recovery from the event is made in Sri Lanka; (2) the slowest is inIndonesia; (3) time period of most building construction is 3.8 months in Sri
Lanka, 11.3 months in Thailand, and 16.4 months in Indonesia. It meansthat Sri Lanka could concentrate the construction effort for shorter period
than the others.
The differences of the recovery process among the countries weremade by regional damage size, complexity of the society, governmental
budget, political leadership, and so on. More discussions are required toclarify the relationship.

Study on recovery curves for housing reconstruction in Sri Lanka, Thailand, and Indonesia after the 2004
Study on recovery curves for housing reconstruction in Sri Lanka, Thailand,
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and Indonesia after the 2004 Indian Ocean Tsunami DisasterOctober 2011, Chiang
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REFERENCES
Badan Rehabilitasi dan Rekonstruksi NAD-Nias (BRR), 2005. Laying
Down the Foundation for a Better Future, Six-monthly Report of the
Executing Agency for the Rehabilitation and Reconstruction of Aceh andNias.
Badan Rehabilitasi dan Rekonstruksi NAD-Nias (BRR), 2007.
Tsunami Recovery Indicators Package for Aceh and Nias English Edition.
Badan Rehabilitasi dan Rekonstruksi NAD-Nias (BRR), 2009.
http://e-aceh-nias.org/home/, 2009.1.31.
Haas, J. E., Kates, R. W., and Bowden, M. J., 1977. Reconstruction
following disaster.
Murao, O., Mitsuda, Y., Miyamoto, A., Sasaki, T., Nakazato, H., andHayashi, T., 2007. Recovery curves and digital city of Chi-Chi as urban
recovery digital archives, Proceedings of the 2nd International Conference
on Urban Disaster Reduction (CD-ROM), Taipei, Taiwan.
Murao, O., and Nakazato, H., 2010. Recovery curves for housing
reconstruction in Sri Lanka after the 2004 Indian Ocean Tsunami. Journalof earthquake and Tsunami, Vol.4, No.2, 51-60.
Murao, O., Sugiyasu, K., and Nakazato, H., 2008. Consideration ofrecovery process and development of recovery curves for buildings in
Thailand after the 2004 Indian Ocean Tsunami, Journal of the City Planning
Institute of Japan, No.43-3, 745-750 (in Japanese).
Rebuilding and Development Agency in Sri Lanka (RADA), 2006.
Progress Report.
Relief Web Map Center, 2005. South Asia Earthquake and Tsunami:
Affected Population.
Research and International Cooperation Bureau, 2006. Thailand
Country Report, Department of Disaster Prevention and Mitigation,
Ministry of Interior.
Sugiyasu, K., and Murao, O., 2010. Comparative Analysis of theReconstruction Process of Urban Facilities in Indonesia based on Recovery
Curves after the 2004 Indian Ocean Tsunami, Proceedings of theInternational Conference on Sustainable Built Environment 2010, Volume02, 363-370, Kandy, Sri Lanka.
World Health Organization (WHO), 2005. Situation Report 32

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NewMarch 11, 2011, Tsunami Earthquake of Japan–Nine epistles to friends and colleagues
Tsuneo KATAYAMA
Professor, Tokyo Denki University, Japankatayama@cck.dendai.ac.jp
ABSTRACT
Following the occurrence of the devastating tsunami earthquake which hit the
Pacific Ocean side of the northern part of the main island of Japan on March 11,
2011, I wrote nine letters and sent them to my friends and colleagues in the fieldof earthquake engineering all over the world. By doing so, I tried to add somecommentaries which, I did not think, were available on the world press in thewake of the disaster as well as to express my very personal views about theearthquake and its effects to the Japanese people. Although my comments are
unduly weighted towards my personal impressions, they may be useful tounderstand how a Japanese person felt about the unprecedented calamity. In thispaper, I would like to summarize the letters to share my impressions. It should be
noted some of my comments could not be substantiated, partly because I have notso far visited the stricken areas, but this is what I would like to leave for my own
memories.
Keywords: 2011 March earthquake of Japan, Tsunami disaster, personal
impressions
1. THE FIRST LETTER DATED MARCH 15, 2011
At the time of the earthquake occurrence, I was chairing a meeting held in thecenter of Tokyo. The shaking was the strongest and the longest I had everexperienced before. According to the record obtained by the Earthquake ResearchInstitute, Uni. Tokyo, the duration of the motion in Tokyo was about 5 minuteswith dominant period of 2 to 3 sec (This is my guess.). Buildings I saw from thewindows of the meeting room were visibly swaying, and it was horrible to watcha tall construction crane just across the street moving back and forth. I felt that“THE ONE” had come. In spite of this, all the buildings were standing intact
after the strong shaking, and I thought everything was OK in the end. We were in
the second floor of a 7-story building. When the major shaking was over, we
walked up, because elevators automatically stopped, to the 5th floor where I have
my office. There are usually some 50 people on the 5th floor, but when we went
there, the large office room was empty. All employees went down to the foyer on
the ground floor according to the disaster preparedness program. Within probably
an hour, it was decided that employees might go home. But soon after that, welearned all public transport was held up for inspection of possible damage. To tell699

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the truth, at that time I took the situations too easy. I just continued to watch TV,
whereas I should have reserved a hotel or a cab as early as possible. Within 2, 3
hours time, there were no hotels or cabs available, and phones were disconnected
because of heavy traffic. Many of the young employees went home on foot, someof them by walking for 2~3 hours. I learned later that getting a taxi did not mean
getting home earlier, because expressways were held up for inspection and streets
were completely jammed. The night of the earthquake, I was lucky that I could
have a nap in the building of a sister organization of the one we were having ameeting at the wake of the earthquake. The room I stayed in is officially used bybuilding guards.
On TV we saw Tsunamis swallow many towns and villages along the Pacificcoast in the Tohoku area, i.e. the northeastern part of the Honshu Island. It was
horrifying and hard to believe that such disasters were really taking place in frontof us. Most of you must have seen on TV such scenes as Tsunami going over a
breakwater as high as 10m. Many small cities and towns were completely
destroyed. It is reported, or rather I expect, that the final death count will reachsomething between 15,000 and 20,000. In hard-hit isolated areas, water, food,and other daily stuff are short, because transport systems have been cut off.
(Although some foreign media reported that things are scarce in Tokyo, it is nottrue. However, quite a few people rushed to convenience stores to get rice,canned food, and so on.)Conditions of nuclear power stations are serious, and I am truly concerned about
them. Information seems to be fragmentary, and some of the information releasedby the Company and the Government are difficult to understand. However,
explosions did take place and radioactive levels are thousand times the ordinary
values. Although they said until yesterday that radioactive effects had not reached
the dangerous level, tones of media are changing today. We cannot stop feelingdoubtful about what they say because they repeat “It is safe” too often. One of
my daughters says: We all have enjoyed civilized, abundant, and bountiful life fora long time because of electricity. If something should happen to us this time, wewould be paying heavy compensation to what we have enjoyed in the past.
I do think children outgrow their parents.
These are my personal observations and impressions on the 5th day of the Great
Tsunami earthquake. I am rather a person with no religious belief, but now I findmyself praying to God.
2. THE FOLLOWING WAS WRITTEN ON MARCH 17
This is the 6th day (March 17) after the earthquake. Life in Tokyo is coming backto normal. But, I see much less people and cars on the street, and public transport
is much less crowded. Quite a few numbers of bus routes have been temporarilyclosed, because of oil shortage. This has taken place because several large-sized
oil refineries were closed after the earthquake, people rushed to gas stations tofill tanks of their cars, and also because more oil is expected to be needed in the700

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stricken areas in future. Many companies are asking their employees to stay home
and work there.
I am surprised that structures at least in Tokyo have survived the strong shaking oflast Friday. The earthquake affected the Tokyo Bay shoreline areas of Chiba Pref.,neighboring Tokyo, some 300~400 km from the epicenter. Liquefaction seems to
be widespread there, forcing the Tokyo Disneyland to close.
In the Tsunami-hit areas, people are still in acute shortage of water, food, andbasic daily stuff. If I am correct, the death count is over 13,000 and more than
400,000 people are still displaced from their homes most of which have been
completely lost. Even undamaged hospitals have to move their patients because
medicines are lacking. Damage to transport systems is causing a most difficult
problem. Areas are not reachable from sea because of Tsunami damage.
People in the northern part of Japan are patient and hardworking. I cannot tellwhat might happen if a similar disaster hit one of larger cities in Japan.
Situations in the nuclear power stations in Fukushima are still bad, maybe getting
worse and worse everyday. They have started to shoot the damaged containers
and the surrounding facilities by pressurized water. We do not know how
effective it is. Foreign students have left and are leaving Japan. Foreigncompanies have, I heard, begun moving their offices and employees to thewestern part of Japan.
After the 1995 Kobe earthquake, I talked and wrote: We the experts had been
ignorant, too self-confident, and we did not tell people what we did not know. I
like hard-boiled mysteries, especially those by Raymond Chandler. In one of his
books, a woman says to the protagonist of the story, ”You self-sufficient, selfsatisfied, self-confident, untouchable bastard.” I feel as if I were him. I think wehave again been ignorant, self-confident, and we have not admitted that there areso many things we do not know. I still believe that Japan’s earthquake
engineering level is generally high. And it is true that we have done quite a few
things to upgrade the strength of structures, including that of nuclear power
stations. But, we stopped thinking any further.
Regarding the characteristics of ground motions, please refer to the following
URL which unfortunately is available only in Japanese at the moment.
http://www.bosai.go.jp/news/oshirase/20110315_01.pdf
3. ACCOUNT OF MY WIFE ABOUT THE DAY OF THE EARTHQUAKE
My wife had been in Ginza, one of the busiest shopping areas in the center ofTokyo. She was in the subway going home, and the train jerked to stop between
stations still in the general Ginza area. There was an announcement that the train
stopped because the early earthquake warning had been received. My wife saysthat the shaking felt in the subway was not very violent. But, at the same time,

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she says that she thought what she should do if destruction aboveground wasserious. These are not contradictory, because, according to the announcement in
the subway, very strong shaking was expected in Tokyo. After some 10 minutes,
the subway began to move to the nearest station where all passengers were asked
to leave. She walked up to the ground level to find all structures nearby sound.
What she remembers most strongly was there were so many men in the darkbusiness suit on the street where there usually are women (window) shopping.
She started walking from Ginza to Shinbashi (Sorry for those who are not familiar
with Tokyo.) I think it was at around 15:00~15:15 (The earthquake occurred at
14:46.). Streets were already becoming crowded with people walking home andcabs taking people from the central part of Tokyo to suburbs.
She took a cab, which was lucky because it must have become difficult or
impossible to do so within a quarter of an hour. It took 2 hours to reach home,four to five times more than it does in the ordinary times. Our apartment house
was undamaged except for some broken porcelain and glass ware. According toa cab driver I happened to meet later, there was some 5-6 seconds before strong
shaking was felt in Tokyo after the issuance of the warning. He also said that hecould decelerate his car to stop near the curb.
4. THIS IS MARCH 18 (FRIDAY)
A week has passed since the earthquake. People in the hard-hit areas are still
struggling because of shortage of basic stuff. There are about 300,000 people
displaced from their homes staying in refuges. It has been snowing andtemperature at night went down below zero. We do not know what is taking placein the nuclear power plants in Fukushima. Unfortunately, there is news thatgasoline was stolen in several but not many places in areas NOT affected by theearthquake.
Although I wrote yesterday that pressurized water would be aimed to the damaged
nuclear power plants, it was not successful. In one case, water did not reach theaim. In another case carried out by the Self-Defense Force, they called it off at
around 20:00 after having tried several times by changing workers as often as
possible not to expose them to the radioactivity. I understand that, unless we cool
down nuclear fuel rods, no farther step could be started.
On TV and in the other media, many so-called experts comment on and criticize
what have been done in Fukushima. But, the laymen have never heard of
millisieverts, microsieverts, nor the radiation levels that cause health damage.
Most of us are sick and tired of the comments by experts given on TV.
Every morning I have a cup of coffee in a café near my office. Customers there
are denouncing the comments by experts. In the ordinary times, one usually stays
in the shop reading newspapers or contemplating what may or may not be
important to the others. But, this morning, we including a girl who serves us
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experts should go near the power plants if they really believe they are safe, in
stead of smugly making useless comments on TV.
Last evening, it was extremely hard for most of us to go home from our working
places. At around 16:00 yesterday, Minister of Economy, Trade and Industry at
an urgent press conference said in person that large-scale blackout might takeplace in the TEPCO’s service area, and that people should go home as early as
possible. This caused extreme traffic jam of the public transport system in Tokyo.
Blackout was fortunately evaded, but hundreds of thousands commuters wereaffected by the traffic jam.
Polat Gulkan, President of the International Association for Earthquake
Engineering, responded to my e-mail as follows:
Dear Tsuneo,
I have read with much interest the description of the Sendai earthquake
from your personal window where you and your immediate family
happened to be on that day. Thank you for conveying to us yourimpressions for the events that occurred, but I think that you are too
harshly critical of your fellow engineers in Japan. True, the nuclear
plant proved to be a showcase for the principle that things can go wrong
in horrible sequence, and that "outlier" events aren't necessarily to beignored. But the performance of the building stock appears to have been
good, and the discipline and self-sacrifice of your fellow countrymen
and women are exemplary. You should feel proud for that. Ourcollective sympathies and prayers that Japan should soon begin toregain its balance are with you.
With best regards,
Polat Gulkan
Polat, I appreciate your kind words. But, what I wanted to do was not to be too
harsh to my fellow engineers but to examine my conscience.
5. MARCH 19 (SATURDAY)
According to TV news, the confirmed death is over 7,000 and 11,000 are still
missing. They say today is the age of telecommunications and the internet. But,in the aftermath of the earthquake of March 11, telephones including cell phones
were disconnected and the internet did not function because of traffic congestion
as well as power outage. In one of the hardest hit cities, the originals of family
registers of all citizens are reported to have been lost. With respect to Tsunami
warning, a city had a plan to use the internet, but it did not work because of thepower outage soon after the earthquake, and because the emergency center werebusy in dealing with inquiries from citizens.

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For example, regarding to the severe accident in the atomic power plants,
information on TV was probably more than enough because of so many channels
available, but its quality was open to question. What commentators and experts
talk on TV were inconsistent. Official announcement made at the same press
conference from the government was often broadcast at different times on
different TV channels without mentioning when the particular conference washeld. There are basically four sources of information; the producer of the plant,
the Tokyo Electric Power Company (TEPCO), the Ministry of Economy, Tradeand Industry, and the Cabinet (i.e. the Government). Since the Self-Defense
Force and several fire departments have begun to be engaged in cooling ofdestructed nuclear plants, the number of press conferences increased includingthat by Minister of Defense. We did not hear anything from the producer of theplant, but the remaining three organizations release almost the same informationin the order shown above. It seems to be complete waste of time for most ofviewers. It is much more efficient for the three (or more) organizations to get
together to make one press conference. The worst and the most critical problem
relating to so-called official press conference is, however, that we are feelingsome important facts are concealed. My wife says, and I thoroughly agree withher, BBC and CNN are more direct in describing the state-of-the-art.
Access roads from the major north-south highway to hard-hit coastal areas havefinally been secured. Isolated areas are becoming less and less in number. Foodand potable water are still scarce. Representative of a volunteer organization saidon TV this morning that there are about 400,000 displaced people and additional
300,000 people who need food in their homes. By assuming two meals a day perperson, a total of 1,400,000 meals have to be prepared every day. It is a sheer
impossibility in the disaster-stricken areas. Electricity is now back to service, but
kerosene gas for stoves broadly used for heating in winter is running out in many
places.
The scheduled power outage in the TEPCO’s service area started on March 14 or
15 resulted in confusion, customers did not at the beginning know when the power
outage of their homes would take place. The Daily Yomiuri (March 16) describes
it as: TEPCO’s poor publicity led to metropolitan mess.
I would like to quote from another Philip Marlowe mystery: The fear of to-day
always overrides the fear of to-morrow.
6. MARCH 20, 2011 (SUNDAY)
As of noon today, the National Police Agency released the following numbers:
Confirmed death: 8,132
Missing (0fficially filed): 12,272
Completely or partially damaged houses: 18,622
People in refuges: About 360,000

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Death count will most probably exceed 20,000 which will be greater than myguess made in the first report, i.e. 15,000-20,000.
In the Fukushima No.1 Nuclear Power Plants, there are 6 reactors of which Nos. 4,
5 and 6 reactors were out of operation for regular checks at the time of theearthquake. Nos. 1, 2, and 3 reactors stopped automatically, but ECCS
(Emergency Core Cooling System) did not work for all of them,Hydrogen blast took place at No. 1 reactor on Saturday (March 12) followed byhydrogen blast at No. 3 reactor on Monday (March 14). Blast blew off reactors’
external containment structures which are supposed to be the last barrier. And, at
No. 2 reactor, reactor vessel was damaged on Tuesday (March 15). No. 4 reactor
is now facing a critical moment. No. 4 reactor was out of operation for regularchecks, but the earthquake knocked out electricity to the reactor needed tocirculate cooling water in the pool that temporarily stores spent nuclear fuel.
The critical point is whether or not the damaged reactors could be cooled down.
The Self-Defense Force and the Tokyo Fire Department are making their best, but
the condition of the Fukushima No, 1 nuclear power plant still do admit of nopresupposition. Whenever I hear Chief Cabinet Secretary say at press conference
that a certain amount of result has been achieved, I cannot stop feeling how empty
such an announcement is.
7. MARCH 21, 2011 (MONDAY)
This is the third day of three consecutive holidays. In Japan, Vernal Equinox Day
is a national holiday. I am tired of writing in my poor English what are taking
place here in Japan since the earthquake. So I decided on quoting headlines ofEnglish newspapers published in Japan. But, unfortunately, in a newsstand of thenearest local station, I was able to get only two, both dated March 21. One is The
Japan Times (JT), and the other THE NIKKEI WEEKLY (NW).
○ Death toll to exceed 15,000 in Miyagi alone: Police Chief (JT)○ Many children face trauma from disaster (JT)○ Pairs found in rubble in Ishinomaki (nine days after the earthquake) (JT)○ Evacuees want more water – to take baths (JT)○ Desperation tests crime taboo (JT)- Cases of looting emerge in areas hit by tsunami- Quake-hit stores in Miyagi hit by hundreds of thefts○ Old-style survival skills put local shop owners in disaster limelight – The panic
buying will subside as people start to realize no real shortages exist and that itis their own panicky hoarding that is creating the problem (Noriko Hama, JT)● Fight at Fukushima rages on – World watches as workers brave radiation in
frantic attempt to cool crippled nuke plant (NW)
● Electricity restored at reactor No. 2 (JT)● TEPCO faked Fukushima repairs – Revelation raises fresh questions overutility’s state ties, tainted past (JT)

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October
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Mai, Thailand● Foreign citizens, workers being told to return home (NW)
● Foreign media take flak for fanning fears (JT)● Short on gas, too close for comfort (although supplying gasoline for emergency
vehicles are made a top priority.) (NW)
● Power precious in greater Tokyo (NW)
● Rain may force TEPCO to cut power (JT)○ Maximum radiation levels in eastern Japan (JT)○ Tokyo radiation levels said not harmful (NW)
○ Latest threat: radiation-contaminated food (JT)○ Iodine from plant detected in Tokyo (JT)○ Radiation detected in U.S. Navy rescue crews (NW)
● Redirect budget outlays to quake relief measures (editorials, NW)● Post-quake risk to the economy (editorials, JT)● Quake shows how fear can choke stocks (NW)
● Promoting tourism (editorials, JT) : Promoting tourism constitutes a promisingavenue for moving beyond manufacturing in a new borderless world. However,“Man proposes, God disposes,” and it remains to be seen how serious a blow
the Tohoku-Kanto earthquake, tsunami and unfolding nuclear plant crisis havedealt to the new efforts.
● Effects of auto output suspension rippling through industry (NW)
● (Computer) Glitches at Mizuho (Bank) hold up wages (NW)
○ In long run, horrific disaster may push Japan toward better future – Because theyears of drift in Japan may be ending (because of the earthquake). If so, wewill look back at the great quake as the moment when the nation truly seized its
future (Japan Business Seminar by Michael Zielenziger, NW)○ “Ironmen of the North (Players from the Kamaishi Seawaves professional rugbyteam) use their mustles to help community (NW)
○ Former quake victims, even toilet experts offer evacuee tips (NW)
○ Twitter a good emergency response tool (NW)○ Helpful websites, and phone numbers (JT)○ Attention Steve Jobs: a few survival apps Japan needs (William Pesek,
Bloomberg, JT)○ Mahathir (a former prime minister of Malaysia) expresses condolences to Japan(JT)
8. MARCH 23 (TUESDAY)
This is the twelfth day since the earthquake. Life in Tokyo is back to almost
normal. Trains in commuting hours are as crowded as before. Bus routes
temporarily suspended due to shortage of gas supply were reopened, because
several of large oil refineries began operation. We do not have to queue up at gas
stations. (My daughter went yesterday evening to a gas station. But, when shecame home, she said that she filled only 20 litters, because she thought gas is
more badly needed in the stricken areas.) But, some of necessary daily stuff isstill difficult, not impossible, to get even in Tokyo, mainly because of the panic

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buying. According to my wife, among others, rice, eggs, toilet rolls are short. My
secretary’s sister had to line up before going to work at a super market to buy rice.
Prices of some food have gone up by 25%, 50%, or 100% in the worst case.
Cabbages, onions, and lettuces became 25% to 50% more expensive, and price of
milk at a super store almost doubled last weekend, according to my secretary. I
think even after panic buying and shop-owners selfish behavior will havesubsided, tendency for higher prices of food stuff will continue, because thehardest-hit Miyagi Pref. is one of the producers of a famous brand of rice, andFukushima Pref. and Ibaragi Pref. are known as agricultural and dairy farming
regions. In addition, most of the fishing ports in Iwate, Miyagi and Fukushima
Prefectures are reported to have received deadly blow by the Tsunamis.
It may be too early to summarize what were the points of special concern for the
March 11 Tsunami earthquake. I would like to do it at this moment in time, and,
therefore, the following are not intended to be complete at all.
First of all, the earthquake accompanied Tsunamis which in some places exceeded
10m in height. They arrived at northeastern shores of Tohoku region much earlier
than expected in disaster preparedness guidelines of municipal governments in theregion. They washed away and devastated small to medium-sized cities andtowns leaving thousands of casualties. Most of wooden Japanese houses could
not resist Tsunami flow once they floated on the water. If there were groundmotions alone, although they were quite strong, the death count must have beenless than 10% of the presently reported number. I may be wrong, but Tsunami
studies have so far focused on the simulation of propagation of Tsunamis over theoceans. Such studies are attractive to the laymen to look at, but academicians
should have paid more down-to-earth issues related Tsunami disasters.
Secondly, the hardship of displaced and survived people with respect to food,water, medicine, gas, and so on, have dragged on, much longer than manymunicipalities assumed in their disaster preparedness plans. Hardly-hit areas werealong the northeastern coast of Honshu island. Since the geographical features of
the northern part of Honshu are small flat lands sandwiched between mountainous
geography and the Pacific Ocean. The coastline is deeply indented, which
magnified the Tsunami height, and small municipalities are scattered along theshoreline. After the devastation by the Tsunamis, areas became almost impossible
to reach from the sea. The arterial highway runs north-south, and access roads
running east-west from the highway were heavily damaged. Tens of patients diedin hospitals because of lack of medicine, and several tens of elder people staying
in refuges also died because of insufficient heating at night there.
Thirdly, urban life was found so fragile even for a disaster that did not hit theregion. Of course, we should remember that many large companies stopped theiroperation because of power shortage and outage, and oil shortage. Buying panic,
selfish shop owners, rise and fall of stocks, these are all expressions and signs of
our sinfulness. When you encounter such a natural phenomena, you feel slightly
to have become a philosopher.

March 11, 2011,
TsunamiEarthquake
Japan -NineMarch
11, 2011,
TsunamiofEarthquakeof epistles
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Lastly, but very importantly, there are problems of reactor accidents. As to Nos. 1– 4 reactors in the Fukushima No. 1 nuclear power plant, situations seem to be
improving. External power supply was successfully obtained, and conditions ofreactors will be more accurately monitored. (I then wonder how accurate the past
information released at press conferences was!) This is only the first step. Most
recent news tells us that iodine was detected in the water ofTokyo, and bottled water has already been sold out in super stores. Onbalance I think I am an optimist, but in the case of the present nuclear accident (?),
I see calamity in every opportunity. Quoting from Robert Lowell, “If we see lightat the end of the tunnel it is the light of an oncoming train.” I only hope that our
train is running on the double track.
9. NINTH REPORT (MARCH 24, 2011)
This is my 9th report on my personal observations about the giant Tsunami
earthquake of March 11. I am going to at least temporarily stop writing the report.
“Nine” seems to be an appropriate number. A baseball game ends in the 9th
innings, unless the game is a tie. It is difficult to tell whether or not we havesuffered a complete defeat in this struggle against the Tsunamis. If I would find a
special reason to restart my report, I promise to e-mail it to you. I have to start
preparing for the lectures beginning in April.
Whenever I go home, I ask my wife, “Is there anything new at Fukushima?” In
the past several days, she answers, “Nothing particular.” Both of us fully knowthat many things are being done there, some with successes and the others with
failures.
Information is too much intricate. It often is extremely hard tofollow what is taking place in which particular reactor. As I wrote before, there
are six reactors, i.e. from No. 1 to No. 6, in the Fukushima No.1 Nuclear Power
Plant. Troubles are occurring in Nos. 1, 2, 3, and 4 reactors, but it is not easy tofollow in what condition each of them is at the most recent moment. There may
be many pieces of information available, but important pieces seem to be missing,or we just do not know how to put them into a picture of a jigsaw puzzle. We
then become more and more indifferent to this critical problem, only
sympathizing with the members of the Self-Defense Forces, and firefighters from
Tokyo and Yokohama who are forced to be engaged in the most dangerous work.
The aftershock of the power shortage will be of extreme significance foreverybody.
It is said that 2 to 3 years will be needed for TEPCO to recover to supply enoughpower. Although other companies will accommodate TEPCO, but the quantity
will be very limited, because the Kansai Electric Power Company, the second
biggest power company in Japan, supplies 60 Hz electricity whereas that in theeastern Japan is supplied with 50 Hz. TEPCO was badly affected, at least
financially, by the 2007 earthquake in the Kashiwazaki-Kariwa Nuclear Power
Plant facing the Japan Sea. Although the Nippon Bank has decided to make a big
urgent financial support, TEPCO will be having hard times in the future.

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Power shortage will have strong effects on Japan’s industry. This does not simply
mean that Japan’s industrial output will be affected, but those of neighboring
countries will be affected because there are many local subsidiary companies
assembling final products by using key parts produced in Japan.
The country will be financially affected to a great extent. It requires a hugeamount of money to recover and reconstruct the impacted areas. Japan’s financial
deficit which has already been evident in the global market will suffer a severeblow.
For ordinary people, some of the things for daily use will become more expensive
and be hard to get. The scheduled blackout will continue, and public transport
has to put up with partial services. Here, I remember what I wrote in my Report
No.1.: We all have enjoyed civilized, abundant, and bountiful life for a long time
because of electricity. If something should happen to us now, we would bepaying heavy compensation to what we have enjoyed in the past.
But all that I wrote above is dependent on the outcome of what is taking place inFukushima. Please keep your fingers crossed for us.
Thank you for having read my reports all the way to this “Thank you."March 11, 2011,
TsunamiEarthquake
Japan -NineMarch
11, 2011,
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Seismic vulnerability of low-rise, single
long span reinforced concrete buildings
Chayanon HANSAPINYO
chayanon@eng.cmu.ac.thAssistant Professor, Department of Civil Engineering,
Chiang Mai University, Thailand
ABSTRACT
Low-rise, single long span reinforced concrete building is among the mosttypical building configurations adopted in governmental school building in
Thailand. Without seismic consideration, the building configuration leads tosizing of high depth beams and slender columns. This paper describes
seismic venerability of the buildings by considering earthquake
performance of the existing buildings located near the Thai-Myanmar
border which were recently hit by the M6.8 earthquake at Shan State,
Myanmar. In addition, evaluation of seismic performance using nonlinear
pushover analysis of a typical three story school building is presented. The
analyzed building has 9.4 m. single span length with 3.4, 3.4 and 3.0 m.
high for the first, second and third stories, respectively. Dimension ofcolumns is 0.30 by 0.40 m. and beam spanning between the two columns is0.25 by 0.80 m. From the earthquake event, severe cracks in columns andbeam-column joints could be observed on the existing buildings. From theanalysis, the maximum base shear coefficient is 8.67% which is less than thedesign value. In addition, the results show the weak column behavior of thetypical school building. Collapse of the analyzed school building is initiatedby yielding at two ends of the columns. The ultimate roof drift ratio is about
1.11% and the roof drift ductility ratio is 2.92. The ratios demonstrate theirreparable and non-ductile behavior. Hence, both evidences indicate
seismic vulnerable and the need for strengthening of the building.
Keywords: seismic evaluation, low-rise, single long span, Myanmar
earthquake, pushover analysis
1. INTRODUCTION
The demand of large open area at the first floor of school building leads to
low-rise single long span reinforced concrete building configuration. The
building model has long been accepted for a standard drawing utilized
widely in construction of governmental school in Thailand. Without seismic
consideration, before the enforcement of the seismic design law in the yearof 1997, the long span beams are heavily loaded under gravity moment andthen detailed with large depth. The depth of the beam is in the range of 0.81.0 m. for about 9-12 m. span length between two edge supporting columns.
In contrary, the reinforced concrete columns may be subjected to a light7111

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axial load. The dimension of the section can be only about 0.3 by 0.4 m.
Hence, the column size is much smaller compared with that of the beams.
This results to the weak column-strong beam behavior which is undesirable
for earthquake resisting structural system.
It has long been considered that Thailand is a zone with no effect fromthe earthquake risk. However, many past earthquakes have shown a certain
level of the attack in the Northern and Western regions. Many researches,for example Lukkunaprasit and Kuhatasanadeekul (1993) and Warnitchaiand Lisantono (1996), have indicated the peak rock acceleration to beapproximately 0.17g with a 10% probability of exceedance in 50 years. In
this intensity of earthquake, seismic vulnerable buildings have highpotential to be severely damaged.
This paper describes seismic vulnerability of the low-rise single longspan reinforced concrete buildings by considering earthquake performanceof the existing buildings located at Mae Sai near the Thai-Myanmar borderwhich were recently hit by the 6.8 earthquake at Shan State, Myanmar. The
distance from the epicenter to the area is about 35 km. In addition,
evaluation of seismic performance using nonlinear pushover analysis of atypical three story school building is presented. Both evidences consistently
indicate seismic vulnerable and the need for strengthening of the building.
2. EARTHQUAKE RESPONSE OF EXISTING LOW-RISE SINGLELONG SPAN BUILDINGS
2.1 Myanmar-Thailand border M6.8 earthquake event
Although, geological structure has shown many active faults in thezone, there have not been large earthquake records since 1912. Until theevening of March 24, 2011, a violent earthquake was originated by the Nam
Ma fault. USGS reported the magnitude of 6.8 while it was about 7.2
informed by local seismological agencies in China. The focal depth wasestimated about 20 km. Figure 1 shows location and intensity of theearthquake event. The United Nations Office for the Coordination of
Humanitarian Affairs (OCHA) reported number of casualties to 73 deaths
and 125 injuries. 224 houses, 11 monasteries, 11 official buildings weredamaged in Tarlay.
People living in the northern parts of Thailand, next to the Myanmar
border, could feel nausea. Persons staying in high rise building in Bangkok
which is 772 km southern away also got the shaking sense. Also, the tremor
could be detected at the area close to the center e.g. Northern parts of Laos,
Vietnam and Southern part of China. The most affected area in Thailand is
Mae Sai in Chiang Rai province. From figure 1, the estimated potential
damage is about light to moderate level with the peak ground acceleration
about 0.18 g.

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2.2 Damage of the existing low-rise single long span reinforced concretebuildings
Under the earthquake event, survey for damage information in
Northern parts of Thailand was performed especially in Mae Sai, Chiang
Rai Province. It is the most interesting zone not only because the area isvery close to the epicenter, but also it is a major trading area crossing theThailand-Myanmar border. The Mae Sai municipal covers an area of 5.13
km square. Most of the area is used for residential and commercial purposes.
There are about 860 commercial building blocks and more than 13 hotels.
The recent population is 19,443. Due to the earthquake, the survey founddamages in both structural and nonstructural parts of buildings in the area.
However, the present work focuses on the examination of school buildings
which are the low rise-single long span reinforced concrete buildings.

Figure 1: Location and intensity of the Myanmar March 24 M 6.8
earthquake (USGS)

Seismic vulnerability
Seismic
vulnerability ofof low-rise,
low-rise, single
singlelong
longspan
spanreinforced
reinforcedconcrete
concretebuildings
buildings

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Figures 2 and 3 show the low rise-single long span reinforced concrete
school buildings in the area. The former shows a three-story building which
was built more than 50 years ago. The latter is a four-story building which isabout 10 years old. The buildings will be hereinafter called buildings “A”
and “B”, respectively. The plan of the two buildings is rectangular shape. It
is single span in one direction and multiple spans in the other perpendicular
direction. The single span length is about 9-10 m. This large span length
makes the spanned beam with about 0.8 m in depth. However, the two edge
supporting columns are much smaller with the cross sectional dimension of
0.3 by 0.4 m. The height of the stories is about 3.5 m.
From the structural damage examination, severe upper end column
cracks could be found in building “A”, especially at the first floor cornercolumn. There were no cracks on other structural members. Only cracks on
the beam plaster could also be observed. For nonstructural components,
unreinforced masonry walls were cracked diagonally. In addition, roofing
material which is cement based panel, was cracked and failed down.
Substructure supporting the roof materials made of light gage steel truss wasbuckled.
For the building “B”, crack around the upper end of the first floor
columns could be seen. However, the crack width was smaller compared tothose of building “A”. This is due to the more recent of construction timewith higher material quality and better standard of practice. Unreinforced
masonry walls were also severely damaged in diagonal crack form showing
highly distorted of the frame structure.

Crack(a) Side View(c) Crack in first floor(viewed from inside)(b) Front view
Figure 2: Damage investigation of the three-story school building

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Crack Crack
Crack Crack(a) Side(a)view
Side view(b) Crack(b) Crackat upperat upperend ofend
the offirst
thefloor
firstcolumn
floor column
FigureFigure
3: Damage
3: Damageinvestigation
investigationof four-storyof four-story
schoolschoolbuildingbuilding
3. PUSHOVER
3. PUSHOVER
ANALYSISANALYSIS
To evaluate
To evaluate
seismic
seismic
capacity
capacityof existingof existingbuildings,
buildings,
nonlinear
nonlinearanalysisanalysisisisneededneeded
to traceto cracking
trace cracking
and yielding
and yielding
phenomena
phenomenaof reinforcedof reinforced
concreteconcreteelements.
elements.
Fibre-based
Fibre-based
finite finite
element
element
programprogramcalledcalled
SeismoStruct
SeismoStruct(SeismoSoft,(SeismoSoft,2010) 2010)
was employed
was employedin thisin study.
this study.
The program
The program
contains
contains
computational
computational
schemeschemecapablecapableof predictingof predicting
the large
the displacement
large displacement
behavior
behaviorof framesof frames
under under
static staticor dynamicor dynamic
loading,loading,takingtaking
into accountinto accountboth bothgeometric
geometric
nonlinearities
nonlinearities
and material
and material
inelasticity.
inelasticity.
The soThecalled
so called“Static“Static
pushoverpushoveranalysis”
analysis”
recommended
recommended
by FEMA-356
by FEMA-356(2000)(2000)
and ATC-40
and ATC-40(1996)(1996)
guidelines
guidelines
was adopted
was adopted
in theininvestigation.
the investigation.
It is aIt method
is a method
for forestimating
estimating
the strength
the strength
capacity
capacityof buildingof building
represented
represented
in form
in ofform
lateralof lateralcapacity
capacityand drift.
and drift.
This procedure
This procedure
appliesapplies
a laterala lateralload patternload patternthat isthat is
distributed
distributed
along along
the building
the buildingheight.height.
The lateral
The lateralforcesforces
are thenare thenincrementally
incrementally
increased
increased
to reachto reacha displacement
a displacement
controlcontrol
at the attop
theoftop
theof thebuildingbuilding
representing
representing
the twothefigures
two figures
as the as
Capacity
the Capacity
curve.curve.
3.1 A 3.1
caseAstudy
case study
The representative
The representativebuildingbuilding
used inused
thisinnonlinear
this nonlinear
pushoverpushoveranalysisanalysisisisa typical
a typical
schoolschoolbuildingbuilding
modelmodel
under under
the Ministry
the Ministryof Educationof Educationof Thailand.
of Thailand.
The building
The building
modelmodel
has been
has been
widelywidelyadoptedadoptedin theincountry
the country
includingincludingschools
schoolsin the inseismic
the seismic
risk areariskandareaalso
andChiang
also Chiang
Mai city.
MaiThecity.building
The building
is a is athree-story
three-story
concreteconcreteframe framewith unreinforced
with unreinforced
masonry
masonry
infilledinfilledbuildingbuilding
whichwhich
is classified
is classified
as C3 as
type.
C3 As
type.
shown
As shown
in Figurein Figure4, the 4,building
the building
floor plan
floor planis narrowis narrowrectangular
rectangularshape shapewith 9.4
withm 9.4
singlem single
span inspanx direction
in x direction
and 56andm 56 mwith 14withequal
14 equalspans spansin y direction.
in y direction.
The story
The heightstory heightis 3.4 is
m.3.4
Them.thickness
The thicknessof concreteof concreteslab isslab
0.1 ism.0.1
Them.lateral
The lateralresistingresistingsystemsystem
is provided
is provided
by generalby generalmoment-resisting
moment-resisting
frame frame
systemsystemwith thewithcontribution
the contributionof brickof infilled
brick infilledwalls. walls.
However,
However,in thisinstudy
this thestudy
effectthe effectof the of
infilled
the infilled
SeismicSeismic
vulnerabilityof low-rise,
single longspan
reinforced
concretebuildings
Seismic
vulnerabilityofsinglelongspanconcretebuildings
vulnerabilityof low-rise,
low-rise,singlelongspanreinforced
reinforced
concretebuildings

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Chiangmai,(a) Side view

Analyzed 2D frame
2.4m 3@2.33 = 7 m.

Col

B9
Col
14@4 m = 56 m(b) Typical Floor Plan
Figure 4: The representative school building
25 cm
3 - φ 25 mm

6 - φ 25 mm

Stirrups
2-6 mm@0.20 m

Stirrups
2-6 mm@0.20 m

80 cm

80 cm

25 cm

9 - φ 25 mm

6 - φ 25 mm(a) Beam B9(midspan)(b) Beam B9(endspan)
40 cm
6 - φ 19 mm
C2-3

3.4 m

C2-3

30 cm

B9

(c) Column C2-3

B98 - φ 19 mm
30 cm

B9

40 cm

3.4 m

C1-2

C1-2

Stirrups
2-6 mm@0.20 m

Stirrups
2-6 mm@0.20 m

9.4 m(e) School building frame(d) Column C1-2

Figure 5: Analysed two dimensional frame

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wall waswallneglected.
was neglected.
FigureFigure
5 shows
5 shows
the structural
the structural
frameframein theinanalysis.
the analysis.
It is It isnotednotedthat thethatroof
the story
roof story
was ignored
was ignoredin theinstudy
the study
due todue
thetolessthe rigidity
less rigidity
comparedcompared
to otherto otherstories.
stories.
FromFrom
the figure,the figure,it canit be
canobvious
be obviousthat thethat thecolumns
columns
are quiteare quite
smallsmall
comparedcomparedto thetosupported
the supported
beams.
beams.
The calculation
The calculation
for bending
for bending
capacity
capacityof theofbeams
the beams
and columns
and columns
at joint
at interfaces
joint interfaces
are shownare shownin Tablein Table
1 showing
1 showingmuchmuchlowerlower
columns
columns
bendingbending
capacity
capacity
comparedcompared
to tothosethoseof theofbeams.
the beams.
TableTable
1: Bending
1: Bending
capacity
capacityof beamsof beams
and columns
and columns
at joint
at interfaces
joint interfaces
Ultimate
Ultimate
Bending
Bending
capacity(kN-m)
capacity(kN-m)
ColumnColumnabove above
Columnabove aboveColumn
Beam Beamjoint joint
joint joint(MB) (MB)(MC2) (MC2)(MC1) (MC1)
84
84
84
84
690 69084
84
84
84
690 69084
84
690 690

Joint Joint
J1
J2
J3

J1
J2
J3

ΣMC/ΣMΣMBC/ΣMB
0.24 0.24
0.24 0.24
0.12 0.12

3.2Fibre
3.2Fibre
Material
Material
modelsmodels
The fibre-based
The fibre-based
approachapproachdiscretizes
discretizes
cross-section
cross-sectionof elementof element
into into
smallsmall
fibre fibre
wherewhere
each eachfibre fibreis associatedis associatedwith witha uniaxial
a uniaxial
stress-strainstress-strain
relationshiprelationshipfor either
for either
unconfined
unconfinedconcreteconcreteor confinedor confinedconcreteconcreteor steelor steelreinforcement,
reinforcement,
as seenas in
seen
Figurein Figure6. Hence,
6. Hence,
materialmaterial
inelasticity
inelasticity
can becan
easilybe easily
implemented.
implemented.
Then,Then,the sectional
the sectional
stress-strainstress-strainstate stateof beam-columnof beam-column
elements
elements
is obtained
is obtained
throughthroughthe integration
the integrationof theof uniaxial
the uniaxial
stress-strainstress-strain
response
responseof theofindividual
the individual
fibres.fibres.
BasedBasedon theoncomputational
the computational
scheme,scheme,the thefibre fibremodelmodel
has more
has moreadvantages
advantages
in relationin relation
to thetosimpler
the simpler
lumped-plasticity
lumped-plasticity
modelsmodelsthat distributedthat distributed
inelasticity
inelasticity
elements
elements
can becangenerally
be generally
used usedwithout
without
predefining
predefining
concentrated-plasticity
concentrated-plasticity
section.In
section.In
addition,
addition,
the spreadthe spreadof ofinelasticity
inelasticity
alongalong
the member
the member
lengthlengthand acrossand acrossthe section
the section
depthdepth
is isexplicitly
explicitly
modelled.
modelled.
Uniaxial
Uniaxial
compressive
compressive
strengths
strengthsof concreteof concreteis 24 isMPa.
24 MPa.
The expected
The expected
yield yieldstrength
strengthof steelof steelbar gradedbar graded
SR24SR24
is 348is MPa.
348 MPa.
whichwhichwere wereused used
for forboth both
longitudinallongitudinal
reinforcement
reinforcement
and stirrup.
and stirrup.
The constitutive
The constitutive
modelsmodelsare areshownshownin Figurein Figure
7. 7.
yCore ConcreteCore Concrete(confined)(confined)
y

y
x

z

y

z

x

z

z

Steel bars
Steel bars

Gauss Gausssectionsection
Cover Concrete
Cover Concrete(unconfined)(unconfined)

FigureFigure6: Discretization
6: Discretizationof crossof cross
sectionsectioninto small
into small
fibersfibers

Seismic
vulnerabilityof low-rise,
singlesingle
long span
concretebuildings
Seismic
vulnerability
of
long
span
concretebuildings
Seismic
vulnerabilityof low-rise,
low-rise,singlelongreinforced
spanreinforced
reinforced
concretebuildings

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Strain-0.016 -0.012 -0.008

Stress (MPa)-0.004

300

-4

200

-8

100

-12
-16
-20

Compression-24

Tension-0.008-0.004Compression

-100

0.004

Strain
0.008

-200
-300

Stress(MPa)(a) Confined concrete(b) Reinforcement

Figure 7: Uniaxial stress-strain relationships
4. RESULTS
Figure 8(a) shows the capacity curve of the typical school building withmaximum base
base shear
shearcoefficient
coefficient(C(C) of
8.67%.
the ultimate
roof
) of
8.67%.
andandthe ultimate
roof drift
smax
smax
drift
theratio
drift atratio
the maximum
baseby thebydrift
85%atof85%
the ofmaximumbase shear,ratio ratio(RDR(RDRult ), definedult), defined
shear,
of 1.11%.
ratio isthe ratioof lateralof 1.11%.
The roofThedriftroof
ratiodrift
is definedas defined
the ratio asof lateraldisplacement
displacementat (Δ)
the tothird
floor (�)to floor
the heightof coefficientthe floor (H).
The
at the third floor
the heightof the(H). The
indicates
coefficientindicates
the needfor upgradingwiththe calculated
the need for
upgradingas comparedwith asthecomparedcalculated
equivalent
baseequivalentbase shear
coefficientof 13.07%
to the for
Thaiearthquake
Standard
shear coefficientof 13.07%
accordingto theaccording
Thai Standard
forearthquake
designin 2009).
the area2009).
In addition,
the
RDR
is
designin the area
(DPT,
In (DPT,
addition,
the RDR
is
lower
than
2%
ult ofult
lower
2%building.
of ductileTheframe
The roof
ductility
ratio (µductilethanframe
roofbuilding.
drift ductility
ratiodrift(µRDR), expressed
asRDR
the),
expressed
as-to-RDR
the ratioyldRDR-to-RDR(see
figure8(a)),
is2.92.
Figure8(b)(seeultfigure8(a)),
is2.92.
Figure8(b)represents
theratio RDRultyld
represents
the ofdamagelevel ofcorresponding
the building corresponding
level ofthedamage level
the building
to the level of tothethepushingforce
pushing
in whichdamages areconcentrated
at buildingcolumns.
in whichforce
the damages
aretheconcentrated
at buildingcolumns.
The progressiveThe
progressive
damagesstartsyieldingof allends andthenof damages
startsofwith
yieldingof withall column
ends
andcolumn
then further
increase
furtherincreasefailurethe first story columns.
to severefailure toofsevere
the first
story ofcolumns.
As seen in Figure 8(b), the story drift ratios are indicated by numbers
in parenthesis. Referred to the FEMA 273 (1996), within load intensity [2]with the ratio less than 0.5%, the damage is in range of repairable. Between[2] to [3] stages, the damage level is too severe to be repaired. Eventually,
after the [4] stage, complete collapse is identified when the ratio is morethan 2.5%.
5. CONCLUSION
This paper presents the seismic vulnerability of Low-rise, single long span
reinforced concrete buildings. The building model is among the most typicalbuilding configurations adopted in governmental school in Thailand. The
study was performed by considering earthquake performance of theexisting buildings

8
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Initial stiffness

Csmax

[3]

0.85Csmax
[4]

[2]

[1]
[5]

RDRyldRDRult(a) Capacity curve(0.07)(0.20)(0.69)(0.04)(0.11)(0.72)[1][2](0.67)(0.46)(2.24)(8.26)[4][3]= Yield= Immediate Occupancy= Life Safety= Collapse Prevention[5]= Failure(b) Yield and failure mechanism with story drift ratio (in parenthesis)
Figure 8: Capacity curve and failure mechanism
located near the Thai-Myanmar border which were recently hit by the M6.8
earthquake at Shan State, Myanmar. In addition, evaluation of seismic
performance using nonlinear pushover analysis of a typical three story
school building is presented. The two results consistently indicate the weakcolumn behavior. From the analysis, collapse of building can be observedwith low ductility. Hence, both evidences indicate seismic vulnerable andthe need for strengthening of the building.
ACKNOWLEDGMENT
The author wishes to acknowledge the Thailand's Office of the Higher
Education Commission under the National Research University Project for
financial support.
Seismic vulnerability
Seismic
vulnerability ofof low-rise,
low-rise, single
singlelong
longspan
spanreinforced
reinforcedconcrete
concretebuildings
buildings

9719

October 2011, Chiang
Mai,Thailand
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REFERENCES
Applied Technology Council-ATC., 1996.Seismic Evaluation andRetrofit of Concrete Buildings (ATC-40), Redwood City, California, USA.
Department of Public Works and Town & Country Planning-DPT.,
2009. 1302-Design Standard for Earthquake Resistant Buildings, Bangkok,
Thailand.
Federal Emergency Management Agency-FEMA. 1996, NEHRP
Guidelines for the Seismic Rehabilitation Buildings (FEMA 273),
Washington, D.C., USA.
Federal Emergency Management Agency-FEMA., 2000. Prestandard
and Commentary for the Seismic Rehabilitation of Buildings (FEMA 356),
Washington, D.C., USA.
Lukkunaprasit, P., and Kuhatasanadeekul, N., 1993. Seismic zoning
and seismic coefficients for Thailand.1993 Annual Conference, Engineering
Institute of Thailand, pp. 268-287.
SeismoSoft, 2010. SeismoStruct - A Computer Program for Static andDynamic Nonlinear Analysis of Framed Structures [on line], available from
URL: http//www.seismosoft.com (June 30, 2010).
Warnitchai, P., and Lisantono, A., 1996. Probabilistic seismic risk
mapping fors Thailand. 11thWorld Conference on Earthquake Engineering,
Acapulco, Mexico

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NewA simple and effective seismic retrofit
scheme for masonry-infilled non-ductile
reinforced concrete frames
1

Panitan LUKKUNAPRASIT1 and Jarun SRECHAI2
Professor, Department of Civil Eng., Chulalongkorn University, Thailand
panitan.l@chula.ac.th
2Doctoral Student, Department of Civil Eng.,
Chulalongkorn University, Thailand

ABSTRACT
A simple and effective scheme has been developed for retrofitting masonryinfilled non ductile RC frames. Three ¾ scaled models of single bay, single
story non-ductile RC frames with infilled un-reinforced masonry (URM)
were tested under horizontal cyclic loading and a constant vertical load of
20% the ultimate capacity of the column based on the concrete grosssection. The unretrofitted specimen suffered corner crushing and abrupt
shear failure in the columns at a very small drift of 0.25%. The specimen
was retrofitted by separating the masonry panel from the vertical columns
so that no shear was transferred to them, eliminating totally shear failurecaused by the strut forces from the masonry. Steel brackets were provided
to transfer the interactive horizontal forces between the RC frame and themasonry panel. With the URM panel separated from the RC frame such thatthe panel width is reduced by 20%, the drift capacity is increased 6 fold,with desirable gradual drop in capacity. The last specimen with the wall
aspect ratio of 1.0 could sustain a drift of 1.75% at 20% drop in strength.
Keywords: masonry infill, retrofitting, reinforced concrete frame, cyclicload, non-ductile
1. INTRODUCTION
Reinforced concrete (RC) frame buildings with un-reinforced masonry(URM) infill panels are prevalent in Thailand as well as developing
countries. Earthquake reconnaissance in past earthquakes in high seismic
prone countries has witnessed poor performance of such structural systems
especially when the RC frames are detailed as non-ductile. Undesirable
abrupt shear failure of the bounding columns or beam-column joints often
follows due to transfer of the huge strut forces resisted by the infill to thecolumns. This is true not only in strong earthquakes, but also in moderateshaking such as that in Chiang-Rai caused by the March 24 2011 M6.8
Myanmar earthquake near Chiang-Rai border. Model tests as well as fullscale tests on real buildings have also yielded similar results (Mehrabi et al.
1996, Korkmaz, et al. 2010, Corte et al. 2008). It is important to note that7211

October 2011, Chiang
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such failure can occur at a relatively small drift ratio, in the order of 0.5%.
On the other hand, there have been incidents of actual performance of suchbuildings in earthquakes (L’Aquilla earthquake, Hassan and Sozen 1997)
which demonstrate beneficial effect of un-reinforced infills. Laboratory tests
with masonry reinforced with wire mesh or the like have also demonstrated
the potential of transforming the brittle masonry panels to a more ductile
one suitable for retrofitting. However, past attempts have accomplishedlimited success. Since infills are cheap building materials for constructing
non-structural partitions, it would be economical and beneficial if they could
be utilized to contribute to earthquake resistance, either in new construction
or in retrofit work. To this end, it is necessary to invent a reliable means
which can reduce the drawbacks of un-reinforced masonry infill in its
interaction with RC frames.
2. RETROFIT SCHEME
In order to be able to effectively utilize the masonry walls for seismic
resistance, one has to address and minimize the following major problems:a) shear failure of the (non-ductile) RC columns and /or beam-column
joints;b) crushing of the corners of the infill;c) sliding of horizontal bed joints in the infill, including the masonrybeam interfaces.
All these modes of failure lead to relatively low ductility capacity ofthe structural system. Guided by failure mechanisms observed in theliterature, the following innovative scheme (depicted in the diagram Figure1) is adopted for resolving weaknesses in non-ductile infilled URM RC
frame:a) The retrofitted masonry is separated from the vertical columns so thatno shear is transferred to them, eliminating totally the shear failurecaused by the strut forces from the masonry;b) Steel brackets are provided to transfer the interactive horizontal
forces between the RC frame and the masonry panel;c) Small vertical steel members (or other equivalent components) areanchored to the vertical boundaries of masonry infill to prevent sliding
joint failure. The steel members are not anchored to the surrounding
beams to minimize tension that would otherwise be induced in the infill.
d) The corners of the infill are reinforced with wire meshes and highstrength mortar.

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Figure 1: Retrofit scheme of URM infilled RC frame.

3. TEST SPECIMENSIn this study, three ¾ scaled models of single bay, single story non-ductile
RC frames with infilled non-reinforced masonry (URM) were tested underhorizontal cyclic loading and a constant vertical load of 20% the ultimate
capacity of the columns based on the concrete gross section. Specimen
MIRCF01 was original unretrofited that had panel aspect ratio(width/height) 2.0. Specimens MIRCF02 and MIRCF04 were retrofittedwith the scheme proposed above.
4. EXPERIMENTAL RESULTS AND DISCUSSION
Figure 2 depicts Specimen MIRCF01 with shear cracks in RC columns andbeam-column joints, and corner crushing of the masonry infill. As
mentioned earlier, the RC frame was non-ductile, and the clay tile panel was
un-reinforced. This frame assembly attained peak load of around 30 tons at
0.25% drift, after which the load suddenly dropped to less than 40% at 0.5%
drift only as illustrated in the hysteretic loop in Figure 3.

Figure 2: Un-reinforced masonry infilled non-ductile with column shear
failure and corner panel crushing at 0.25% drift
A simple and effective seismic retrofit scheme for masonry-infilled non-ductile
A simple and effective seismic retrofit scheme for masonry-infilled non-ductile reinforced concrete frames7233
reinforced concrete framesOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,
35
30
25
20

Lateral Load (Ton)

15
10
5
0
-5
-10
-15
-20
-25
-30
-35
-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Story Drift (%)

Figure 3: Hysteresis Loop of Specimen MIRCF01

Specimen MIRCF02 has demonstrated remarkable improvement in
performance over the original system, with the drift capacity of 1.5%
achieved at a sustainable lateral load of 80% the peak capacity and a gradualdrop of load capacity (see Figure 5). It should be noted that at 2.0% story
drift, although the URM panel suffered severe damage, only small shearand flexural-cracks occurred in the RC columns (Figure 4).

Figure 4: Retrofitted masonry-infilled RC frame (MIRCF02) with theinnovative scheme at 2% drift (test terminated for safety reason)
35
30
25
20

Lateral Load (Ton)

15
10
5
0
-5
-10
-15
-20
-25
-30
-35
-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Story Drift (%)

Figure 5: Hysteretic loop of specimen MIRCF02
Specimen MIRCF04 with the wall aspect ratio of 1.0 could sustain adrift of 1.75% at 20% drop in strength (see Figure 6-7). At a drift of 2.5%,

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spalling of concrete and longitudinal steel buckling can be observed in thecolumn near the beam-column joint. Significant rocking of the panel
occurred and a major diagonal tension crack cut through the masonry infill(Figure 6).

Figure 6: Retrofitted masonry-infilled RC frame (MIRCF04) with theinnovative scheme at 2.5% drift (test terminated for safety reason)
35

25

Lateral Load (ton)

15

5

-5

-15

-25

-35
-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Story drift (%)

Figure 7: Hysteretic loop of specimen MIRCF04
It is interesting to compare the performance of the proposed retrofit
scheme with others in the literature. As evident in Table 1, past retrofit
schemes using heavy external mesh reinforcement with plaster composite
achieved the best drift capacity of only 1.69 % at 20% drop in peak capacity(Korkmaz et al. 2010), while the best from carbon fiber reinforced polymer
retrofit was 1.7% (Yuksel et al. 2010). The retrofit method presented is low
cost and does not have any mesh or carbon fiber reinforcement, and yet it
could attain a drift capacity of 1.5-1.75 % at 20% drop in peak capacity.
With reinforcement applied to the masonry panel, better performance isanticipated.

A simple and effective seismic retrofit scheme for masonry-infilled non-ductile
A simple and effective seismic retrofit scheme for masonry-infilled non-ductile reinforced concrete frames7255
reinforced concrete framesOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table 1: Comparison of different retrofit schemesNo.

Samples by

Masonry
panel W/H

1

Kyriakides et al.
(2008) et al.

1.79

Drift @ 20%
drop incapacity
1.2%

2

Korkmaz et al.
(2010)

1.63

1.19-1.69%

3

Acun andSucuoglu (2006)
Altin et al. (2008)

1.72

0.75% to 1.1%

1.73

1.0%

1.17

1.0% to 1.7%.

2.00

0.25%

1.60

1.50 %

1.00

1.75%

4
5
6
7
8

Yuksel et al.
(2010)
This research
MIRCF01 (2011)
This research
MIRCF02 (2011)
This research
MIRCF04(2011)

Remarksprayable ductile cementbased composites and weldedwire fabricheavy external meshreinforcement with plastercomposite
external mesh reinforcement
carbon fiber reinforced
polymer; CFRP ruptured
various configurations of
CFRP
Un-reinforced panel
Separated panel, load transfer
bracket, corner strengthening
Separated panel, load transfer
bracket, corner strengthening

CONCLUDING REMARKSThe innovations presented seem to be promising judging from thesatisfactory performance of the test specimens in the laboratory. Of course,
the practicality and the effectiveness of the schemes over a wide range ofapplications are subject to further extensive investigations.
ACKNOWLEGEMENTS
The authors are grateful for the funding from the Commission on Higher
Education of Thailand, AUN/SEED-Net, and grant No. CA2/2553 fromFaculty of Engineering, Burapha University, Thailand. The assistance of
Building 33 Company Limited in casting the test specimens is greatly
appreciated.
REFERENCES
Acun B., and Sucuoglu H., 2006. Strengthening of Masonry Infill
Walls in Reinforced Concrete Frames with Wire Mesh Reinforcement.
Proceedings of the 8th U.S. National Conference on Earthquake
Engineering, San Francisco, California, USA, paper No. 1852.
Altin S., Anil OZR M., Emin Kara, and Mustafa Kaya, 2008. An
experimental study on strengthening of masonry infilled RC frames using
diagonal CFRP strips, Composites: Part B 39 680–693.
Kyriakides MA., and Billington SL., 2008. Seismic retrofit ofmasonry-infilled non-ductile reinforced concrete frames using sprayable

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ductile fiber-reinforced cementitious composites. Proceedings 14th World
Conf. on Earthquake Eng., Beijing. Paper Number 05-04-0063.
Yuksel E., Ozkaynak H., Buyukozturk O., Yalcin C., Dindar AA.,
Surmeli M., and Tastan D., 2010. Performance of alternative CFRP
retrofitting schemes used in infilled RC frames. Construction and Building
Materials 24 596-609.
Corte DC., Fiorino L., Mazzolani FM., 2008. Lateral-loading tests ona real RC building including masonry infill panels with and without FRP
strengthening. J Mater Civil Eng, ASCE; 20(6):419_ 31.
Hassan AF., and Sozen MA., 1997. Seismic vulnerability assessmentof low-rise buildings in regions with infrequent earthquakes. ACI Struct J;
94(1):31_9.
Korkmaz SZ., Kamanli M., Korkmaz HH., Donduren MS.,and Cogurcu MT., 2010. Experimental study on the behavior of nonductile
infilled RC frames strengthened with external mesh reinforcement andplaster composite, Nat. Hazards Earth Syst. Sci.; 10:2305-2316.
Mehrabi AB., Shing PB., Schuller MP., and Noland JL., 1996.
Experimental evaluation of masonry-infilled RC frames. J Struct Eng(ASCE); 122(3):228_37.

A simple and effective seismic retrofit scheme for masonry-infilled non-ductile
A simple and effective seismic retrofit scheme for masonry-infilled non-ductile reinforced concrete frames7277
reinforced concrete framesOctober 2011, Chiang Mai, Thailand

728

New Technologies for Urban Safety of Mega Cities in Asia

Evaluation model of the five story
horizontally-mixed hybrid timber structure
Mengting TSAI1 and Mikio KOSHIHARA2
Doctoral Student, Department of Architecture,
Faculty of Engineering, the University of Tokyo, Japantsai@iis.u-tokyo.ac.jp
2
Associate Professor, ICUS, Institute of Industrial Science,
The University of Tokyo, Japan
1

ABSTRACTThe primary objective of this study is to understand the vibration behavior
and the force distribution under seismic loading of the five storey
horizontally-mixed hybrid timber structure, which has been constructed in a
shrunk one third scale model and was tested in 2006, in order to find out aproper static evaluation model based on the building code in Japan. The
proposed static evaluation model examined how the seismic loading
suffered in timber part transmit to the core part, which is constructed bysteel, through the floor system and connector. Furthermore, thedisplacement relationship between timber part and core part of each floor
under seismic loading will also be calculated. In addition, the comparisonof the analysis results between experimental study, static model and result
from structural analysis program will also be discussed. This paper gives anoverall view of the static evaluation of the horizontally-mixed hybrid timber
structure, and with the confirming required knowledge of this kind of
structural systems, the enhanced performance and improvement of the midrise hybrid timber structural system will also be expected.
Keywords: horizontally-mixed hybrid timber structure, force distribution,
seismic loading, static evaluation model
1. INTRODUCTION
The mid-rise or high-rise timber buildings higher than 4 storey require atleast two hours fire resistance ability based on the building code in Japan.
Nowadays, the latest fire resistance technology of the timber structure canonly last for one hour. In order to fit the requirement and study thefeasibility of the mid-rise or high-rise timber buildings, the horizontallymixed hybrid timber structure which were constructed by timber pare andnon-timber part (steel) was designed in a shrunk one third scale model(shown in figure 1) and was tested in 2006.
The primary objective of this study is to understand the vibration
behavior and the force distribution under seismic loading of the five storey
horizontally-mixed hybrid timber structure in order to create a proper7291

October 2011, Chiang
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Chiangmai,

evaluation system including establish of the static and the dynamic analysis
model based on the building code in Japan. In addition, the parameterstudies of the stiffness of the timber floor are also studied in order tounderstand the efficient of the force transmit between timber part and steel
part.
RF
5F
4F
3F
2F
Y13
Y09

X01

X05

Y05
Y01

X09

Seismic loading

Figure 1: The experimental specimen (left) and the axis (right)
2. THE ESTABLISH OF THE STATIC EVALUATION MODEL
To establish the static evaluation model contains two steps. The first step is
to find the value of the storey shear coefficient Ai, the distribution of theseismic force at each storey. After the value of Ai is obtained, the required
seismic shear force Qei in each joint of each storey can be calculated as well.
Figure 2 shows how Ai will distribute in the modified building model(Figure 2 left) and the distribution of the required seismic shear force Qei(Figure 2 right) after Ai is determined.
Ai-Y13

Qe 13

Ai-Y9

Qe 9

Ai-Y5

Qe 5

Ai-Y1

Qe 1

Y13
X01

Y09
X05

Y05
X09

Y01

Y13
X01

Y09
X05

Y05
X09

Y01

Figure 2: The model of Ai distribution (left) and required shear force Qei(right)2.1 The Ai distribution
Based on the seismic design code in Japan, the Ai distribution is oneof the factors used to generate the seismic force instead of inverted

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triangular loading distribution that is used in North American. The equation(1) shows how the value of Ai can be calculated,T⎛ 1⎞
Ai = 1+ ⎜− ai⎟ × 2 ×
1+ 3T
⎝ ai
⎠
5
5
(1)
ai = ∑Wn ∑Wn
n=in=1
where i = storey number, Wn = weight of storey n, ai = weight ratio atstorey i,
T = primary natural period according to T=0.03h.

2.2 The calculation of the required seismic shear force Qei
Once the storey shear coefficient Ai is determined, the seismic shear
force Qei at each joint of each storey can also be calculated by following
equation,
5

Qei = Ci× ∑ Wi = Z × Ri× Ai× Co×Wi

(2)

n=i

where Z = area modulus, Ri = vibration characteristic coefficient, Co= standard shear coefficient, Qei = seismic shear force at storey i.
In the equation (2) the standard shear coefficient Co represents theearthquake magnitude, for example Co=0.2 can be described as the designof the building can resist 200gal loading in the earthquake. Usually, thevalue of Co is from 0.2 to 1.0 depending on the demand or type of thebuilding. In this study, it is considered Co = 0.2 and 1.0 both, the area
modulus Z = 1.0, vibration characteristic coefficient Ri = 1.0, which means
the building is located on the ground type 2. The results of the shear force
Qei in each storey alone the Y axis are shown in the table 1.
StoreyTable 1(a): The calculation results of the Qei in Axis Y1

ai

ai
0.436
0.624
0.775
0.894
1

Ai

1.384
1.202
1.107
1.046
1

ΣWi
(KN)

5
4
3
2
1

0.19
0.39
0.6
0.8
1

4.75
9.79
14.77
19.78
24.78

Storey

ai

ai

Ai

ΣWi
(KN)

5
4
3
2
1

0.19
0.39
0.6
0.8
1

0.436
0.624
0.775
0.894
1

1.384
1.202
1.107
1.046
1

9.15
18.73
28.3
37.88
47.45

Ci

Co=0.2
0.277
0.240
0.221
0.209
0.2

Qei (KN)

Co=1.0
1.384
1.202
1.107
1.046
1

Co=0.2
1.31
2.35
3.27
4.14
4.96

Co=1.0
6.57
11.77
16.35
20.69
24.78

Table 1(b): The calculation results of the Qei in Axis Y5
Ci

Co=0.2
0.277
0.240
0.221
0.209
0.2

Evaluation model
horizontally-mixed hybrid
hybrid timber
timber structure
structure
Evaluation
model ofof thethe five
five storey
story horizontally-mixed

Qei(KN)

Co=1.0
1.384
1.202
1.107
1.046
1

Co=0.2
2.53
4.5
6.27
7.92
9.49

Co=1.0
12.66
22.51
31.33
39.62
47.45

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Table 1(c): The calculation results of the Qei in Axis Y9

Storey

ai

5
4
3
2
1

0.19
0.39
0.6
0.8
1

ai

Ai

0.436
0.624
0.775
0.894
1

1.384
1.202
1.107
1.046
1

ΣWi
(KN)
13.48
27.57
41.66
55.75
69.84

Ci

Co=0.2
0.277
0.240
0.221
0.209
0.2

Qei(KN)

Co=1.0
1.384
1.202
1.107
1.046
1

Co=0.2
3.73
6.63
9.22
11.66
13.97

Co=1.0
18.66
33.14
46.12
58.31
69.84

Table 1(d): The calculation results of the Qei in Axis Y13

Storey

ai

5
4
3
2
1

0.19
0.39
0.59
0.8
1

ai
0.436
0.624
0.768
0.894
1

Ai

ΣWi
(KN)

1.384
1.202
1.111
1.046
1

8.78
18.38
27.97
37.56
47.16

Ci

Co=0.2
0.277
0.240
0.222
0.209
0.2

Qei(KN)

Co=1.0
1.384
1.202
1.111
1.046
1

Co=0.2
2.43
4.42
6.21
7.86
9.43

Co=1.0
12.15
22.09
31.07
39.29
47.16

2.3 The evaluation model and transmission of the force
After the seismic shear forces Qei at each storey are obtained,
meanwhile the floor slab which resists the seismic shear force can beconverted into the equivalent brace based on the stiffness of the floor which
was generated from the results of the experiment, in order to simplify the
analysis. Figure 3 illustrates the equivalent brace model of the floor and thetransmission of the seismic shear force Qei. In this model, the transmissionof the force is calculated span by span, and the supporting in point D, E and
F are the connecting joints of each span in the building. The supporting
located in axis Y09 is the connector connects the timber part and steel part.
The spring supporting in point A, B and C shows the affection of the shear
wall alone the axis, and the stiffness is different because of the different
numbers of the shear wall panels are applied in the experiment. The types
and specifications of the shear walls and floor slabs are shown in the next
chapter discussing the made of the dynamic analysis model.
Y05

C1

F1

B1

Y09

C2

F3

C3

F2

B2

B3
E3

E1

A1

E2

A2

A3

D3
D1

qe 1

D2

qe 5

1 - T IM B E R S P A N

CONNECTOR

qe 9

2 - T IM B E R S P A N

qe 13

3 - STEEL SPAN

Figure 3: The equivalent brace model of the floor

4732

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2.4 The
2.4summary
The summaryof the ofstaticthe static
evaluation
evaluation
AccordingAccordingto the toanalysis
the analysis
modelmodelshow inshow
figurein figure3, it is3,understood
it is understood
the themaximum
maximumshear shear
force occurs
force occurs
in the intwo
thesidetwoconnectors
side connectors(X01 and(X01X09),
and X09),
which whichfits onefitsofone
the offorce
the distribution
force distribution
patternpatternobserved
observedin the inexperiment
the experiment(table (table2). The2).value
The ofvalue
the ofcalculation
the calculationshowsshows
the shear
the forceshear calculated
force calculated
from fromthe model
the model
is approximately
is approximately
0.75 times
0.75 times
the maximum
the maximum
value valueof theof theexperimental
experimental
result,result,which which
providesprovidesdesigners
designers
an estimating
an estimating
systemsystemtotodesigndesign
the connector.
the connector.
Also theAlsoresults
the resultsof theofmaximum
the maximum
deformations
deformations
occur occur
in axisin Y01
axis Y01
showsshowsin tablein 3table
provide3 providean outline
an outlineof the ofdeformation
the deformationin eachin floor.
each floor.
The Theanalysisanalysis
resultsresults
generally
generally
predicted
predicted
the deformations.
the deformations.
However,
However,
the theevaluation
evaluation
modelmodel
providedprovidedin thisin study
this study
assumesassumes
all theallelements
the elements
are areelasticity,elasticity,
therefore
therefore
the larger
the larger
the seismic
the seismic
loadingloading
applied,applied,with thewith thedeformations
deformations
occurredoccurredin the inexperimental
the experimental
specimen
specimencomingcomingin to thein tononthe nonelasticelastic
area, andarea,theanddeformations
the deformations
calculated
calculated
from thefromstaticthe static
evaluation
evaluation
modelmodel
will bewill
smallerbe smaller
than thethanexperimental
the experimental
results.results.
Table Table
2: The2:force
The (KN)
forcein(KN)
the inconnector
the connector

Storey Storey
ResultsResultsof the evaluationof the evaluation
model model
1st
2nd
3rd
4th
5th

X01
1st 4.53
2nd3.79
3rd 2.99
4th 2.16
5th 1.23

X01X05
4.53 3.79 2.99 2.16 1.23 -X05X09- 4.32- 3.60- 2.85- 2.04- 1.13

X09
X01
4.32
3.60
4.75
2.85
2.04
1.13

Experimental
Experimental
results results
BCJ200BCJ200
KOBE200
KOBE200
X01
X05

X05
X09

X09
X01

X01
X05

X05
X09

X09

0.75
4.75

0.75
5.75

5.75
4.25

0.9
4.25

0.9
5.25

5.25

Table Table
3: The3:maximum
The maximum
displacement
displacement(mm) in(mm)
AxisinY1
Axis Y1Storey Storey
Evaluation
Evaluation
model model
Experimental
Experimental
results results
Co=1 Co=1
Co=0.5Co=0.5
Co=0.2Co=0.2BCJ200BCJ200
KOBE200
KOBE200KOBE500
KOBE500
1st
1st 5.19 5.19 3.22 3.22 1.31 1.31 1.45 1.45
1.1
1.1
4
4
2nd 2nd 4.33 4.33 2.69 2.69 1.09 1.09
3rd
3rd 3.42 3.42 2.13 2.13 0.86 0.86 2.55 2.55
2.1
2.1
5.95 5.95
4th
4th 2.46 2.46 1.53 1.53 0.62 0.62
5th
5th 1.38 1.38 0.85 0.85 0.35 0.35 0.85 0.85 1.05 1.05
2
2
Total Total16.78 16.7810.42 10.42 4.22 4.22 4.85 4.85 4.25 4.25
11.95 11.95

3. DYNAMIC
3. DYNAMIC
EVALUATIONEVALUATION
Structural
Structuralelements
elements
and joints
and joints
are modeled
are modeledconsidering
consideringsome idealizations.
some idealizations.
The idealizations
The idealizations
and simplificationand simplification
make makethe results
the resultsof theof analysis
the analysis
different
different
form theform
experimental
the experimental
results.results.
In thisIn
chapter
this chapter
it is discussed
it is discussed
that thethat thebasic basic
specifications
specificationsof theofevaluation
the evaluation
modelmodelthat havethat been
have build
been buildin thein thecomputercomputeranalysisanalysisprogramprogram
MIDAS.
MIDAS.
With theWithconfirmation
the confirmationof theofbasic
the basic
specifications,specifications,the model
the model
can becan
used
befor
used
theforfurtherthe further
analysis.
analysis.

Evaluation
model ofthe five
storeyhybridhybrid
timbertimber
structure
Evaluation
model
of
five
storeyhorizontally-mixed
hybridtimberstructure
Evaluation
modelof thethefive horizontally-mixed
story horizontally-mixed
structure

5 7335

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

3.1 The made of the analysis model
To build an analysis model, the first step is to convert the wall panel
and the floor slab, which are elements that resist seismic loading, into theequivalent brace. The types of these elements are shown in the table 4. And
equation (3) shows how the equivalent brace can be converted,
P

KW

W

EA

b2
h2

b2

3

b

(3)

where P is the loading applied, K W is the stiffness of the wall obtained fromthe specimen experiment, W is the deformation of the specimen and b is thedeformation of the equivalent brace model, which is the same with W . Basedon the equation (3), it is expected to obtain the value EA of the equivalentbrace.
Table 4: The types of the elements resisting seismic loading at timber part
Wall panel

2 panels(axis X1 to X9)

2 panels(axis Y1)

Floor slab

4 panels(axis Y5)

The other specifications which are also required for the made ofmodel are listed in table 5. And the final product that has been made in thecomputer program MIDAS is shown in the figure 5. The input of theseismic loading is alone the Y axis. The height of each storey is 1 meter andeach span is 2 meters.
Table 5: The specifications of the model
Material
Timber part
Columns andBeams
Wall plate (4panels)
Floor slab
Steel part
Columns, Beams,
bracesFloor slab

6
734

Size
(mm)

Classification

Density(g/cm )

E
(KN/mm )100 100

E105-F300

0.5

10.5

667 1000, t=92000 2000, t=9Type1 Grade 2
Type1 Grade 2

0.5
0.5

1.54
2.55

H-100*100*6*8

SN400

7.85

199.9

7.85

355.5

t=4.5

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10001000
10001000
10001000
X

X

Y

Y

Seismic
Seismic
loadingloading

10001000
10001000
20002000
20002000
20002000

Figure5: Theanalysismodel
converted
equivalent
brace
Figure5: Theanalysismodel
withwith
converted
equivalentbrace
4. PARAMETRIC
STUDY
THE
FLOOR
SLAB
4. PARAMETRIC
STUDY
OFOF
THE
FLOOR
SLAB
From
previous
study,
is understoodfloor
is theelement
Fromthetheprevious
study,
it isitunderstood
thatthat
thethefloor
is thekeykeyelementto totransmit
seismic
force
fromtimberto steelthroughtransmit
thetheseismic
force
fromthethetimberpartpart
to steel
partpart
throughthetheconnector.
In thischapter,in orderto realize
stiffnessof theconnector.
In thischapter,in orderto realize
thethehowhowthethestiffnessof thefloor
influencevibration
behavior
deformation
floor
cancaninfluence
thethevibration
behavior
andandthethedeformation
of ofthethebuilding,
different
parametersof thestiffnessof thefloorsstudied.
building,
thethedifferent
parametersof thestiffnessof thefloorsarearestudied.
4.14.1
TheThetype
type
of theof thefloor
floor
stiffness
stiffness
TheThetypes
types
of theof thestiffness
stiffnessof theof thefloorsfloorsareareshown
shown
in tablein table
6. In
6. theIn thetable
table
6, the6, thestiffness
stiffnessof theof theanalysisanalysis
model
model
Kf-4
Kf-4
is theis thestandard
standard
oneonewhich
which
thethevalue
value
waswasobtained
obtainedfromfromthetheexperiment.
experiment.
Based
Based
on on
thethe
model
model
Kf-4,
Kf-4,
thetheotheranalysismodels
were
made
with
differenceof thefloor
stiffness.
other
analysismodels
were
made
with
thethedifferenceof thefloor
stiffness.
input
seismic
loadingin theanalysis
is Kobein order
TheTheinput
of ofseismic
loadingin theanalysis
is Kobe200200galgalin orderto tosimplify
analysisfactor.
simplify
thetheanalysisfactor.
Model
Model
Kf-1Kf-1
Kf-2Kf-2
Kf-3Kf-3
Kf-4Kf-4
Kf-5Kf-5
Kf-6Kf-6

Table
Table
6: The6: Theparameterparameterof theof thefloor
floor
slabslab
Stiffness
Stiffnessof theof thefloor
floor(KN/mm)(KN/mm)45 45
10 times
10 times
Kf-4Kf-4
18 18
4 times
4 times
Kf-4Kf-4
9 9
2 times
2 times
Kf-4Kf-4
4.5 4.5
Experimental
Experimental
value
value
2.252.25
0.5 0.5
times
times
Kf-4Kf-4
0.450.45
0.1 0.1
times
times
Kf-4Kf-4

Converted
Converted
EA EA
(KN)
(KN)
255400255400102160102160
51080
51080
25540
25540
12770
12770
2554
2554

4.24.2
TheTheresults
resultsof theof theanalysisanalysis
TheTheresults
resultsof theof theanalysisanalysisshow
show
thatthat
thetheimprovement
improvementof theof thestiffness
stiffnessof theof the
floor
floor
makes
makes
thethestiffness
stiffnessof theof thebuildingbuilding
been
been
improved.
improved.
Furthermore,
Furthermore,thethedeformation
deformationin eachin eachstoreystoreyis alsois alsobeen
been
reduced,reduced,figurefigure6 (left).
6 (left).
In theIn the
other
other
hand,
hand,
it isitobserved
is observed
thatthat
thethestiffness
stiffnessof theof the
floor
floor
been
been
improved
improved
makes
makes
thethedeformation
deformationin thein thesteel
steel
partpart
increased,
increased,
figurefigure6 (right).
6 (right).
TheThereasonreasoncancanbe be
explained
explained
thatthat
thethefloor
floor
is oneis oneof theof themost
mostimportantimportantelements
elements
to resist
to resistandandto transmit
to transmit
thetheseismic
seismic
force.
force.
Therefore
Therefore
when
when
thethebuildingbuilding
is suffering
is suffering

Evaluation
modelof thefivefive
storeyhorizontally-mixed
hybridtimberstructure
Evaluation
modelof
storeyhorizontally-mixed
hybridtimberstructure
Evaluation
modelof the
the
five
story
horizontally-mixed
hybridtimberstructure77357

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

the seismic loading, the seismic force occurred in the timber part can betransmitted through the floor span by span to the connector first andtransmit to the steel part via connectors.
2.00

1
0.8
Di s p . ( c m)

Di s p . ( c m )

1.50
Kf‐1
Kf‐2

1.00

Kf‐3
Kf‐4
0.50

Kf‐1

0.6

Kf‐2
Kf‐3

0.4

Kf‐4

Kf‐5

Kf‐5

0.2

Kf‐6

Kf‐6
0

0.00
0

1

2

3

4

0

5

1

2

3

4

5

StoreyStroeyFigure 6: The storey displacement, left: timber part, right: steel part
According to the analysis results, it is believed that the stiffer thetimber floor is, the more efficient the seismic force transmits from timberpart to steel part through floors and connectors, and in the end the larger
deformation is discovered in the steel part. In the figure 7, it is also noticed
that the influence of the floor stiffness is much obvious in the lower floor
than the higher floor.
1/120

1/45

Storey drift ( rad )Storey drift ( rad )

1/90
Kf‐1
Kf‐2

1/60

Kf‐3
Kf‐4

1/30

Kf‐1

1/30

Kf‐2
Kf‐3
Kf‐4

1/15

Kf‐5

Kf‐5

Kf‐6

Kf‐6

0

1

2

3

4

5

0

6

1

2

3

4

5

6

StoreyStoreyFigure 7: The storey draft angle, left: timber part, right: steel part
4.3 The summary
From the results of the analysis, it has been understood that the
stiffness of the floor gives the great influence to the seismic force
transmitting from timber part to the steel part. And the transmitting efficient
can be simulated by the equation (4), which is called the force transmitting
ratio,
Dkf - i =D woodD steel(4)

where, Dkf-i is the force transmitting ratio, Dwood is the largest
deformation occurs at the timber part in model Kf-i, and Dwsteel is thelargest deformation occurs at the steel part in model Kf-i. The smaller the8736

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Dkf-i value
Dkf-iis,value
the betteris, thethe
betterforcethetransmitting
force transmitting
efficientefficientis, shownis, inshown
figurein8figure 8(left). And(left).if And
each ifforce
eachtransmitting
force transmitting
ratio is ratio
compareis compare
to the Dkf-4(theto the Dkf-4(thestandardstandard
stiffness),
stiffness),
it is discovered
it is discoveredthat a trendthat line
a trendshows
linetheshowssametheresult
sameasresult as
well, figure
well,8figure(right).8 (right).

100

100
80

Dwood / Dsteel ( Dkf‐i )Dwood / Dsteel ( Dkf‐i )

80
60
40
20

Dkf‐1
60
40
20

0

Dkf‐1

1

02

13
Storey

24

35

46

8

7

6

6
5

Dkf‐2

Dkf‐2

5

Dkf‐3

Dkf‐3

4

4

Dkf‐4

Dkf‐4

Dkf‐5

Dkf‐5

3

3

Dkf‐6

Dkf‐6

2

2

1

1

0
0

8

7

5

6

0

Dkf‐4/1

0

Dkf‐4/2
Dkf‐4/2
Dkf‐4/4
Dkf‐4/3
Dkf‐4/5
Dkf‐4/4
Dkf‐4/6
Dkf‐4/5
Dkf‐4/1Dkf‐4/3

Dkf‐4/6

StoreyFigure 8:
Figure
The force
8: Thetransmitting
force transmitting
ratio Dkf-i
ratio(left)
Dkf-i
and(left)
the andtrend
thelinetrend(right)line (right)
5. CONCLUSIONS
5. CONCLUSIONSIn this In
study,
this thestudy,
generalthe generalbehaviorbehaviorof the fiveof thestoreyfive plane
storeymixed
plane hybrid
mixed hybrid
timber timber
structurestructure
under seismic
under seismic
loading loading
becomesbecomesclarity, clarity,especially
especiallythethetransmitting
transmittingof the forceof thebetween
force between
timber parttimberandpartsteel
andpart.
steelThe
part.
research
The research
results are
results
concluded
are concluded
as follow:
as follow:
1. As the
1. final
As theresults
final which
resultsare
whichobtained
are obtained
from thefrom
experiment
the experimentexamineexaminethetheresults resultsthat arethatcalculated
are calculated
from thefromstaticthe evaluation
static evaluation
model, model,thethecorrection
correctionof the modelof the ismodel
expectedis expected
to be established.
to be established.
The results
The ofresults
the of thestatic evaluation
static evaluation
model showsmodelthe
shows
shear
theforce
shearcalculated
force calculated
from thefrom
model
the model
is approximately
is approximately
0.75 times
0.75thetimes
maximum
the maximum
value invalue
the experimental
in the experimental
results, results,
which provides
which provides
designers
designers
an estimating
an estimating
system system
to design
to designthetheconnector.
connector.
And theAnd
maximum
the maximum
deformation
deformation
can be obtained
can be obtained
accordingaccordingtotothe model
theas
model
well.as well.
2. According
2. According
to the staticto theanalysis
static analysis
model, model,
it is clear
it isthatclear
thethatshear
thewallshear
is wall isthe maintheelement
main element
to resistto theresistdeformation
the deformationof the ofbuilding
the building
and theand thestiffnessstiffnessof the offloor
thedemonstrates
floor demonstrates
the forcethe transmission
force transmission
form theform thetimber parttimberto thepartsteelto thepart.
steel part.
3. The3.additional
The additional
study ofstudy
the differentof the different
parametersparametersof the stiffnessof the stiffnessof the of thefloor verifies
floor verifies
the efficientthe efficientsystem systemof the forceof thetransmitting
force transmittingfrom timberfrom timberpart to partthe steelto thepart.
steelThe
part.
analysis
The analysis
result shows
result theshows
stiffer
the thestiffertimberthe timberfloor is,floor
the moreis, theefficient
more efficient
the seismic
the seismic
force transmits
force transmits
from timberfrom parttimber partto steel topart
steel
throughpart throughfloors andfloorsconnectors,
and connectors,
and in andthe endin thetheendlargerthe larger
deformation
deformation
is discoveredis discoveredin the steel
in thepart.
steel part.
This study
This gives
study angives
overallan overall
view ofview
the ofstaticthe evaluation
static evaluationof the of thehorizontally-mixed
horizontally-mixed
hybrid hybrid
timber timber
structure,
structure,
and withand thewithconfirming
the confirming
requiredrequired
knowledgeknowledgeof this ofkind
thisofkind
structuralof structural
systems,systems,
the enhanced
the enhanced
performance
performanceand improvement
and improvementof the of
mid-rise
the mid-risehybrid hybrid
timber timber
structural
structural
system will
systemalsowillbe expected.
also be expected.

Evaluation
model ofmodel
the fivehorizontally-mixed
hybrid timber
Evaluation
of
thestoreyhorizontally-mixed
hybridstructure
timber structure
structure
Evaluation
model
ofstorey
the five
five
story horizontally-mixed
hybridtimber97379

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

REFERENCES
Koshihara Mikio, Isoda Hiroshi, Yusa Shuitsu, 2009, The design andinstallation of a five-story timber building in Japan, The international
symposium on timber structure, Istanbul, Turkey.
Nakagawa Manabu , Kawai Naohito , Koshihara Mikio , Araki
Yasuhiro , Isoda Hiroshi, 2007, Static tests of shear wall and structural floor
to estimate behavior of scaled five story hybrid structure, Summaries oftechnical papers of Annual Meeting Architectural Institute of Japan, Vol.C1, Structures III, 179-180.
Kawai Naohito and Okabe Minoru, 2002, Development ofTechnology for Hybrid Timber Building Structures: In-plane Shear
Performance of Floor Systems, Summaries of technical papers of Annual
Meeting Architectural Institute of Japan, Vol. C-1, 317-318

10738

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NewA study on seismic performance andreinforcement methodof rammed earth wall, ‘HANCHIKU’Mikio KOSHIHARA1 and Akiko TAKADACHI2
1
Associate professor, ICUS,
Institute of Industrial Science, the University of Tokyo, Japan
kos@iis.u-tokyo.ac.jp
2
Structural engineer, Nikken Sekkei LTD
ABSTRACT‘HANCHIKU’ wall is Japanese traditional rammed earth wall. They havebeen used as the wall around the old temple like ‘HOURYU-JI’. But new‘HANCHIKU’” wall could not been built because they have much damage
due to large earthquake.
In this study a seismic performance of traditional ‘HANCHIKU’ is clearedusing shaking table test and analysis. These walls are observed rocking
phase and phase of resisting by bending moment depending on the scale ofthe input motion.
Some reinforcement methods are proposed and are verified the effectagainst earthquake. For stronger allowance shear force quicklime is mixed
in soil. For rocking effect, a rammed earth wall is anchored by bamboos orplastics. For stronger allowance bending moment, they are reinforced using
bamboo or plastics like reinforce concrete. Using bamboo has better
seismic performance, but this method use the 1.6 times work forces than
traditional method.
In this study the possibility for seismic designed rammed earth wall,‘HANCHIKU’, is proposed.
Keywords: Cob, Rammed earth, Mud wall, shaking table test
1. INTRODUCTION
In Japan, from ancient time cob structured building such as cob storage or
cob wall have been built. Not only in Japan but also all over the world there
exists many cob structured building; for example, Great Wall in China. In
Japan, the design and construction work are done by plasterer, various kindsof rule of thumb exists.
In this research, we define cob structured building, especially whose
cob itself works as the structure as ‘cob-structured-building’. This researchworks on especially ‘Rammed Earth Wall’, which is found in the ancient
Houryuji-Temple or Nishinomiya-Shrine and still used in houses in thepresent. This Rammed Earth Wall is made by laminating cob layer, this cob

7391

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

layer is made by stacking cobs which consists of bittern and lime in a molduntil its volume become almost half.
When this kind of cob structured building is designed and constructed,
it is necessary to think over about the method scientifically, as well as
taking rule of thumb into consideration. To clarify the seismic performance,
shaking table tests of 1/2 scale models are conducted, this test focused on
Rammed Earth Wall which don’t have much resistance to the bending
tension and tends to collapse to outplane direction in case of earthquake.
Furthermore, we grasp the structural ability of Rammed Earth Wall whenit’s constructed in traditional way. We focused on the anchors between
Rammed Earth Wall and basement, which is one of the problem in case ofearthquake and we proposed reinforcement method and inspected theefficiency.
2. OUTLINE OF THE SHAKING TABLE TEST
2.1 Specimens
One part from the sequence of the Rammed Earth Wall was taken out
as shown in Figure 1 and shaken in outplane direction. This research deals
with 6 kinds of specimens, actually most of the Rammed Earth Wallconstructed at the present time is classified in type HN1 or KN1, whose
bottom is not anchored to basement.
The size of specimens is 1/2 scale model of Rammed Earth Wall fromsouth-west side of Rammed Earth Wall in `Saiin in Houryuji-temple’. Eachspecimen is directly constructed on concrete basements. 2 kinds of cob wereused to compare the performance between different kinds of cob. One cob(H) has sprinkling distribution of grading, is suitable for Rammed EarthWall and is from Nara, the other (K) is from Chiba and contains much sand.
The construction method of Rammed Earth Wall has its advantage in the
point that, performance of any cob can be improved by handling grading
distribution or adding admixture. The ratio of combination and admixture ofeach cob are shown in Table 1, cob H refers to the method in restoration of
Horyuji-temple, cob K refers to the most suitable ratio of combinationachieved from the result of room experiment by Lee(2009). In actual
construction, because of the climate condition the ratio of the water waschanged based on experience of the plasterer, thus the mixing ratio wasmeasured during the construction work. Unconfined compressive strength
obtained from test is shown in Figure 2. Compressive strength is
proportional to its density.

2740

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ICUS Report 56
Shaking Direction`Saiin in Houryuji-temple’
Figure 1: Specimen

Specimen(unit : mm)Table 1: Mixing ratio

Water with Bittern(volume)
5-9%
9

Cob H

Cob (H)‘Nashimedo’

Target ratio
Measured ratio

2
59

1
32

Cob K

Cob (K)

Sand

Quick Lime

Water

Target ratio
Measured ratio

62
58

10
10

8
8

20
24

3.50

y = 6.3776x – 7.8446

3.00

R2 = 0.9301

2.50
2.00
σc
[N/mm2]

1.50
1.00
0.50
0.00
1.35

1.40

1.45

1.50

1.55

1.60

1.65

1.70
Density

Figure 2: Compressive strength and density ( Cob K)
2.2 Reinforcement method
This study proposes 2 sorts of reinforcement method for bending andoverturning to the outplane direction, reinforcement by bamboo (KB) andmesh reinforce material of plastics (KM).
In KB natural material bamboo is used for tensile member, which istraditionally used for cob wall as reinforcement. Since direct anchor of
bamboo to the basement leads rapid decay, steel reinforcement rod is used
to anchor it and with grout reinforcement rod and bamboo are connected.

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reinforcement method
method ofof rammed
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October 2011, Chiang
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Thailand
Chiangmai,

Takadachi [2009] has been reported about reinforcing bamboo ofSpecimens KB. This study made an experiment on tensile capacity ofbamboo anchor in KB and indicated that the tensile capacity was determinedby shearing strength of the node of bamboo. Moreover, shearing test of thenode of bamboo was carried out, the shearing strength was evaluated. At thesame time, adhesion test was put into practice, there the adhesion force
between bamboo with a hemp rope(4,5φ mm) twisted around at intervals of
45mm and cob was examined. For the shape of the bamboo used for
calculating the shearing strength of each node, the arithmetic mean of
specimens at shearing test was used. With the value on table 3 and thetensile strength of cob 0.2N/mm2, out of required capacity of reinforcement
the specifications were determined. First of all, using ‘Standard for
Structural Design of Reinforced Concrete Structures’, out of bending
moment, the required amount of reinforcement rod was calculated, bamboo
was designed to exceed the yield strength of the reinforcing rod. This
experiment made use of such specimens with reinforcing bamboo as in
Figure 3, D10 for reinforcement rod for anchor, ‘Madake’ bamboo from
Chiba whose diameter is 50mm and for horizontal reinforcement split
bamboo whose diameter is 60mm. For vertical reinforcement bamboo with ahemp rope (4,5φ mm) twisted around at intervals of 45mm was used so thatit gets higher adhesion force.
Bamboo has demerit in construction method, that cob doesn’t getcompacted well around the bamboo owing to the cylinder shape. Therefore
a test on reinforced specimens KM with mesh reinforcement of plastic iscarried out as well, which is often used for ground reinforcement as thintensile reinforcement. The material capacity of reinforcement was referred
to study [5]. Out of the result of calculation of required ability,
reinforcement SS-35 with product standard strength 37.0 kN/m wasarranged as in Figure 3.

KB

Figure 3: Specimen (Reinforced)

KM

2.3 Input motion
This experiment made use of simulation wave of the building centerof Japan (hereinafter BCJ-L2) and NS components of JMA Kobe recordedin Kobe earthquake in 1995 wave (hereinafter Kobe). As shown on table 2,

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after shaking test No.4, because of the capacity of shaking table the time
axis and the period of wave were shortened to half so that the maximum
acceleration get bigger. The specimens were shaken until it collapsed, while
the maximum acceleration increased.
No.
1
2
3
4
5
6
7
8
9

Table 2: Input motion

Wave name
BCJ-L2
BCJ-L2
Kobe
Kobe
Kobe
Kobe
Kobe
Kobe
Kobe

Duration
120 sec.
120 sec.
80sec.
40sec.
40sec.
40sec.
40sec.
40sec.
40sec.

Time axis
1
1
1
1/2
1/2
1/2
1/2
1/2
1/2

Max. Acc.
100
355
1049
1049
1200
1400
1600
1800
1950

2.4 Measuring plan
Measurement was done with total 31 channels of acceleration anddeformation measuring instrument and image measuring system. The
position of main acceleration and deformation measurement instrument isshown on figure 4. Each instrument has its positive direction like an arrowon figure 4.

Figure 4: Measuring Plan
3. RESULT OF SHAKING TABLE TEST
3.1 Comparison of shaking level
The results of each specimen are shown in table.3. Table 3 shows
maximum input acceleration of each shaking level on the concrete basementon which specimens are set up and the damage at each shaking level inround brackets.

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October 2011, Chiang
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No. HN1
1
148
2
449
3

KN1
179
444

Table 3: Result of Shaking Table Test

HN2
KN2
182
139
472
477
1069
1060
Bending 955(1050)
Rocking
failure

KB
150
463

KM
173
491

952

1022
Crack at Pt.1

4

－

－

－

979

1029
Crack by bending
moment1191
Crack at Pt.2

5

－

－

－

1199
Bending
failure

1232

1252

6

－

－

－

Collapse

1365

1401
Crack at Pt.3
1458
Crack at Pt.3

7

－

－

－

－

1554
Crack by bending
moment between 6 and 7
layer

8

－

－

－

－

(1800)（1800）

9

－

－

－

－

(1950)（1950）
Collapse

3.2 Damages
The damage was following; In KB, although a dry crack was
expanded, that didn’t result in collapse. Each specimen showed brittle
fracture property.
During Shaking No.3 of specimens KN1, one side floated up becauseof overturning, however no large damage was observed except for that apart of the corner of bottom of the specimen was broken off (Figure 5).
Specimen HN2, KN2 didn’t float up, however collapsed by bending
tension collapse. In HN2, between 3rd and 4th layers a crack by bending
tension was observed at first, afterwards the upper part floated up and fell,
the impact caused interlayers between from 2nd to 5th layers peeled off.
Figure 6 shows the frame by frame image from high speed camera. In KN2
a crack by bending tension was observed between 4th and 5th layers, while
shaking No.5 was carried out. Furthermore, it stood by itself after bending
tension collapse, thus shaking No.6 was done. The result was following; theupper part separated by bending tension collapse floated up, fell and gave an
impact on the lower part, as a result the lower part collapsed. This result
indicate that after bending tension collapse, unless it’s reinforced between
layers, Rammed Earth Wall doesn’t possess resistance force.
In KM a dry crack on front of bottom of the specimen was expanded
and penetrated to the sideways, while shaking No.3 was carried out. Next,
during shaking No.4, 6 and 7, cracks by bending tension were observed on aside of bottom of the specimen. Afterwards during shaking No.8 there occur

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a crack, because of these bending tension cracks, the shearing area become
smaller and finally, shearing collapse was brought about during shaking
No.9.

Figure 5: Overturning and Collapse of Bottom Layer (KN1 No.3)

Figure 6: Process of Bending Failure (HN2 No.3)
4. Seismic performance and efficiency of reinforcement of Rammed
Earth Wall
The properties of specimens are classified into 2 groups based on historicalresponse acceleration and into 3 groups based on historical response
deformation.
(1) Rigid body deformation
Before bending tension collapse, horizontal response acceleration was
distributed in proportion to the height. From this one may say that Rammed
Earth Wall behaves as one rigid body. Take No.5 of KB for example andlook into the relationship between measured horizontal deformation on topof the specimen (δ [mm]) and rotation deformation calculated fromrotation angle on bottom of the specimen. They are plotted along line y=x,
which makes it clear that Rammed Earth Wall behaves as one rigid body.
After shaking No.3 of specimen KM, a crack was found from front to side
(between 1st and 2nd layer) of bottom of the specimens. This crack isthought to make the specimen behave divided into upper and lower part.
Compare each horizontal deformation, rotation angle of bottom of thespecimen (lower part) and rotation angle of the center of the specimen(upper part), the relationship between rotation deformation and measured

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

horizontal deformation on the center of the specimen are line up along line
y=x, it behaved as 2 rigid bodies. However the horizontal response
acceleration at each height on the center of the specimen are distributed inproportion to the height. The reason for it is thought that because
deformation was restrained by reinforcement, response acceleration didn’t
differ each other so much. When shaken by No.8, the horizontal
deformation was so big that the specimen behaved as 3 rigid bodies, in thiscase this principal was not applied.
33

h× tanθ [mm]211

δ [mm]

0
-3

-2

-1

h×tanθ[mm]

2

0

1

2

3

KB_5
y=x

δ[mm]

0
-3

-2

-1

0

-1

-1

-2

-2

-3

-3

1

2

3

KM_5_中層部
KM_5_下層部
y=x

Figure 7: Horizontal deformation and rotation angle(2) Relation of moment and rotation angle
When it behaves as a rigid body, the distribution of acceleration
become a linear figure, the moment is calculated by following formula. a(h)is approximation formula of the linear, each height of center of gravities hw
become h through formula (2). Here h+dh is approximated as h. In figure 8of the relation between moment and rotation angle, the moment working onbottom of the specimen is used for Fig. 8. Rotation angle was calculated
from vertical deformation obtained by the deformation measuring
instrument on bottom of the specimen.
Hh��h� � � ��1 � ��2 � �1� � � � � � ��h� � � � hw � �hHhhh � �h�h � ���1 � ��2 � �1� � � � 2 � ��1 � ��2 � �1� �
��
H
H
hw �
�h
h � �hh� � ���1 � ��2 � �1� � H� � ��1 � ��2 � �1� � H ��

Z1

(1)
(2)

Z2

Z1 � Z2
��400

Figure 8: Moment and rotation angle

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ICUS Report 56(3) Sliding
Seeing in the horizontal deformation on bottom of the specimen
obtained from shaking No.1, No.2 of specimen HN1, KN1, no sliding wasobserved. This reveals that the friction modulus between cob and concrete isbigger than 0.51.
(4) Overturning
Given that specimen KN1 is rigid body, the theoretical value of
moment Mf which cause uplift is 5.5kNm. Seeing in the time history of
moment working on bottom of the specimen, floating occurred when the
moment was bigger than theoretical value Mf (dotted line in figure 9).
30

kNm

20
10
M
Mf(正)
Mf(負)

0
-10
-20
-30
12

12.5

13

13.5

14

14.5

15

sec

Figure 9: Moment of bottom of specimen and uplift(5) Bending failure
As well as HN1, KN1, specimen HN2, KN2 deformed as rigid body.
In case of KN2, maximum shearing stress caused by horizontal force
working on each layers is 0.028 N/mm2, which is much smaller comparedwith the shearing strength calculated from the value obtained from 3 axial
compression test of Lee[2009]. Also in case of HN2, compared withshearing strength in condition of φ = 0, maximum shearing stress was far
smaller. Therefore both specimens were thought to collapse by bending
tension. Thus the stress caused by maximum moment M in the shaking level
in which bending tension collapse happened (dotted line) and the stressworking on each layers due to the dead load (solid line) were calculated andshown on figure 10. The maximum tensile stress at the edge is taken placein case of HN2 at height of 0.357m (0.075N/mm2) and in case of KN2 atheight of 0.424m (0.140 N/mm2). Material test shows tensile strength of thespecimen is approx.5% of compression strength, 0.05N/mm2 (HN2),
0.11N/mm2 (KN2), each of maximum stress in figure 10 was over thetensile strength. The thick line on figure 10 shows interlayer, 2 layers on andunder which weren’t constructed in the same day. It collapsed in thisinterlayer, we can recognize that the interlayer had smaller tensile strengththan the others.

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October 2011, Chiang
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Figure 10: Bending moment distribution(6) Efficiency of reinforcement
Let us evaluate the tensile force working on reinforcement. In
specimen KB tensile force was measured by load cell set up withreinforcing rod in bamboo. From shaking No.4 it measured tensile force
more than initial tensile force. At that time a bending tension crack was
observed on side of the specimen. The theoretical value of tensile force
whose center of rotation is calculated from the vertical deformation ofbottom of the specimen is 29.8kN, which almost corresponds to theexperimental value 28.6kN. The adhesion force of each bamboo ranges
from 32.4kN to 35.9kN, the condition of the specimen after the test showedthat it kept adhering. Thus bamboo reinforcement is thought to act
effectively to bending tension.
(7) Result of test and comparative consideration
The theoretical value at which Rammed Earth Wall get damaged inearthquake was calculated and is shown on table 4 with experimental value,
input acceleration at which the specimen get damaged is shown on table 5.
Round brackets in the table means that phenomena weren’t observed untilthe value in round brackets, that is, the specimen has superior property. The
underline shows theoretical value.
Table 4: Bending moment and phenomena
HN1

KN1

Sliding(5.37)(4.44)

Overturning
Mf
Bending Failure
Mb
Allowable stress(Reinforced) Ma(5.37)
6.82

5.83
5.50

10
748

HN2

KN2

KB

KN

6.33

10.73

10.65

11.31

17.08
25.45

14.42

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Table 5: Input Max. Acceleration and phenomena
HN1

KN1

Sliding

(449)

(444)

Overturning

(449)

495

Bending Failure
Shear Failure

HN2

KN2

KB

KN

524

856

775

649

1554

1458

(8) Reinforce efficiency
Table.4 and 5 make it clear that in the shape of this specimen, in case
Mb > Mf, the resistance to earthquake is improved by anchoring to basement,
and moreover, with reinforcement the resistance become even better.
However in case Mb < Mf it is possible to improve the resistance toearthquake by reinforcement with or without anchoring.
5. SUMMARY
Based on collapse property and test result of 6 kinds of specimens, thisstudy indicated that in the shape of this specimen, up to the relationshipbetween Mb and Mf, the method of anchoring to the basement andreinforcement can be decided. In this experiment specimen KB had the best
performance to earthquake, however, in comparison to HN1 (HN2), KN1(KN2), 1.6 times of labor is required to construct KB. Furthermore, during
the drying period a lot of drying cracks are found on the surface of Rammed
Earth Wall, further research on construction method and consideration ofdesign are necessary.
REFERENCES
Lee Jina, 2009, Mechanical properties of lime-treated soil and its
application to earthen walls, Doctoral thesis of the University of Tokyo,
Japan
A.Takadachi and M.Koshihara, 2009, The Joint of using Bamboo’s
node, Summaries of technical papers of Annual Meeting Architectural
Institute of Japan, pp.91-92, AIJ.

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A study on the effect of wall stiffness
on the vibration characteristics of
traditional timber frames
including Kumimono
Iuko TSUWA1, Mikio KOSHIHARA2
1
Graduate Student, Graduate School of Eng.,
the University of Tokyo, Japantsuwa@iis.u-tokyo.ac.jp
2
Associate Professor, IIS, the University of Tokyo, Japan
ABSTRACTIn building or renovating traditional timber structures such as temples andshrines in Japan, earthquake resistant designed buildings are increasing.
As the way of reinforcement for such traditional timber buildings, there are
the change from mud wall to plywood wall and the insert of braces etc.
These ways are same as conventional wooden houses. However the
structural elements of traditional timber structures are different withconventional wooden houses. Additionally it is not clarified how eachstructural element of traditional timber structures behaves against
earthquakes by using the present seismic reinforcement technique. In thisstudy, we focused on Kumimono which is said that it is a structural seismic
element in traditional timber structures. We conducted earthquake response
analysis about traditional timber frames including Kumimono with theresults of shaking table tests using two types of frames without walls andwith a mud wall. Based on the model from the analysis, we analyzed theearthquake response of a frame including plywood walls in order to reveal
how the vibration characteristics of traditional timber frames including
Kumimono change by different wall stiffness. The vibration characteristicsof Kumimono in each frame were compared.
Keywords: traditional timber frame, Kumimono, shaking table test,
earthquake response analysis,
1. INTRODUCTION
In building or renovating traditional timber structures such as temples andshrines in Japan, earthquake resistant designed buildings are needed.
Therefore the quantitative evaluation of their structural behaviors is
indispensable. When we build temples and shrines, column, mud wall, Nuki
which is a tie beam extending from one pillar to another, and bracket
complexes called Kumimono in Japanese which is a structural component
between a column and roof, etc, are considered as structural elements. Eachelement has been researched and modelled experimentally and analytically.
However it is not clear how each element contributes to the whole structural7511

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

behavior. The aim of this research is to clarify the vibration characteristics
of each element in a frame and how the vibration characteristics of
traditional timber frame including Kumimono change by different wall
stiffness. In this study, the shaking table tests were performed withspecimens modeling the frame of the first story in fifth storied pagoda. We
used two types of specimens. One is without walls. The other one is with
mud wall. Based on the test results and existing theoretical model, we
modeled restoring-force characteristics of each structural elements and we
conducted earthquake response analysis. The analysis results werecompared with experimental ones. Additionally, we analyzed with themodel including plywood wall instead of mud wall.
2. EXPERIMENT
We conducted vibration tests as we presented at USMCA 2009. The details
were shown in the paper. We explain the experimental outline and theresults used in the analysis here.
2.1 Experimental method
Two types of specimens were used in the tests as shown in Figure 1.
Specimen 1 consisted of columns, Nuki, bracket complexes. Specimen 2
was made by adding mud wall between the columns of the Specimen 1. The
specimens were the 2/3 scale model of a frame in the Asuka style of the
five-storied timber pagoda. A cornerstone was put under each column. They
were connected with a dowel. Tree species were yellow cedar.
We carried out the shaking table tests as shown in Figure 2.
Horizontal unidirectional shaking was conducted. The vertical load of
39.9kN made of steel frames and lead was put on the specimen. A load cellto measure axial force and shear force was placed under each column. The
acceleration, displacement and the strain of specimens were measured using
about 75 devices.
We put BCJ-L2, the level 2 of a simulated wave provided from thebuilding center of Japan, as a large input motion. In the tests of Specimen 1,
the maximum input acceleration was increased by 10% from 10% to 100%.
In the tests of Specimen 2, one input with BCJ-L2 20% and two inputs with
BCJ-L2 100% were carried out.
3060
1260

900

900
Toshi-hijiki

726

Kumimono

Column

300

1980

2706

Daiwa

Mud wall300
Koshi-nuki

Mud wallJi-nuki

Specimen 1

2
752

Figure 1: Specimens

Specimen 2

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VerticalVertical
Load Load

Specimen
Specimen

Load cell
Load cell
ShakingShaking
table table

FigureFigure
2: Experimental
2: Experimental
methodmethod
2.2 Experimental
2.2 Experimental
resultsresults
FigureFigure
3 shows
3 shows
the relationshipthe relationshipbetweenbetweenload andloaddisplacementand displacement
got bygot by
inputting
inputting
BCJ-L2
BCJ-L2
100%100%of Specimenof Specimen
1 and 1Specimen
and Specimen
2. The2.characteristics
The characteristics
of everyof everyhysteresis
hysteresis
curve curve
were almost
were almost
same sameafter theaftercollapse
the collapseof theofmud
the mudwall. wall.
However
Howeverthe load
the ofload
Specimenof Specimen
2 less2 thanless about
than about
50 mm
50 becamemm became
higherhigher
than thatthanofthat
Specimenof Specimen
1. It can
1. Itbecan
assumedbe assumed
to be due
to betodue
the toresistancethe resistanceforce offorce
mud
ofwall.
mud Thewall.deformation
The deformationof bracketof bracket
complexes
complexes
in bothinspecimens
both specimens
was very
was minutevery minutecomparingcomparingwith one
withofone
theofwhole
the whole
structure
structure
as shown
as shownininFigureFigure
4.
4.
20

20

10

10

5

5

0
-100 0
-5

0
-5

-10

-10

-15

-15

Specimen 1 Specimen 1
Load (kN) Load (kN)Specimen 2 (100%Specimen-1) 2 (100% -1)
1515Specimen 2 (100%-2)
Specimen 2 (100%-2)-200-200 -100

0100
100 200
200
Displacement
Displacementmm)mm)

FigureFigure
3: The3:relationshipThe relationshipbetweenbetweenload andloaddisplacementand displacement
15
Specimen 1Specimen(100%) 1 (100%)

[kN]

10

5

5

-150
-200 -100-150 -50-100

Load（ｋN） Load（ｋN）
15
15

[kN]

Specimen 2Specimen(100%-2) 2 (100%-2)

Kumimono Kumimono 10
Whole Frame
Whole Frame

0
-200

15

0-50

0
50 0

10
Kumimono Kumimono
Whole FrameWhole Frame

10

5

5

0

10050

150
100

-200 -100-150 -50-100
200
150 -200200 -150

0
0 -50

50 0

-5

-5

-10

-10

-10

-15

-15

-15

-5

-5

-10
-15

[mm]

[mm]

10050

150100 200150

200

Displacement（mm）
Displacement（mm）

FigureFigure
4: The4:relationshipThe relationshipbetweenbetweenload andloaddisplacementand displacementof bracketof bracket
complexes
complexes
study
the ofeffectwall stiffness
the vibration
characteristicsof traditional
includingA studyA on
the oneffectwallofstiffness
on the onvibration
characteristicsof traditionaltimbertimber
framesframes
includingA study on the effect of wall stiffness on the vibration characteristics
3 7533
Kumimono
Kumimonoof traditional timber frames including Kumimono

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

3. EARTHQUAKE RESPONSE ANALYSIS
3.1 Modeling of restoring-force characteristics
We conducted earthquake response analysis. Specimens were modeled
as two-mass system with the springs of columns, Koshinuki, Jinuki, bracket
complexes, and mud wall as shown in Figure 3. Restoring-force
characteristics of each structural element were modeled as follows. Figure 5
shows each characteristic.

Kk :Spring of Kumimo
Kc +Kn+Kj+Kw: Spring of Column, compressive strains
inclined to
the grain at Koshinuki and Jinuki, andMud wallFigure 5: The model of a whole frame
Column:Restoring force of columns was calculated by equation (1) withreference to previous experiments and researches of Ban, 1942 and Kawai,
1992.
(1)

y=H0{1-δ/b＋0.99625e-7.5675δ/b - 1.9963/(25δ/b＋１)}

y: Restoring force, δ: Horizontal displacement, b: Diameter of column,
H0: = Pb/h Restoring force of rigid body, h: The length of column,
The maximum of restoring force was 80% of H0. The horizontal
displacement of this force was 0.088 times of a column width. Assumingthat two columns were connected with a parallel spring, the stiffness of bothcolumns can be added.
In addition to the restoring force of columns, compressive strains inclined to
the grain occurred at the bottom of the column were also calculated by the
Merikomi theory (Inayama, 1992). The restoring-force characteristics wereshown in Figure 6 (b).
Koshinuki:
Bending moment of column-Koshinuki joint was measured by strain
gauges in experiments. We evaluated the rotational stiffness of Koshinuki ineach specimen based on the experimental results. The stiffness was also

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ICUS Report 56

calculated by Merikomi theory (Inayama, 1992). However the second
stiffness was smaller than experimental results. Thus we modeled therestoring-force characteristic based on the experimental results.
Shear force（kN）

6

Shear force
（kN）

4
3

4

2

2

1

0
‐0.1

‐0.05

0

0

0.05
0.1
Deformation angle（rad.)‐2‐0.05 ‐0.04 ‐0.03 ‐0.02 ‐0.01

‐1

0

0.01

0.02

0.03

0.04

0.05

Deformation angle（rad.)

‐2

‐4

‐3

‐6

‐4

(b) Restoring-force at the(a) Restoring-force ofbottom of columns
Figure 6: The restoring force of columns
4500
3500

4500 Moment

Moment
モーメント

3500(kN・mm)(kN・mm)

2500

2500

1500

1500
500

500
-0.1

-0.05

-500 0
-1500

0.05

0.1

-0.12

Rotational angle(rad.)
接合部の回転角(rad.)-0.08-0.04 -500 0

0.08

0.12

Rotational angle (rad.)Specimen 2
Model
Theory-2500

Specimen
試験体１1
Model
モデル化

-2500

-3500

Theory
めり込み理論

-3500

-4500

0.04

-1500

-4500

(a) Specimen 1(b) Specimen 2
Figure 7: The restoring force of Koshinuki
Jinuki:After experiments, compressive strains inclined to the grain occurred
due to the joint of columns were observed on Jinuki. The restoring-force
characteristic of Jinuki was given by Merikomi theory (Inayama, 1992).
4

Shear force
(kN)

3
2
1
0
-0.1

-0.05

0
-1

0.05

0.1

Deformation angle (rad.)

-2
-3
-4

Figure 8: The restoring force of Jinuki
Kumimono:
Each relationship between load and displacement of Kumimono in
specimen 1 and 2 was got as shown in Figure 9. The horizontal
displacement of Kumimono was calculated by subtracting one of Daiwa
from one of top. The results of Kumimono got by vibration tests werecompared with ones of static horizontal loading tests (Tsuwa et al, 2010) as
shown in Figure 10. From the comparison, both results were almost same
A study on the effect of wall stiffness on the vibration characteristics of traditional timber frames including
A study on the effect of wall stiffness on the vibration characteristics
Kumimono7555
of traditional timber frames including Kumimono

October 2011, Chiang
Mai,Thailand
Thailand
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although the range of displacement was different. From the result, therestoring-force characteristic of Kumimono was given as bi-linear as shownin Figure 11.
Shear Force
(kN)
15

15
10

10

5

5
Deformation (mm)

0
-15

-10

-5

-5

Shear Force
(kN)

20

20

0

5

10

Deformation (mm)

0
-15

15

-10

-5

-5

0

5

10

15

-10

-10
-15

-15
Specimen 2

Specimen 1

-20

-20

Specimen 1
Specimen 2
Figure 9: The relationship between load and displacement of Kumimono
0.8

Shear force 20
（kN）
15

Shear
force/Verticalforce （kN/kN）

0.6
0.4

10

0.2

5

0
-0.06

-0.04

-0.02

-0.2

Deformation angle（rad.)

0
0

0.02
0.04
0.06
Deformation angle（rad.）

-0.4

‐0.05

‐0.025

-0.8

0

0.025

0.05

‐10

One part
Specimen 2
Specimen 1
Two parts

-0.6

‐5

‐15
‐20

Figure 10: Comparison with static
loading tests

Figure 11: The restoring- forceof Kumimono

Mud wall:
We conducted the material tests of mud wall in order to figure thestrength of mud wall out. From the results, the restoring-force characteristicof mud wall was modeled like a heavy line shown in Figure 12 (a). However
the mud wall collapsed in vibration tests and the load decrease as much as
7kN in actual when the whole frame of specimen 2 deformed at about
50mm. Thus we modeled the restoring-force characteristic of mud wall
based on both results of material and vibration tests as shown in Figure 12
(b).
20

20

Shear force[kN]

Experiment
Model

15

15

10

10

5

5

0
0.00

Deformation angle[rad.]
0.02

0.04

0.06

0.08

0.10

Shear
force（kN）

Material test

Model

Deformation angle（rad.)

0
0

0.025

0.05

0.075

(b) The model for the(a) Material test result
analysis
Figure 12: The restoring force of characteristic of Mud wall

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3.2 Analysis results
Figure 13 shows earthquake response analysis results compared withexperimental results of the relationship of load and displacement for wholeframe in each specimen. The input wave was BCJ-L2 100%. Damping
factor was 0.05. In both specimens, the analysis results almost corresponded
to experimental ones. It is clarified that the restoring-force characteristics ofcolumns, Koshinuki, Jinuki, and mud wall can be added.
Experiment
Theory15
1020

Experiment
TheoryShearforce（kN）

Shear force
（kN）

15
10

5

5

0
‐200

‐100

‐5

0

0

100

‐200

200

‐100

‐5

Deformation （mm）

0

100
200
Displacement （mm）

‐10

‐10

‐15

‐15

‐20

(a) Specimen 2(b) Specimen 1

Figure 13: The relationship between load and displacement of Mud wall
3.3 Analysis of the frame including different wall
Based on the model of specimen 1 and 2, we simulated the model withplywood wall instead of mud wall and conducted the earthquake response
analysis. Figure 14 shows the restoring-force characteristics of plywood
wall. It was assumed that the wall input between the columns, that is to saythat it did not cover the columns. Figure 15 shows the displacement of loadand displacement of the whole frame from the analysis. Input wave was
BCJ-L2 100%. We show the results of specimen 2 in the graphs for thecomparison as well. The deformation of whole frame with plywood wall
was smaller than one of specimen 2 as shown in Figure 15. Figure 16 shows
the displacement of load and displacement for Kumimon in each specimen.
The deformation of Kumimono in the frame with plywood wall was larger
than one of specimen 1 and 2. It can be assumed that the higher the stiffnessof wall is getting, the larger the deformation of Kumimono is.
25

Shear force
(kN)

20
15
10
5

Deformation angle（rad.)

0
0

0.02

0.04

0.06

0.08

Figure 14: The restoring-force characteristics of plywood wall
A study on the effect of wall stiffness on the vibration characteristics of traditional timber frames including
A study on the effect of wall stiffness on the vibration characteristics
Kumimono
7577
of traditional timber frames including Kumimono

October 2011, Chiang
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30 Shear force（kN）
25

Experiment(Speci
men2)
Theory

20
15
10
5
0

‐200

‐5 0

‐100

100
200
Displacement（mm）

‐10
‐15
‐20
‐25
‐30

Figure 15: Analysis results of the frame including plywood wall
30
Specimen 1

Specimen 2

0

10

20

-10

Theory10
Displacement (mm)

0
-20

30
20

10
Displacement (mm)

0
-10

Shear
force（kN）

20

10

-20

Shear Force
(kN)

30

Shear Force
(kN)

20

0

10

20

0
‐20

‐10

-10

-10

-20

-20

‐20

-30

-30

‐30

‐10

0

10
20
Displacement （mm）

(c) Specimen with plywood
wall
Figure 16: Load-displacement relationship for Kumimono in each specimen(a) Specimen 1(b) Specimen 2

4. CONCLUSIONS
Shaking table tests were performed using a traditional timber frame
consisted of columns having large diameter, Kumimono, Nuki. Specimens
were with mud wall and without one. The specimen was modeled on twomass model with springs of columns, Kumimono, Nuki and mud wall basedon the experimental tests and previous theory. We conducted the response
earthquake analysis with the model. Additionally we simulated the modelwith plywood wall instead of mud wall. The results were compared withspecimen 2 including mud wall. In the case of including plywood wall, thedeformation of Kumimono became larger than specimen 2 with mud wall. It
is clarified that the wall stiffness effect on the deformation of Kumimono.
REFERENCES
Ban, S., 1942. A study on the determination of the stability about main
hall structures, Vol. 3: a mechanical study on the Japanese Traditional
Frame, 1, the stability restoring force of a column. Papers of annual meetingof Architectural Institute of Japan, March, 252-258. (in Japanese).
Kawai, N., 1992. A study on the structural stability of traditionaltimber structures, Report of the Building Center of Japan, March. (inJapanese).

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Inayama, M., 1991. The theory of compression perpendicular to thegrain in wood and its application, Dissertation of the University of Tokyo.
(in Japanese).
Kato, K., Tsuwa, I., and Koshihara, M., 2008. Shaking table tests oftraditional timber frames including Kumimono Part 1 Experimental outline
and results, Summaries of technical papers of Annual Meeting Architectural
Institute of Japan, C-1, Structures III, pp.43-44 (in Japanese).
Tsuwa, I., Kato, K., and Koshihara, M., 2008. Shaking table tests oftraditional timber frames including Kumimono Part 1 Experimental outline
and results, Summaries of technical papers of Annual Meeting Architectural
Institute of Japan, C-1, Structures III, pp.45-46 (in Japanese).
Tsuwa, I., Koshihara, M., 2009. Shaking table tests of traditionaltimber frames including Kumimono - Modeling of horizontal resistanceforce -, USMCA 2009
RYONO, S., TSUWA, I., et al, 2010. Static Lateral Loading Test of
Bracket Complexes Used In Traditional Timber Five Storied Pagoda,
Summaries of technical papers of Annual Meeting Architectural Institute ofJapan, C-1, Structures III, pp.557-558, (in Japanese).

A study on the effect of wall stiffness on the vibration characteristics of traditional timber frames including
A study on the effect of wall stiffness on the vibration characteristics
Kumimono7599
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October 2011, Chiang Mai, Thailand

760

New Technologies for Urban Safety of Mega Cities in Asia

A new generation software for regulated
river system operations
Dushmanta DUTTA1,2, Wendy D. WELSH1,2, David NICHOLLS2,3
and Shaun KIM1,2
1
CSIRO Water for a Healthy Country National Research Flagship,
CSIRO Land and Water, Australia
2eWater Cooperative Research Centre, University of Canberra, Australia
3
DA Nicholls Pty Ltd, Nicholls, ACT, Australia
E-mail for correspondence: dushmanta.dutta@csiro.au
ABSTRACTThe eWater Cooperative Research Centre of Australia has recently
developed a new generation software package called Source Integrated
Modelling System (Source IMS), which allows a seamless integration ofcontinuous rainfall-runoff and river system models for operational andplanning purposes. The Source IMS provides tools for the prediction andquantification of water and associated constituents from catchments to theestuary. It has been designed and developed within Australia to provide atransparent, robust and repeatable approach to underpin a wide range ofwater planning and management purposes. It can be used to develop water
sharing plans and underpin daily river operations, as well as be used forassessments on water quantity and quality due to changes in, i) land use &climate ii) the influence of demands (irrigation, urban, ecological) and iii)
infrastructure types (weirs storages, reservoirs); iv) the influence of various
management rules that may be associated with these, as well as v) the
impacts of all of the above on various ecological indices. The model can be
configured in either a spatial, or schematic layout, depending on therequirements of the modelling situation. Source IMS includes three modes
for building project scenarios for various applications. One of those is theRiver Operations mode, which has been designed for improving daily andseasonal operations of regulated river systems. The paper introduces the
Source IMS and discusses the key features and functionalities in River
Operations mode.
Keywords: Source IMS, river system modelling, river operation, Murrayriver system
1. INTRODUCTION
Many of the large river systems around the world are highly regulated withnumerous physical flow control and storage structures as well as a range ofwater sharing rules and regulations. Operation of a regulated river system
involves directing releases from storages and controlling diversions of waterfrom the river for irrigation, agricultural and environmental uses, and for7611

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consumers in urban areas. River operators of large regulated systems are
increasingly facing complex challenges in operations due to a range ofissues including: rapid growth in urban and agricultural sectors,
environmental mandates, recreational interests, hydropower generation,
over-allocation, changes to land-use, climate change, and the fragmented
nature of available information. The operational decisions take a range oftechnical considerations under different hydro-climatic conditions such as
flow requirements, water level changes, estimated evaporation, forecast
rainfall and the water-carrying capacity of the river at various locations forbalancing competing objectives such as structural safety and maintenances,
water orders, water security, water trade, environmental outcomes,
navigation and recreation (MDBA 2011). River system modelling plays a
key role in the operational decision making process.
In most of the countries around the world, river operations havehistorically utilized a diverse set of software tools in its decision-making
and reporting processes (Carron et al. 2010). These tools require significant
manual manipulation of data, are sometimes inconsistent, and do not always
consider a priori all of the institutional constraints and policies in thedecision-making process because such tools were not designed for planningpurposes. For example, river operators in Australia have been using
spreadsheet-based software for day-to-day river operations. Such tools are
entirely dependent on input from an experienced user familiar with thenuances of the river system being modelled. Current operational tools inAustralia model the river system in a manner that is distinctly different fromthe long-term planning tools used to develop water sharing plans. This
creates a number of inconsistencies between the planning and operational
management of river systems (Bridgart and Bethune 2009).
As demands on river systems have increased, and spurred on by aprolonged drought in southeastern Australia, the need to accurately accountfor policy and legal constraints in the decision-making process has grown. It
has become increasingly important to operate the system more efficiently
and to ensure that operational decisions appropriately reflect rules andpolicies. There is an increasing need for a new suite of river system
operational models that have a more robust decision-making foundation forreservoir and river operations, which more accurately reflects water rights
and operational policies in the decision-making process. Such tools should
allow comparisons of water orders with actual diversions, forecast inflows
with actual river gains, and environmental target operations with actual
deliveries. A review of the user requirements for a river operational tool
undertaken by Nicholls (2006) shows that no existing operational tools inAustralia meet the key user requirements. End users of these models havealso expressed a strong desire for a tighter link between operational andplanning tools, based on river management models (Nicholls 2006).
There have been significant improvements in quantitative forecasts ofprecipitation by numerical weather prediction models in the recent years(BoM 2010). This brings an opportunity to improve short and medium term

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streamflow forecasts for river operations by integrating rainfall-runoff
models with the river system operational tools (Dutta et al. 2011).
The complexity and diversity of challenges faced by water
management organizations highlight a need for new modelling tools to
assist in decision making for operations of regulated river systems to not
only meet today’s needs, but tomorrow’s as well. To meet these needs, a
new software package called ‘Source Integrated Modelling System (IMS)”
is recently developed by the eWater Cooperative Research Centre (CRC) of
Australia in collaboration with several of its research and industry partners.
River Operations is one of the three modes of the software, which canbe used to underpin daily river operations to support the efficientmanagement of water storage, flow and delivery in regulated river systems.
The paper introduces the Source IMS and discusses the key features andfunctionalities of the River Operations mode of the Source IMS.
2. SOURCE INTEGRATED MODELLING SYSTEMThe Source IMS is designed as a transparent, robust and repeatable tool tounderpin water planning and management in complex regulated andunregulated river systems. It provides tools for the prediction andquantification of water and associated constituents from catchments to theestuary. The components used to model regulated rivers within the Source
IMS encompass (and enhance) the key functionalities of the three widelyused river system modelling tools in Australia: IQQM, REALM and MSMBigmod, as well as new scientific research. The Source IMS is an evolutionof the E2 catchment modelling framework (Argent et al. 2009), which itself
is built upon the general purpose TIME framework (Rahman et al. 2003).
TIME is an environmental software library designed to support
environmental modelling applications. The physical and regulatory
processes and management rules of a regulated river system areconceptualised in seven major components within the Source IMS
simulation engine: i) Catchment runoff; ii) River system network; iii)
Interactions between river and groundwater systems; iv) Water quality; v)
River regulation and storages; vi) Demands (urban, irrigation andenvironmental) and vii) Complex river management rules. Each of theseincludes several subcomponents to comprehensively represent theunderlying processes, rules and regulations. The various components andtheir functionalities are elaborated in Welsh et al. (2011).
The system as a whole is extensible through expression editor andplug-in (eWater 2011, Kim et al., 2011) functionalities, which can modify
either the simulation engine or the application user interface. A plug-in is asection of computer code compiled as a DLL (Dynamically Linked Library).
Plug-ins can be used to add new modelling components to Source IMS thatare not otherwise available in the system.

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The Source IMS includes three scenario modes: catchment runoff (hereaftertermed Source catchment mode), river management (hereafter termed
Source RM mode) and river operations (hereafter termed Source RO mode).
Source Catchment mode includes a conceptual rainfall runoff (RR)
modelling framework for estimating catchment water yield and runoff
characteristics. Source RM mode, which includes a conceptual river systemmodelling framework using a node and link concept, is designed primarily
for use in the consideration of long-term water resources planning andmanagement issues using historical data. Source RO mode is primarily
designed for river system operators to forecast and route flow for daily river
operations. Source RO mode uses same underlying node and link river
network definitions and calculations as the Source RM mode to define andparameterise the river system being modeled. In the node-link system, ariver network begins and ends with a node, and all nodes are interconnectedby links. Runoff is fed into the network as an inflow at the relevant locationin the network. Links represent a length of stream and are used to transfer
flow and constituents between nodes, with or without routing andtransformation. Lag time and storage routing concepts are used in links forrouting. The length of a link can be zero for near coincident processes.
Nodes represent a physical location along a river where flow and water
quality constituents either enter the system or are stored, extracted, lost or
measured, and can be used for the application of management rules. The
details of links and nodes and their functionalities are elaborated in Welsh etal. (2011).
2.1 River Operations using Source IMS
There are many features and functions in the RO mode of Source IMS
that allow the presentation of system behavior more realistically andaccurately, leading to improvements in water resources management andwater delivery. Some of the major features and functions are briefly
explained here.
2.1.1 Graphical user interface
The Source RO mode has a robust graphical user interface (GUI) thatallows river operators to interact with the underlying complex computercode and view and analyse model output. The GUI includes two views:
schematic and tabular editors.
i) Schematic editor
The schematic editor is used to construct a river system network by
selecting graphical icons representing system components (nodes and links
and their attributes) and run the software for the user-defined scenarios.
Figure 1 shows a schematic view of a river system operational model built
using the schematic editor.

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FigureFigure1: A1:
snapshot
A snapshotof a ofriver
a riversystemsystemoperation
operation
model
model
builtbuilt
in Source
in Source
RO RO
mode
mode
ii) Tabularii) Tabular
editoreditor
The Thetabulartabulareditoreditorpresents
presents
a tabulara tabular
viewviewof temporalof temporalobserved
observed
datadata
and andpredicted
predicted
results
results
at everyat every
node.
node.
ThisThisallowsallowsan anoperator
operator
to tosimultaneously
simultaneously
looklook
at bothat bothtemporal
temporal(y axis,(y axis,columns)
columns)
and andspatialspatial(x axis,(x axis,
rows)
rows)
aspects
aspectsof theof riverthe riversystem.
system.
TimeTime
is represented
is represented
withwithobserved
observed
datadata
at at
the thetop toprunningrunning
down
down
to theto thepredicatedpredicatedfuturefuturedatadata
below.
below.
The Thevariousvarious
network
network
elements
elements(nodes(nodesand andlinks)
links)
are listed
are listed
as a asrow
a row
fromfrom
upstream
upstream(left(leftside)side)
and andheading
heading
downstream
downstream(right(rightend).end).
Users
Users
are also
are also
given
given
the ability
the ability
to torearrange
rearrange
the columns.
the columns.
The Theviewview
providesprovidesthe individual
the individual
datadata
points,points,which
which
are ofareinterestof interest
to operators,
to operators,
in anineasily
an easily
accessible
accessible
way.way.
A snapshot
A snapshotof theof thetabulartabulareditoreditoris shown
is shown
in Figurein Figure2. The2. Thetabulartabulareditoreditoralso also
allowsallowsthe userthe userto toaccessaccessand andconfigureconfigurethe theunderlying
underlying
modelsmodelsfor foreacheachof theof thenetwork
network
elements.
elements.

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RegulatedRiver
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systemoperations

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Figure 2: A snapshot of tabular editor of a river system operation model
2.1.2 Daily Operation
The Source RO mode can be used for daily operations to model
alternative storage release patterns and weir pool operations. It allows users
to estimate an optimal operating scenario for a storage release whilesatisfying all the short-term system demands, and adhering to any operating
rules in place for the system under the set of forecast conditions. Users canreconcile data collected from the field on a daily basis against the model
predictions, and if necessary, reconfigure the inflow, demand or
unaccounted difference forecasts to reflect the system behaviour that iscurrently being observed.
2.1.3 Seasonal Operation
The planning of seasonal operations is especially critical where asystem has one or a combination of channel capacity constraints, en-routestorages, parallel storages, compressed demand periods or large volumes ofwater to transfer. The Source RO mode can be used for seasonal operations
to analyse system responses for a given level of resource allocation under anumber of possible climate conditions and to investigate system behavior interms of storage levels and flows, making sure the system has the ability tosatisfy demands across the full delivery period. In general, users review
extractions to date, storage levels and unaccounted differences on a monthly
basis, and depending on these results, might increase allocation levels andmodify operating plans for the remainder of the season.

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2.1.4 2.1.4
Data Data
ImportImportInterface
Interface
For any
Forriverany river
operation,
operation,
river river
operators
operators
need need
to usetoinput
use input
data fromdata fromaarangerangeof differentof different
sources.
sources.
Data Data
sourcessources
couldcould
vary fromvary fromindustryindustry
databases
databases
such suchas Hydstra,as Hydstra,
to text
to filestext files
and web
and web
services.
services.
The Source
The Source
RO modeRO modeincludesincludesa usera interface
user interface
capablecapableof supportingof supportinginteractions
interactions
with somewith someof theof thewidelywidelyused used
databases,
databases,
namely:namely:Hydstra,Hydstra,
MySQL
MySQL
and Oracle
and Oracle(Figure(Figure3). 3).
ThroughThroughthis interface,
this interface,
the software
the software
allowsallows
users users
to import
to import
data fromdata fromthese these
databases
databases
and converts
and converts
to a standard
to a standard
formatformatfor modelling.
for modelling.

FigureFigure3: GUI
3: forGUIimportingfor importingtime series
time series
inputsinputs
from fromstandard
standard
databases
databases
2.1.5 2.1.5
Forecast
Forecast
modelsmodelsBoth Bothobserved
observed
and forecast
and forecast
data data
are required
are required
for aforriver
a riversystemsystemoperation.
operation.
Forecast
Forecast
data, data,
whichwhichrefersrefers
to thetoprediction
the predictionof futureof futureoccurrences
occurrences
for any
forvariable
any variable(e.g., (e.g.,
inflowinflow
and demand)and demand)in theinsystem,
the system,
can becangenerated
be generatedusingusing
variousvariousmathematicalmathematical
forecast
forecast
models.
models.
Forecast
Forecast
modelsmodelsrangerange
in incomplexity
complexity
from from
simplesimpleregression
regression
modelsmodelsto moreto morecomplexcomplexmodelsmodelsthat usethat use
data suchdata assuch
rainfallas rainfall
predictions
predictions
to approximate
to approximate
futurefuture
tributary
tributary
inflows.
inflows.
The TheSourceSourceRO modeRO modeprovidesprovidesusers users
with several
with several
options
options
to incorporate
to incorporate
forecast
forecast
models.
models.
For any
Forgiven
any given
forecast
forecast
variable,variable,
SourceSourceRO modeRO modecan include
can include
multiple
multiple
forecast
forecast
models.
models.
The first
The model
first model
can generate
can generate
a forecast
a forecastof theofnear
the futurenear future(typically(typicallyone week
one weekout) andout)theandsecond
the second
generates
generates
a forecast
a forecast
from fromthe endtheofend of
the first
theonwards.
first onwards.
This enables
This enables
the userthe touser
specifyto specify
a suitablea suitablemodelmodel
for useforinuse in
the immediate
the immediate
future,future,such suchas a simple
as a simple
regression
regression
modelmodel
to predict
to predict
streamstreamflow, flow,
and toandthento revert
then revert
to a model
to a model
whichwhichmightmightuse historic,use historic,
monthlymonthlyor orseasonal
seasonal
averages
averagesto produce
to produce
its forecast.
its forecast.
A snapshot
A snapshotof short-termof short-termwaterwater
demanddemandforecast
forecast
usingusing
three threedifferent
different
forecast
forecast
options
options
are shownare shownin Figurein Figure
4. 4.
SeveralSeveraldemanddemandforecast
forecast
modelsmodelsare built
are built
into Source
into Source
RO modeRO modeto toforecast
forecast
irrigation
irrigationand environmental
and environmental
demands.
demands.
SourceSourceRO modeRO modealso allows
also allows
users users
to incorporate
to incorporate
user-specificuser-specificforecasting
forecasting
techniques
techniquesthroughthrough
expression
expression

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editor and plug-in functionalities. Streamflow forecasts from unregulated
catchments by RR models in the Source Catchment mode can also be linked
to a Source RO project scenario.
Recently, Dutta et al. (2011) undertook a case study using the Source
RO mode for a comparative evaluation of streamflow forecasting by threetime series based linear models and a suite of RR models in two selected
unregulated sub-basins in the upper Murray River system of the MurrayDarling Basin. The study showed that third party forecast models, such as
linear time series models, can be efficiently plugged into the Source RO
mode using the expression editor functionality of the software. The
outcomes of the case study demonstrated that a well calibrated RR model
can provide accurate forecasts when using high quality quantitative
precipitation forecasts. With a suite of six RR models and a combination of
objective functions and optimization methods for calibration of thesemodels in the Source catchment mode, Source IMS can be effectively
utilised for improved streamflow forecasts for river operations.

Figure 4: A snapshot of short-term water demand volume forecast using
three different forecast options and actual volume of water ordered
3. DISCUSSION
The paper has introduced the new generation software package: Source IMS,
and described the functionality and applicability of the Source RO mode for
improving daily and seasonal operations of regulated river systems in the
21st Century.

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The RO mode of Source IMS represents a significant and positive
advance in daily and seasonal river system operations modelling through the
integration of catchment flow simulation, river planning and operational
tools into a single software platform. The software is a transparent, robust
and repeatable tool to underpin water planning and management. It provides
an opportunity to use new forecast tools based on recent advances in climate
science and water engineering for improving the efficiency of river
operations.
With the tailored interface of the Source RO mode, the ability todynamically calibrate RR models and plug-in functionality to incorporate
third party forecast techniques, the Source IMS fulfils the need of an
integrated system to support river operational decisions. It is expected that
this new generation package will contribute to improved decision-making inriver operations, leading to increased economic benefits through more
efficient water allocations.
REFERENCES
Argent, RM, J-M Perraud, JM Rahman, RB Grayson and GM Podger(2009). A new approach to water quality modelling and environmental
decision support systems, Environmental Modelling & Software, 24(7):809818.
BoM (2010). Operational implementation of the ACCESS Numerical
Weather Prediction systems, NMOC Operations Bulletin No. 83, Bureau of
Meteorology, Australian Government, 34p.
Bridgart, RJ and M Bethune (2009). Development of RiverOperator: atool to support operational management of river systems, Proceedings of the
18th World IMACS/MODSIM Congress, Cairns, Australia 13-17 July 2009,3782-3788.
Carron J, D Walker, K Wheeler, G Saunders, R Brown (2010). The
Lower Colorado River Authority Daily River Operations Model,
Proceedings of the 2nd Joint Federal Interagency Conference, Las Vegas,
NV, June 27 - July 1, 2010.
Dutta D, W Welsh, J Vaze, S Kim, D Nicholls (2011). Improvement
in short-term streamflow forecasting using an integrated modelling
framework, International Congress on Modelling and Simulation, MODSIM
2011 (in press).
eWater (2011). How to write a Source plugin. eWater CRC, Canberra.
46p.Kim S, D Dutta, R Singh, J Chen and W Welsh (2011). Providing
flexibility in GUI-based river modelling software - Using plug-ins to create
Custom Functions in Source IMS, 2011 International Congress on
Modelling and Simulation (MODSIM 2011) (in press).
MDBA (2011) River Murray System Annual Operating Plan 2011-12,
Murray—Darling Basin Authority, Canberra, MDBA Publication No.
211/11, 55pages.
Nicholls, D (2006). River Operations and Management (ROM)
Products, River operations tools and guidelines (P1). eWater CRC, Canberra,
Australia.
A new
New generation
Generationsoftware
Softwarefor
forregulated
RegulatedriverRiver
SystemOperations
Asystemoperations

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Rahman, JM, SP Seaton, J-M Perraud, H Hotham, DI Verrelli and JR
Coleman (2003). It’s TIME for a new environmental modelling framework.
Proceedings of MODSIM 2003, 4: 1727–1732.
Welsh, W, J Vaze, D Dutta, D Rassam, J Rahman, I Jolly, P Wallbrink,
G Podger, M Bethune, MJ Hardy, J Teng, J Lerat (2011). An integrated
modelling framework for regulated river systems, Environmental Modelling& Software (in review).

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NewEnvironmental management in Cambodia
case study: Community forest governanceat local context
Ham KIMKONG
Senior lecturer and Researcher of the Royal University of Phnom Penh,
Department of Environmental Science
Cambodiakimkongham@yahoo.com
ABSTRACTThis paper discusses about environmental management in Cambodia,
particularly a case study on community forestry governance at local context.
In ecological perspective, forest plays very important role and help toprotect the soil erosion, stabilize the watershed and regulate water flows
and weather system. Cambodia is particularly dependent on its forest
system due to the unique hydrological system of Mekong River and Tonle
Sap Lake. From economic point of view, forest is considered as one of thecountry’s most valuable economic assets that provide an important sourceof revenue. Both forest resource and institutional contexts are either
enabling or constraining the construction of well-being of people incommunities as well as urban residents. In particularly, this paper
demonstrates that the Upper Mekong basin ecological systems provide
fisheries and forestry resources on which a great number of people living in
the along the Mekong area (O'svay village) have been sustaining their living.
However, the forest resource is not only important for local people
livelihoods, but also a source of income of the state and private logging
firms. Competing for logging in which amongst different parties have been
mounted, resulting the destruction of forest resources and environmental
disasters. The erosion of forest resources, the growing scarcity of forest
product will directly result on the livelihoods, especially lowering wellbeing of the poor which lead to migrate out to cities. Have seen issues,
Royal Government of Cambodia (RGC) has taken action to reform forestry
policies, established new forestry law, giving more rights to access forest
resource, and more roles to protect forest resources to "Community
Forestry Management". Albeit such policy reform and new forestry law
received a national political supports, this policy and law has not yetmaterialized, especially al local forest governance level. This paper showschanges in exchange and mobility between two ecological regimes in which
livelihoods of forest resources—communities are likely to be affected
negatively. People from outside have migrated into the areas for overexploit/harvest resources, grabbing lands. This has increase tension on theuse, conflict interests and destruction of forest resources significantly.
Livelihoods of people in community forestry are therefore at jeopardy.
Keywords: Governance, Conflict over Natural Resources, Migratioon7711

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1. HISTORICAL BACKGROUND
Generally, Cambodia forest cover to have up to 73% of the total country
lands in 1970s. However, according to Forestry Administration (FA) 2004shows that this figure, has reduced down to about 58% to 60% of total land
cover area corresponding to approximately 10.7 million hectares.
Referring to FA recently has conducted several studies and reported
that the net annual rate of deforestation was estimated as 0.5 per cent during
the period 2002-2005/06 representing a significant decrease compared toearlier estimates. According to the forestry outlook 2020 shows that
Cambodian Millennium Goals aim to maintain forest cover at 60% by 2015.
However, the forest outlook illustrates that there are some challenges anddifficulties such as an insecure title over forested land and unclear rights touse de facto open access forest resources mitigate efforts to maintain theforest cover, to secure livelihoods or to contribute to rural economic growthin Cambodia( Forestry outlooks, 2008).
This situation reflects a lack of coherence in rural land management
policies, weak capacities of sub-national sector line agency departments,
poor service delivery mechanisms and the limited involvement of rural
land and resource users in formalized natural resource management
procedures. The key challenges in the sector are the need to ensuresustainable management and equitable use of forests, to improve rural
livelihoods, and to promote a balanced socio-economic development in
Cambodia. Past forest management systems have not contributed sufficiently
to these broad policy objectives (Forest Outlook, 2008). The Forest
Administration (FA) is the key government agency in the forestry sector in
Cambodia. There are also a large number of other actors including forestdependent rural communities, Development Partners (DPs), investors andinternational and national Non Governmental Organizations. In 1998 theRoyal Government of Cambodia (RGC) initiated the forestry reform processby establishing a national committee on forest policy reform with support
from DPs.
In 2002, the secretariat of the committee formulated a national forest
policy statement. Subsequently, a new Forest Law was promulgated in
2002, and a new Forestry Administration was established in 2003
(replacing the former Department of Forestry & Wildlife). A temporary
Joint Coordinating Committee, representing RGC and DPs, and chaired by
the Minister of MAFF, commissioned an Independent Forest Sector
Reviewin2003,(availableat
http://www.cambodia-forestsector.net/index.htm). In 2004, the RGC established a Technical
Working Group on Forestry and Environment (TWG-F & E) to
provide a mechanism for government-DP coordination to support andstrengthen development activities within the sectors ( www.twgfe.org). As
a result, a four-year Forestry and Environment Action Plan 2007-2010 and
one-year Framework Work Plans and Indicative Budgets for 2007 and2008 have specified 26 prioritised activities within six prioritized
programmes of National Forestry Planning (NFP). The national forestry

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planning aim at assisting FA’s efforts to promote sustainable and equitable
forest management in Cambodia i n p e r i o d o f 2008-2020.
2. FOREST MANAGEMENT AND CONSERVATION
Brief of Forest Policy Formulation
Since the 1980s the forestry sector has been reformed and createdunder the Ministry of Agriculture and Forestry and Fisheries, such as Subdecree, regulation and laws after Khmer Rouge regime. First, Sub-Decree(Kret-Chbap) No. 35 entered into force in 25 June 1988 and had been
implemented up until 2002, to manage and control forestry sector activity.
To Compliance with main regulations, following there has been a bunch offorest regulations issued and established (Forestry Outlook, 2008),• In 2006, Royal Decree on the establishment of the National
Authority for forestland• conflict resolution was set up. The National Authority plays role inidentifying illegal• forestland encroachment of state forest.
• Sub-Decree on the Forestry Sector:
Table 1: Sub-Decree and regulations, Law on the Forestry Sector

Date
In 2003

Early, 2003

Institutional function
Re-structuredof
Department of Forestry andWildlife entered officiallyrecognition as Forestry
Administration (FA)
EstablishmentofCommunity Forestry SubDecree.

2004

Elephant
corridorinsouthwestern Cardamom
Mountain. It has beencreatedbyNGOscollaborated with FA.

2006

Convention
International
Endangered(CITES).

2000

ForestConcession
Management Sub-Decree
Declaration (Prakas)

2004

of
Trade inSpecies

Key roles and responsibilities
Management of forest land covers. Protecting
and controlling illegal forestry activities.
National Forestry planning strategy.

The community forestry Sub-decree plays a
key roles and empower to deliver
decentralization of forest governance andmanagement from central to
local
communities, to manage and use forest
resource sustainability and effectively.
As a result, since 2006 reported that in wholecounty, there are 264 communities forestry
has been established.
The areas of the corridor used to be under
forest concession. As the areas are important
for local communities and wildlife
conservation, elephant, the FA and its
partners, WildAId, seeking approval of thePremier to have the areas for special
protection and community development.
CITES was introduced to Cambodia in early
1990s and Cambodia became member of the
CITES in 1997. It plays to conserve andprotect endangered species in particularplaces such as Tonle Sap, Upper Mekong…
etc.
To manage and use forest resource insustainability.
Mother Tree Seeds (2004)

Environmental management
Environmental
management inin Cambodia
Cambodia case
case study:
study: community
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Endangered tree species banned classification(2005)
NTFPs classification and rights of their use(2005)
1996.

Prohibition on Export ofRound Logs and Sawn
Wood from the Kingdomof Cambodia

No dateNational Forest Statement

Having seen that processing of round logs in
the country could provide more jobs and savewood materials, the RGC declared that export
wood could be permitted unless sawn. Exportof all kinds of round logs from Cambodia had
been prohibited.
Take into consideration of sustainable
development, good governance, poverty
alleviation, environmental protection, andequity benefit sharing compliance with the
1992 Rio de Janeiro declaration of the United
Nation Conference on Environment andDevelopment(UNCED)inforestmanagement and biodiversity conservation.

Source: Forestry Outlook, 2008

3. THE HISTORY OF FOREST GOVERNANCE
The Concept of Forest governance has been emerged through various
regimes with different system aspects. Many studies shown that theforestry sector started its management systems in 1898 since of French
protectorate ruling Indochina and Cambodia, however, at that time before
the French management initiative forest and non-forest products uses werecompletely free of control. It is because of the use of forest resources as incommunity and domestic scale for substitute purpose only (FA, 2008).
Then, the French strict forest management rules in Cambodia have applied,
however, confronted with traditional uses. Since then, the forest governancesystem which set up by France, had been continuously implemented till theearly 1970s by then the country entered into civil unrest and civil war. The
French forest management system had considered as centralized
governance because the center made all decisions in regard to forest
exploitation, rehabilitation, and or plantation.
During the 1970s to 1980s forests, part of civil war, the country has
difficult to control resources, particular, and natural resources, therefore,
there was no proper and legal government control on forest sector. Even
more, in Khmer Rouge, public sectors were under absolute decision of theleader of top ranking people (Angkar or Organization). It was hard toknow clearly about how the top lead decision making on using andmanaging of natural resources due to very limited studies and document
shown. It was seemed that the forest management system was even more
top- down approach. People Republic of Kampuchea, and later on called
State of Cambodia (1979-1993), was a communism management regime.
During that time Cambodia forests were under central decision annual
timber harvest plans. With technical recommendations of the Department ofForestry and Wildlife (DFW) and the MAFF, timbers and non-timber forest

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products (usually timber only) were exploited according to the central
government plans. Again, this system of forest management was central
governance with annual or five-year plan (FA 2004).
Significantly, in 1990s, the system of forest governance was changed.
New forest management approachwas
introduced
into
forestmanagement system in 1993. In 2001 all forest concessionaires wererequired to develop Strategic Forest Management Plan (SFMP) for forest
concession management and by the communities were involved in theprocess of forest management. In addition to the involvement ofcommunities in forest management, communities have been given rights
to establish their community forestry (CF) that located near communes orvillages. Very recently, in 2003, CF Sub-Decree was ratified and enteredinto force trough out the country. This is shown that some level ofdecentralized governance of forestry management system has been
introduced into the Kingdom of Cambodia (FAO, 2006). According toHeng, (2007) study shows that forest management and governance havebeen noticeably improved. In 2006 the National Forest Programme wasestablished under technical and financial support from Danida, DEFID, NZ,
and FAO. It is developed under new model that is broadening as many
stakeholders as possible including inter-ministerial, private, and civilsociety to participate in policy development and planning (Sokh Heng,2007).
4. SUSTAINABLE FOREST MANAGEMENTWith the increase of both technical capacities, number of skilled staffs that
supports from regional and international cooperation in forestry sector.
Royal government of Cambodia, especially, Forestry Administration had
put its efforts to improve sustainable forest management by establishing ofmost important guidelines, regulations and forestry laws s u c h a s :1. Forest management guidelines including Reduce Impact Logging
and forest concession monitoring guidance;
2. Code of practice for forest harvesting (1999), officially bound;
3. National Forest Statement (2002);
4. Sub-Decree on the Request of Master management plans of alllegitimacy forest concessions (till present);
5. Ministerial declaration (Prakas) on Seed Source Siteestablishment. (FA, 2008)
But it is remarkable that to make sustainable forest management is agreat challenge and difficulties which FA had faced, like in many othercountries, due to a variety of influenced factors such as high population
growth caused to forest degradation and deforestation, high timber market
demand, and expansion of agricultural and settlement lands. In addition,
currently, economic land concessions, forestland concessions to agroindustrial crops have been granted widely in the country. According to manystudies recently shows that there is approximately 6 percent of country
Environmental management
Environmental
management inin Cambodia
Cambodia case
case study:
study: community
Communityforest
forestgovernancegovernanceatatlocal
localcontext
context

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Chiangmai,

forest-land has been allocated for economic land concessions throughout
country. Nevertheless, MAFF permitted agro-industrial lands only on
already degraded forestlands in order to develop country economics andcontribute to rural poverty alleviation (Sokh Heng, 2007).
5. COMMUNITY FORESTRY ESTABLISHMENT
Background of Community forestry Set Up
Community forestry establishment in Cambodia had been introduced
and initiatively established by international NGOs, as known Concern
Worldwide and the Mennonite Central Committee, in the early 1990s at a
few pilot sites in two provinces (Takeo and Kampong Chhnang) (Sokh &Iida 2001:116; Braeutigam 2003:8). Community forestry then grew rapidly
as of 2002 there were approximately 83,000 ha under introduced community
forestry management, representing 0.7% of Cambodia’s total forest area
suitable for community forestry. According to Fichtenau 2002 shows thatarea of community forestry encompassed 57 initiatives at 22 sites, andcomprising 404 villages and 415,000 people (3.6% of Cambodia’s
population). These sites were situated in 18 of Cambodia’s 24 provinces,although most of these sites are concentrated in agricultural areas, wheremost of Cambodia’s population is found. In relation to this, the objectives ofcommunity forestry creation are to protect and rehabilitate sustainable usesof forestry resources. The use of these forests is limited to the collection of
NTFPs and firewood, so income generation in the medium term is likely to
be very limited, according to Braeutigam (2003:41).
McKenney & Tola (2002:97) shown that the Ministry of Agriculture,
Forestry and Fisheries had the authority to allocate an area of Permanent
Forest Reserve to a community or a group of people, and the cantonment
chief of the Forest Administration had approved mandate for the period of
15 years for community forestry agreements. However, for the Community
Forest Management Plan governing will be revised every five years(Braeutigam 2003:11). The FA plays very important roles and direct
responsibility for sites on production forest lands, whereas the Ministry for
the Environment has responsibility for sites in protection forests.
6. COMMUNITY FORESTRY CHALLENGE AND DIFFICULTIES
Many studies have shown that community forestry system faces several
problems and challenges as the community forestry aims at improving the
local livelihoods of villagers who depends on collecting non-timber forestry
products for their survival condition only. Furthermore, the challenges areincluding a tendency toward conflict which are related in part to unclear andinsecure tenure and lack of land use planning; a lack of benefit sharing
arrangements; and weak government finances and capacity in support of thesystem (Forestry outlook, 2008). According to Fichtenau, et al, 2002,
indicated there are key main of conflict occurred in community forestry arefollowing such as, conflict among villagers and villagers of un-equality of6776

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forest resource used, conflict between outsiders (military, commercial
enterprise, agriculture and forestland concession) with communities of
unclear boundary demarcation between forest concession and community
forestry boundary, and conflict including distrust of forest authorities…etc.
Another difficulty for the community forestry is late of endorsement
and approval from government agency because of some unclear condition
such as unclear community forestry boundary, conflict over overlapping
demarcation frontier between commercial forest land concession withallocation of community forestry areas, (Braeutigam, 2003:2 & 26).
Financial resources and personal capacity are most difficulties andchallenges for community forestry as most of community forestry set up isheavily dependent of external foreign assistances and local and international
non-governmental organizations.
7. A CASE STUDY ON FORESTRY GOVERNANCE AT O’SVAYCOMMUNITY FORESTRY INITIATIVE
The case study is a part of course field based teaching which implemented
by the Department of Environmental Science, Royal University of Phnom
Penh. The study explored and observed how local villagers formed andestablished their natural resource to be own common property throughcreation for community forestry management. In addition, the study
emphasizes on teaching competition over natural resources in Mekong, inforestry resource at local level in particularly O’svay community,
Thalaboriwat District, Stung Treng province. This case study is acomplementary field base practice with courses in which regular teaching in
the classroom. It also aims at bringing the students to learn and explore
about what and why the conflict over natural resource have been occurred
such as over-exploited fishing, illegal logging and land use grabbing,
especially forestry resource competition between local community, private
forest land company and powerful business.
8. BACKGROUNDMANAGEMENTOFO’SVAYCOMMUNITY

FORESTRY

Historically, O'svay community is located along upper Mekong River, andadjacent to Cambodia-Laos border shared, within Thallaboriwat district,
Stung Treng province. Most of populations have been migrated fromdifferent provinces, under the state policy to protect Cambodia border line.
It reported that they are retired soldiers and government officers during
Sang Kumreas Niyum since 1962. In meantime, individual household was
divided a pieces of land for their cultivation and subsidy from the State.
Currently, they have been living in O’svay community and formed up tovillage. Now there are 5 villages in O’svay commune, living with mixed
Khmer, Kuy (ethnic minority) and Laos who are evacuated from neighborarea during Pol Pot regime.

Environmental management
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management inin Cambodia
Cambodia case
case study:
study: community
Communityforest
forestgovernancegovernanceatatlocal
localcontext
context

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In past decades, the area was rich in natural resource, especially forest
and fish. Main occupation of villager is found that they totally depend on
agricultural based practices, collecting of non timber forest products andfishing activities for their livelihoods. However, it shown that O’svay
commune has rapidly changed and natural resources have been gradually
declined due to many factors influenced such as forestland concession,
rubber plantation investment and illegal logging and fishing activities in thelast recent decade. As a result, a lot issue and problem that communities
have challenged and coped with them and also faced difficulties such as
huge amount of losing natural forest resources for livelihoods. Natural forest
land conversion for commercial and cash crops and plantation, andindividual greedy powerful land grabbing are being sensitively taken places.
Obviously, the changes have however, increases of some families in thecommunities are vulnerable with losing more and more of natural resourcesin community. Fisheries resources provide such protein and food diet frommajority of communities have been dramatically decreased and declined.
Increasing of tension and more difficulties with their daily lives,
villagers sought out to find alternatives and helps therefore, in 2002, CEPA
is a local non governmental organization, conducted studied and found thatthe area has potential to set up community based natural management,
therefore, CEPA has offered technical assistances to enhance local people inO’svay commune, to start developing forestry community in some particularareas, in order that they would be able to maintain and protect, manage
remained natural resources for their internal management, protection andsustainable uses.

Students visited O’Svay CF,
O’svay commune encompasses five villages, namely O’svay, O’run,
Koh Phnov, Veun Sien, Koh Heb. These villagers have strongly committed
and agreed to set up community fisheries and forestry since 2002 withinitially assisting technical support by a well-known local non governmentorganization as CEPA. Until now these have been passed through somerequired steps principle to set up community establishment process such as,[1] dissemination of information and identify problems, [2] establish
committee by voting by all people in the 5 villages, [3] establish the internal
principle of the community, [4] map the boundary of the community. Even
though some communities have been passed significant steps, but members

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of committees
of committees
are arestill stillconcerns
concerns
howhow
to manage
to manage
thosethosecommunities
communities
in insustainable
sustainable
and andachievableachievable
ways,
ways,
when
when
the CEPA
the CEPA
has finishedhas finishedits mandate,its mandate,howhow
far faris strongest
is strongest
commitmentcommitmentof localof localvillagers
villagersin protectionin protection
and andpreservation
preservationof naturalof natural
resource,
resource,
becausebecauseof thisof thisareaarea
is currently
is currently
and andpotentiallypotentially
under
under
threatened
threatened
and andinfluenced
influenced
fromfromfeasibility
feasibilityof newof newdevelopment
development
paradigms
paradigms(development(development
corridors),
corridors),
commercial
commercial
investments
investments(natural(naturalforestforestlandlandconversion)
conversion)and andborderborderdevelopment
development
specialspecialeconomic
economiczone,…
zone,…
etc. etc.
MapMapof Areaof Area

Source,Source,CEPA,
CEPA,20072007

9. APPROACHES
9. APPROACHESOF THISOF THISSTUDY
STUDY
The Thecasecase
study
study
is partis partfieldfieldbasebaseteaching
teaching
activities.
activities.
There
There
are aresimplysimplymethods
methods
havehave
beenbeen
appliedappliedto obtain
to obtain
datadata
and andor information.
or information.
These
These
applicableapplicable
methods
methods
are areliteratureliterature
review
review
fromfrom
different
differentsources,sources,fieldfieldobservation,observation,
and andinformalinformal
group
group
discussion
discussion
duringduringover-nigh-home-stay.
over-nigh-home-stay.
• Information• Information
relatedrelatedto community
to community
forestry
forestry
management
management
and andgovernancegovernancefromfrom
different
different
reports.
reports.
SelectingSelectingparticularparticular
casecase
study
study
in in
which
which
writtenwrittenon theon theoverovernaturalnaturalresources
resources
and andkey key
actorsactorswhowhoinvolved
involvedin thein conflictthe conflict
and andforestry
forestry
management.
management.
ThisThis
process
processof ofsecondarysecondary
datadata
collection
collectionneedneedto getto involvement
get involvement
somesomeof students
of students
in orderin orderthat thattheythey
would
would
havehavelearnlearn
and andgaingainexperiences
experiencesin researchin research
capacity
capacitybuildingbuildingskills.
skills.
• Secondly,• Secondly,
fieldfieldobservation
observation
and andinformalinformal
group
group
discussion
discussion
werewereusedused
to getto getinformation
information
and anddatadata
relatedrelatedto how
to howtheythey
managedmanagedand andcontrolledcontrolled
theirtheirresources
resources
and andhowhowto they
to theyshareshareand andallocateallocate
naturalnaturalresources
resources
for sustainable
for sustainable
usesuses
and andmanagement.
management.
• Key
• Key
informants
informants
are arechosenchosensuchsuch
as village
as village
headheadman,man,locallocal
authorities,
authorities,
staffstaff
fromfrom
provincial
provincial
department
departmentof waterof waterresources,
resources,
and andenvironment.
environment.
• Participatory• Participatory
consultations
consultations
withwith
villagers
villagers
werewerealso also
conducted
conducted
duringduringthe field
the field
datadata
collection.
collection.
ThisThis
approachapproachusedused
aimsaims
at exploringat exploring
and andrecovering
recovering
existing
existing
on conflicton conflict
overovernaturalnaturalresources
resources
usesuses
and andcompletion.
completion.

Environmental
managementin Cambodia
casecasestudy:
community
forestforest
governanceat localcontext
Environmental
managementinstudy:
community
governanceatatlocal
Environmental
managementin Cambodia
Cambodiacasestudy:
Community
forestgovernancelocalcontext
context

9 7799October 2011, Chiang
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10. LESSON LEANT
O’Svay Community Forestry Governance Challenges• Local Villagers Challenge with Outsiders
Traditionally, villagers harvest and practice slash and burn farming,collecting non-timber forest products for their income and subsistence. They
have freely accessed to forest area without any interference and disturbance.
Some villagers have their own plots of land for cultivation farm and rice
within the forest areas.
Forests are an important source of food, medicine construction
material and income for rural population. Usually, local people use forest
products in their daily livelihood. However, some not timber forest products
are in highly demanded in both local and international markets, (Hirsch &Ahmed, 2002). In addition, the villagers hold the Baddish religion andbelieve in spirits to protect forest “ Prey Nakta--spiritual forest”. Therefore,
the forests are highly respected and recognized, when those forests destroy,
it results to harmful accident to local villagers get sick and or die. At thattime, the villagers live with their harmony condition with nature.
In 1994, a Flour Manufacturing Company1 has conducted feasibility
study in O’ Svay commune to seek for potential natural forest land to invest
for teak and cassava plantation. By 2001, the company has given andapproval by Ministry of Agriculture Forestry and Fisheries a forestland
concession with amount of 4,700 hectares inside evergreen-dense forest inwhich located in O’ Svay Commune, Thalabariwat district, Stung Trengprovince. Since then, the company has started cleared forest for exports andsmall proportion of land given to grow cassava plantation2.
Within forestland concession, there were 75 families who have theirsmall piece of farmlands. In early year that company came, those families
allowed cultivate their rice-farm and access to forest for collecting nontimber forest products. But gradually, the families have threatened andviolated by banning not planting and cultivating rice. The company has also
expended their activities and forest area. In early stage, the company has
promised to employ many local villagers to works with their company, but
until now there are not many villagers who have been recruited yet.
The company has very strict to villagers who have their rice field tocultivate and others to access forest for collecting non timber forest products
and other products within land concession boundary where areas thatvillagers used to collect. At the present, the conflict over natural resource isbeing increased gradually for example, state-land, forestland have been
grabbed and taken away by powerful business and companies. According to1

This company is a jointed shared- investment with Khmer- Chinese-Malay. It name is
Koe Vuthy flour Manufacturing Company, based in provincial town of Stung Trengprovince.
2
Villagers at O’ Svay reported and complained.

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some concerns raised by villagers during informal group discussion, foundthat:
Concerns:zVillagers are not confidential and they are so worry about the lost ofnatural resources as forest and fisheries in their commune as
currently many illegal logging and fishing occurs.
z
Rapid unclear planned investment and development might be
impacts on villagers and their communities in sense of loss theirlivelihoods.
zPresently many migrants have come to villages and they try tochange the traditional way of life of villagers.
z
Regarding to community forestry management and establishment,
local villagers still have limited their capacity building andsupporting from laws, regulation and sub-degree is taking place very
inappropriate way and low.
z
Unclear demarcation of boundary of forest area of company on the
ground which result causing to creating intention and conflict overnatural resource.
z
Most of villagers and committee needs more supports in order toenhance and strengthen legal committee structure, roles and tasks.
Economic incentive is very crucial for effective resource
management, but it is being challenging now in community forestry.
zMore concerns about potential investment for economic growthrather than conservation perspectives.
Local Response on Scarcity Resource Competition
The study shown that in 2002, the villages mentioned earlier haveformed and organized a peaceful demonstration to show their concerns
about their scarcity of resources that faced to villagers to make their living
condition and livelihoods. According to village statistically record showsthat 90% of population in village have depended on natural resources suchas forest, fish and non timber forest products for generating income on theirlivelihoods.
•

However, since, some companies have come to make investment by
converting natural forest to plantation, there were intention and conflict overresource use between company and villagers because, some villagers who
have their own farm areas existed in company land boundary, did not allow
to access into their farming for rice cultivation and also collecting nontimber forest product. As a result, villagers have organized movement toshow their demand and concerns against to the company. Since then, there
have no better/appropriated resolutions yet, local people complained thatthey face suffers from a limited forest area and not allowing to cultivate
their rice-farm in forest land concession.

Environmental management
Environmental
management inin Cambodia
Cambodia case
case study:
study: community
Communityforest
forestgovernancegovernanceatatlocal
localcontext
context

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Hand-drawing CF map of O’svay, 2002
Having seen problem, villagers have discussed among themselveswith facilitated and technical assistance from different agencies. Early 2003,
the villagers have proposed and requested land forest area within amount of
5,000 hectares, with good condition of forest covered area to establish
community forestry. The reason to set up community forestry aim at
protecting, preserving and sustainable use and management of existed forest
resources. Until now that community forestry area has yet been recognized
and approved from Forest Administration (AF), Ministry of Agriculture,
Forestry and Fisheries (MAFF). Villagers have seriously concerns andworry as forest area still has valuable and commercial timber trees because
the company has also attempted to get that area for their own forestland
concession. Therefore, MAFF since now has not yet responded to their
proposal since 2003 until 2006. Even though, their proposed community
forestry area approval yet and in order to protect illegal cutting tree andhunting from outsiders, villagers have divided up their roles and tasks
voluntarily to have patrol and guard regularly to curb-down an illegal
logging, wildlife hunting and other activities in their own. Below arevillagers having strong optimism on creating of Community forestry:
Optimism:z
They have very strongly commitment amongst villagers in social
capital spirits by giving their hands-in-hands; value times and efforts
to protect, conserve and manage the remaining of natural resources
such as forest resources.
z
Community Forestry now has gained a highly experience inmanaging and protecting and preserving value forest resources theirlivelihoods.
zSuccessful with supporting from local authorities and agencies,
NGOs and compliance with the Forestry Law, Sub-degree andothers… etc.

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11. CONCLUSION
This paper illustrates about environmental management in Cambodia,
particularly case study on Community forestry governance at local
perspectives and context. Rural population in O’svay commune particularly
depends on natural resources such as forestry and others for improving theirlivelihoods and quality of life. However, villagers have faced recently todestruction of forest resources and environment by many factors, as a result,the erosion of forest resources, the growing scarcity of forest product will
directly result on the livelihoods, especially lowering well-being of the poor
which lead to migrate out to cities.
To response this, Royal Government of Cambodia (RGC), especially
Ministry of Agriculture, Forestry and Fisheries has taken action to reform
forestry policies, established new forestry law, giving more rights to accessforest resource, and more roles to protect forest resources to "Community
Forestry Management". The policy reform and forestry law received anational political supports, this policy and law has not yet materialized,
especially al local forest governance level.
For instance, unclear demarcation of boundary community forestry
area is still remaining unsolved. As a result, there is creation somedifficulties to recognize and solving with where is boundary of Community
Forestry to manage and control. In addition, local and international nongovernment organizations have supported technical advises on communities
forestry establishment, training to local authorities to make their knowledge
improvement and competency. The efforts and achievements andcommunity forestry establishments are tools and strategies to poverty
alleviation, sustainable use of resources and improve local livelihoods andwell-being, but those needs to come along with reinforcement of policy
reform, complied with laws and participation from all stockholders,
especially local people in order to achieve its efforts and mutualachievement.
REFERENCES:
Arnold, J. E. M. (1991). Community Forestry: ten years in review, FAO,
Rome.
Country Paper. (2008). Country Paper on Forestry outlook 2002,
Forestry Administration, Ministry of Agriculture and Forestry, Cambodia.
Independent forest sector Review. (2004). Policy Choice, issues andoptions, Forestry Sector in Cambodia, Forestry Administration, Cambodia.
Sokh Heng and Iida Shigeru. (2000). Community forestry guidelines,
Sustainable forest management project. Faculty of Agriculture, Graduate
School, Kyushu Univ., Fukuoka 812-0053
Tom Blomley. T, Tola. P, Mam Kosal. M, Dyna. E and Mark
Dubois.K (2010). Review of Community Forestry and Community
Fisheries in Cambodia Report, Fisheries Administration (FiA), Cambodia.
William D. Sunderlin. (2004). Community Forestry and Poverty
Alleviation in Cambodia,
Environmental management
Environmental
management inin Cambodia
Cambodia case
case study:
study: community
Communityforest
forestgovernancegovernanceatatlocal
localcontext
context

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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Lao-PDR, and Vietnam: An Agenda for Research, Center forInternational Forestry Research (CIFOR), Jakarta, Indonesia

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NewPotential bioavailability of pops in lake
sediment: A case study of Mae Thang
reservoir, Northern Thailand
Pannawee MEKWICHAI1, Preeda PARKPIAN2and Nguyen Thi KIM OANH3
1
Research associate, AIT-SINTEF cooperation, EEM, SERD,
Asian Institute of Technology, Thailand
pannawee@ait.ac.th2
Associate Professor, EEM, SERD, Asian Institute of Technology, Thailand
3
Professor, EEM, SERD, Asian Institute of Technology, Thailand
ABSTRACTAs the population has significantly increased in various developing
countries over the last few decades, and the great pressure is being placedon agricultural sector for high demand of food. The obsolete pesticides,
especially those of Persistent Organic Pollutants (POPs) are still being
used for agriculture and vector control of diseases in order to increase theirproductivity which ultimately contaminate the environment. This study
investigated Organochlorine Pesticides (OCPs) contamination levels, which
are well-known as POPs, as well as to predict potential ecological risk byusing hazard quotient (HQ). Sediment core samples were collected fromfour locations along Mae Thang reservoir, Northern part of Thailand
during dry season (November) in 2007. This reservoir supplies irrigationwater for cultivation, fishery, consumption and recreation activities forpeople living arounding along downstream areas. The samples were
measured for various OCPs residues using soxhlet extraction method andgas chromatography with electron capture detector (GC-ECD).
Hexachlorocyclohexanes (HCHs) which average ranged 17.87-79.48 μg kg1
dry wt was the main residue compound that consist of αHCH (average
ranged 12.11-50.47 μg kg-1dry wt) and γHCH (average ranged 5.7629.01μg kg-1dry wt) following by endosulfans (average ranged 2.08-130.67
μg kg-1dry wt) and heptachlor (average ranged 1.27-51.65 μg kg-1dry wt).
Whereas its bioavailable fraction from LDPE method were HCHs (ranged
0.01-0.23 µg kg-1dry), endosulfans (ranged 0.67-2.50 µg kg-1dry), andheptachlor (ranged 0.36-0.90 µg kg-1dry). This indicated that the eroded
particles carry with the pesticides were deposited into the lakecorresponding with runoff and sedimentation time. In addition, theenvironmental risk was assessed through HQ using bioavailable fraction
extracted by LDPE to compare with Thailand, Canada and Netherlands
standards. The results illustrated that based on the HQ values all were
acceptable which mean that harmful effect on living species and ecologicalsystems in the reservoir is unlikely to occur.

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Chiangmai,

Keywords: Persistent Organic Pollutants, Organochlorine pesticides,
Hexachlorocyclohexane, Endosulfan, Mae Thang reservoir
1. INTRODUCTION
Under the treaty of the Stockholm Convention in 2001, 92 countries agree toreduce or eliminate the production, use and release of 12 key POPs (U.S.
EPA, 2006) which known as the Dirty Dozen. All of POPs are toxic andaccumulate in living organisms and plants. They do not readily break downin the environment with half-lives in soil in the order of years, and they aretransported across boundaries far from their sources, even to other regions
where they have never been used or produced. The ecosystems and humanpopulations are particularly at risk because of the long-range environmental
transportation and biomagnifications of these substances (UROPA, 2006).
Organochlorine Pesticides (OCPs) is a major substance in the 10
intentionally produced chemicals of POPs. 80% of OCPs has been used inagriculture and moved in the environment through volatilization, runoff,
infiltration, biomagnifications via the transmission process in the food chain(El-Shahawi et al., 2009). In Thailand, restrictions on use of organochlorine
pesticides (OCPs) were imposed in the late 1980s (Ruangwises et al., 1994).
Even though most OCPs have been phased out, their residues are still foundin different environmental substrates, such as air, water, soil and sediment
as well as accumulated in the living organism because of their lipophilic
properties that can potentially harmful to human health (Leadprathom,2009). One of the matrices that acts as a natural sink of these toxic
chemicals is soil (Cupr et al., 2009), these compounds are strongly sorbed
onto the surface of particles associated with the organic content of solidphase matrix and can be deposited to the depth increments in the sediment(Doong et al., 2008). Furthermore, they are prone to further redistribution(erosion, percolation and re-emission) or can be recirculated in the aquatic
environments via natural or anthropogenic processes and then back to thewater bodies which becomes increasingly release to wildlife health andecosystem (Fatoki and Matha batha, 2001).
Mae Thang reservoir is located in Rong Kwang district, Phareprovince in Northern part of Thailand. This reservoir is provided irrigationwater for various functions for people in the surrounding areas. Therefore,
there are many farmlands in the vicinity where agricultural chemical
applications are commonly used to improve crop yields. These
agrochemicals could be the major sources of contaminates by means oferoded particles with sloping land and runoff during the wet season which
discharge directly into the reservoir. This study aims to determine theconcentration distribution and toxicity of several OCPs in the sedimentalong the Mae Thang reservoir in order to develop the database of thepollution potential and predict ecological risk in aquatic environment in thisregion.

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2. MATERIALS AND METHODS
2.1 Study area and sediment sampling
The landscape of Mae Thang reservoir is rolling to mountainous innorthern of Thailand (Figure 1). The maximum water capacity of thereservoir is 35x106 m3 and the maximum depth is 43 meters (Thothong,2005). In the region, The main land use pattern along the Mae Thangwatershed is the agricultural activities included planting rice, corn, beans,vegetables and fruit trees on a very steep slope of the mountain which
increasing pesticides use and enhances soil erosion (MSEC, 1999).
According to the cultivation activities, the soil is splashed downhill whichcauses deterioration of soil and contaminants discharged into the terrestrial.
Two sediment cores were collected randomly for each sampling point(totally 8 cores) from different zones of the reservoir based on the water
depth (Figure 2) by using KC Kajak sediment core during dry season in
November 2007. The samples were preserved at -20 °C until analysis.

Figure 1: The Mae Thang reservoir located in Phare, Northern Thailand

Figure 2: Sampling zones and points

Potential bioavailability of pops in lake sediment: A case study of Mae Thang reservoir,
Potential bioavailability of pops in lake sediment: a case study of Mae Thang reservoir, northern Thailand
7873
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2.2 Samples preparation and extraction
The sediment samples (0-35 cm) were homogenized and decanted
from wet samples by centrifugation. After that the samples were passed
through 0.2 mm sieve, and 4-gram sediment was mixed with Na2SO4 to
reduce the moisture and water before extraction. OCPs residues in
sediments were extracted for 16 h with a mixture of 200 ml of n-hexane andacetone (V:V = 1:1) in a Soxhlet apparatus and used the florisil column tocleanup the extracts (U. S. EPA., 1998; U.S. EPA., 2000). Bioavailable
fraction extracted by low density polyethylene (LDPE) method wereanalyzed base on Leadprathom 2009, 10 gram of LDPE plastic pellets weremixed within 90 gram of wet sediment samples and placed into shaker
machine for 7 days at 27 °C which the temperature in the water from Mae
Thang reservoir, then separate LDPE plastic pellets to further soxhlet
extraction following the sediment extraction method.
2.3 Samples analysis and analytical quality assurance
The OCPs residues were measured using HP 5890 series II gas
chromatography system equipped with an electron capture detector (GCECD). The concentrations of OCPs were calculated against known
concentration standard (pesticide standard mix) peak area. Recovery rate(%) was performed for each sample by adding of pesticide surrogate
standard prior to extraction (U.S. EPA., 2000).
3. RESULTS AND DISCUSSION
3.1 Contamination level of OCPs in sediment
The concentration of OCPs levels in sediment for different locations
along Mae Thang reservoir during November 2007 is summarized in Table
1. Despite OCPs have been official banned and restriction on the usage in
Thailand, pesticide residues were detected in all sampling sites. The OCPs
found in this study included α-HCH, γ-HCH (Lindane), α-enodosulfan, βendosulfan and heptachlor.
The results of the mean concentrations showed that HCH compounds
were the predominant OCPs in sediment of Mae Thang reservoir following
by endosulfan and heptachlor. This is due to the fact that the contaminationof HCH isomers is a serious problem worldwide from usage for agricultural
purpose (Fellin et al., 1996). Moreover, the chemicals properties such assolubility and vapor pressure of HCHs (vapor pressure, 3.26x10-5 mm Hg at
25°C and solubility, 7.3 mg/L at 25 °C) would have more tendency to bedeposit into sediment or long range hydrological transport by riverdischarge and atmospheric fallouts from remote source as compared to
endosulfans (vapor pressure, 1x10-5 mm Hg at 25 °C and solubility, 0.32
mg/L at 22°C) (UNEP Chemicals, 2002).

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For the For
distribution
the distributionof HCHofisomers,
HCH isomers,
the dominant
the dominantisomer isomerin this study
in thiswas
study was
α-HCHα-HCH
which concentration
which concentration
is higher
is thanhigherγ-HCHthan γ-HCH
in all locations
in all locations(Table 1.)(Table 1.)
It couldIt be
could
noted
be thatnoted
a highthat apercentage
high percentageof α isomerof α isomer
was reflecting
was reflecting
thethecomposition
compositionof technicalof technicalmixturemixture
for industrials
for industrials
consist consistof 65-70%
of 65-70%
α-HCH,α-HCH,
14-15%14-15%
γ-HCH,γ-HCH,
and 7-10
and% 7-10β-HCH% β-HCH(Ramesh(Rameshet al., 1989;
et al.,Kim,
1989;etKim,al., 2006)
et al., 2006)
and α-HCHand α-HCH
is moreislikely
more tolikelypartition
to partition
to the air
to theandairtransport
and transport
for longfor long
distancedistance(Doong(Doonget al., 2008).
et al., 2008).
From theFromcomparison
the comparison
all of all
locations,of locations,ƩOCPs ƩOCPs
concentration
concentration
in
in
-1
was
dw)
highestwas highest
following
followingby location
by location
1 (83.991 µg(83.99 µg
locationlocation
3 (261.80
3 (261.80µg kg-1dw)
µg kg
-1
-1
kg-1dw),kg4-1(65.91dw), 4 µg(65.91kg-1dw)
µg kg
and
dw)
2 (23.66
and 2 µg(23.66kg-1dw).
µg kgRegardingdw). Regarding
to HCHs,
to HCHs,
the maintheOCPs
maincompounds
OCPs compounds
was foundwasinfoundeach inlocationseach locations
except endosulfans
except endosulfans
detecteddetectedwith thewith
hightheresidue
high residue
only at only
location
at location
3, it is 3,
possible
it is possiblethat waterthat water
current current
from stream
from stream
A, which
A, whichcome fromcome upstream
from upstream
and flows
and into
flows into
downstream
downstream
at outletatofoutlet
the damof the(Figdam2.).(Fig
Because2.). Becauseof this, of
it hasthis,tendency
it has tendency
totobring bringup resuspension
up resuspension
processprocessof endosulfans
of endosulfans
from waterfrom water
current current(Maldonado(Maldonado
and Bayona,
and Bayona,
2002; Holvoet,
2002; Holvoet,
et al., 2007)
et al., that
2007)
cause
thatofcause
higherof higher
suspendedsuspendedparticulate
particulate
and deposit
and deposit
into theinto
sediment.
the sediment.
Table 1:Table
Organochlorine
1: Organochlorine
Pesticides
Pesticides
concentrations
concentrations(µg kg-1(µgdry kgwt)-1dryin thewt) in thesediment
sedimentcore acrosscore theacross35 cm
thedepth
35 cmatdepth
Mae atThang
Mae reservoir
Thang reservoir
LocationLocation
1

1

2

2

3

3

4

4

α-HCH α-HCH

30.23±14.67
30.23±14.67
12.11±17.13
12.11±17.13
50.47±17.30
50.47±17.3043.86±29.33
43.86±29.33

γ-HCH γ-HCH

11.88±5.73
11.88±5.735.76±3.05
5.76±3.0529.01±30.08
29.01±30.0816.20±9.88
16.20±9.88

aHCHs HCHsa42.11±20.40
42.11±20.40
17.87±14.07
17.87±14.07
79.48±12.78
79.48±12.7860.10±39.21
60.10±39.21

Enodosulfan
EnodosulfanI
I 16.31±9.52
16.31±9.521.54±2.18
1.54±2.1867.69±67.39
67.69±67.390.44±0.48
0.44±0.48
Endosulfan
EndosulfanII
II 14.29±3.69
14.29±3.692.98±4.21
2.98±4.2162.70±60.61
62.70±60.611.64±2.31
1.64±2.31bbEndosulfans
Endosulfans
30.60±13.22
30.60±13.22
4.52±6.39
4.52±6.39
130.67±128.00
130.67±128.002.08±2.79
2.08±2.79

Heptachlor
Heptachlorc11.29±0.26
11.29±0.261.27±0.32
1.27±0.3251.65±63.14
51.65±63.143.78±5.35
3.78±5.35

c83.99 83.99
23.66 23.66
261.8 261.8
65.91 65.91
ƩOCPs ƩOCPs
Data show
Data
averageshow average
concentration
concentrationfrom duplicate
from duplicate
samplessamples(± Standard(± Standard
deviation)
deviation)a
Sum of aα-HCH,
Sum of γ-HCH
α-HCH, γ-HCHb
Sum of bα-enodosulfan
Sum of α-enodosulfan
and β-endosulfan
and β-endosulfanc
Sum of ctheSumaverageof the ofaverage
α-HCH,of γ-HCH,
α-HCH, α-enodosulfan,
γ-HCH, α-enodosulfan,
β-endosulfan
β-endosulfan
and heptachlor.
and heptachlor.

3.2 Potential
3.2 Potential
risk evaluation
risk evaluationof OCPsof compound
OCPs compound
3.2.1 Determination
3.2.1 Determinationof bioavailableof bioavailable
fractionfraction
by low density
by low density
polyethylene
polyethylene(LDPE)(LDPE)
methodmethod
The study
The forstudy
bioavailable
for bioavailable
fractionfraction
from Belfroidfrom Belfroid
et al., 1996
et al.,and
1996 and
Leadprathom
Leadprathom
2008 were
2008described
were describedthat bioavailability
that bioavailability
is an importantis an importantfactor factor
to determine
to determine
the degree
the todegreewhich
to awhichchemicala chemical
is able tois ablemovetointo
moveorganisms.
into organisms.
It is alsoIt definedis also definedas the fraction
as the fractionof bulk ofamountbulk amountof the chemicalof the chemical
accumulates
accumulates
in soil/sediment,in soil/sediment,
and by andwater
by takenwater uptaken
potentiallyup potentiallyby organisms
by organisms
during during
their lifespan
their lifespaninto tissues.
into tissues.
In order
In to
order
determine
to determine
bioavailability
bioavailabilityofofcontaminants,
contaminants,
semipermeable
semipermeable
membranemembranedevice (SPMDs)
device (SPMDs)
that is madethat iswith
made withlow density
low density
polyethylene
polyethylene(LDPE)(LDPE)
was used.
wasThisused.is Thisa toolis whicha tool widely
which widelyused toused
determine
to determine
the potential
the potentialof hydrophobicof hydrophobic
contaminants
contaminantsin the in the
Potential bioavailability of pops in lake sediment: A case study of Mae Thang reservoir,
PotentialPotential
bioavailabilityof pops ina case studyof study
Mae Thangnorthernnorthern
ThailandThailand
bioavailabilityof lakepopssediment:in lake sediment:a caseof Maereservoir,
Thang reservoir,
5 7895
Northern ThailandOctober 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

environment such as OCPs adsorption through hydrophobic sorption fromwater and sediment (Takada, et al., 2005)
Bioavailable fraction concentrations from LDPE method at 0-35
depths sediment was presented in Table 2. These comprised of α-HCH, γHCH, α-enodosulfan, β-endosulfan and heptachlor. Based on chemical
analysis along the reservoir seemed to have endosulfans contamination,
following by heptachlor whereas HCHs did not have much present inbioavailable fraction.
Table 2: Bioavailable fraction of OCPs (µg kg-1dry wt) by LDPE extraction
method from combination of 4 locations along Mae Thang reservoir
LDPE
a

HCHsa

Endosulfans

Heptachlor0.01-0.23

0.67-2.50

0.36-0.90

HCHs = α-HCH, γ-HCH
Endosulfans = α-enodosulfan, β-endosulfanb

3.2.2 Ecological risk assessment
The hazard quotient (HQ) is widely used as a screening method forpotential risk under an ERA (Driscoll et al., 2002). The HQ approach wasapplied in preliminary risk assessment by comparing concentrations of
toxicity chemicals found in the environmental media with benchmark whichcalculated using the following equation:
HQ = Exposure concentration/Screening Benchmark(1)Final determination of risk from contaminants in question is made in
the Baseline Ecological Risk Assessment. When the HQ is calculated to begreater than one for a particular contaminant, the assessed ecological system
is assumed to be potential for adverse impact to ecological system (NEPC,
1999).
Environmental contaminant concentration in reservoir was represented
by sediment media which was determined from the bioavailable fraction
using LDPE extraction method. The HQ values of each compound areshown in Table 3. HCHs, endosulfans and heptachlor concentrations of
LDPE method was 0.01-0.23 µg kg-1dry wt, 0.67-2.50 µg kg-1dry wt and0.36-0.90 µg/kg, respectively. The HQ values by bioavailable fraction of
HCHs, endosulfans and heptachlor on Thailand benchmark, Canada andNetherlands benchmark were not shown potential risk because the values
obtain were lower than 1 indicating no potential risks of pesticides toaquatic life at the time cause of assessment. As a result, HQ value obtained
from the LDPE method indicated acceptable risks when Thailand, Canada
and Netherlands benchmark were applied.

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Table
Table
3:TableHazard3: Hazard
3: Hazard
quotient
quotient
quotient(HQ)(HQ)
of(HQ)OCPs
of OCPs
ofinOCPs
sediment
in sediment
in sediment
from
from
Mae
from
Mae
Thang
Mae
Thang
Thang
reservoir
reservoir
reservoir
Exposure
Exposure
Exposure
Concentration
Concentration
Concentration
Screening
Screening
Screening
BenchmarkBenchmarkBenchmark
a
a
a
c
c
c
ThailandThailandThailand
Netherlands
Netherlandsbbb Netherlands
Pesticide
Maximum
Pesticide
Pesticide
Maximum
Maximum
CanadaCanadaCanadaHQHQ HQ -1 -1 HQHQ
HQ -1 -1
HQHQ HQ-1-1) (µg) kg-1(mg) (mgkg-1kg)(mg) kg-1)(µg(µgkg kg) (µg) kg-1)
(g kg
(g kg
) (g
) kg-1)(µg(µgkg-1kgcontaminantcontaminantcontaminant
HCHs
HCHsHCHs 0.230.23 0.23
Endosulfans
Endosulfans2.502.50 2.50
Endosulfans

2.742.74 2.74
0.050.05 0.05
< 4.4
< 4.4 <0.00005
4.40.00005
0.000050.080.08 0.08
0.0000046
0.0000046
0.0000046

Heptachlor
Heptachlor0.900.90 0.90
Heptachlor

0.00005
1.381.38 1.38
0.650.65 0.65
NVNV NV NVNV NV< 1.1
1.10.00005< 1.1 <0.00005

-

-

- -

-

- -

-

--

-

-0.010.01 0.010.00025
0.000250.00025

NV:NV:
No No
value
NV:
value
No valueaaPollution
Pollution
Pollution
Control
Control
Department,
Control
Department,
Department,
2004
2004 2004bbb
Canadian
Canadian
Canadian
Sediment
Sediment
Sediment
Quality
Quality
Guidelines
Quality
Guidelines
Guidelines
for forthe theProtection
forProtection
the Protectionof Aquaticof AquaticofLifeAquatic
Life(CCMC),(CCMC),
Life (CCMC),
2002
2002 2002ccc
Netherlands
Netherlands
Netherlands
Environmental
Environmental
Environmental
Assessment
Assessment
Assessment
Agency,Agency,2005
Agency,2005 2005a3.33.3Comparison
Comparison
3.3 Comparisonof OCPs
of OCPs
oflevels
OCPs
levelsinlevels
sediment
in sediment
in sedimentat different
at different
at different
area
area area
Comparison
Comparison
Comparison
of of
OCPs
OCPs
ofconcentrations
OCPs
concentrations
concentrations
in inthisthis
reservoir
in reservoir
this reservoir
sediment
sediment
sediment
withwith with
other
other
studiesotherstudieswasstudies
was
shown
shown
wasin
shown
Table
in Tablein4.Table
From
4. From
4.the
From
the
resultresulttheofresult
thisof thisstudy,
ofstudy,
thisHCHs
study,
HCHs
and
HCHs
and andheptachlorheptachlorheptachlor
concentration
concentration
concentration
were
were
higherwere
higherwhen
higherwhen
comparedwhen
comparedcomparedto thoseto thosetoreportedthosereportedreported
fromfrom fromthetheother
other
theparts
other
parts
ofpartsofThailand.
Thailand.
of Thailand.
ExceptExceptthe
Excepttheresultresulttheinresult
agriculturalin agriculturalin agriculturalareas,
areas,
northernareas,
northernnorthern
partpart
of ofThailandpart
Thailandof Thailand
from
from
Thapinta
from
Thapinta
Thapinta
andandHudak,
Hudak,and Hudak,
2000
2000
that
2000
that
were
were
that
extremely
wereextremely
extremelyhighhigh highon onendosulfans.
endosulfans.
on endosulfans.
Furthermore,
Furthermore,
Furthermore,
when
when
comparedwhen
comparedcompared
pesticidepesticidepesticideconcentration
concentration
concentrationof of ofThailandThailandThailand(including(including(including
thisthisstudy)
study)
thiswith
study)
with
Asian
with
Asian
locationsAsian
locationslocations
they
they
were
they
were
much
were
much
highermuch
higherhigher
than
than
other
than
other
locations.
otherlocations.
locations.
TheThereasonThereasonreasonforforthisthisforduedue
this
to to
due
thethefact
to factthethatfact
thatthethatthefastfast
the fast
development
development
development
in in
agricultural
agriculturalin agricultural
sectorsectorduringsectorduringduring
1994-2003,
1994-2003,
1994-2003,
ThailandThailandThailandmostlymostlymostlyimported
imported
importedorganicorganicorganic
andandinorganicandinorganic
inorganic
chemicalchemicalchemical
substances,
substances,
substances,
which
which
comprisedwhich
comprised
comprisedchemicalchemicalchemicalproducts
products
products
andandactiveactiveandingredientsactiveingredients
ingredients
(PCD,
(PCD,
2006)
(PCD,
2006)
and
2006)
and
mostlymostlyand imported
mostlyimported
imported
pesticidepesticidepesticidein inASEAN
ASEAN
in ASEAN
MemberMemberMemberCountries
Countries
Countries
in in1988
1988
in (FAO,
1988
(FAO,
(FAO,
undate).
undate).
undate).
Consequently,
Consequently,
Consequently,
a similara similara lowsimilarlow
concentration
concentration
low concentration
of of
all all
three
ofthreeallpesticides
threepesticides
pesticides
monitored
monitored
monitored
in sediments
in sediments
in sedimentsof selectedof selectedof selected
Asian
Asian
countries
Asian
countries
countries
waswasobserved.
observed.
was observed.
-1
Table
Table
4:TableComparison
4: Comparison
4: Comparisonof OCPs
of OCPs
ofconcentration
OCPs
concentration
concentration(µg(µgkg-1kg(µg
kg-1wt)
dry
dry
wt)
in
drytheinwt)
thesediment
insediment
the sediment
from
from
other
from
other
Asian
other
Asian
locationsAsian
locationslocations

Location
Location
Location

Ʃ HCH
Ʃ HCH
Ʃ HCH
ƩendosulfanƩendosulfanƩendosulfan
Heptachlor
Heptachlor
Heptachlor
Reference
Reference
Reference
Thapinta
et al.,
Thapinta
Thapinta
et al., et al.,
- Agriculturalareas,NDND ND 1.22–634.90- Agricultural- Agriculturalareas, areas,
1.22–634.90
1.22–634.90 NDND ND2000
2000 2000
Northern
partpartof Thailand
Northern
Northern
ofpartThailandof Thailand- Agriculturalareas,NDND ND 0.011–8.818
0.005–0.297- Agricultural- Agriculturalareas, areas,
0.011–8.818
0.011–8.818
0.005–0.297
0.005–0.297
Eastern
partof Thailand
Eastern
Eastern
part
ofpartThailandof Thailand
Poolpak
etPoolpakal.,Poolpak
et al., et al.,- Tributaries
of Mae<0.001-2.050<0.001-1.920
2007- Tributaries- Tributaries
of Maeof Mae 0.64-6.92
0.64-6.92
0.64-6.92<0.001-2.050<0.001-2.050<0.001-1.920<0.001-1.920
2007 2007
Klong
river
Klong
Klong
river river- RangTub
TabTabCanal,<0.001-16.18<0.001-5.95- Rang- Tub
Rang
TubCanal,
Tab Canal,0.34-24.10
0.34-24.10
0.34-24.10<0.001-16.18<0.001-16.18<0.001-5.95<0.001-5.95
MaeKlong
river
basin
MaeKlong
MaeKlong
river
basin
river basin
Leadprathomet etLeadprathom
Leadprathomet- Chanthaburi
estuaryal., al.,2008- Chanthaburi- Chanthaburi
estuaryestuary 0.5-49.5
0.5-49.5
0.5-49.5 4.0-70.5
4.0-70.5
4.0-70.5 0.4-13.0
0.4-13.0
0.4-13.0
2008
al., 2008
Eastern
partof Thailand
Eastern
Eastern
part
ofpartThailandof Thailand
ThisThisstudy.,
study.,
This study.,
- Mae
Thang
reservoir,nd-221.18
2008
- Mae
-ThangMae
Thang
reservoir,
reservoir,7.92-88.51
7.92-88.51
7.92-88.51
nd-221.18
nd-221.18nd-96.30
nd-96.30
nd-96.30
2008 2008

Potential bioavailability of pops in lake sediment: A case study of Mae Thang reservoir,
Potential
Potential
bioavailability
bioavailabilityof popsof popsininlake
sediment:a casea casestudyof Maeof MaeThang
reservoir,
northernnorthern
ThailandThailand
Potential
bioavailability
oflakepops
insediment:lake sediment:a studycase
studyof Thang
Maereservoir,
Thangreservoir,
northern
Thailand7 7 7917
Northern ThailandOctober
2011, 2011,
Chiang
Mai,Thailand
Thailand
October
Chiangmai,
Chiangmai,
ThailandNorthern
Northernpart ofpart
Thailandof Thailand- Osaka- Osaka
Bay, Japan
Bay, Japan- Ariake- Ariake
Bay, North
Bay, North
JapanJapan

0.073-6.20
0.073-6.20

ND

ND

ND

ND

0.78-1.5
0.78-1.5

ND ND

nd

nd

TanabeTanabe
et al., et al.,2002 2002

Kim etKimal., et al.,2006 2006
Lee etLeeal., et al.,- Kyeonggi- Kyeonggi
Bay, Korea
Bay, Korea<0.19-1.20<0.19-1.20 ND ND
ND ND 2001 2001
- Lake- Lake
Shiwha,Shiwha,KoreaKorea 0.59-2.40
0.59-2.40
ND ND
ND ND
Rajendran
Rajendranetetal., 2001- Bay -ofBay
Bengal,of Bengal,
India India 0.17-1.56
0.17-1.56
ND ND
ND ND al., 2001
Bhattacharya
Bhattacharya
2003
al., 2003- Hugli- Hugliestuary,
estuary,
India India <1-130<1-130<1-220<1-220ND ND et al., et- Da-han- Da-hanriver, river,NorthNorth
DoongDoonget al., et al.,TaiwanTaiwan<0.12-4.94<0.12-4.94<0.08-3.78<0.08-3.78 <0.15-1.57<0.15-1.57
2002 2002- Erh-jen- Erh-jenriver, river,SouthSouth
DoongDoonget al., et al.,TaiwanTaiwan<0.12-6.90<0.12-6.90<0.08-7.16<0.08-7.16 <0.15-5.61<0.15-5.61
2002 2002
Zhou Zhou
et al., et al.,- Daya- Daya
Bay, China
Bay, China
0.32-4.16
0.32-4.16
ND ND
ND ND 2001 2001
- Minjiang- Minjiang
river river
ZhangZhang
et al., et al.,estuary,
estuary,
ChinaChina
2.99-16.21
2.99-16.21 0.57-8.84
0.57-8.84 0.88-2.77
0.88-2.772003 2003
HongHong
et al., et al.,- Ha long- Ha Bay,long Vietnam
Bay, Vietnamnd-0.85
nd-0.85
ND ND
ND ND 2008 2008
- Hai -Phong
Hai Phong
Bay, Bay,
VietnamVietnam
0.15-1.00
0.15-1.00
ND ND
ND ND
ND: noND:
datano data
nd: nonnd:
detectablenon detectable

4. CONCLUSION
4. CONCLUSION
The results
The results
obtained
obtainedin thisin study
this study
suggestsuggestthat therethat there
still remained
still remained
OCPsOCPs
residues
residues
in theinsediment
the sedimentof Maeof MaeThangeThangereservoir,
reservoir,
althoughalthoughthe usetheofusePOPsof POPs
in Thailand
in Thailand
had been
had beenprohibitedprohibitedfor 30foryears.
30 years.
The organochlorine
The organochlorine
pesticidepesticidecompounds
compounds
particularly
particularly
α-HCH,
α-HCH,
γ-HCH
γ-HCH
among
among
HCHs,
HCHs,
α-enodosulfan
α-enodosulfan
and andβ-endosulfan
β-endosulfan
among
among
endosulfans
endosulfans
and heptachlorand heptachlor
were weredetecteddetectedalongalong
the thereservoir.
reservoir.
This Thismightmight
due dueto theirto theirprevious
previous
extensiveextensive
applications
applications
in inagriculture
agriculture
activities,
activities,
runoffrunoff
from from
cultivation,cultivation,
and andthe thehydrologicalhydrologicalcharacteristic
characteristic
such suchas wateras watercurrent,
current,
seasonal
seasonal
variation
variationof flowof flow
and floodand flood
disasters.
disasters.
HCHsHCHs
is a ispredominate
a predominate
compoundcompoundshowedshowedas theas highest
the highest
concentration
concentrationin eachin eachlocation,
location,
only only
in onein location
one locationnear near
the damthe damoutletoutlet
showedshowedhigh highlevel levelof endosulfans
of endosulfans
whichwhichmightmight
be because
be because
of sedimentof sedimentresuspension
resuspension
influenced
influenced
by waterby watercurrent.
current.
In addition,
In addition,an ecologicalan ecologicalrisk risk
assessment
assessment
from fromthis study
this study
indicatedindicatedthat Maethat Mae
Thang
Thang
reservoir
reservoir
is notisatnot
riskat risk
sincesince
the hazard
the hazard
quotient
quotient
from frombioavailable
bioavailable
fraction
fractionof LDPEof LDPE
methodmethodis islowerlower
than than
1. However,
1. However,
all theall OCPsthe OCPs
concentration
concentrationof thisof reservoir
this reservoir
are aregenerally
generally
higherhigherthan otherthan other
AsianAsianareas,areas,thus monitoring
thus monitoring
programprogramfor POPs
for POPs
contamination
contaminationin thisin reservoir
this reservoir
is recommended
is recommended
in orderin orderto protect
to protect
harmfulharmfuleffects
effects
on theonecosystem
the ecosystem
and living
and livingorganisms
organisms
especially
especiallyon humanon humanhealth.
health.

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ACKNOWLEDGEMENTS
The authors wish to acknowledge Dr. Warinya Thothong for helping in
sediment samples collected at Mae Thange reservoir. The authors also
express their gratitude to Dr. Supat Ponza and Dr. Napaporn Leadprathom
for their valuable suggestions and useful comments.
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Mai,Thailand
Thailand
Chiangmai,

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Takada, H., Mato, Y., Endo, S., Yamashita, R., and Zakaria, M. P.,
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Tanabe, S., Lee, K. T., and Koh, C.H., 2002. Distribution oforganochlorine pesticides in sediments from Kyeonggi Bay and nearby
areas, Korea. Journal of Chemosphere 48, 237–246.
Thapinta, A., and Hudak, P. F., 2000. Pesticide use and residual
occurrence in Thailand. Environment Monitoring Assessment 60, 103–114.
Thothong, W., 2005. GIS-aided spatial and temporal mapping ofreservoir water quality in an agricultural watershed: A case study of Mae
Thang reservoir, Northern Thailand. Master Thesis No. NR-05-04 Asian
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Potential bioavailability of pops in lake sediment: A case study of Mae Thang reservoir,
Potential bioavailability of pops in lake sediment: a case study of Mae Thang reservoir, northern Thailand
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The effect of moisture on the groundsurface for LiDAR DEM generation
Takahiro ENDO1, Yoshito SAWADA2 and Haruo SAWADA3
Assitant Professor, ICUS, IIS, The University of Tokyo, Japan
2
Project Researcher, ICUS, IIS, The University of Tokyo, Japan
3
Professor, ICUS, IIS, The University of Tokyo, Japan
1

ABSTRACT
Recently, LiDAR (Light Detection and Ranging) measurement is becoming
useful tool to generate Digital Elevation Model (DEM) and Digital Surface
Model (DSM) on national land surface. Especially in the forest area, LiDAR
becomes a powerful tool for forest management, since LiDAR can directly
measure the elevation under tree canopy which visible sensors can‘tmeasure. However, LiDAR sometime directly can't generate DEM due to alack of points under tree canopy. Authors considered that the reason of thisphenomenon mainly depends on an effect of soil moisture on the groundsurface, since laser beam is a kind of microwave. An aim of this study is toquantitatively reveal relationship between moisture on the ground surface
and the probability of DEM generation using a simulation. The relationshipwas analyzed by a LiDAR simulator which consists of computer graphic
technology and a 3D plant growth model. Five conditions of moisture on the
ground surface were simulated. As the results of analysis, the reflectancedecreased in proportion to increment of moisture on the ground surface.
The result indicated that DEM generation depends on three parameterswhich are the sensitivity of sensor, the moisture on the ground surface andthe gap size. It was difficult to generate DEM in case of high moisture
condition. LiDAR measurement should avoid wet condition on the groundsurface in order to get DEM with high accuracy.
Keywords: simulation, reflectance, forest, gap size, crown edge
1. INTRODUCTION
LiDAR is one of remote sensing tools. The LiDAR consists of thetransmitting and receiving apparatus of laser beam, the DGPS and the IMU.
At present, the LiDAR is widely used for the survey of national land, theshape of urban area and forest management. The reasons why be used
LiDAR in these work fields is that the LiDAR can directly measure three
dimensional shape and position of a target. Principle of airborne LiDAR
measurement is that firstly, laser beam is emitted from the position decided
by the DGPS and the IMU and secondly, the receiver detects the echo froma target, and thirdly, CPU calculates the geographical position of a target
using both the position of sensor and the traveling time of laser beam.

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Mai,Thailand
Thailand
Chiangmai,

Wavelength used by LiDAR is usually 1064nm. Since laser beam iselectromagnetic wave, an intensity of the echo from target depends onreflectance of a target at 1064 nm. Hence, DEM generation rate is expected
to depend on moisture content on the ground surface. Especially, soil
moisture on the ground surface is expected to affect DEM generation inforest.
This study aims to investigate that the moisture on the groundsurface effect for DEM generation in forest using a LiDAR simulator.
2. MATERIALS AND METHODS
2.1 An over view of a LiDAR simulator
The LiDAR data is simulated using a three dimensional plant modeland ray tracing method. The method consists of four steps; (1) modeling atarget in virtual space, (2) calculating intersections between an object andlaser beam by ray tracing method, (3) calculating intensity of an echo at theintersection, and (4) creating points in case of the echo over a specificthreshold.
2.2 Modeling of forest and the ground
Trees are created in virtual space using 3DCG software and a plant
growth model. In this study, natFX (commercial software) was used as aplant growth model. The natFx can create tree as full polygons using threeparameters which are species, age of stand and season. The shape of createdtrees is similar to actual tree shape in the point view of crown, leaves andstems.
On the other hand, the ground data is used from actual DEM data or avirtual data. Table 1 shows software configurations of LiDAR simulator.
Table 1: The software configurations of LiDAR simulator.

3DCG software
Tree growth model
Programming language

Autodesk 3ds max 2011
natFX
max script and Matlab 2011a

2.3 Simulation of the discrete LiDAR measurement
To create LiDAR’s point cloud, ray tracing is carried out against themodeled trees and the ground in 3DCG. This simulation calculatesintersection points and reflectance of the echo. Specifically, point density oflaser beam, scan angle, footprint size, reflectance of leaves and the groundand leaf size are used as initial values. Intersection points and its reflectanceare calculated by the following steps; (1) origin of laser beam is calculated
from point density, (2) sub rays are created in a main ray from footprint sizeand leaf size, (3) intersection points are calculated using sub rays and thetarget, (4) reflectance of each intersection points is calculated using

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ICUS Report 56

inclination of the target. In this study, each inclination was calculated ashorizontal, since reflectance mechanism at intersection point define aslambertian.
Moreover, the discrete LiDAR can't record two strong intensities
within 3m due to hardware limitation. Usually, the discrete LiDAR records
four points per one laser beam. Therefore, point generation algorithm in thissimulation was adapted to this procedure. The algorithm is the followings.
Firstly, an intersection point with maximum Z value was selected as a startpoint for calculation of reflectance of the echo. Secondly, summation ofreflectance of the echo by 15 cm interval was calculated. If the summation
value is over threshold value, a point is created using average value of allintersection points within 15 cm interval. Next search position is skipped
3m from the created point. This procedure is repeated until the lastintersection point.
2.4 Modeling condition for simulation of soil moisture effect
In this study, moisture on the ground surface defined as reflectance on
the ground surface. To investigate moisture effect in forest in DEM
generation, virtual forest and the ground were created in 3DCG. In thisstudy, the ground was set as flat to investigate only soil moisture effect.
Japanese cedar was selected as species of virtual forest, since this species
was one of dominant plantation species. Figure 1 shows a vertical view of
the created virtual forest and the ground. Nine trees were modeled usingparameters which were 45 years age of stand and summer. Trees were
distributed as closed or open canopy like Figure 1 to evaluate canopy
condition. LiDAR simulation was carried out as the followings; footprint
size was 20cm, scan angle was 90o, point density was 10 points/m2,
wavelength was 1064 nm, leaf reflectance was 50% at 1064 nm, the groundreflectance was 50%, 40%, 30%, 20% and 10% at 1064 nm, respectively,
leaf size was 0.09 m2 derived from virtual tree’s leaves.

Figure 1: The created virtual forest.

The effectTheeffect ofof moisturemoisture onon thethe groundground surface
surface forfor LIDAR
LiDAR DEM
DEM generation
generation

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3. RESULTS AND DISCUSSION
3.1 Effect of moisture on the ground surface for DEM generation

8000

70.0%

7000

60.0%

Ratio of DEM generation# of points on the groundFigure 2 (a) shows a result of relationship between each reflectance ofthe ground surface and the number of reached laser beams on the ground.
Also, Figure 2 (b) shows a result of relationship between each reflectance ofthe ground surface and the ratio of DEM generation. Since the reflectance ofthe ground that was 10% was less than the threshold, naturally, the numberof reached laser beams on the ground and the ratio of DEM generation werezero, respectively. In case of the decrement of the reflectance of the ground,the number of reached laser beams on the ground was decreased (Figure 2(a)), and also the ratio of DEM generation was decreased (Figure 2 (b)). The
results indicate that the moisture on the ground surface affects DEM
generation.

6000
5000
4000
3000
2000
1000
0

0

20
40
Reflrctance of the gournd (%)

60

50.0%
40.0%
30.0%
20.0%
10.0%
0.0%

0

20
40
Reflrctance of the gournd (%)

60

(b)
(a)
Figure 2: A result of relationship between each reflectance of the ground surface
and the number of reached laser beams on the ground (a), and relationshipbetween each reflectance of the ground surface and the ratio of DEM generation(b).
3.2 Relationship between the ratio of DEM generation and the size ofgap areas
The ratio of the DEM generation in range of from 50% to 20% wasn't
linear, but was exponential relation. Authors considered that the reason
depended on relationship between the gap size and mesh size ofrasterization. Therefore, a vertical 2D black and white image (BW image)was created from 3D virtual forest data (Figure 3) and investigatedrelationship between the gap size and its number using the rasterized BW
image. Its mesh size was 10 cm for understanding the relation in detail.
Figure 4 stands for the relationship between the gap size and its number ofpixels.

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Figure 3: The 2D black and white image derived from the 3D virtual forest
6000# of pixels

5000

y = 8470x-0.693
R² = 0.965

4000
3000
2000
1000
0

0

20

40
60
80
The gap size (cm2)

100

120

Figure 4: Relationship between the gap size and its number of pixels
As a result of the analysis of the relation, the relationship between the
gap size and its number of pixels was exponential relation. Its multiple
correlation coefficient (R2) was 0.965. Both curves were quite similar. The
result indicates that DEM generation depends on three parameters which are
the sensitivity of sensor, the moisture on the ground surface and the gap size.
3.3 The affected area by moisture
Figure 5 (a) – (d) are results of 1 m grid DEM generation derived fromthe simulated data. Figure 4 (a)-(d) are 50%, 40%, 30% and 20% ofreflectance of the ground surface, respectively. White pixels stand forsuccess of DEM generation. On the other hand, black pixels stand for
failure of DEM generation. Figure 5 (e) is the subtracted image. R:G:B
corresponds with 50%: 40%: 20%. Gray pixel is the difference. The
distribution of the different was around edge of tree crown. Hence, theresults showed that it was difficult to create DEM around the edge of thecrown, in case of the low value of the reflectance of the ground surface.

The effectTheeffect ofof moisturemoisture onon thethe groundground surface
surface forfor LIDAR
LiDAR DEM
DEM generation
generation

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(a)

(b)

(c)

(d)
(e)
Figure 5: the results of 1 m grid DEM generation derived from thesimulated data. (a) –(d) are 50%, 40%, 30% and 20%, respectively. (e) is
the subtracted image (R:G:B=50%, 40%, 30%).
4. CONCLUSION
To investigate the effect of moisture on the ground surface for DEM
generation, LiDAR simulation was carried out. As the results, DEM
generation depended on three parameters which were the sensitivity of
sensor, the moisture on the ground surface and the gap size. Moreover, incase of low reflectance on the ground surface, the affected area was edge ofcrown.
To make laser beam frequently be hit against the ground in forest, theonly parameter we can control is measurement condition. In other words,
LiDAR measurement should avoid wet condition on the ground in order to
get the DEM with high accuracy.
REFERENCES
Endo,T. and Sawada,H. 2010. Development of a LiDAR simulation
system for forest, SEISAN KENKYU, 62 (4), 445-448

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Multi-temporal study on PM10 distribution
for urban air quality in upper Northern ofThailand using spatial technology
Nion SIRIMONGKALERKAL 1, Vivarad PHONEKEO 2
and NGUYEN Luong Bach 3
1
PhD candidate, NREM, Fahluang University, Thailand
nion_siri@hotmail.com
2
Senior Researcher, GIC, SET, Asian Institute of Technology, Thailand
3
Assistant Professor, NREM, Mae Fahluang University, Thailand
ABSTRACT
Upper northern region of Thailand yearly faces with smoke and haze
problem due to open-spaced biomass burning activities related to land use
preparation for agriculture of the local people, in particularly in March –April 2007. It is direct negative impact to the health of the people in many
cities in the region, as reported by the Ministry of Public Health of Thailand.
In order to manage this smoke-and-haze problem, Pollution Control
Department (PCD) is monitoring the air quality in the region continuously
using the 5 measurement stations. However, these stations can provide thedata only in limited area and it is not possible to cover large area.
Therefore, to have better understanding the air quality scenario in theregion, the authors have conducted air quality monitoring using spatial
technology including remote sensing and GIS. In this paper, the authors
used MODIS aerosol optical thickness (AOT) product from NASA and PM10
concentration hourly data from PCD measurement stations during 2007 to2010 for data analysis and generating estimated PM10 concentration
distribution maps. The obtained result could be useful guiding information
for spatially understanding of the PM10 concentration distribution which
would support for public health decision making and urban planning.
Keywords: urban air quality, aerosol optical thickness, PM10 concentration,
MODIS, remote sensing
1. INTRODUCTION
Smoke haze related to biomass burning is a recurring environmental
problem in Southeast Asia which affects air quality not only in the source
regions, but also in the surrounding areas. Major episodes of fire and transboundary haze pollution occurred in the region during the1980s and 1990s.
The blaze of 1997-1998 which affected Brunei Darussalam, Indonesia,
Malaysia, Philippines, Singapore and Thailand, was among the mostdamaging in recorded history. More than 9 million hectares of land wereburnt, 6.5 million of which were forested areas. The damage was estimated8031

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at more than 9 billion US dollar in terms of economic, social andenvironmental losses, including the release of an estimated 1-2 billion tonsof carbon. More recently, trans-boundary haze pollution has also become aserious problem in Cambodia, Lao PDR, Myanmar and Thailand. In
northern Thailand, land and forest fires caused the air quality to deteriorate
to unhealthy levels during the dry season of 2006 and 2007 (Environment
Division of ASEAN Secretariat Haze Online v.2008).
In Upper North Thailand (UNT), smoke haze problem recurs in dry
season yearly (February-April) when the level of particulate matter or PM10
in the ambient air is elevated typically by forest fires. Forest fires are foundor increase during this season in this region due to dry weather conditions.
Additional burnings of agricultural residues to prepare land for next-cycle
plantation (in the rainy season) also worsens the problem. UNT borders on
East Myanmar, North and East Laos, and is not too distant from South
China. Its geography is generally mountainous with north-south-aligned hillridges parallel from west to east, forming a number of valleys, e.g., Chiang
Mai-Lamphun, Chiang Rai, Lampang, Mae Hong Son valleys. This
geographical characteristic can also cause the ventilation of air
pollutants out of a valley to be difficult. One of the worst air pollution
episodes in UNT and Thailand took place in March 2007, during which
elevated smoke haze pollution was prolonged for 2-3 consecutive weeks andthe 24-hr average ambient PM10 concentration exceeded the national
ambient air quality standard for many days (Kasemsan et al, 2009).
However the main causes that initiate haze/smoke crisis in the upper
northern part of Thailand are forest fires and agricultural residue burning(Kasemsan, 2010). Furthermore, the hot spot occurrence found in the upper
northern part of Thailand occurred in forest area 79%, agricultural area 20%
and only 1% in urban area. (Ketsisri, 2009).
In term of the impact of smoke and haze distribution to the local
people health, the Office of Disease Prevention & Control has reported thatthe haze/smoke occurred in Northern Thailand has affected a large numberof local people health. According to the report in March 17, 2007, therespiratory syndrome patients were increased dramatically. In total, there
were 34,769 patients with some patients with acute severe symptom such as
159 heart disease patients, 782 infected eye disease patients and 6 dermatitis
patients. The average number of patients admitted for treatment was 1,500
patients a day. Based on these reasons, it is necessary to conduct researchon the distribution of the smoke and haze in the study area. Only using theinformation gathering from the ground air quality measurement stations,sparsely distributed in the study area are not enough to understand thesmoke and haze phenomenon, Therefore, it is necessary to apply spacetechnology, in particularly remote sensing and GIS to the study of the
distribution of PM10 for better understanding of the phenomenon and tosupport air quality management in the study area.

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2. OBJECTIVES OF THE STUDY
The objectives of the study are listed below
1. To analyze the trend of the aerosol optical thickness (AOT)
acquired from Terra/Aqua MODIS and PM10 concentration from
12 PCD air quality ground measurement station in the period of2007 – 2010 and find out their relationship.
2. To generate estimated PM10 Concentration maps for Upper
Northern of Thailand during the period of 2007-2010 based on theobtained relationship.
3. SCOPE OF THE STUDY
The study focus on Upper Northern Thailand, which is our study area,that smoke and haze problem occurs in dry season each year, mainly
from February to April, when the level of PM10 concentration raise up
due to forest fires and biomass burning related to agricultural activities.
In this study, we use MODIS aerosol optical thickness product(MOD04/MYD04) which has spatial resolution of 10x10 km2 andPM10 concentration from 12 PCD air quality measurement stations
located in many provinces of the study area (Figure 1). Since the main
purpose of the study is to study the relationship between MODIS AOT
and PCD PM10 concentration distribution, other atmospheric or
meteorological parameters such as air temperature, air humidity, windspeed and direction are not considered in this study.
4. STUDY AREA
The study focus on Upper Northern Thailand, covering 8 provinces
which are Chiang Mai, Chiang Rai, Mae Hong Son, Nan, Prae,
Phayao, Lampang and Lamphun, within the approximated geographic
coverage of 20.47° N, 97.37° E and 17.18° N, 101.37° E withapproximated area of 159,100 km2. The study area also includes partly
the area of the neighboring countries (Laos and Myanmar) along theborders with Thailand (Figure 1)

Multi-temporal study on PM10 distribution for urban air quality in upper Northern of Thailand using spatial
Multi-temporal study on PM10 distribution for urban air quality in upper Northern
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Figure 1: PCD air quality measurement stations in upper
northern part of Thailand, marked by red squares.
5. METHODOLOGY
The study on the distribution of the PM10 in the Upper Northern Thailand isrelated to the understanding on the trend and relationship of two main
parameters which are aerosol optical thickness acquired by MODIS on
board Terra/Aqua and PM10 data recorded by 12 PCD air quality
measurement stations, therefore, the methodology of this study has two
main parts as the following:
5.1 Trends and relationship of MODIS AOT and PCD PM10
Concentration Distribution
MODIS AOT product for the duration of 2007 – 2011 wasdownloaded from NASA website, from which the AOT physical value was
extracted at the selected pixels where the 12 PCD stations are located. The
hourly PCD PM10 data also collected from 12 PCD stations for the same
duration. AOT MODIS data which has the same acquiring date and timewith the measurement date and time of PM10 stations were selected to makeyearly and monthly groups of matching pairs. Using these matching pairs,
we can generate graphs to observe the trend of the AOT and PM10
distribution available within the interested year and month. The relationshipof these two datasets can be found by calculating the correlation coefficientand the linear regression equations. Figure 2 shows the dataset of matchingpairs for year 2009 and 2010 and for the months of February, March andApril of each year, and only February for 2011. The total matching pairs
used in this step are 140. In this Figure, the total number of matching pairs
available within year 2007-2011were used to calculate the correlation
coefficient and generated linear regression equation. Here the correlation is0.32 which is not high, due to scattered points that are unusual observations,according to the statistical analysis which need to be investigated. Other

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possible reasons related to meteorological and environmental conditions
could be also the factors that cause unusual observations.
An additional study the trend of the two parameters is to use the AOT
value extracted from the AOT product available within one month at the
pixel where a interested measurement station is located to plot a graph to see
the its monthly temporal distribution. Similarly, hourly PM10 concentration
value recorded within a period of the same month at the same measurement
station can be used to plot a graph to see observe the trend of its temporal
distribution. Figure 3 shows an example of the monthly distribution of AOT
concentration detected by MODIS (red graph) within the month of February
2007 at the location of measurement station ‘ChiangMai1’ in Chiang Mai
province, and also the monthly distribution of PM10 concentration (bluegraph) measured at the same station within the same period.
From visual analysis of these graphs, we found that most of the
MODIS AOT and PCD PM10 matching pairs have very similar trend, forexample, the graphs of February, March and April in year 2007, 2008, 2009
and 2010 for station ChiangMai1, March 2008 for ChiangMai2, March andApril 2010 of ChiangMai2, April 2009 and March 2010 of ChiangRai1,
February and March 2008 with February and April 2009 of Lampang1,
March 2008, February 2009 and March 2010 of Lampang2, April 2010 ofLampang3, March 2010 of Lampang4, April 2010 of Lampoon1, March andApril 200, February and March 2010 of Maehongson1 and February and
April 2010 of Nan1. However, there are still many graphs of many stations
that show different trend of the two parameters, which is possibly related tomany environmental and geographical factors that are not taking toconsiderations in this research.
The correlation coefficients and linear regression equations which wehave obtained for each yearly and monthly matching pairs of the AOT and
PM10 can be also used to have more clear explanation for the trend of thesegraphs. One another possible reason, for the measurement of the PM10
concentration, we assume that the landscape, where the measurement
stations are located has influence to the measurement of the PM10, since thewind speed and direction including air humidity can be influent to themeasurement. For the case of the MODIS AOT, a pixel with coarse spatial
resolution of 10x10 km2 could give more deviation to the calculated AOT
value within the large observed pixel. These factors will be taken toinvestigation in further study.

Multi-temporal study on PM10 distribution for urban air quality in upper Northern of Thailand using spatial
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Figure 2: Temporal distribution of MODIS AOT and PM10 concentration
within the period years 2007-2011 of 140 matching pairs and it statistical
relationship.

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Figure 3: Trend of monthly distribution of MODIS AOT and PM10
concentration obtained at the geographic location of station‘ChiangMai1’ in Chiang Mai province in February 2007
5.2 Generation of Estimated PM10 Concentration Maps for Upper
Northern of Thailand
In previous section, we have analyzed the trend of yearly and monthly
distribution of MODIS AOT and PM10 concentration obtained for thelocation of 12 measurement stations in the study area in the period of 2007
to 2011, and obtained fairly relationship, as the correlation coefficient is
0.32, with the linear regression equation of y = 57.09 x + 70.93, where, x is
AOT value in digital number (DN), it should be multiplied by a scale factorof 0.001 to be AOT physical parameter, and then can be converted to PM10
value. We apply this equation to convert AOT to PM10, even though thecorrelation is fairly small (correlation = 0.32), but since it was generated
from the data collected from 12 stations located in the study area within the
period of 4 years from 2007 to 2010. Figure 4 shows the quick look imageof the MODIS AOT map (top) and the estimated PM10 concentration(bottom) generated from the MODIS AOT map for Southeast Asia region.
Multi-temporal study on PM10 distribution for urban air quality in upper Northern of Thailand using spatial
Multi-temporal study on PM10 distribution for urban air quality in upper Northern
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Figure 4: MODIS AOT map of February 19, 2009 04:00 GMT from (top)and the estimated PM10 concentration (bottom) for Southeast Asia region.
6. RESULTS AND DISCUSSION
Figure 5 shows an example of the output of our study which is an estimatedPM10 concentration map for Upper Northern Thailand for the date of
February 19, 2009 04:00 GMT, which is generated using MODIS AOT of
the same date and time. The color bar on the right side show the maximum

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ICUS Report 56(reddish color tone) and minimum (dark blue color tone) estimated PM10
value of the PM10 image, therefore, the area with reddish color tone has highvalue of PM10 concentration, while the area with dark blue tone isconsidered to be the area with low value of PM10 concentration. The area
covered by clouds or out-of-scene area have value of 25 μg/m3 which ismarked by the lowest part of the color bar. The white line on the map is thepolitical boundaries. As the original input AOT image has spatial resolutionof 10 x 10km2, therefore, the output estimated PM10 also has same spatial
resolution which is represented by coarse pixels on the output map. The
PM10 value obtained by this conversion can considered as ‘estimated value’or an appearance of the actual PM10 value, which is need to be validated
using ground truth data. As this AOT to PM10 conversion was done using
linear regression equation with low correlation, we can improve it byinvestigating the unusual observed point in the scatter graph shown in
Figure 2, and if it is reasonable to remove it, it would improve therelationship of the datasets and their correlation. In the another hand, thePM10 data provided from PCD in this study, do not cover all of the months
within the time period and also not cover for all stations. Therefore, it isnecessary to have hourly-data cover all months and stations in the year andfor long period of many years, to ensure the best result of data statisticalanalysis. The cloud cover in AOT MODIS images, downloaded from NASAis also one reason that causes data unavailability of AOT value for theimage pixel where the ground station is located, therefore, having multitemporal MODIS AOT data can ensure the availability data within the study
period.

Figure 5: Estimated PM10 concentration map for Upper Northern
Thailand for February 19, 2009 04:00 GMT

Multi-temporal study on PM10 distribution for urban air quality in upper Northern of Thailand using spatial
Multi-temporal study on PM10 distribution for urban air quality in upper Northern
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February 14, 2007 04:00GMT

March 11, 2007 07:00GMT

April 19, 2007 04:00GMT

February 10, 2008 03:50GMT

March 26, 2008 06:15GMT

April 14, 2008 03:50GMT

February 03, 2009 04:00GMT

February 15, 2010 07:00GMT

March 23, 2009 04:00GMT

March 26, 2010 04:00GMT

April 05, 2009 06:40GMT

April 11, 2010 04:00GMT

Figure 6: Estimated PM10 concentration maps for Upper Northern Thailandof selected dates in February, March and April of 2007 - 2010
6. CONCLUSIONS
Trend of MODIS AOT and PM10 concentration from 12 PCD groundmeasurement station in the period of 2007 – 2010 were studied and theirstatistical relationship is obtained and the estimated PM10 Concentration
maps for Upper Northern of Thailand during the period of 2007-2010 basedon the obtained relationship were generated.

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REFERENCES
Environment Division of ASEAN Secretariat HazeOnline. (2008).
Tenth Meeting of the Sub-Regional Ministerial Steering Committee (MSC)on
Transboundary
Haze
Pollution.
Retrieved ,http://haze.asean.org/news/1280390969/, Last access on April 9,
2010
Kasemsan Manomaiphiboon1, Petch Pengchai, Vanisa Surapipith,
Sarawut hepanondh, Rattapon Onchang, Nuwee Wiwatwattana, Veerachai
Tanpipat, & Savitri Garivait. (2009, May). Smoke-Haze Forecast
Modeling for Upper North Thailand during March-April 2008. Paper
presented at The 3rd International Conference on “Sustainable Energy andEnvironmet, Bangkok, Thailand.
Ketsiri Leelasakutum. (2009). The Chiang Mai haze episode in march
2007: Cause investigation and exposure assessment. Master research study.
Asian Institute of Technology, Bangkok.

Multi-temporal study on PM10 distribution for urban air quality in upper Northern of Thailand using spatial
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New Technologies for Urban Safety of Mega Cities in Asia

Site characteristics estimation of BUET
campus by microtremor H/V technique
Mehedi Ahmed Ansary1 and Md. Saidur Rahman2
1
Professor, Department of Civil Engineering,
BUET, Dhaka, Bangladesh
ansary@ce.buet.ac.bd
2

Research Engineer, BNUS, BUET, Bangladesh,srahman.ce.71@gmail.com

ABSTRACT
Degree of damage during earthquakes strongly depends on dynamic
characteristics of buildings as well as amplification of seismic waves.
Among the other approaches, microtremor is the easiest and cheapest way
to understand the dynamic characteristics of soil as well as structuralelement. The purpose of this research is to apply H/V Microtremor
Technique for Site Response Analysis at Bangladesh University ofEngineering and Technology (BUET) campus. Microtremor measurements
have been carried out in one hundred and thirty two selected locations infree-field and fourty five buildings within BUET campus. The amplitude
ratio (H/V) of horizontal to vertical spectra has been used to estimate
predominant frequency and amplification.
For spectral analysis three low noise to signal ratio segments of 20.48s of
the recordings have been taken at 100 Hz instrumental sampling. Fast
Fourier Transformation (FFT) has been applied on the time domain records.
Then, spectral ratio (H/V) technique has been applied. The resultant of two
horizontal components of H/V ratio have been digitally filtered using
suitable average smoothing point. After calculating three sets of the H/Vratios at selected location, the mean H/V ratio has been plotted with half
standard deviation in order to assess the deviation of microtremor data at
different time instants.
From analysis of data it can be said that Horizontal to Vertical spectral(H/V) ratio provides stable data to estimate predominant frequency andamplification of soil without source effect. Fourier Spectrum along EastWest and North-South provides better result to estimate predominantfrequency at building. Out of 132 sites, the overall mean predominantfrequency and mean peak H/V ratio are 1.39 Hz and 2.09. The predominantfrequency for most of the locations lies between 1.0 Hz and 1.99 Hz. Fourbuildings have been identified as vulnerable due to resonance criteria
within BUET campus. Most of the buildings predominant frequency is not
close to the predominant frequency of site soil.

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Keywords: Fast Fourier Transformation,
predominant frequency, resonance criteria

microtremor

H/Vratio,

1. INTRODUCTION
In the recent past, Bangladesh has not suffered any damaging large
earthquakes, but in the past few hundred years, several large catastrophic
earthquakes struck this area. So far, all the major recent earthquakes haveoccurred away from major cities and have affected relatively sparsely
populated areas. In 1897, an earthquake of magnitude 8.7 caused serious
damages to buildings in the northeastern part of India (including
Bangladesh) and 1542 people were killed. Recently, Bilham et al. (2001)
pointed out that there is high possibility that a huge earthquake will occur
around the Himalayan region based on the difference between energy
accumulation in this region and historical earthquake occurrence. The
population increase around this region is at least 50 times than the
population of 1897 and city like Dhaka has population exceeding several
millions. It is a cause for great concern that the next great earthquake may
occur in this region at any time.
The use of microtremor, an idea pioneered by Kanai et al. (1954) turns
into one of the most appealing approaches in the site effects studies, due to
its relatively low economic cost and the possibility of recordings without
strict spatial or time restrictions (Rodriguez and Midorikawa, 2002). The
H/V spectral ratio technique of microtremors gained popularity in the earlynineties, after the publication of several papers (Nakamura, 1989; Lermo
and Chávez-García, 1994) claiming the ability of this technique to estimate
the site response of soft sedimentary deposits satisfactorily. This method israther attractive in developing countries characterized by a moderate
seismicity, where only very limited resources are available for seismic
hazard studies. The H/V spectral ratio determined from microtremors has
shown a clear peak that is well correlated with the fundamental resonancefrequency at “soft” soil sites (Bard, 2004; Horike et al., 2001; Field et al.,
1995; Lachet and Bard, 1994; Lermo and Chávez-García, 1993).
Comparison of microtremor and earthquake spectral ratios at strong-motion
instrument sites across SW British Columbia showed similar fundamental
periods and in greater Victoria remarkably similar amplitudes, validating theuse of the method for linear earthquake site response Molnar et al. (2007).
Ohmachi et al. (1991) and Lermo and Chávez-García (1994) applied
the H/V ratio method to analyze microtremor measurements. Lermo andChávez-García (1993) used it to assess the empirical function of the S-wave,
part of an earthquake record, obtained from three cities in Mexico. Theirresults clearly indicated that the H/V ratio could provide a robust estimate of
frequency and amplitude of the first resonant mode, albeit not of the higher
modes. In the meantime, Field et al. (1995) considered the response of
sedimentary layers to ambient seismic noise and claimed that the H/V ratio
method has been an effective and reliable tool to identify the fundamental
resonance frequencies of all layered sedimentary basin. Further evidence

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has been given by Suzuki et al. (1995) who used both microtremor andstrong-motion data in Hokkaido, Japan and ascertained that the peakfrequency determined by the H/V ratio seemed to correspond with thepredominant frequency estimated from the thickness of an alluvial layer.
Based on numerical calculations, many other researchers (Lermo andChávez-García, 1993, 1994; Lachet and Bard, 1994; Dravinski et al., 1996)
have shown that the H/V ratio method is obviously able to predict
fundamental resonant frequency well. Huang et al. (2002) found that the
ground vulnerability index (Kg) values in the liquefied areas have been
higher than those in the neighboring areas without liquefaction at 42 points
in central Taiwan. This study shows supporting evidence for the first timethat the H/V ratios of microtremor can be a good alternative indicator for an
area’s potential for liquefaction. Site amplification characteristics can beevaluated by one-point two-component surface recordings of earthquake
ground motion, in a similar manner as proposed by Nakamura for
microtremor (Ansary et al., 1996).
For this research microtremor observation has been carried out at one
hundred and thirty two selected locations in free-field and fourty fivebuildings within BUET campus. Although it is not possible to prevent such
calamities, it is however, possible to mitigate the impacts of earthquake.
Specific roles and responsibilities relating to earthquake hazard should beemphasized in our disaster mitigation plan. The objective of this thesis is toanalyze seismic hazard of BUET campus in terms of dynamic
charactersistics of soil (Predominant frequency and Amplification) andresonance criteria.
2. MICROTREMOR STUDY AND SITE SELECTION
Microtremor consists of different types of waves producing in soil fromvarious sources. The common noise sources are vibrating machine, traffic,
environment and human movement. Microtremor observation is carried out
to record time history of noise data. Horizontal to Vertical (H/V) Fourier
spectral ratio technique is applied to assess the vulnerability of soil andbuilding. To check the stability of microtremor observation fourteen
locations of West Palashi within BUET campus has been selected. Afterchecking the stability of microtremor data, microtremor observation has
been carried out at one hundred and eighteen additional locations in soils
and 45 buildings within the BUET campus (See Figure 1).
3. OUTLINE OF METHODOLOGY
The amplitude ratio (H/V) of horizontal to vertical spectra of microtremor
has become popular to determine predominant period and amplification of asite. It is well known that, degree of damage during earthquakes strongly
depends on dynamic characteristics of buildings as well as amplification ofseismic waves. Among the other time consuming and expensive approaches,

Site characteristics
Sitecharacteristics estimation
estimation ofof BUET
BUET campus
campus bybyMicrotremor
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H/V technique
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October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

microtremor is the easiest and cheapest way to understand the dynamic
characteristics of soil as well
as structural element. In a short period of time it provides several
information including natural frequency, amplification and vibration
characteristics of soil and structure at different frequencies. Following steps
have been followed in this research:
A. Microtremor Analysis:
Microtremor observation has been carried out in selected locations
within BUET campus of Dhaka city. Each record comprises of threecomponents, viz., EW, NS and UD. For spectral analysis three noise-freesegments of 20.48s of the recordings have been taken at 100 Hz
instrumental sampling. At each point of sensor location microtremor data
recording have been carried out at different time of the day. Time domain
data is not suitable for the clear identification of soil response due toambient noise. This is why First Fourier Transformation (FFT) has been
applied on the time domain records. After smoothing the corresponding
spectra, spectral ratio (H/V) technique have been applied to derive transfer
functions. The applied sequences are given below:

Figure 1: One hundred and thirty two microtremor observation points insite soil and fourty five points in various building of BUET campus

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I. FFT Transformation:
At first, Fourier spectra of the two horizontal directions (East-Westand North-South) and the vertical component (Up-Down) have been
calculated.
II. Smoothing of the Spectra:
After Fast Fourier transformation (FFT), the combined horizontal andvertical spectra have been digitally filtered applying a logarithmic window
with a suitable bandwidth coefficient. These filtering techniques have been
applied to reduce the distortion of peak amplitudes.
III. Calculation of the Soil Response functions:
The smoothed combined horizontal spectrum have been divided withthe smoothed vertical component to plot Horizontal to vertical spectral ratio(H/V) which will provide the desired predominant frequency andcorresponding amplification factor of the investigated portions (20.48 s) ofrecords.
IV. Estimation of Predominant Frequency and Amplification:
After calculating three sets of the H/V ratios at selected grid, they
have been normalized to obtain a relatively non-biased site specific H/Vratio. Then, Normalized H/V ratios at different time of the day have beenplotted in Logarithmic window. From this normalized H/V ratio thepredominant frequency and corresponding amplification factor of this site
have been taken.
4. MICROTREMOR DATA COLLECTION AND ANALYSIS
Microtremor measurement was carried out in 132 selected locations (Figure1) within BUET campus. In BUET campus, 240 second duration wererecorded at different times in the specific locations. The measurements havebeen carried out from morning to midnight in order to minimize artificial
noises due to traffic and human activities. The microtremor measurement
apparatus for data recording includes Geodas 15-HS equipment (Data logger
and Laptop), Sensor, Cable, Battery and GPS. Mtobs.exe software is used torecord microtremor data. Sensors comprise three components, which canrecord the horizontal motion (in Latitude and Longitude directions) and thevertical motions (up and down). Microtremor sensor sensitivity was
295900μm/sec/V. The converting speed was 50 kHz. The sampling
frequency was 100 Hz. The amplification factor was used 20 db in
observation system.
Figure 2 shows a typical time history field data recording of MT132 at
1:52 AM on 12 February, 2011. The content of all input data are 2 CR4.5-1S
velocity type sensors, 24000 observation data length, 100Hz sampling
frequency, 0.05 Hz Low-pass filter and 20db amplification ratio. Timehistory data is not suitable to estimate the dynamic properties (predominantfrequency and amplification ratio). So, transformation of time domain data
Site characteristics
Sitecharacteristics estimation
estimation ofof BUET
BUET campus
campus bybyMicrotremor
microtremor H/V
H/V technique
technique8195

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

to frequency domain data is required with Fourier Transformation.
Therefore, Fast Fourier Transformation (FFT) has been used to transfer time
domain data to frequency domain data.

Figure 2: Time history free-field data recording at MT132 of BUET campus.
5. STABILITY OF MICROTREMOR DATA
Microtremor is the combination of shear wave, Rayleigh wave and Lovewave. The effect of different waves on microtremor data is significant.
Therefore, stability check of microtremor data is important to estimate
dynamic properties of any site soil. To carry out this research velocity time
history data have been recorded time ranging between morning to midnightat 14 locations in West Palashi, BUET. The observation microtremor data
recording varies from 5 to 20 minutes. Ten minutes observation time has
been taken in most of the observation points. Three segments of 20.48 stime domain data have been used to transform frequency domain spectrum.
In order to get low noise data these Fourier spectra have been filtered using
rectangular windows. The mean of these three segments of frequency
domain data have been calculated using smoothing function with averagesmoothing point 5. From these observations, stability of time variation
microtremor data has been compared from Fourier spectrum. The horizontal
to vertical spectral ratio has also been calculated in these locations toanalyze the stability of H/V ratio with Fourier spectrum.
Instead of using all the observed time records, three to four different
times instants are selected from 24 hour observation for fourteen sites, forinvestigation. Figure 3 shows the vertical and horizontal Fourier spectra of
microtremors observed at MT05. The mean peak value of Fourier spectra
varies from 2.1 Hz to 3.1 Hz for both the horizontal and vertical motions.
Figure 3 also illustrates three time instants (13:07 PM, 16:20 PM and 01:06
AM) and their mean value. From the Fourier spectra analysis of 14 sites, it
can be said that the amplitude level of Fourier spectra vary at different time

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ICUS Report 56

instants of a day. It is not possible to estimate the dynamic characteristics(Predominant frequency and Amplification) of these sites on the basis of theamplitude level of Fourier spectra.
The Horizontal to Vertical spectral ratio along EW and NS directions
are shown in Figure 4 for three different time instants (13:07 PM, 16:20 PM
and 01:06 AM) at MTO5. The characteristics of the peak frequency of theamplitude ratios are different from those for Fourier spectra. The
predominant frequency of two horizontal directions at MT05 is around 0.77.
Although the Fourier spectra are not stable with time, the amplitude ratios at
different time instants along three directions within a day are stable at thesesites. From analysis of Fourier spectra ratio, it can be concluded that thechange of amplitude ratio at different time instants of a day is comparatively
small. In addition to this, the amplitude ratio is less influenced by the sourceof vibration than the Fourier spectrum of any direction and may reflect theparticular charactersistics of the site. Therefore, the Horizontal to Vertical
spectra ratio has been found more reliable to estimate dynamic properties(Predominant frequency and Amplification) of any particular soil.
0

0

10

13:07 PM (EW)
16:20 PM (EW)
01:06 AM (EW)
Mean (EW)

Fourier amplitude spectrum, µm

Fourier amplitude spectrum, µm

10

-1

10

-2

10

-1

10

-2

10

-3

10

-3

10

13:07 PM (NS)16:20 PM (NS)
01:06 AM (NS)Mean (NS)

-1

10

0

Fourier amplitude spectrum, µm

10

-1

0

10

1

10

Frequency (Hz)

10

10

1

10

Frequency (Hz)

0

10

-1

10

-2

10

-3

13:07 AM (UD)
16:20 PM (UD)
01:06 AM (UD)Mean (UD)

-1

10

10

0

Frequency (Hz)1

10

Figure 3: Stability of Fourier Spectrum at different times along EW, NS and
UD directions at MT05

Site characteristics
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estimation ofof BUET
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October 2011, Chiang
Mai,Thailand
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Chiangmai,
1

H/V Ratio10

13:07 AM (EW)
16:20 PM (EW)
01:06 AM (EW)
Mean (EW)

0

10

10

-1
-1

10

10

0

1

10

Frequency (Hz)1

H/V Ratio10

13:07 AM (NS)16:20 PM (NS)
01:06 AM (NS)Mean (NS)

0

10

-1

10

-1

10

0

1

10

10

Frequency (Hz)Figure 4: Stability of H/V ratio data at different times along EW and NS
direction at MT05.
6. ANALYSIS RESULTS AND DISCUSSION
The BUET campus is situated in latitude ranging from 23°43'16.58" N to
23°43'59.44" N and longitude from 90°23'13.31"E to 90°23'43.56" E.
Microtremor observation at 132 selected points in soils and 45 locations inbuilding have been carried out in BUET campus. The analysis results ofthese points have been discussed in Section 6.1 and 6.2.
6.1 Soil sites
Figure 1 shows the observed microtremor locations at 132 selected
locations. Out of 132 sites, the overall predominant frequency is 1.39 Hz
where as standard deviation is 0.289. On the other hand, the overall peak
H/V ratio is 2.09 where as standard deviation is 0.523.
Out of 132 microtremor observation locations, the maximum
predominant frequency is around 9.62 Hz where as H/V ratio is 2.43 at
MT82. Horizontal to Vertical spectral ratio (H/V) varies from 1.65 to 2.51.
On the other hand, the minimum predominant frequency is around 0.25 Hz
where as H/V ratio is 9.51 at MT72. This is the highest peak of H/V ratio in
132 selected locations in BUET campus.

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ICUS Report 56

The predominant frequency of 132 locations has also been classified
into five types. Type I (0 – 0.49), Type II (0.50 – 0.99), Type III (1.0 – 1.99),
Type IV (2.0 – 2.99) and Type V (> 3.00). From this classification of
predominant frequency, it can be said that most of the locations
predominant frequency lies between 1.0 Hz and 1.99 Hz. These
predominant frequencies are classified as Type III. The second mostcommon type of predominant frequency is Type II. The number of locations
predominant frequency classified as Type V is 21. In addition to this, there
are sixteen Type I locations.
On the other hand, Horizontal to Vertical spectral ratio (H/V) has beenclassified into four types. Type I (0 - 0.99), Type II (1.0 - 1.99), Type III(2.0 - 2.99) and Type IV (>3.0). According to classification of H/V ratio,
most of the selected locations are classified as Type III. There are seventy
five Type III locations. Type II is the second most predominant H/V ratio.
There is no H/V ratio ranging between 0 and 0.99. The number of locations
H/V ratio greater than 3 is 15.
6.2 Building sites
Microtremor observations at 45 residential and academic buildings of
BUET campus are shown in Figure 1. The Horizontal to Vertical spectra
ratio at building does not provide reliable dynamic characteristics. In thatcase Fourier Spectrum provides better result of predominant frequency atbuilding. Out of 45 microtremor observation in buildings, the maximum
predominant frequency is 5.56 Hz along both EW and NS directions in
MTB10 at Controller of Examination Building. This is a four-storied frame
structure building with 324sqm floor area. There are no lift and shear wall inthis building. The foundation of the building is individual footing. There are
no structural irregularities in building. But torsional irregularity, re-entrant
corner and diaphragm discontinuity exist. The minimum predominantfrequency is 2.00 Hz along EW and NS directions at MTB02 at the Eleven
Story Tower Building. This is an eleven-storied frame structure with
673sqm floor area. There are three lift cores and a shear wall in the building.
The foundation of the building is pile-raft system. No structural irregularity
exists in this building. But torsional irregularity, re-entrant corner anddiaphragm discontinuity exist.
7. DAMAGE ASSESSMENT
Earthquake vulnerability of the 45 buildings within BUET campus is carriedout from predominant frequency obtained by the analysis of microtremor
data. Microtremor observation has been carried out at 132 selected free-field
locations within BUET campus. The Horizontal to Vertical spectra ratio(H/V) of these locations have been compared with the predominantfrequency of building along EW and NS direction, respectively. The
occurrence of resonance between building and soil has been discussed in
section 7.1. The damage assessment of consolidated soil using Nakamura’s
Seismic Vulnerability Index (Kg) has been described in section 7.2.
Site characteristics
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estimation ofof BUET
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Chiangmai,

7.1 Resonance
7.1
Resonance between
between site
site soils
soils andand buildings
buildings
The resonance criteria of building and soil can be explained using thefollowing simple relation:
Resonance criteria, �
βR =

(1)

Where, �βR = Coefficient for resonance occurrence, = Predominantfrequency of building and = Predominant frequency of soil.
���In ���������
equation �����
(1), ���
if �βR becomes close to 1 (1±0.20), resonance may
occur. The resonance between buildings and soil has been analyzed using���������������������������
this resonance criterion, βR, in both EW and NS directions. Four buildings
have been found as vulnerable due to resonance occurrence. These buildings
are Eleven Story Tower Building, URP Building, Titumir Hall and Building# 1.
7.2 Seismic
7.2
Seismic damage
damage assessment
assessment ofof soils
soils using
using Nakamura’s
Nakamura’s technique
technique
Seismic vulnerability index (Kg) is an index indicating the level ofvulnerability of a layer of soil to deform. Therefore, this index is useful forthe detection of areas that are weak zone (unconsolidated sediment) at thetime of occurrence of earthquakes. Some studies like Daryono (2009) andNakamura (2000) showed a good correlation between seismic vulnerability
index (Kg) and the distribution of earthquake disaster damage. This index is
obtained from the peak value of HVSR squared, divided by the value of the
predominant frequency. From the analysis at 132 locations, the overall mean
Vulnerability Index (Kg) is 1.77 wheras standard deviation is 3.51. The
Vulnerability Index (Kg) value lies between 0.52 and 9.51. The maximum
Kg value is 9.51 at MT-72. On the other hand, the minimum Kg value is0.52 at MT-09.
8. CONCLUDING
8.
CONCLUDING REMARKSREMARKS
From the overall result and analysis of the study following findings may besummarized.
(a) Stability(a)Stability ofof microtremor
microtremor data
data onon ground:ground:Fourier spectra depend on the source of vibration. This data does notshow significant site amplification. That’s why horizontal to vertical
spectral ratio (H/V) of both East-West and North-South have been
calculated. Microtremor H/V ratio do not show the source vibration effect.
Whatever the source is, the amplification result is similar for different time
instants. From this research, it can be concluded that Horizontal to Vertical
spectral (H/V) ratio of microtremor is effective for site response analysis.
This technique is reliable for site soil response compared to Fourier spectra.
(b) Microtremor(b)
Microtremor observation
observation within
within BUETBUET Campus:
Campus:10824

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ICUS Report 56

Microtremor observation at 132 selected points in soil has been
carried out in BUET campus. Out of 132 locations, the overall predominantfrequency is 1.39 Hz. On the other hand, the overall peak H/V ratio is 2.09
where as standard deviation is 0.523. The maximum predominant frequency
is around 9.62 Hz MT82. On the other hand, the minimum predominantfrequency is around 0.25 Hz at MT-72. This lower predominant frequency
and higher amplification ratio show that this location is highly susceptible
due to any seismic hazard. The minimum Horizontal to Vertical spectral
ratio (H/V) is 1.24 at MT 108. From this classification of predominantfrequency, it can be said that most of the locations predominant frequency
ranging between 1.0 Hz and 1.99 Hz. There is no H/V ratio ranging between
0 and 0.99. The number of location H/V ratio greater than 3 is 15.
Microtremor observation on 45 buildings has been carried out within
BUET campus. Fourier Spectrum provides better result of predominantfrequency for buildings. Out of 45 microtremor observation in buildings, themaximum predominant frequency is 5.56 Hz along both EW and NS
directions at Controller of Examination Building. The minimum
predominant frequency is 2.00 Hz along EW and NS directions at Eleven
Story Tower Building.
(c) Resonance between site soil and building:
The resonance between the site soil and building has been analyzed
using the H/V ratio of soil and Fourier spectra of building in both EW and
NS direction. It has been found that resonance may occur at four BUET
buildings. These buildings are Eleven Story Tower Building, URP Building,Titumir Hall and Building # 1. For most of the building predominantfrequency is not close to the predominant frequency of soil. From the subsoil characteristics within BUET campus, it can be concluded that stiff soil
with higher SPT value exists in most of the investigated locations.
(d) Seismic Vulnerability Index (Kg) for soils:
From the analysis at 132 locations, the overall mean Vulnerability
Index (Kg) is 1.77 wheras standard deviation is 3.51. The Vulnerability
Index (Kg) value lies between 0.52 and 9.51. The maximum Kg value is9.51 at MT-72. On the other hand, the minimum Kg value is 0.52 at MT-09.
REFERENCES
Ansary, M. A., Yamazaki, F. and Katayama, T., 1996. Application of
microtremor measurements to the estimation of site amplification
characteristics, Bulletin of Earthquake Resistant Structure Research Center,
IIS, University of Tokyo, No. 29, PP. 95-113.
Bard, P. Y., 2004. Effects of surface geology on ground motion:
Recent results and remaining issues, Proceedings of the 10th European
Conference on Earthquake Engineering, Vienna, Austria, August 28 –September 2, 1994, 305-325.
Bilham, R., Gaur, V. K. and Molnar, P., 2001. Himalayan Seismic
Hazard, SCIENCE, 293.
Site characteristics
Sitecharacteristics estimation
estimation ofof BUET
BUET campus
campus bybyMicrotremor
microtremor H/V
H/V technique
technique11825

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Daryono, 2009. Eftek Tapek Lokal (Local site effect) di Graben
Bantul Berdasarkan Pengakuran Mikrotremor. International Conference
Earth Science and Technology. Yogjakarta.
Dravinski, M., Ding, G. and Wen, K. L., 1996. Analysis of spectral
ratios for estimating ground motion in deep basins, Bull. Seism. Soc. Am.,86, 843-847.
Field, E. H., Clement, A. C., Jacob, K. H., Aharonian, V., Hough, S.
E., Friberg, P. A., Babaian, T. O., Karapetian, S. S., Hovanessian, S. M. andAbramian, H. A., 1995. Earthquake site response study in Giumri (Formerly
Leninakan), Armenian using ambient noise observation. Bull. Seism. Soc.
Am., 85, 349-353.
Horike, M., Zhao, B. and Kawase, H., 2001. Comparison of site
response characteristics inferred from microtremors and earthquake shear
waves, Bulletin of the Seismological Society of America, 91, 1526-1536.
Huang, H. C. and Tseng, Y. S., 2002. Characteristics of soilliquefaction using H/V of microtremors in Yuan-Lin area, Taiwan, TAO,
Vol.13, No.3, 325-338, September, 2002.
Kanai, K., Tanaka, T. and Osada, K., 1954. Measurements of Microtremors 1. Bulletin Earthquake Research Institute, Tokyo University, 32,
199-210.
Lachet, C. and Bard, P. Y., 1994. Numerical and theoreticalinvestigations on the possibilities and limitations of Nakamura’s technique,
Journal of the Physics of the Earth, 42, 377-397.
Lermo, J. and Chavez-García, F. J., 1993. Site effect evaluation using
spectral ratios with only one station, Bull. Seism. Soc. Am., 83, 1574-1594.
Lermo, J. and Chavez-Garcia, F. J. (1994). Are Microtremors Usefulin Site Response Evaluation? Bulletin of Seismological Society of America,
84, 1350-1364.
Molnar, S., Cassidy, J. F. Monahan, P. A. and Dosso, S. E., 2007.
Comparison of geophysical methods to determine shear-wave velocity,
Proceedings of the Canadian Conference on Earthquake Engineering, June
24-27th 2007, Ottawa, ON, Paper 1173.
Nakamura, Y., 1989. A Method for Dynamic Characteristics of Subsurface Using Microtremors on the Ground Surface, Quick Report ofRailway Technical Research Institute, 30, No. 1, 25-33 (in Japanese).
Ohmachi, T., Nakamura, Y. and Toshinawa, T., 1991. Ground motion
characteristics in the San Francisco Bay area detected by microtremor
measurements, Proc. 2nd International Conference on Recent Advances inGeotech. Earth. Eng. & Soil Dyn. Saint Louis, Missouri, 11-15
Rahman, M. S., 2011. Applicability of H/V Microtremor Techniquefor Site Response Analysis in Dhaka city, Masters of Science Thesis,
Department of Civil Engineering, Bangladesh University of Engineeringand Technology.
Rodriguez, V. S. H. and Midorikawa, S., 2002. Applicability of the
H/V Spectral Ratio of Microtremors in Assessing Site Effects on Seismic
Motion, Earthquake Engineering and Structural Dynamics, 31, 261-279.
Suzuki, T., Adachi, Y. and Tanaka, M., 1995. Application of
Microtremor measurements to the estimation of earthquake ground motionsin the Kushiro city during the Kushiro-Oki earthquake of 15 January 1993,
Earthquake Eng. Struc. Dyn. 24, 595-613

12826

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NewPassporting of buildings, its safety andquality in Ulaanbaatar city, Mongolia
Enebish NINJGARAV1, Mendbayar OYUNCHIMEG2,
Yasuoshi ICHIHASHI3 and Danzan DAMIRAN4
1
Vice director, Associate professor,
School of Civil Engineering and Architecture,
Mongolian University of Science and Technology (MUST), Mongolia
ninjgarave@gmail.com
ninj@must.edu.mn
2
Associate professor, School of Civil Engineering and Architecture,
Mongolian University of Science and Technology (MUST), Mongolia
3
Visiting Professor, ICUS, University of Tokyo, Japan
4
Associate professor, School of Civil Engineering and Architecture,
Mongolian University of Science and Technology (MUST), Mongolia

ABSTRACT
Researching and preventing from sudden natural disasters and earthquakes
is one of the most important issues, as half of the population lives in
Ulaanbaatar, the capital city. In Mongolia, most of the buildings built
before 1970 year was not checked for the stability, safety and rigidity during
earthquake. Due to these, in 1998 year there was released a government
decision to issue the buildings a passport or a special document that shows
the quality and all of the related information about it. Furthermore, there
was done a project, whose aim was to register and check the building
quality, moreover prevent it from sudden destructions and damages; andrenew or reconstruct buildings not satisfying the meeting requirements. In
Ulaanbaatar, we need several additional projects to be fulfilled including tocontinue register all of the existing and newly constructed buildings andmake some research on risk of how the earthquake will affect and what kindof damages it can cause on buildings.
Recently, most of the apartments in nine districts of Ulaanbaatar werechecked and classified for the rigidity and stability during earthquake.
Keywords: passporting of buildings, safety, earthquake, building quality,
destruction, damage, register
1. INTRODUCTION
Objective of the experiment and research:
As a result of industrilization, climate change and global warming,
natural disaster occurs so often that we have to protect and take someprevention before irreversible damage of buildings, bridges and all of the8271

October
2011,
Chiang
Mai,Thailand
Thailand
October
2011,
Chiangmai,
Chiangmai,
Thailandfacilities
facilities
peoplepeopleuse.use.
Earthquake
Earthquake
is oneis oneof commonof common
types
types
of disasterof disaster
thatthatcancanoccur
occur
in Mongolia,
in Mongolia,
therefore
therefore
wewe
have
have
conducted
conducted
a researcha research
on on
20 20
buildings
buildings
in in
Ulaanbaatar
Ulaanbaatar
andand
in in
other
other
provincesprovincesthatthat
were
were
built
built
in in
1950-1960
1950-1960
years
years
andandarearenotnotresistive
resistive
to toearthquakes
earthquakes
of of
more
more
than
than
7 Richter7 Richterscales.
scales.
TheTheobjective
objectiveof ofourourresearch
research
is is
to to
determine
determinebuildings
buildings
notnotsatisfying
satisfying
thetheMongolian
Mongolianstandards,
standards,
andand
to to
take
take
some
some
reconstruction
reconstruction
andandpreventions
preventions
on on
these
these
buildings.
buildings.
AccordingAccording
to to
their
their
resistingresistingproperties
properties
to toearthquake
earthquake
andandits its
quality,quality,thethebuildings
buildings
were
were
divideddividedintointo
3 main3 maincategories
categories
includingincludinghighhighrisky,
risky,risky
risky
andandlowlow
risky
risky
to to
thetheearthquake.
earthquake.
TheThefigurefigureof ofthethebuilding,building,
locatedlocatedin in
Songino-Khairhan
Songino-Khairhan
district,
district,belonging
belongingto tothethe
most
most
risky
risky
category
category
is shown
is shown
below.
below.
AsAs
an an
example,example,all allof ofthethecalculations
calculations
andandresearch
research
resultresultwillwill
be be
shown
shown
on on
Songino-Khairkan
Songino-Khairkan
district
districtbuilding.
building.

FigureFigure1: Map1: Mapof Songino-Khairkhanof Songino-Khairkhan
district
districtFigureFigure2: Apartment-4
2: Apartment-4
of Songinoof SonginoKhairkhan
Khairkhan
district
district

2. THE
2. THE
GENERAL
GENERAL
CHARACTERISTICS
CHARACTERISTICS
OFOF
THE
THE
BUILDING
BUILDING
Songino-Khairkhan
Songino-Khairkhan
district
districtbuildingbuildinghashas12 12floorsfloorsandandit wasit wasbuilt
built
at theat theendendof of
1980s.
1980s.
After
After
some
some
years
years
of of
use,use,cracks,cracks,deformations
deformations
andandsome
somedetrition
detrition
appearedappeared
in in
thethe
walls
walls
of of
thethebuildingbuilding
andandit wasit wasclassifiedclassified
to to
high
high
riskriskbuilding,building,
becausebecauseof itsof itslocation
locationin thein thezone
zone
of earthquakeof earthquakeof Richterof Richter
scale
scale
8. 8.
In thisIn thisandandin otherin other
20 20
buildings,
buildings,
some
some
of theof themain
main
structures
structures
were
were
modified
modifiedor ordestructed
destructedby bythetheowners
ownerswithout
withoutconsulting
consultingthethespecialists
specialistsof of
construction
constructionandandengineering,
engineering,which
whichmay
maycausecausesome
somedifficulties
difficultiesandand
deteriorates
deteriorates
thethequalityqualityof theof thebuilding.
building.
2.12.1The
The
methods
methods
andandequipments
equipments
used
used
in experiments
in experiments
andandresearch
research
In In
order
order
to to
research
researchandanddetermine
determine
thetheexact
exact
condition
conditionof ofSonginoSonginoKhairkhan
Khairkhan
district
districtbuilding,building,
wewe
analyzed
analyzed
andandtestedtestedthetheproperties
properties
such
such
as as
vibrational
vibrationalresistivity,
resistivity,physicalphysicaldetrition,
detrition,deformation,
deformation,rigidity
rigidityandand

2 2
828

New
New
Technologies
Technologies
for for
Urban
Urban
SafetySafetyof MegaMegaof Mega
CitiesCitiesin Asia
Asia
in AsiaNew
Technologies
for
Urban
Safetyof
CitiesinICUS Report 56

resisitivity
resisitivityof constructionof construction
materials
materials
and its
and mechanicalits mechanicaland physicaland physicalproperties.
properties.
To testTothe
testproperties
the properties
above,
above,
the following
the following
equipments
equipments
were wereused:used:• “DIGI-SCHMIDT• “DIGI-SCHMIDT2000”,
2000”,
concreteconcretetest hammer
test hammer
performing
performing
rapid rapid
non-destructive
non-destructive
qualityqualitytesting
testing• “SilverSchmidt”,• “SilverSchmidt”,
the concrete
the concrete
test hammer
test hammer• “Profometer-5”,• “Profometer-5”,
devicedevice
indicating
indicating
location
locationand orientationand orientation
of ofreinforcing
reinforcing
bars bars• “Canin”,• “Canin”,
corrosion
corrosion
analyzing
analyzing
instrument
instrument• “Pundit• “Pundit
Lab”,Lab”,
ultrasonicultrasonicconcreteconcretetest test• “GSR-24”,• “GSR-24”,
apparatus
apparatus
for measuring
for measuring
microvibration
microvibration• “SOUTH• “SOUTH
ML-421”,ML-421”,electronic
electronic
devicedevice
for measuring
for measuring
the thedeformation
deformation

FigureFigure3: GSR-24
3: GSR-24
is being
is being
placedplacedoutsideoutsideof theofbuilding
the building

FigureFigure4: Profometer-5
4: Profometer-5
indicating
indicating
reinforcing
reinforcing
bars bars

3. RESEARCH
3. RESEARCHPROCEDURES:
PROCEDURES:
Vibration
Vibrationmeasurements
measurements
and researchand research
The center
The center
for Geophysics
for Geophysics
and Astronomy
and Astronomy
of Mongoliaof Mongolia
conducted
conductedaaresearch
researchon earthquakeon earthquake
magnitude
magnitude
measurements
measurementsthat thatcan canoccuroccur
in inUlaanbaatar
Ulaanbaatar
city. city.
AccordingAccordingto theirto theirresearch
researchwork,work,
the strongest
the strongest
possiblepossibleearthquake
earthquake
in Ulaanbaatar
in Ulaanbaatar
city iscityabout
is about
6.5 magnitude
6.5 magnitude
and theanddegree
the degree
of ofpossiblepossible
damagedamageand destruction
and destruction
were were
determined.
determined.
(Recent(Recent
earthquakes
earthquakes
and andrelatedrelatedmeasurements
measurementswith itwith
are itshown
are shownin table3.)in table3.)
The nearest
The nearest
activation
activationof ofearthquake
earthquake
to Ulaanbaatar
to Ulaanbaatar
city iscity
in is
Gavjinin Gavjin
shandshandand Songino-Sonsgolon,
and Songino-Sonsgolon,that arethatlocatedare locatedin theinwest
the westof Ulaanbaatarof Ulaanbaatar
city. Althoughcity. Although
it is notit isknown
not known
whenwhenthe earthquake
the earthquake
will occur,
will occur,
it is obvious
it is obviousthat itthat
hasit highhas high
occurance
occurance
possibility,
possibility,
so in soorder
in orderto preventto prevent
damagesdamagesand destructions,and destructions,
we have
we haveto be to beprepared.
prepared.

Passportingof buildings,
its safety
and quality
in Ulaanbaatar
city, Mongolia
Passporting
of
its
and
ininUlaanbaatar
city,
Passportingof buildings,
buildings,
its safety
safetyandquality
quality
Ulaanbaatar
city,Mongolia
Mongolia

3 8293

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table-3. Recent earthquakes that were near Ulaanbaatar city
MS

Distance
from
UB,
km

106.93

3.5

6

Ulaanbaatar

47.88

106.95

2.8

6Ulaanbaatar

01:55:45.9

49.33

104.47

4.1

236

Burengiin Nuruu,
Khentii province

02.24.1991

10:22:17.1

47.70

108.92

4.2

154

Baganuur

02.27.1998

05:22:25.8

49.34

107.894.1

174

Selenge09.24.1998

18:53:41.0

46.26

106.305.5

180Deren sum,
Dundgovi
province

12.03.2005

00:50:05.3

47.97

105.365.0

113

02.18.2006

01:52:16.9

50.25

105.47

5.2

279

Date

Occurredtime

09.29.1987

Geographic location
LatitudeLongitude

10:04:18.8

47.96

11.17.1987

13:24:12.2

09.25.1989

Place nameLun sum, Tuv
province
Selengeprovince

Building vibration measurements
The measurements were done in the 1st 8th and 12th floors of thebuilding with GSR-24 device during 30th of May to 13th of June, 2011. The
data we got from these measurements are given in the table 4, table 5 andtable 6.
Table-4. 1st floor measurement result (Acceleration)
№

Year

Month

Day

1

2011

06

2

0.00070.00110.00090.0009

2

2011

06

3

0.00050.00060.00050.0005

3

2011

06

4

0.00080.00050.00070.0006

4

2011

06

5

0.00070.00080.00060.0007

5

2011

06

6

0.00070.001

0.00080.0008

6

2011

06

7

0.00080.00090.00060.0007

7

2011

06

8

0.00070.00080.00080.0007

8

2011

06

9

0.00080.00090.00080.0008

9

2011

06

10

0.00060.00090.00070.0007

10

2011

06

11

0.00050.00030.000350.0003

11

2011

06

12

0.00060.00070.00060.0006

12

2011

06

13

0.00060.00070.00060.0006 m/sec2

0.0007 m/sec2

0.00060.00063
m/sec2Average value

4830

Acceleration
along y axis103

Acceleration
along x axis103

average
acceleration
along z, y, xaxis 103

Acceleration
along z axis103

0.0006 m/sec2

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ICUS Report 56

Displacement
№

Year

Month

Day

Displacement
along z axis 106

Displacement
along y axis 106

1

2011

06

2

0.0000007

0.0000008

Displacement
Averagealong x axis displacement,
106
1060.0000013
0.0000009

2

2011

06

3

0.0000012

0.0000013

0.0000013

0.000001

3

2011

06

4

0.000006

0.000.001

0.0000006

0.0000022

4

2011

06

5

0.000001

0.0000008

0.0000012

0.000001

5

2011

06

6

0.0000012

0.0000007

0.0000008

0.0000009

6

2011

06

7

0.000001

0.000002

0.000001

0.0000013

7

2011

06

8

0.000006

0.000001

0.000008

0.000005

8

2011

06

9

0.0000007

0.0000016

0.0000015

0.000001

9

2011

06

10

0.0000001

0.0000006

0.000001

0.0000005

10

2011

06

11

0.0000012

0.000001

0.0000008

0.000001

11

2011

06

12

0.0000013

0.0000013

0.000001

0.0000012

12

2011

06

13

0.000001

0.0000006

0.0000012

0.0000006

Average value

0.000001 m

0.0000009m

0.000001m 0.0000009m

Table 5: 8th floor measurement result (Acceleration)
№

Year

Month

Day

Acceleration
along z axis103

1

2011

06

6

0.00110.001

0.0013average
acceleration
along z, y,x axis 103
0.001

2

2011

06

7

0.001

0.00020.00140.0008

3

2011

06

8

0.00090.00020.00120.0023

4

2011

06

9

0.00060.00020.00080.0007

5

2011

06

10

0.001

0.00020.00130.0008

6

2011

06

11

0.001

0.00030.0017

0.001

7

2011

06

12

0.00090.00030.00130.0008

8

2011

06

13

0.001

Average value

0.0009 m/sec

Acceleration
along y axis103

0.000220.0003 m/sec

Acceleration
along x axis103

0.001220.00080.001 m/sec

20.0007
m/sec2

Displacement

Year

Month

Day

Displacement
along z axis 106

Displacement
along y axis 106

1

2011

06

6

0.000005

0.000003

Displacement
along x axis
106
0.000004

2

2011

06

7

0.000003

0.000002

0.000003

0.000008

3

2011

06

8

0.000005

0.000002

0.000005

0.000002

4

2011

06

9

0.000019

0.000014

0.000003

0.000012

5

2011

06

10

0.000005

0.000002

0.000007

0.000004

6

2011

06

11

0.000005

0.000002

0.000004

0.000003

7

2011

06

12

0.000006

0.000004

0.000006

0.000005

8

2011

06

13

0.000005

0.000003

0.000006

0.000004

0.000006 m

0.000004m

0.000004m

0.0000046m

Average value

Passportingof buildings,
its safety
qualityin Ulaanbaatar
city, Mongolia
Passportingof buildings,
its andsafetyand quality
in Ulaanbaatar
city, Mongolia

Averagedisplacement,
106
0.000004

5 831

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Table 6: 12th floor measurement result (Acceleration)
№

Year

Month

Day

Acceleration
along zaxis103

1

2011

06

2

0.06

0.06

0.007

average
acceleration
along z, y, xaxis 103
0.04

2

2011

06

3

0.1

0.09

0.09

0.09

3

2011

06

4

0.12

0.11

0.11

0.1

4

2011

06

5

0.13

0.12

0.11

1.12

5

2011

06

6

0.14

0.14

0.15

1.14

6

2011

06

7

0.15

0.17

0.16

0.16

7

2011

06

8

0.11

0.11

0.1

0.1

8

2011

06

9

0.09

0.09

0.1

0.09

9

2011

06

10

0.12

0.14

0.12

0.12

10

2011

06

11

0.06

0.06

0.05

0.05

11

2011

06

12

0.05

0.05

0.05

0.05

12

2011

06

13

0.1

Average value

0.1 m/sec

Acceleration
along yaxis103

Acceleration
along xaxis1030.1
2

0.1 m/sec

0.1
2

0.3

0.09 m/sec

2

0.096 m/sec2

Displacement

№

Year

Month

Day

Displacement
along z axis 106

1

2011

06

2

0.0005

Displacement
along y axis
106
0.0007

2

2011

06

3

0.00050.00050.00050.0005

3

2011

06

4

0.00060.00050.00070.0006

4

2011

06

5

0.00060.00040.00060.0005

5

2011

06

6

0.00060.00050.00090.0006

6

2011

06

7

0.00050.00050.00060.0005

7

2011

06

8

0.00050.00050.00040.0004

8

2011

06

9

0.00040.00040.00050.0004

9

2011

06

10

0.00070.00070.00080.0007

10

2011

06

11

0.00030.00030.00030.0003

11

2011

06

12

0.00030.00030.00040.0003

12

2011

06

13

0.00040.00040.00040.00040.0004m

0.0004m

0.0005m

0.00048m

Average value

Displacement
Averagealong x axis displacement,
106
1060.00070.0006

Table 7: Comparison of displacement values in each floor

6832

AverageFloor

Y axisZ axisX axis10.001mm

0.0009mm

0.001mm

0.0009mm

80.006mm

0.004mm

0.004mm

0.004mm

12

0.4mm

0.4mm

0.5mm

0. 4mm

Displacement

New Technologies
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ICUS Report 56

Figure 5: Vibration measurement X,Y,Z axis

Time (sec)
According to the measurements shown in table 6,7,8 the most displacement
Figure 6: Device records of displacement measurement
was along y axis, which implies that this building is not resistive toearthquake of 8 Richter scale. Results of the engineering calculations weredone on the program Lira. The building located in Songino-Khairkhan
district is a reinforced concrete construction that is in earthquake region of 8
Richter scales. The soil was unstable soil type classified to degree of 2
according to the earthquake properties.
Passporting ofPassportingof buildings,
buildings, its
its safety
safety andandquality
qualityininUlaanbaatar
Ulaanbaatarcity,
city,Mongolia
Mongolia

8337

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

CONCLUSION• Physical detrition of the building is 24 percents, which implies thata reconstruction is needed. If the rehabiliation is done as on the
Mongolian standards of construction, it is possible to use thebuilding.
• Concrete and reinforced concrete structures are sufficient enoughand is resistive to earthquakes, however the reinforcing bars don’t
meet the technical requirements.
• According to the vibration experiment result, the mostdisplacement was from right to left, from which we come to aconclusion that this building is not resistive to the earthquake ofRichter scale of 8.
• In the result of this research, most of the buildings were classified
and analyzed by their properties and passported depending on its
stability and resistivity to earthquake.
REFERENCES
Standards
forconstructionofbuildings
onseismic
zones“BNbD22.01.01*”, 2006
Handbook for Analysing resistivity of old buildings to earthquakes” BNbD 31-102-00, 2007
Program“Мonomakh-SAPR 2011
Program “Lira-SAPR” 2011
Handbook for Passporting of buildings on seismic zones ” BD31-10300

8834

New Technologies
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Mega Cities
Cities inin Asia
Asia
NewInfluence of underground structures
on cavity formation due to repetitionof water penetration
Mari SATO1, Reiko KUWANO2
Ph.D Student, Dept. of Civil Engineering,
Faculty of Engineering, the University of Tokyo, Japanmsato@iis.u-tokyo.ac.jp
2
Associate Professor, ICUS, IIS, the University of Tokyo, Japan
1

ABSTRACT
Many cave-in accidents happen nowadays in urban roads. Cave-in means
sudden collapse of the ground like a pitfall. The accidents are serious
problem because it sometimes injures people.
Recent research showed that expansion of underground cavities finallyleads cave-in accidents. Underground cavities have expanded in the groundwithout being noticed. Then finally surface ground is crashed when cavities
have reached near the surface ground. Many cavities were found close tounderground structures. Some of those cavities were caused due to
breakages of buried structures such as sewer pipes. Soil is flowed out froma crack of a pips with water, and then a cavity is formed. However, in manycases, obvious breakages are not found in underground structures when acavity is formed. It is not clear why cavities were generated around buried
structures even if they didn’t have clear damages, but is empiricallysuggested that water flows more easily around underground structures thanin other part of the ground. Soil is carried with water flow around buried
structures, which might cause a cavity around underground structures.
In order to study the influence of a buried structure on formation of a cavity
due to water penetration, a series of model tests was conducted with a small
soil chamber in various conditions. Specifically, the soil chamber has an
opening, from which soil can be flowed out. A wooden block simulating theunderground structure was placed into the soil chamber. Then small amountof water was flowed into the soil chamber repeatedly from a certain positionand deformation of the model ground was observed. Position of the wooden
block, relative density of soil and direction of water penetration werechanged. From a series of model test, it was suggested that position of theblock and direction of water penetration has large influence on cavity
formation. In addition, the ground around the block has high water content.
Keywords: underground cavity, model test, water penetration, undergroundstructure, cave-in accident

8351

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

1. INTRODUCTION
Many ground cavities are found in the ground close to undergroundstructures nowadays. It is a serious problem in urban cities because cavities
sometimes lead to cave-in accidents which injure people. (Referring to
Figure 1) One of main factor of expansion of cavities is a distinct spot ofsoil outflow like broken parts of sewer pipes, as shown in Figure 2. Kuwano
et al. (2006) conducted model test simulating how a cavity is generated dueto the broken parts of sewer pipes.1) However, specific spots of soil outflow
are seldom found near to cavities. The reason why cavities and loosening
are generated and expanded around the underground structures without
visible spots of soil outflow is not clear. But existence of “water pathway”
surrounding buried structures was empirically suggested. To reveal
influence of underground structures on generation of cavities, model test
simulating soil outflow around an underground structure due to repetition ofwater inflow was conducted with a small soil chamber.

RainfallRise of ground water level
Loosening

CavitySoil outflow

Figure1:Cave-in accident(6th August, Tokyo Newspaper)

Figure 2: Process of cavity expansion
due to breakage of a wewer pipe

2. TEST APPRATUS AND PROCEDURE
2.1 Test apparatus and procedure
Model ground of 300mm long, 50mm wide and 200mm high wasmade by compaction in the small soil chamber having an opening of 5mm ina base plate. Water is flowed out from the opening when drainage valve wasreleased. A wooden block of 21cm long, 50mm wide and 100mm high wasplace into the model ground. Width of the wooden block is same as that ofsoil chamber This wooden block is waterproof so that water doesn’t passinside the block. Overburden weight was put on the top of the model groundby a wooden stand.

2836

New Technologies
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ICUS Report 56

Water is supplied from two different positions which are shown in
Figure 3 and Figure 4. In this paper, test cases of supply position like Figure
3 is named as “Position (A)” and test cases like Figure 4 is named as“Position (B)”. In Position (A), water is supplied from the opening at thecenter of the bottom plate. After stopping water supply and waiting for1mimute, drainage valve was released. The process of water inflow andoutflow is repeated. In Position (B), water is supplied from light or left endof the ground and 150mm height from the bottom. During the test, drainage
valve is kept released. Only water inflow was repeated. In both water supply
positions, Water was supplied from a water tank, which has 100cm headdifference from the soil chamber. The amount of water supply in one time
was approximately 100cc. Details of experimental procedure of Position (A)and Position (B) is shown in Figure 5. This paper defined “a cycle” as watersupply in one time. Cycles were repeated till a cavity expanded large
enough. Photograph was taken in front of the chamber during the test andthe weight of drained soil in dry condition was measured after the test.

Drainage valve
Figure 3: Test apparatus of Position (A)Drainage valve
Figure 4: Test apparatus of Position (B)Influence ofInfluenceof undergroundunderground structures
structures on
on cavity
cavity formation
formation due
due totorepetition
repetitionof
ofwaterwaterpenetration
penetration

8373

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Figure 5: Flowchart of test procedure
3. TEST CONDITIONSAll experimental conditions are shown in Table 1. Relative density was 80%,
initial water content was 10% and overburden weight was around the weightof 80cm depth of the ground in all the test case. Two different types ofwater supply position are prepared (Referring to chapter 2). An
experimental code represents Position of the water supply,(Material,
position of the block).Two kinds of materials are employed: Toyoura sandand Silica sand. Both of two materials are clean uniform sand but average
particle size of silica sand no.5 is twice as that of Toyoura sand. Particle size
distribution is shown in Figure 6. 4 patterns of position of the block were
employed, as indicated in Figure 7. Data of A(T,N) is referred from Sato etal (2010)2).
Table 1: Test conditions
Materials

Positon of Position of thewater supply
block

Initial watercontent (%)

Relative
Density (%)

Test code

Toyoura

A

Vfar

10％

80%

A(T, Vfar)

Toyoura

A

Vnear

10％

80%

A(T,Vnear)

Toyoura

A

H

10％

80%

A(T,H)

Toyoura

A

Vside

10％

80%

A(T,Vside)

ToyouraA

No block

10%

80%

A(T,N))

Silica no.5

A

Vside

10％

80%

A(S,Vside)

Toyoura

B

Vfar

10%

80%

B(T,Vfar)Toyoura

B

Vnear

10%

80%

B(T,Vnear)

Toyoura

B

H

10%

80%

B(T,H)

Toyoura

B

Vside

10%

80%

B(T,Vside)4838

New Technologies
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ICUS Report 56

Figure 6: Particle size distribution

Figure 7: 4 patterns of position of the block
4. TEST RESULT
4.1 Cavity formation
4.1.1 Common formation without the block
Typical forms of a cavity created in the model ground are obtained
from test A(T,N) as shown in Figure8. A cavity of fan-like shape, having
slope at both sides and arching ceiling, was generated above the opening. If

Influence ofInfluenceof undergroundunderground structures
structures on
on cavity
cavity formation
formation due
due totorepetition
repetitionof
ofwaterwaterpenetration
penetration

8395

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,a cavity became large and 100cc water didn’t reach to the top of the cavity,
cavity didn’t expand anymore.

Figure 8: Typical formation of Cavity
4.1.2 Cavity formation with the block of Position (A)Cavity formations of Position (A) are shown in from Figure 9 to
Figure 13. By comparing Figure 9 with Figure 10, distance of the blockfrom the opening didn’t much influence on generation of cavity. However,cavity and ground deformation expanded top or the ground even if theamount of supply water in one time is only 100cc. (Referring to 4.1.1)
Figure 11 suggested that the block which is above the opening prevents soil
drainage and a cavity was expanded below the block. Boiling happened
during water inflow in case the block was beside the opening, which cause
rapid expansion of a cavity (Referring to Figure 12 and Figure 13).

Figure 9: A(T,Vfar) at 14th cycle

Figure 10: A(T,Vnear) at 15th cycle

Figure 11: A(T,H) at 9th cycle

Figure 12: A(T,Vside) at 7th cycle

6840

New Technologies
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ICUS Report 56

FigureFigure13: A(S,Vside)
13: A(S,Vside)at 3rdatcycle
3rd cycle
4.1.34.1.3
CavityCavityformationformationwith withthe blockthe blockof Positionof Position(B) (B)
CavityCavityformationformationof Positionof Position(B) is(B)shown
is shown
in fromin from
FigureFigure14 to14
Figureto Figure
18. White
18. White
arrow
arrow
line line
represents
represents
the water
the water
supplysupplyposition.
position.
FigureFigure18 is18a is aprevious
previous
condition
conditionof Figureof Figure14. In14.allIntest
all cases
test casesof Positionof Position(B), (B),cavitycavitywas wasgenerated
generatedcloseclose
to theto block.
the block.
Dot Dot
arrow
arrow
line lineof Figureof Figure
15 and15 andFigureFigure16 16
represents
represents
the direction
the directionof waterof waterflow.flow.
Therefore,
Therefore,
direction
directionof expansionof expansion
of ofcavities
cavities
was along
was alongthe direction
the directionof waterof waterflow.flow.
ColoredColoredsandsandlayerlayer
was wasformedformedin everyin every
3cm 3cmfor observationfor observationof theof thegroundgrounddeformation
deformationin Bin(T,Vfar)
B (T,Vfar)
as Figureas Figure
14 and14 Figureand Figure
18. Figure
18. Figure
14 14
and andFigureFigure18 suggested
18 suggested
that thatthe groundthe grounddeformation
deformation
happened
happened
beforebeforecavitycavitywas generated.
was generated.

FigureFigure14:B(T,
14:B(T,
Vfar)Vfar)
at 12th
at 12thcyclecycleFigure
Figure15:B(T,Vnear)
15:B(T,Vnear)
at 7thatcycle
7th cycle

FigureFigure16: B(T,H)
16: B(T,H)
at 7thatctcle
7th ctcle

FigureFigure17: B(T,Vside)
17: B(T,Vside)
at 7thatcycle
7th cycle

Influenceof undergroundstructures
on cavity
formation
due todue
repetitionof waterpenetration
Influenceofstructuresonformation
toofofwater
penetration
Influenceof undergroundundergroundstructures
on cavity
cavityformationdue
torepetition
repetitionwater
penetration

7 8417

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Figure 18: B (T,Vfar ) at 10th cycle
4.2 Weight of soil loss
4.2.1 Soil loss of Position (A)A relationship between cycles and cumulative weight of soil loss in
Position (A) was shown in Figure 19. It was suggested that rapid soil
drainage happened in A (S,Vside), A (T,Vside) and A(T,H). Silica sand no.5
caused more rapid soil outflow than Toyoura sand. On the other hand, in A
(T,Vfar) and case A (T,Vnear), soil drainage didn’t happen so much until
10th cycle. It is supposed because the block is not to close to the direction ofwater inflow/outflow from/to the opening. Then after 10th cycle, soil
drainage happened very rapidly. In case A (T,N), soil outflow stopped at 8th
cycle because cavity became too large to be filled by the water (Referring to4.1.1). Consequently, it was supposed that existence of the block madecumulative weight of soil loss at final cycle larger than that without theblock.

Figure 19: Cumulative weight of soil loss in Position (A)8842

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4.2.1 Soil loss of Position (B)A relationship between cycles and cumulative weight of soil loss in
Position (B) was shown in Figure 20. From Figure 20, it is suggested that
rapid soil outflow happens if the block is near to the opening like B(T,Vnear) and B (T,Vside). On the other hand, soil outflow was very gentle
in the case the block is not near to the opening like B (T,Vfar) and B(T,Vfar). Influence of the block’s distance from the opening on soil outflow
was suggested.

Figure 20: cumulative weight of soil loss in Position (B)5. DISTRIBUTION OF WATER CONTENT IN THE MODELGROUNDFor examining of the distribution of high water content area in the model
ground, water content ratio was measured at 9 spots in B (T,Vfar) after
finishing the experiment. Result of water content ratio in each spot is shownas Table 2. From Figure 21 and Table 2, the high water content area existed
right side of the block. This area especially extended from the water supply
point to the opening. Therefore, it was proposed water pass through left sideof the block to the opening and the water flow caused the cavity and grounddeformation. On the other hand, at spot 6, water content ratio was very highbut the cavity didn’t generated because direction of water flow didn’t set tothe opening.

Figure 21: measurement spot of B (T,V far)Influence ofInfluenceof undergroundunderground structures
structures on
on cavity
cavity formation
formation due
due totorepetition
repetitionof
ofwaterwaterpenetration
penetration

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Table 2: water content ratio of each spot
Spot

Water content
(%)

5

23

1

34

6

41

2

26

7

32

3

34

8

20

4

29

9

39

6. DISCUSSION AND CONCLUSION
Water flow to the opening causes soil drainage. The block has large
influence on the generation of cavity when the block was placed as blocking
the water flow to the opening. The wooden block caused rapid soil outflow
in some conditions. Concentration of water flow surrounding the blockcaused cavity expansion and sometimes boiling happens. On the other hand,
Water flow was prevented by the block in the other conditions, which makes
soil outflow gently. However, if direction of water flow was changed,
sudden expansion of cavity may happen. In the real ground, same process is
supposed to occur around the underground structures. Process of generationof cavity around an underground structure is estimated in Figure 22.
Concentration of water flow around a buried structure underground structure

Figure 20: Schematically water flow surroundings a buried structure
REFERENCES
Sato, M. & Kuwano, R. Model Tests for the Evaluation of Formationand Expansion of a Cavity in the ground. Proc. of the 7th International
Conference on Physical Modelling in Geotechnics 2010. Zurich, June 2010,
pp.581-586
Kuwano, R, Yamauchi, K., Horii, T. and Kohashi, H. 2006. Defects ofsewer pipes causing cave-in’s in the road. Proc. of 6th International
Symposium on New Technologies for Urban Safety of Mega Cities in Asia.
Phuket: No.H63.

10844

New Technologies
Technologies forfor Urban
Urban Safety
Safety ofof Mega
Mega Cities
Cities inin Asia
Asia
NewApplication of elastic wave measurement
to model tests using bender elements
1

Sho OH1and Reiko KUWANO2
Graduate Student, School of Eng., The University of Tokyo, Japansoh@ iis.u-tokyo.ac.jp
2
Associate Professor, ICUS, IIS, The University of Tokyo, Japankuwano@iis.u-tokyo.ac.jp

ABSTRACT
Elastic wave measurement using Bender Elements have been developed as adynamic measurement method for element test in geotechnical field. Now
this method is expected to apply also for model tests in order to obtain thepressure distribution inside soil chamber. This research aims to obtain thebasic performance information of bender elements in model tests. First, inorder to detect the wave arrival clearer, signal analysis is conducted. Low
frequency noise is reduced by polynomial approximation, and highfrequency noise is dealt with FFT filter. Next, the effect of attachingaluminum block to bender element is discussed. Some change in thereceived wave form is found, but wave velocity was almost same. Also,
property of wave propagation is checked using plural receiver for one
transmitter. Finally, shear modulus is calculated for obtained data forvalidation. Results showed good agreement with those of element test.
Keywords: elastic wave measurement, bender elements, model test,
aluminum block, increment of earth pressure
1. INTRODUCTION
Box culvers are structures buried inside high embankment as tunnels forwater, electric line, communicate line and so on. In designing of these box
culverts, increase in vertical earth pressure must be considered, sincedifferential settlement often occurs around a buried structure, as
schematically shown in Figure 1. However, in practice, the increment ofvertical earth pressures on underground structures is estimated in theempirical manner, mainly based on the information of past earth pressure
measurements in limited of sites (General guidelines for road earthworks,
1999). In this method, degree of settlement and mechanical properties ofbackfill materials are not considered. Some research have been conducted tosolve this problem. However, due to the limited performance of earthpressure transducers used in experiment, details of the earth pressure
distribution were not clearly understood.
Recently, a sophisticated trap door apparatus is developed by Ebizuka
and Kuwano (2010), in order to improve the problems in previous studies. A
soil chamber for trap door testing is constructed, the inside of which is8451

October 2011, Chiang
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Chiangmai,

shown in Figure 2. It can accommodate model ground of 700mm wide,
294mm long and 555mm high. The base of the chamber consists of five
separated movable blocks whose size is 99.8mm wide, 293.6mm long and
105mm high, and fixed parts in both sides, in order to create unevensettlement in the model ground, as schematically shown in Figure 3.
The final goal of this research is to obtain pressure distribution insidemodel test using this soil chamber to quantitatively evaluate the verticalearth pressure acting on buried structures. For the method of measurement,
elastic wave measurement using bender element is chosen.
Elastic wave measurement using bender elements have beendeveloped as a dynamic measurement method for element test. Measuring
propagation time of S wave inside soil gives shear modulus of soil. And by
conducting shear wave tomography, distribution of pressure can be obtained.
Although this is a useful method, no application for model test is conducted
before. In this paper, basic performance information of bender elements isstudied for model tests.

Figure 1: Increment of the earth pressure due to the uneven settlement

5 movable parts

Figure 2: Detail of soil chamber

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2. ELASTIC WAVE MEASUREMENT
2.1 Bender Elements
Bender elements are small measurement devise that transfer electric
voltage to physical deformation and vice versa. There are two types of
elements as shown in Figure3. Series type is more suitable for receiver andparallel type is better used as transmitter. Measurement is done by burying
these two types of bender elements in soil.
(a)

(b)

Figure 3: Bender Elements of (a) Series and (b) Parallel type
2.2 Measurement Apparatus
Measurement apparatus used in this study is shown in Figure4, and thedetails of setting are shown in Table 1.
Table 1: Setting of Aparatus

Output Voltage of Function Generator
Trigger Interval
Wave form
Amplifier rate
Averaging times by Oscilloscope

8Vpp
1s
Sin wave
100 time
20

(b)

(a)

Figure 4: Aparatus used in this study. (a) Function Generator (b)Oscilloscope
3. DETECTION OF WAVE ARRIVAL
The biggest problem of bender element application in model test so far isthe difficulty of detection of wave arrival. In order to make the detection
more accurate, two methods are taken. One is signal analysis and another is
attaching an aluminum block on the top of bender element. The effect ofeach method is discussed in this chapter.

Application ofApplicationof elastic
elastic wave
wave measurement
measurement toto modelmodel tests
testsusing
usingbenderbenderelements
elements8473

October 2011, Chiang
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3.1 Signal Analysis
Figure 5 (a) shows original obtained wave signal. To reduce the large
low noise in this signal, polynomial approximation using quadratic curve isconducted for 2000 points out of 5000. Subtracting the fitted curve from theoriginal signal gives more clear view of response but still some highfrequency noise as shown in Figure 5 (b).
(a)

Wave Response (Vpp)

0.000-0.002-0.004-0.006-0.004-0.002

0.000

0.002

0.004

0.002

0.004

time (s)(b)
0.0004

Wave Response (Vpp)

0.00020.0000-0.0002-0.0004-0.004-0.0020.000

time (s)Figure 5: (a)Original obtained signal and (b) Low noise reduced
signalIn order to reduce the high frequency noise, the spectrum intensity ofsignal at -0.003 to -0.001s (before wave arrival) and 0.001 to 0.002 (after
wave arrival) is compared and shown in Figure 6. Three strong peaks seen
before wave arrival (a) are reduced after wave arrival (b), therefore thesefrequency can be regarded as noise.

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(a)
0.005

0.004

Intensity
強度

0.003

0.002

0.001

0.000

-0.001
050000

100000150000200000250000

周波数 (Hz)
Frequency

(b)
0.06
0.05

強度
Intensity

0.04
0.03
0.02
0.01
0.00
-0.01
0

50000

100000150000200000250000Frequency
周波数(Hz)Figure 6: Spectrum intensity (a) before wave arrivaland (b) after wave arrival
Removing high frequency noise by FFT filter gives final version ofwave signal as shown in Figure 7. Method of wave detection is shown in
Figure 8.
0.0004

Wave Respose (Vpp)

0.00020.0000-0.0002-0.0004-0.004-0.002

0.000

0.002

0.004

time (s)Figure 7: Wave signal after noise cutting

Application ofApplicationof elastic
elastic wave
wave measurement
measurement toto modelmodel tests
testsusing
usingbenderbenderelements
elements

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October 2011, Chiang
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0.0004

Wave Respose (Vpp)

0.00020.0000-0.0002

Wave Arrival-0.0004-0.004-0.002

0.000

0.002

0.004

time (s)Figure 8: Wave arrival point
3.1.1 Effect of Aluminum Blocks
In element tests, attaching aluminum blocks on top of a benderelement reduced much noise and gave clear wave. This method is appliedalso for model tests. Size of aluminum blocks used in this study is
5mm/5mm/10mm.
There are several ways of attaching. Results are shown in Table 2.
Transmitter

Table 2 Results of aluminum block

ReceiverObtained Signal0.0004Filtered Y1

0.00020.0000-0.0002-0.0004-0.004-0.002

0.000

0.002

0.004

Filtered X1

0.0004Filtered Y1

0.00020.0000-0.0002-0.0004-0.004-0.002

0.000

0.002

0.004

Filtered X1

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0.0004Filtered Y1

0.00020.0000-0.0002-0.0004-0.004-0.002

0.000

0.002

0.004

0.002

0.004

Filtered X1

0.0004Filtered Y1

0.00020.0000-0.0002-0.0004-0.004-0.0020.000

Filtered X1

Following facts can be said from this result.Attaching aluminum block
to both transmitter and receiver make arrival of wave small. Transmitterwith aluminum block cause different shape of arrival wave, but travel timeis almost same as non-aluminum block. Attaching aluminum block toreceiver gives almost same wave shape and arrival time with non-aluminum
blocks. As a result, attaching aluminum blocks does not have effect to clear
arrival wave in model test.
4. VALIDATION OF OBTAINED DATA
4.1 Simitenous Recieving
Property of shear wave propagation should be checked. Three
receivers are set for one transmitter to see if wave is propagating in straight
way as shown in Figure 9.

Application ofApplicationof elastic
elastic wave
wave measurement
measurement toto modelmodel tests
testsusing
usingbenderbenderelements
elements

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Thailand
Chiangmai,

S

S

S

P

Direction of Wave Propagation

S

S

S

P

Figure 9: Experiment for wave propagation checking
Results are shown in Figure 9. Divergence of result for last receiver israther large because of the long distance between bender elements. Wavevelocities are almost same, which suggest wave is propagating in straightway.

Wave Velocity (m/s)

200

150

100

4kHz
50

8kHz
10kHz
12kHz

0
0

5

10

15

20

25

Distance between Elements (cm)Figure 9: Results for wave propagation checking
4.2 Shear modulus
Shear modulus is calculated for obtained data using following
formulas.
G = ρVs 2(1)(2.17 − e) 2
f (e) =
1+ e
(2)

8
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ICUS Report 56

where G is shear modulus, e is density, Vs is shear wave velocity ande is void ratio. Since model test is conducted under nearly uniform condition,next relationship is approximated for calculation. Results agreed favorablywith element test as shown in Figure 10.

12σh = σv(3)

Normalized shear modulus (G/f(e)). MPa

1000

100

10
Element Test (DT)Element Test (TA)Model Test (BE)

1
1

2.5

5 7.5 1025

50 75100250

500 7501000

0.5(σ1.σ3) ,kPa

Figure 10: Normalized shear modulus versus earth pressure
5. CONCLUSION
1. In order to detect the wave arrival clearer, signal analysis is conducted.
Low frequency noise is reduced by polynomial approximation, and highfrequency noise is dealt with FFT filter.
2. Effect of attaching aluminum block to bender element is discussed.
Some change in the received wave form is found, but wave velocity wasalmost same.
3. Property of wave propagation is checked using plural receiver for one
transmitter and found to be in straight way.
4. Shear modulus is calculated for obtained data for validation. Results
showed good agreement with those of element test.

REFERENCES
General guidelines for road earthworks - culvert work -, 1999. Japan
road association, ISBN 978-4889504101, Maruzen Print Co. Ltd. (inJapanese).

Application ofApplicationof elastic
elastic wave
wave measurement
measurement toto modelmodel tests
testsusing
usingbenderbenderelements
elements8539

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

Kuwano, R., Horii, T. and Kohashi, H., 2007, Increment of Earth
Pressure Acting on a Buried Box Structure due to Differential Settlements,
New Frontiers in Chinese and Japanese Geotechniques, Proceedings of theThird Sino-Japan Geotechnical Symposium, 2007, 309-314.
Suwal, L., Kuwano, R., Small strain stiffness measurement of sandand gravel using disk shaped piezo-electric transducer, 5th International
Conference on Earthquake Geotechnical Engineering, 2011

10854

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New

City development safety and improvementof urban planning of Ulaanbaatar city
Yondonsuren JARGALSAIKHAN1, Yasuoshi ICHIHASHI2
1
Senior officer, National Security Council, Mongolia
jargalsaikhan@nsc.gov.mn
2
Visiting Professor, ICUS, University of Tokyo, Japan
yo_jagaa@yahoo.com
ABSTRACT
Since its transition from socialist planned economy to market oriented in
1990, considerable changes occurred in all social and economic sectors ofMongolia. While before 1990, entire population has job, living standards
were quite alike, today we have high rate of unemployment and poverty,
particularly in rural areas. In this regard, people are constantly migrating
to the capital and other cities where the industrial and business environment
is segmenting.
As a result, population of Ulaanbaatar city increased from 600,000 in 1990
to 1,150.0 thousand today, in other words 2.1 times increase; where most ofwhich migrated from rural areas. Following this increase, demand forsocial and economic sectors such as health, education and many others
substantially increased, consequently with subsiding supply of these sectors.
Taking in consideration the future perspective of Ulaanbaatar City, a major
planning challenge is how to address further growth of city and mainly
continuation of migration. Current situation as well many social andeconomic parameters directly impact the urbanization level of Ulaanbaatar
city. Expansion of economy, migration of population to the city, both have
immediate connection to Ulaanbaatar’s population diversion.
Given a scenario of “Do-Nothing” in terms of land-use management during
urbanization, urban sprawl will continue to take place in any available
areas in Ulaanbaatar City. Land occupation will be disorderly, hereby
blighting the city and eroding its potentials for urban economic growth.
Therefore, the management of urban growth will surely become crucial
along with the growing urban economy.
Surrounding area of Ulaanbaatar City, as part of it, is becoming
independently growing economic zone. With sensible planning of satellite
cities and formation of Ulaanbaatar city, alleviate of population
concentration will be manageable with provision of necessary security.
Mongolian Housing Program includes following strategies, namely:• New town development;• Densification of housing in the center of the city;8551

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,•••“Ger” area improvement;
Development of mortgage capital market; andCapacity building, promotion of the construction industry andconstruction materials’ production.

1. INTRODUCTION
During 20 years time, since its transition from central-planned economy to amarket- oriented economy in 1990, considerable changes occurred in allsocial and economic sectors of Mongolia. Before 1990, all the working age
people used to own jobs, living standards and level of the population weresimilar. However, today unemployment and poverty level is in high rate,particularly, in rural areas. Due to this challenge, people are constantly
migrating to the capital and other cities where the industrial and businessenvironment is segmenting.
As a result of it, population of Ulaanbaatar city increased 2.1 times
from 550,000 in 1990 to 1,160.0 thousand today, where most of themmigrated from rural areas. Following this increase, demand on social andeconomic sectors such as health, education and many others substantially
increased. In other words, the existing capacities cannot cover the required
demands.
Today Mongolia has 2.7 million populations. The biggest city is
Ulaanbaatar, where 1161.8 thousand people are and next 2 cities /Darkhan,
Erdenet/ have 50.0-100.0 thousand people respectively, 10 cities have 20.050.0 thousand people, 10 cities with 10.0-20.0 thousand people respectively.
Ulaanbaatar, Darkhan, Erdenet cities have formed central region of thecountry, becoming more manufactured and agricultural cities with
infrastructure. 48.6 percentage of the whole population live in these threecities.
The other cities are aimags centers which hold main administrative
unit of the country. Comparing to the cities of another countries there arefew populations in Mongolian aimag centers-cities. Mongolia has vast land
but few populations. Therefore, slowing down the migration fromcountryside to the center, developing regions delivering social services andintroducing urban culture to the rural area people are very important for
Mongolia.
Table 1: Comparison of the cities population

1

2
856

Urbanization levelCity
quantityMore than 1.000.000

1Name of the cities /population in thousandpeople/by date 01/01/2011
Ulaanbaatar (1,161.8)

Between 100.0001.000.000--

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ICUS Report 56
2
3

4

Between 50.000100.000
Between 20.00050.000

Between 10.00020.000

Total

2

Darkhan (87.6), Erdenet (80.1)

10

Choibalsan (39.1), Murun (33.1), Ulgii (30.0),
Khovd(28.4),
Undurkhaan(26.9),
Bayankhongor (26.3), Arvaikheer (25.1),
Zuunkharaa (22.9), Sainshand (22.6), Ulaangom(21.9),

10

Tsetserleg (18.8), Altai (18.5), Uliastai (16.5),
Bulgan (15.7), Dalanzadgad (14.8), Zuunmod(13.6), Mandalgovi (10.2), Sukhbaatar (12.4),
Baruun –Urt (12.4), Choir (7.6)

23

Cities population in total 1,760.7 thousand,which means 63.9 % of the total population ofMongolia.

As seeing by the official census of population number of population in
Ulaanbaatar was 1,500 in 1926, 10,500 in 1930, but 1,031.2 thousandpeople in 01/01/2008, and it became one of the world cities, which haveover one million population. Population census shows that since 1990, ourpopulation has been increased twice, and if the mechanic increase continues
as this way, the city population will estimated 1,563.7 thousand by 2015,
and 1,965.1 thousand by 2020. Our calculation shows that if Ulaanbaatar
city’s population increases continuously this way, almost 59-63 percent ofMongolian population will live in the capital.
In recent years, the country’s GDP per capita has been continuously
increasing, and as a result of the government actions such as for improvingsocial life of the rural people, giving livestock to herders (who’s livestock
died by harsh winter), supporting small and medium facilities and farmers,building road networks, creating industry& trading zones trend of the
migration to the cities has been slowing down.
Ulaanbaatar city has totally 9 districts, including central districts namelly
Sukhbaatar,
Chingeltei,
Bayanzurkh,
Bayangol,
Khan-uul,Songinokhairkhan, and outskirt districts namelly Baganuur and Nalaikh. It
has 4,704 square km area. Whereas Bayanzurkh, Songinokhairkhan districts
have 1200 square km area, the Bayangol district has only 29.5 square km
area. In the last 3 years, the capital city’s population has been increased by
110.0 thousand people.

City development
Citydevelopment safety
safety andand improvement
improvement ofof urbanurban planningplanningof
ofUlaanbaatar
Ulaanbaatarcity
city

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Table 2: Ulaanbaatar city’s population and number of households
Districts

Popualtion Households Average Territory
Dencityfamily(km ) (person\km2)
members
136,91734,503
4.0
208,40657,01

Sukhbaatar

2

Chingeltei

147,438

31,648

4.2

89,30

3

Bayanzurkh

265,997

63,483

4.2

1,244,12213,84

Bayangol

185,104

43,545

4.3

29,49

6,276,85

Khan-Uul

112,055

27,808

4.0

484,66231,2

6Songinokhairkhan

252,264

55,6004.5

1,200,63

210,1

Central districts

1,099,775

256,5874.3

3,256,60337,7

7

Baganuur

26,9057,092

3.8

620,2043,48Nalaikh

31,4588,527

3.7

687,6445,79

Bagakhangai

3,647

976

3.7

140,0026,1

Outskirt districts

11617852731824.24704442469

1,651,0Eventually in Mongolia, population density is 1.7 people per 1 squarekm, while in most provinces 0.5-1.0, in Ulaanbaatar city 237.2, by the
district such as: in Sukhbaatar district 657.0 in Chingeltei district 1651.0, in
Bayangol district 6276.8.
Japan’s density is 337 person per square km, which ranks 4th(Bangladesh -975, South Korea -477, Nederland – 386, this are top 3
countries) in the world, has 14 cities, which have over 1 million people, 6 ofthem has density of 6-13 thousand per square km. Now Ulaanbaatar city’s
population number is reaching to the level of the world biggest cities facing
the same problems as in the big cities.
Ulaanbaatar which is in distinguished geological condition andlocationsurroundedbyBogdkhan,Chingeltei,
Bayanzurkh,
Songinokhairkhan mountains and urban infrastructure has limited space.
First urban planning was drafted during 1960 to 1980’s and in this planning
Ulaanbaatar city’s population was predicted to be 500.0-600.0 thousandpeople. But in reality, the population has been doubled and facing somedifficulties. Therefore, there is an urgent need to determine the right ways
and rational policies to solve these problems:
•

4
858

Current urban development implementation has not being
complied with Ulaanbaatar city’s urban development master
plan, construction norms and standards for last 10 years. That’s
why urban development has not been carried systematically,green area, public space, road, parking space are small or not

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ICUS Report 56

•
•

•
•
•
•
•
•

built by the requirements of the related norms and standards andsome of them even disappeared.
City is located in seismic active area, but it might be that most of
the existing buildings are not resistant enough to earthquake.
61.2 percent of the city’s population lives in a traditional “ger”
tent house, which doesn’t have central heating, water supply, andsanitation system, proper roads, green zones, and the ger area isheavily polluted with smoke and dust.
Now the air-pollution in the city is many times over thepermitted level, since in winter time, ger area people use
ordinary stove and coal for heating.
Tuul river has been polluted because many leather processing
factories, which use harmful chemicals, are located in the central
area.
Solid waste and other rubbish pollute the city’s land, water andair.
Traffic jam and crashes occur many times due to insufficienttraffic network.
The city, which has over 1 million people, uses big and small
buses, cabs, for public transport and always lacks of transport
service.
Central heating, electric, water supply source are not sufficientwith the public demand.

In last 8-9 years, our economy is stabilizing, manufactures,companies’ capacities are strengthening, and there are many positivechanges in the living conditions of the people.
However the problems occurred during the transition period, which
influence to the development and safety of Ulaanbaatar city. In order toresolve the problems we are taking the following measures:••

We are drafting “Urban redevelopment law” to create a favorable
legal framework in order improving urban planning of
Ulaanbaatar city. The draft law includes matters such as
neutralizing centralization, developing satellite towns, renewing
old apartment buildings and districts, building new apartmentareas in the existing ger areas or introducing land readjustment
plans in ger areas.
We are planning to develop the following satellite cities toreduce disaster risk, improve social and economic development: Developing Zuunmod city as wholesaling and servicing,
warehousing and transportation center; Develop Baganuur area: as mining, coal- chemistry,electricity, construction material, processing livestock raw
materials, developing export oriented production facilities
and transportation;

City development
Citydevelopment safety
safety andand improvement
improvement ofof urbanurban planningplanningof
ofUlaanbaatar
Ulaanbaatarcity
city

8595

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

•
•

•

•

•
•
•

 Developing Nalaikh area: as tourism, student campuses,
advanced technology, developing export oriented small size
production facilities;
 Developing Bagakhangai area: as developing export oriented
production facilities, wholesaling and trading service,
warehousing and transportation;
 Developing
Emeelt-Songino-Tuul mini zone area: as
breeding livestock, farming, agriculture and settlement area ; Developing Gorkhi- Terelj area: as relaxing, tourism center.
 Developing Jargalant mini zone area: as breeding livestock,advanced farming, agricultural, warehousing; Developing Argalant area living area: as product processing,
and warehousing.
Also we are taking some actions such as enforcing to follow
urban planning rules and standards, demolishing some nonstandard constructions, building roads and creating green areas.
Have started checking quality of all apartment buildings using
professional tools and devices within 2 years time since its
operation. Using the results of this checking process we aregoing to have a detailed plan to renew the old buildings.
In June, the Mongolian Government has made a decision toestablish earthquake early warning public system in the capital
city and nationwide. To implement the Government’s decision,
we have started choosing equipments and looking for financial
sources. Also “Technical council” with participants of the relatedorganizations has been established.
“Law on reduction of the Capital city’s air pollution” wasapproved in January, 2011 by the Parliament of Mongolia. In
accordance with the law confinement zones are determined, andnon-smoke or smokeless stoves are being introduced.
Removing leather processing factors from the central area toisolated area.
Research work and studies are under implementation to use
metro, monorails and special roads for public bus services.
Working to build new 5th Power plant in Ulaanbaatar city.

We hope by implementing the above-mentioned measures,
Ulaanbaatar city will became safest city and have clean air, non-polluted
water and soil, and green environment, with good quality and modernbuildings and infrastructure and the citizens will have good working andliving conditions

6860

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NewEvaluation of tsunami strengths ofhouses subjected to a Tsunami wave load
1

Gaku SHOJI1 and Hirofumi SHIMIZU2
Associate Professor, University of Tsukuba, Japan
gshoji@kz.tsukuba.ac.jp
2
Graduate Student, University of Tsukuba, Japan

ABSTRACTThe damage of confined-masonry-brick and concrete-block houses isassessed subjected to a tsunami wave load due to the recent threeearthquakes and tsunamis at the 2001 Near Coast of Peru, the 2009 Samoa
Islands, and the 2010 Maule, Chile. We analyze 13 data surveyed for
affected houses, which are single-storey ones located along the coastlines,
focusing on the evaluation of tsunami wave pressure distribution on a houseinferred by various failure modes when subjected to an inundation depth.
Based on the related formula by Asakura et al. (2000) hydraulicexperimental results, we identify the required tsunami strength of a wall
which is not suffered with an inundation depth.
Keywords: tsunamis, damage assessment,
concrete-block, tsunami wave pressure

confined-masonry-brick,

1. INTRODUCTION
Recent severe earthquakes and tsunamis in the world cause many fatalities
and missing: the 2001 Near Coast of Peru, June 23 (UTC 20:33:14, MW=8.4)(2001 Peru tsunami), the 2004 Sumatra, Indonesia, Dec.26 (UTC 00:58:53,
MW=9.1) (2004 Indian Ocean tsunami), the 2006 South of Java, Indonesia,
July 17 (UTC 08:19:28, MW=7.7) (2006 Java tsunami), the 2009 Samoa
Islands, Sept. 29 (UTC 17:48:10, MW=8.1) (2009 Samoa tsunami) and the2010 Maule, Chile, Feb.27 (UTC 06:34:14, MW=8.8) (2010 Chile tsunami)
as well as the Great East Japan earthquake and tsunami occurred on March
11, 2011 in Japan (UTC 05:46:24, MW=9.0) (2011 Japan Tohoku tsunami).
The reason of the catastrophe is that houses located within few kilometersfrom a coastline are suffered severely by a tsunami wave. Therefore it isvery essential to clarify the mechanism of a tsunami wave load acting on ahouse, based on the tsunami damage assessment for suffered houses.
Matsutomi and Izuka (1998) propose the simple formulation to derive
the tsunami fluid velocity on a house, based on the results of hydraulicexperiments. Matsutomi et al. (2004) clarify the dependence of tsunami
fluid force on a house on hydraulic quantity such as a drag coefficient.
Asakura et al. (2000) propose the formula (Asakura formula) to evaluate
tsunami wave pressure distribution on a structure located at the land behind8611

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

on-shore structures and this formula is used for designing a tsunami
evacuation building (Japanese Cabinet Office, 2005). Shoji et al. (2007)
discuss validness of Asakura formula from damage assessment for suffered
houses at the 2006 Java tsunami. Regarding the research on development oftsunami damage function of structures, Matsutomi and Shuto (1994) reveal
relations between the inundation depths and velocities, and damage ranks ofsuffered houses. Koshimura et al. (2009) propose the methodology todevelop the tsunami damage function by using tsunami damage data fromremote sensing, field survey and numerical analysis.
From the reason above, we analyze the tsunami damage data ofconfined-masonry-brick and concrete-block houses affected by the 2001
Peru tsunami, the 2009 Samoa tsunami and the 2010 Chile tsunami. Basedon the Asakura formula, we identify the required tsunami strength of a wall
which is not suffered with an inundation depth.
2. SUBJECT EARTHWUAKE TSUNAMIS AND STRUCTURES
We use the investigation data for damage of concrete-block houses at the2001 Peru tsunami (Tani et al., 2010) (Peru data), that for damage of lifeline
systems and confined-masonry-brick houses at the 2009 Samoa tsunami(Miyajima et al., 2009) (Samoa data) and that for damage of confinedmasonry-brick houses at the 2010 Chile tsunami (Shoji et al., 2010) (Chiledata). Walls in suffered houses are analyzed. Among all survey data weselect houses for analysis which are single-storey ones located along thecoastlines and do not affected by floating debris as well as by seismic
excitations. It means that houses for analysis have no crack at joint parts ofbeams and columns, and related structural components such as a beam, acolumn and a wall get damaged dominantly due to a tsunami wave load.
Table 1 shows height H, width B and thickness w of subject wall. In
addition Table 1 shows inundation depths h and the related references.
Height H, width B and thickness w of subject wall are basically from Peru,
Samoa and Chile survey data. When the related data are lacked, we detect
those parameters by analyzing the digital pictures for subject walls.

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ICUS Report 56

Table Table
1: Height,
1: Height,
width width
and thickness
and thicknessof subjectof subject
wall andwallrelated
and related
observed
observed
inundation
inundation
depth depth

Wall'sHouse's House's
Wall'sWall's
Latitude Latitude
LongitudeLongitude
height※※numbernumbernumber number
H [m]
p1

p1 p1

p1
S16°39'19.6"
S16°39'19.6"
W72°40'35.1"
W72°40'35.1"
2.35

p2

p2

p21
p22

p21
2.60
S16°39'31.8"
S16°39'31.8"
W72°38'45.3"
W72°38'45.3"
p22
2.60

Wall'sWall'sWall's Inundation
Wall's Inundation
ReferencesReferences
for inundation
for inundation
heightwidth thickness
width thickness
depth
depth
depths depths
H
B [m]
B
w[m]
[m]
w [m]
h [m]
h [m]
InundationInundation
depth measured
depth measured
3.50
2.35
3.50
0.16
0.16
2.60
2.60
3.3km in the
3.3km
nearestin thedirectionnearest direction(Tani et al.,
(Tani
2010)
et al., 2010)
3.20
2.60
3.20
0.16
0.16
2.60
2.60
InundationInundation
depth mesured
depthinmesured in
the house the
(Tani
house
et al.,(Tani
2010)
et al., 2010)
3.60
2.60
3.60
0.15
0.15
2.60
2.60

p3

p3 p3

p3
S16°39'36.0"
S16°39'36.0"
W72°38'04.7"
W72°38'04.7"
0.65

4.95
0.65

4.95
0.16

0.16
2.13

p4

p4 p4

p4
S16°39'35.9"
S16°39'35.9"
W72°37'59.9"
W72°37'59.9"
2.20

3.30
2.20

3.30
0.16

0.16
2.13

p5

p5 p5

p5
S16°39'35.8"
S16°39'35.8"
W72°37'57.2"
W72°37'57.2"
2.50

2.80
2.50

2.80
0.16

0.16
2.28

s1

s1

s11

s11
2.00
S14°15'06.7"
S14°15'06.7"
W170°33'53.5
W170°33'53.5
s12
2.03

2.53
2.00

2.53
0.15

0.15
2.55

3.96
2.03

3.96
0.15

0.15
2.55

s2

s2

2.68
1.80

2.68
0.15

0.15
2.55

s22

s21
1.80
S14°15'15.5"
S14°15'15.5"
W170°33'51.9"
W170°33'51.9"
s22
1.80

2.16
1.80

2.16
0.15

0.15
2.55

c1

c1 c1

S36°33'9.69"
c1
S36°33'9.69"
W72°57'25.33"
W72°57'25.33"
2.33

3.82
2.33

3.82
0.15

0.15
0.97

c2

c2 c2

S36°32'14.89"
c2
S36°32'14.89"
W72°57'32.42"
W72°57'32.42"
2.07

1.35
2.07

1.35
0.15

0.15
0.81

c3

c3 c3

S36°44'48.72"
c3
S36°44'48.72"
W73°5'3.57"
W73°5'3.57"
2.67

2.90
2.67

2.90
0.15

0.15
1.00

s12
s21

InundationInundation
depth obtained
depthnearobtained near
2.13 the investigation
the investigation
spot(Koshimura,spot(Koshimura,
2001)
2001)
InundationInundation
depth obtained
depthnearobtained near
2.13 the investigation
the investigation
spot(Koshimura,spot(Koshimura,
2001)
2001)
InundationInundation
depth masured
depthinmasured in
2.28
the house the
(Tani
house
et al.,(Tani
2010)
et al., 2010)
Inundation
Inundation
depth measured
depth measured
at
at
2.55
the front wall
the front
in subject
wall in subject
2.55
house(M iyajima
house(Met iyajimaal., 2009)
et al., 2009)
InundationInundation
depth measured
depth measured
2.55
0.3km in the
0.3km
nearestin the nearest
direction(Mdirection(Miyajima et iyajimaal.,
et al.,
2.55
2009)
2009)
InundationInundation
depth measured
depth measured
at
at
0.97the side wall
the inside
subjectwall in subject
house(Shoji
house(Shojiet al., 2010)
et al., 2010)
InundationInundation
depth measured
depth measured
at
at
0.81
the side wall
the inside
subjectwall in subject
house(Shoji
house(Shojiet al., 2010)
et al., 2010)
InundationInundation
depth measured
depth measured
at
at
1.00the side wall
the inside
subjectwall in subject
house(Shoji
house(Shojiet al., 2010)
et al., 2010)※p denotes※p denotes
Peru, s Peru,
denotess denotes
Samoa Samoa
and c denotes
and c denotes
Chile respectively.
Chile respectively.

3. COMPUTATION
3. COMPUTATION
OF TSUNAMI
OF TSUNAMI
STRENGTHS
STRENGTHS
OF SUBJECTOF SUBJECT
WALLS
WALLS
3.1 Calculation
3.1 Calculationof Tsunami
of Tsunami
Strengths
Strengths
3.1.1 Type1
3.1.1 Type1
FailureFailureModeMode
As shown
As shown
in Figurein Figure1(a), when
1(a), whenshear shear
crackscracks
occur occur
in pairedin pairedwalls walls
whichwhich
are placed
are placedat right
at angles
right angles
to a coastline,
to a coastline,
we classify
we classify
the failure
the failuremode modeof a wallof a aswall
type1
as type1
failurefailuremode mode(hereinafter(hereinafterty1). Shearty1). Shearstrength
strengthof a wallof a wall
V1 is calculatedwith ty1
withV1ty1
is calculated
as theas
following
the following
equation,
equation,by settingby setting
W=W/2
W=W/2
when when
adapting
adapting
AsakuraAsakuraformula,formula,V1 = τ 1VA1 = τ 1 A

(1)

(1)

wherewhere
A is cumulative
A is cumulative
surfacesurfaceareas areasof bricksof bricks
and concrete-blocks,
and concrete-blocks,
since sinceaawall iswall
madeis madeby bondingby bonding
bricksbricks
and concrete-blocks
and concrete-blocks
with mortar.
with mortar.
In Eq.In(1)Eq. (1)τ 1 is τshear
τ
τ
is
shear
stressstress
and
we
and
set
we
the
set
value
the
value
of
of
based
based
on
the
on
following
the following
1
1
1
2
2
procedure
procedureby referring
by referring
the value
the valueof 0.4ofN/mm
0.4 N/mmby previousby previous
research
research(Nakano,(Nakano,2005, 2005,
and Nakano
and Nakano
and Park,and 2005a,
Park, 2005a,
2005b).
2005b).
For dealing
For dealing
with Peru
with Peru22τ 1 is assumed
τ 1 is assumed
data (concrete-blocks)
data (concrete-blocks)
to be to0.2N/mm
be 0.2N/mm
which
which
is 1/10
is of
1/10 ofcompression
compression
strength
strengthof a ofconcrete-blocka concrete-blockused used
for a fornon-proofa non-proofEvaluationof tsunami
strengthsof houses
subjected
to a tsunami
wave load
Evaluationofstrengthsofsubjected
towave
Evaluationof tsunami
tsunamistrengthsof houses
housessubjected
toaatsunami
Tsunamiwaveloadload

3 8633

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,

strengthening wall (Ministerio de Vivienda, Republica del Peru, 2006). For
dealing with Chile data (masonry-bricks) τ 1 is assumed to be 0.35N/mm2,
which is conservative value, and which is 1/20 of compression

W

A

H

TsunamiCrack
B
coastline

w(a) Paired walls placed at right angles

TsunamiH
Bw(b) A wall out of placed along a

to a coastline

Figure 1: Relation between direction of a tsunami wave and longitudinal
axis of subject wall strength of a brick used for a prism-type wall specimen(Yanez et al., 2004).
3.1.2 Type2 Failure Mode
As shown in Figure 1(b), when tensile and shear failures occur out ofa wall placed along a coastline, we classify the failure mode of a wall astype 2 failure mode (hereinafter ty2). Ty2 is classified into two mechanisms:
tensile failure between bricks and concrete-blocks bonded with a frame bymortar (mechanism 1; ty2-m1) and shear failure between those (mechanism
2; ty2-m2).
We calculate tensile strength T2 and shear strength V2 by the following
equations, by setting W = B when adapting Asakura formula,

T2 = 2 ( B + H ) wσ 2(2a)V2 = 2 ( B + H ) wτ 2(2b)where σ 2 is tensile stress between bricks and concrete-blocks bonded with aframe by mortar, and we use the value of σ 2 =0.24N/mm2 by referring
Architectural Institute of Japan Standard Specifications for Concrete-Block
Structures (1997). τ 2 is shear stress between bricks and concrete-blocks
bonded with a frame by mortar, which value is assumed to be 0.09N/mm2
from the research by Sanada et al. (2006).
3.2 Results on Tsunami Strength
Table 2 shows results of ty1 shear strength V1 , ty2 tensile strength T2
and ty2 shear strength V2 , and the parameters related with tsunami wave
pressure on subject wall as we mention later.

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Wall p1 failure mode is assumed to be ty2 since p1 failed out of the plane.
onty2-m1,Based, while basedon ty2-m2,
As well wall p21 failure mode is assumed to be ty2 since most part of it wascollapsed. Hence, for p21 T 2 and V2 are computed respectively as shown in
Table 2. In contrast, wall p22 is placed at right angles to the coastline in thesame house as wall p21, then the failure mode is assumed to be ty1. Basedon ty1 for wall p22. On theother hand we can suppose wall p22 failed out of the plane after the tsunami
flow attacked wall p21. Viewed in this light wall p22 failure mode isassumed to be ty2, and the related values
values ofof TT22 and V 2 are computed asshown in Table 2. Wall p3 failure mode is assumed to be ty2 since most partof it was collapsed as well as wall p1. By considering wall p3 boundary
conditions as upper and one side
side boundaries
boundaries areare free,free, we
we computecompute TT22 and VV2
by modified Eq (2a) and (2b):andasshown in Table 2. In the same way, for rest of Peru data (p4, p5), Samoa
data (s11, s12, s21, s22) and Chile data (c1, c2, c3), the related wall failuremode is classified into ty1
ty1 andand ty2,ty2, andand wewe computecompute VV11, TT22 and V 2 as shownin Table 2.
Table 2: Computed ty1 shear strength V1 , ty2 tensile strength T2 and ty2
shear strength V2 , and the parameters related with tsunami wave pressure
on subject wall
Wall'snumber
p1
p21
p22
p3
p4
p5
s11
s12
s21
s22

c1
c2
c3

Failue mode Tensile stress Shear stressnumber[kN][kN]
p1-ty2-m1
449.28́‐
p1-ty2-m2
́
168.48‐p21-ty2-m1
445.44
́‐
p21-ty2-m2
́167.04‐p22-ty1p22-ty2-m1

́‐446.40p22-ty2-m2
p3-ty2-m1
p3-ty2-m2

́‐215.04́‐́
‐
407.04p4-ty1
p5-ty2-m1
p5-ty2-m2
s11-ty2-m1
s11-ty2-m2

́‐326.16s12-ty2-m1
s12-ty2-m2
s21-ty2-m1

́‐431.28́‐
322.56s21-ty2-m2
s22-ty2-m1

́‐218.88s22-ty2-m2
c1-ty2-m1

́‐442.80c1-ty2-m2
c2-ty1c3-ty1

́
‐
́
‐
́
‐

η'
��

aa

6.75
3.26
6.76

2.60
1.25
2.60

3.35
2.77

1.29
1.07

6.16
3.12
7.14
2.88

2.37
1.20
3.35
1.35

́
‐
152.64

2.66
7.18
3.47

1.25
3.15
1.52

́
‐
122.31

7.57
3.46

2.97
1.36

́
‐
161.73
́‐
120.96

6.49
3.06
7.72

2.55
1.20
3.03

3.46
8.38

1.36
3.29

3.70
6.23
3.07

1.45
6.77
3.34

3.57
5.12

4.41
5.12

108.00́‐
167.40́‐
80.64
105.60

́
‐
82.08
́
‐
166.0570.88
152.25

Evaluation of
Evaluationof tsunami
tsunami strengths
strengths ofof houses
houses subjectedsubjectedto
toaatsunami
Tsunamiwave
waveload
load

5
865

October 2011, Chiang
Mai,Thailand
Thailand
Chiangmai,
Collapse

p3

Cracking

p4 p5

c2

No damages1,s2 p1,p2

c1 c3

Concrete block
Masonry brick

0

1

2

Inundation depth[m]3

Figure 2: Relation between inundation depth and damage rank of subject
wall
4. TSUNAMI WAVE PRESSURE DISTRIBUTION ON SUBJECT
WALLS
4.1 Relation between Inundation Depth and Damage Rank
Figure 2 shows relation between observed inundation depth anddamage rank of subject wall. We categorize wall damage into three damage
ranks: completely and mostly collapse (collapse), partially collapse andoccurrence of cracks (cracking), and no structural damage (no damage).
Damage ranks of ‘collapse’ and ‘cracking’ for concrete-block houses (Perudata) show in the range of inundation depth from 2.13m to 2.60m. Damage
ranks of ‘no damage’ and ‘cracking’ for masonry-brick houses (Samoa andChile data) show with inundation depth from 0.81m to 1.00m, and damage
rank of ‘collapse’ with inundation depth 2.55m.
4.2 Evaluation of Tsunami Wave Pressure Distribution based on
Observed Inundation Depth
Tsunami wave pressure distribution on subject wall in horizontal
direction is computed by the following Asakura formula (Asakura et al.
2000),px ( z ) = ρ g ( aηmax − z )(3)where px ( z ) is horizontal wave pressure, ηmax is maximum run-up height,
ρ is density of mass of sea water in a unit volume and z is height fromground level. a is defined as horizontal wave pressure index which means
magnification factor of hydrodynamic pressure on a rigid body due to atsunami wave compared with hydrostatic pressure with ηmax . Asakura et al.
indicate a = 3.0 for a non-breaking wave from their experimental results.
Therefore it indicates that assumption of a ≥ 3.0 is required theoretically todesign a tsunami-proof structural component subjected to a non-breaking
tsunami wave. To put it another way for a non-breaking tsunami wave,
horizontal wave pressure distribution of a = 3.0 on a structural component
is the border that a structural component becomes whether damaged or

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undamaged.
undamaged.
In thisInstudy
this study
firstlyfirstly
we suppose
we suppose
ty1, ty2-m1
ty1, ty2-m1
and ty2-m2
and ty2-m2
failurefailuremodesmodes
defineddefinedin Section
in Section
3.1 for3.1subject
for subject
walls walls
exposedexposedto a tsunami
to a tsunami
wave wave
and calculate
and calculate
the corresponding
the corresponding
tsunamitsunamistrength
strength
R (including
R (including
ty1 shearty1 shear, ty2 tensile
strength
strength
T2 andT2ty2
andshearty2 shearstrength
strength
V2). Second
V2). Second
we westrength
strength
V1, ty2V1tensilea asfollowing
computecomputeinversely
inversely
the value
the valueof a asof thethe following
equations
equationsby assumingby assumingηmax equalηmax equal
h . Byhcomparing
to be observed
to be observed
inundation
inundation
depth depth. By comparing
the value
the valueof a of awith tsunami
with tsunami
damagedamageof subjectof subject
walls,walls,
we discuss
we discussvalidness
validnessof Asakura
of Asakura
formula.
formula.

1 2R
1 2R
a= a=
h ρ gWh ρ gW(4a) (4a)⎞1 ⎛ 12 R⎛ 2 R ⎞a = a ⎜=
⎜ + H ⎟+ H ⎟2h ⎝ ρ2gWHh ⎝ ρ gWH⎠⎠(4b) (4b)wherewhere
W is width
W is widthof a wallof asubjectedwall subjected
to a tsunami
to a tsunami
wave wave
as shown
as shown
in Figurein Figure′ = aisηmax
1. When
1. Whenthe value
the valueof η ′ =ofaηmax
lessisthan
less orthanequal
or equal
to a wall
to a heightwall heightH, H,
horizontal
horizontal
wave wave
pressurepressure
distribution
distribution
is the istriangle
the triangle
one asoneshown
as shown
and aandis a is′ = aisηmax
more
is morethan athan
walla wallcomputed
computedby Eqby(4a).
Eq (4a).
WhenWhenthe value
the valueof η ′ =ofaηmax
heightheightH, horizontal
H, horizontal
wave wave
pressurepressure
distribution
distribution
is the istrapezoid
the trapezoid
one andoneaandis a isη ′ andη ′aand
a . Figure
computed
computedby Eqby(4b).
Eq Table(4b). Table
2 shows
2 shows
computed
computed. Figure
3 shows
3 shows
h . Similarly,
h . Similarly,
relation
relationof a withof a observedwith observed
inundation
inundation
depth depth
FigureFigure
4 shows
4 shows
the results
the resultsfor Srifor
Lank
Sri Lank
and Thailand
and Thailand
data atdata
the at2004
the Indian
2004 Indian
OceanOcean
tsunamitsunamiby Nakanoby Nakano
et al. et(2005)al. (2005)
and Java
and data
Javaatdata
the at2006
the 2006
Java tsunami
Java tsunami
by Shoji
by Shojietetal. (2007)
al. (2007)
as well
as aswellin asFigure
in Figure3, with3, withshowing
showing
the analytical
the analyticalresultsresultscorresponding
corresponding
to ty1toandty1ty2
andfailurety2 failuremodesmodes
for subject
for subject
walls.walls.
aa≤ 3.0a ≤are
3.0observed.
From From
FigureFigure3(a) among
3(a) among
Peru data
Peru 10
datadata
10 withdata awith
are observed.
h of 2.13m~2.60m,
h of 2.13m~2.60m,
showsshows
1.07~2.60
1.07~2.60
for inundation
for inundation
depth depth
whichwhichindicates
indicates
AsakuraAsakuraformulaformulais valid
is validin thesein thesecases cases
becausebecausethese thesewalls walls
are actually
are actually
sufferedsufferedwith thewithdamage
the damage
rank ofrank
eitherof either‘collapse’‘collapse’or ‘cracking’.
or ‘cracking’.
On theOn theother other
hand among
hand among
Peru data
Peru2datadata2withdata awith> 3.0a >are3.0observed,
are observed,
showing
showing
the theh of 2.13m
h of 2.28m.
collapse:collapse:
3.35 with
3.35 hwithof 2.13m
and 3.15
and with
3.15 hwithof 2.28m.
It is inferred
It is inferreda is slightly
largerlarger
than 3.0,
thana3.0,
walla wallfrom thesefrom thesedata that
datawhenthat whenthe value
the valueof a isof slightly
has low
has possibility
low possibility
to actuallyto actuallycollapsecollapsedue toduevariation
to variationof strengthof strength
of ofmaterialmaterial
properties
properties
and construction
and construction
condition
condition
when when
fabricating
fabricating
a wall.a For
wall. Fora ≤ 3.0a ≤are
3.0 observed,
SamoaSamoa
data (Figure
data (Figure3(b)) 3(b))
6 data6 withdata withare observed,
showing
showingh of 2.55m.
1.20~2.97
1.20~2.97
with hwithof 2.55m.
TheseThesewalls walls
collapsecollapse
actually,
actually,
the reason
the reason
is whyis why> 3.0a >are
3.0 areAsakuraAsakuraformulaformulais valid
is validin thesein thesecases.cases.
In addition
In addition
2 data2withdata awith
h of 2.55m.
observed
observed
as wellas as
wellforasPeru
for data:
Peru data:
3.03 and3.033.29
and with
3.29 hwithof 2.55m.
TheseThesea > 3.0a .>From
3.0 . Fromwalls walls
also collapse
also collapse
althoughalthough
FigureFigure3(c) Chile3(c) Chiledata hasdata4 hasdata4 data
> 3.0a :>they
3.0 : show
h of 0.81m~1.00m.
with awith
they show
3.34~6.77
3.34~6.77
with hwithof 0.81m~1.00m.
Among
Among
them them
we canwesay
canAsakura
say Asakura
formulaformulamay bemay
valid
be valid
becausebecause3 data3 havedata nohave
damageno damagealthoughalthough
one data
oneshows
data shows
cracking.
cracking.

Evaluationof tsunami
strengthsof houses
subjected
to a tsunami
wave load
Evaluationofstrengthsofsubjected
towave
Evaluationof tsunami
tsunamistrengthsof houses
housessubjected
toaatsunami
Tsunamiwaveloadload

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Inundation depth[m]6Collapse
Cracking

5

p1-ty2-m1, p21-ty2-m1

p21-ty2-m2
4
p22-ty2-m2 p5-ty2-m2

p5-ty2-m1

32

p22-ty11

p1-ty2-m200p3-ty2-m1

p3-ty2-m2

p22-ty2-m1

p4-ty11

3

2
aInundation depth[m]6Collapse

54

s22-ty2-m2

3 s12-ty2-m2

s21-ty2-m1

s12-ty2-1

2

s11-ty2-m1
1 s11-ty2-m2, s21-ty2-m2 s22-ty2-m1

0
0

2
a

1

(a) Peru data

34(b) Samoa data

6

Inundation depth[m]4

Cracking
No damage

5
4
3
2
1
00

c1-ty2-m2

c3-ty1c1-ty2-m1

c2-ty13a69(c) Chile data

Figure 3: Relation between computed horizontal wave pressure index a andobserved inundation depth h for Peru, Samoa and Chile data
When walls with a of slightly larger than 3.0 in Peru and Samoa data
are assumed to be suffered by ty2-m2, a becomes less than or equal to be
3.0. It is quite likely that these walls actually collapsed with a failure mode
by not ty2-m1 but ty2-m2.
By comparing Figure 3(a), (b) with Figure 4(a), no data with a ≤ 3.0
showing no damage in Peru and Samoa data are observed while 4 data witha ≤ 3.0 showing no damage in Sri Lanka and Thailand data are observed. In
contrast, Sri Lanka and Thailand data have one data with collapse regardless8868

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of a > 3.0 as well as Peru and Samoa data. By comparing Figure 3(c) with
Figure 4(b), as we mentioned above, there are one data with a > 3.0
showing cracking with ty1 failure mode in Chile data as well as two data inJava data, which a especially show 4.19~5.33. Therefore it is possible thata wall with a of around 4~5 beyond a = 3.0 , that has larger tsunami strength,
suffers with cracking failure mode due to a tsunami wave.

Inundation depth[m]65

All plots are ty1

No damage
Cracking
Collapse

4
3
2
1
00
6

Inundation depth[m]63aCracking

5

4

3
ty2-m12
1

ty2-m200(a) Sri Lanka and Thailand data

ty1

ty2-m2ty1

3
aty2-m16(b) Java data

Figure 4: Relation between computed horizontal wave pressure index aand observed inundation depth h for Sri Lanka and Thailand data (Nakano
et al., 2005), and Java data (Shoji et al. ,2007)
5. CONCLUDIONSWe analyzed the tsunami damage data of confined-masonry-brick andconcrete-block houses affected by the 2001 Peru tsunami, the 2009 Samoa
tsunami and the 2010 Chile tsunami. We classified them into three failuremodes of a wall subjected to a tsunami wave: shear cracks induced in paired
walls which are placed at right angles to a coastline (ty1), tensile failure
induced out of a wall between bricks and concrete-blocks bonded with aframe by mortar (ty2 mechanism 1) and shear failure induced out of a wall
between those (ty2 mechanism 2). Based on the formula proposed by
Asakura et al. (2000) (Asakura formula) to evaluate tsunami wave pressure
distribution on a structure located at the land behind on-shore structures,
Evaluation of
Evaluationof tsunami
tsunami strengths
strengths ofof houses
houses subjectedsubjectedto
toaatsunami
Tsunamiwave
waveload
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used for designing a tsunami evacuation building (Japanese Cabinet Office,2005), by assuming 24 failure modes for subject 13 walls, we identified therequired tsunami strength of a wall which is not suffered with an inundation
depth. Following conclusions were deduced.
(1) 16 data with a ≤ 3.0 show collapse and cracking failure modes,
and 3 data with a > 3.0 show no damage among 24 assumed failure modes.
Hence from these results, Asakura formula is almost valid to evaluate
tsunami strength of a wall subjected to a non-breaking tsunami wave.
(2) When subject walls with a of slightly larger than 3.0 (3.03~3.35)
in Peru and Samoa data are assumed to be suffered by ty2 mechanism 2, a
becomes less than or equal to be 3.0. It is quite likely that these walls
actually collapsed with failure mode by not ty2 mechanism 1 but ty2
mechanism 2.
(3) One data with a > 3.0 showing cracking with ty1 failure mode inChile data is observed as well as two data in Java data, which a especiallyshow 4.19~5.33. Therefore it is possible that a wall with a of around 4~5
beyond a = 3.0 , that has larger tsunami strength, suffers with cracking
failure mode due to a tsunami wave.
ACKNOWLEDGEMENTS
This study was sponsored by the research project on earthquake and tsunami
disaster mitigation in Peru under the framework of "Science andTechnology Research Partnership for Sustainable Development(SATREPS)", by Japan Science and Technology Agency (JST) and Japan
International Cooperation Agency (JICA) (leader, Professor F. Yamazaki at
Chiba University and Professor S. Koshimura at Tohoku University). And
the authors deeply appreciate research information and valuable assistanceassociated with the field survey provided by the related professors,researchers and officers of local government at Peru, American Samoa andChile.
REFERENCES
Architectural Institute of Japan, 1997. Standard Specifications forConcrete-Block Structures.
Asakura, R., Iwase, K., Iketani, T., Takao, M., Kaneto, T., Fujii, N.,
and Ohmori, M., 2000. Experimental study on wave force acting on onshore structures due to overflowing tsunamis. Proceedings of Coastal
Engineering 47, JSCE, 911-915.
Japanese Cabinet Office, 2005. Guideline for Tsunami Evacuation Bui
lding. http://www.bousai.go.jp/oshirase/h17/050610/guideline.pdf, 2011.2.1
3.
Koshimura, S., Okal, E., Dengler, L., Araya, S., Borrero, J., Gomer, B.,
Laos, G., Olcese, D., Ortiz, M., Swensson, M., Titov, V., and Vegas, F.,
2002. Field survey of the 2001 Peruvian Earthquake Tsunami. Proceedingsof Coastal Engineering 49, JSCE, 1461-1465.

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Koshimura, S., Namegaya, Y., and Yanagisawa, H., 2009. Fragility
functions for tsunami damage estimation, Doboku Gakkai Ronbunshuu B,
Vol.65, No. 4, 320-331.
Matsutomi, H., and Shuto, N., 1994. Tsunami inundation depth,
tsunami velocity and the related damage of houses. Proceedings of Coastal
Engineering 41, JSCE, 246-250.
Matsutomi, H., and Iizuka, H., 1998. Tsunami current velocity on land
and its simple estimation method. Proceedings of Coastal Engineering 45,
JSCE, 361-365.
Matsutomi, H., Ohmukai, T., and Imai, K., 2004. Fluid force on a
structure due an inundated flow caused by a tsunami. Proceedings of
Hydraulic Engineering 48, JSCE, 559-564.
Ministerio de Vivienda, Republica del Peru, 2006. Reglamento
Nacional de Edificaciones E.070 Albanileria.
Miyajima, M., Shoji, G., and Shigihara, Y., 2009. Reconnaissance ofthe damage caused by the September 29th, 2009, Samoa Islands Earthquake
and Tsunami in American Samoa. Proceedings of the symposium on
disaster mitigation of lifelines considering system interactions, JSCE, 40-45.
Nakano, Y., 2005. Investigation Report for Damaged Structures due to the 2004 Indian Ocean Tsunami Ver. 2.2. http://sismo.iis.u-tokyo.ac.jp/Re
search.files/topic4.files/topic4-007.files/T4-7-1.pdf.
Nakano, Y., and Park, J., 2005a. Studies on lateral resistance ofstructures and tsunami load caused by the 2004 Sumatra Earthquake Part 1
Outline of survey. Proceedings of AIJ Annual Meeting, 723-724.
Nakano, Y., and Park, J., 2005b. Studies on lateral resistance ofstructures and tsunami load caused by the 2004 Sumatra Earthquake Part 2
Comparison of tsunami load and lateral resistance. Proceedings of AIJ
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Sanada, Y., Nakamura, Y., Yamauchi, N., Ho, C., and Nakano, Y.,
2006. A method to enhance seismic performances of unreinforced masonry
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AIJ, 159-166.
Shoji, G., Moriyama, T., Kosa, K., Matsutomi, H., Shigihara, Y., andMurashima, Y., 2007. Damage assessment of structures due to the 2006
Java Tsunami. Proceedings of Coastal Engineering 54, JSCE, 861-865.
Shoji, G., Pulido, N., Sekiguchi, T., Alva, J., Lazares F., and Saito, T.,2010. Damage investigation of the 2010 Chile Earthquake and Tsunami consideration to the damage of a structure subjected to a seismic excitation
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Tani, Y., Shoji, G., Koshimura, S., and Estrada, M., 2010. Damage
assessment of houses due to the 2001 Southern Peru Earthquake andTsunami. Proceedings of 13th Japan Earthquake Engineering Symposium,
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USGS,
http://neic.usgs.gov/neis/eq_depot/2001/eq_010623/,
2011.2.13.
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009mdbi/,

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Evaluationof tsunami
tsunami strengths
strengths ofof houses
houses subjectedsubjectedto
toaatsunami
Tsunamiwave
waveload
load

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2011.2.13.
USGS,http://earthquake.usgs.gov/earthquakes/eqinthenews/2010/us20
10tfan/, 2011.2.13.
Yanez, F., Astroza., M., Holmberg, A., and Ogaz, O., 2004. Bahavior
of confined masonry shear walls with large openings, Proceedings of 13th
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Asia
NewIntegrated climate adaptation and disaster
resilience - a landscape cooperatives
paradigm
Alfredo ANCENO1, Nitin TRIPATHI2, and Oleg SHIPIN3
1 Research Scientist, EEM FoS, Asian Institute of Technology, Thailand
2 Associate Professor, RS-GIS FoS, Asian Institute of Technology, Thailand
3 Associate Professor, EEM FoS, Asian Institute of Technology, Thailand
anceno@ait.ac.th, nitinkt@ait.ac.th, oshipin@ait.ac.th
ABSTRACT
Strategic approaches to climate change adaptation (CAA) and disaster risk
reduction (DRR) have traditionally operated in isolation from each other,posing a challenge to integration into development planning processes.
CAA deals exclusively with climate-related hazards of global and longer
temporal scale, while DRR focuses mainly on national/local levels.
Interactions and funding between these two approaches are often ad-hoc,
while systematic efforts to sustain and institutionalize these interactions
have been limited. Recently, however, developments in CAA and DRR
approaches are converging. DRR approaches tend to coincide with a futureoriented perspective of CAA on vulnerabilities, while CAA emphasizes
improved government capacity in addressing climaterelated disaster risks
and vulnerabilities. Vulnerabilities and gaps nevertheless remain due touncoordinated initiatives, particularly true of many Southeast Asian
countries where disaster efforts are focused on relief and rehabilitation
while existing CAA-DRR measures and policies remain uncoordinated. We
hence expound a landscape cooperatives paradigm whereby the governance,technology, and policy support layers that rationally integrate climate
adaptation (CA) and disaster resilience (DR) strategies are amply
addressed.
Keywords: climate adaptation, disaster resilience, landscape cooperatives,
integrated approaches to sustainable development, web-based geospatial
information, strategic environmental assessment
1. CONTEXTS AND RATIONALE
Hazards are phenomena that may manifest with or without warning thatthreaten natural, economic, political, and social processes. A full range ofhazards includes those of natural cause or induced by anthropogenic
processes. Whereas climaterelated or hydro-meteorological hazards only
represent one type of hazard, these actually constitute 90% of natural
hazards. Climate change alters the average climatic conditions and climate
variability, causing increased magnitude and frequency of climate-related
hazards. Disaster results from a progression of vulnerability from8731

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underlying causes and trigger events or hazards, while adaptation orresilience results from reduction of vulnerabilities and mitigation of hazards(Figure 1). Policies and measures aimed at addressing climate change anddisaster management issues are referred to as climate change adaptation(CCA) and disaster risk reduction (DRR), respectively. CCA is defined as
an adjustment in natural or human systems in response to actual or expectedclimate stimuli or their effects, which moderates harm or exploits beneficial
opportunities (IPCC, 2007); whereas DRR the broad development andapplication of policies, strategies and practices to minimize vulnerabilities
and disaster risks throughout society, through prevention, mitigation andpreparedness (UNISDR, 2004).

Figure 1: Contextualization of climate change (CC) related disasters andadaptation/resilience pressures, adapted and modified from IFRCRCS(2006).
Because the time frames for reactive adaptations to climate change(longer time scale) and disasters (immediate) are distinct, CCA deals
exclusively with climaterelated hazards of global scope while DRR is
focused on national/local levels (Table 1). In many Asian countries, DRR is
the concern of national disaster management offices, while CCA is led by
the departments/ministries of environment (USAID-OFDA, 2009).
Interactions between these two and funding are often ad-hoc and systematicefforts made to sustain and institutionalize these interactions were limited(Ahmed, 2010). On the other hand, the aims of both CCA and DRR to
reduce adverse effects of external impacts, natural hazard risk and climatechange are increasingly converging (Schipper and Pelling, 2006; Thomalla
et al., 2006). DRR adopts a more anticipatory approach on future
vulnerabilities, typically a CCA disposition. CCA also increasingly
emphasize on improving the capacity of governments and communities inaddressing vulnerabilities and hazards, typically a DRR disposition. Despite
efforts, Asia-Pacific governments still seem to have little capacity tosystematically organize and prioritize CCA-DRR activities (SELA, 2010).

2
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Table 1: Comparison of CCA and DRR contexts

Given that a variety of factors exacerbate vulnerability to the climate
related disasters, often unrelated to physical environment but are rather
societal in nature (USAID-RDMA, 2008), an integrated approach is neededto address this complex issue without compromising environmental
sustainability. Here we address a major strategy and implementation gap
characteristic of the entire planet but particularly relevant to the third
countries, notoriously prone to climate change and disaster-related risks.
The gap is an improper and insufficient integration of issues pertaining to
CCA and DRR into development planning both in developed anddeveloping worlds (Tearfund, 2008; USAID-RDMA, 2008; Wamsler, 2009).
This calls for an approach that simultaneously addresses such
adaptationresiliency capacity aspects as (i) institutional framework, (ii)technological support, (iii) policy advocacy, and (iv) community-driven
interventions, including appropriate spatial and temporal scales for planningand assessment.

Integrated climate
landscape cooperatives
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climate adaptation
adaptation andand disasterdisasterresilience
resilience−- aa landscapecooperatives paradigm
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2. INSTITUTIONAL FRAMEWORK
Mechanisms to address the short-comings of the nexus between climatechange, development planning and the incomplete approaches to risk
reduction and its mainstreaming require a governance framework to enhancecooperation. An inspirational example of such a knowledge sharingcoordination platform is the recent introduction of the LandscapeConservation Cooperatives (LCC) by the US Fish and Wildlife Service: 20
LCCs were introduced across the US. Essential features of LCCs include asteering committee that provides management direction, science andtechnology coordinators, geospatial information system capacity, anddecision analysis expertise. LCCs are expected to provide a major boost to
frequently failing community-based conservation of natural landscapes
impacted by land use pressures and resource threats, amplified by achanging climate and related disasters (USFWS, 2009). The concept ofconserving wildlife communities the LCC way may well be adapted for the“conservation” of human communities—i.e. saving them from the effects ofclimate change and disasters— a conceptually similar effort within
identified landscapes. We hence envision landscape climate adaptation anddisaster resilience cooperatives (LCADRCs) which are fundamental unitsof partnership in planning and science capacity, targeting the right scientificand technological approach for efficient and effective climate adaptation(CA) and disaster resilience (DR) in defined geographic areas or landscapes.
We define landscape as the entire range of identified priority terrain or
topography classified according to density of settlements (e.g. urban, periurban, rural), ecosystem quality (e.g. pristine, semi-pristine,
exploited/degraded), elevation (e.g. high-altitude, low-lying), and relevanthazard and vulnerabilities.

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LCADRCs’ core functions will be predicting climate and disaster
impacts, mitigating them and, if not possible, adapting to them, thereby
reducing vulnerability to risks and as a result creating optimal functional
conditions for the communities. The LCADRC coordinator will facilitate
the link between science, technology and management, and provide day-today leadership of the partnership. All staff positions, including thecoordinator, may be supported through any participating organization, or
shared between organizations. Core staff may be collocated within a partner
facility while complementary staff may participate virtually from remotelocations. Staff may be added in phases as the LCADRC
matures and demand for LCADRC products and services change and grow.
LCADRC technical personnel will share their expertise both within andacross LCADRCs by participating in local, national, and international
training programs. Not to overburden existing governance structures, thesecooperatives are best integrated into national community empowerment
national programs (CENPs) that are already operational. Since climatechange and disasters contribute to poverty and hit hardest on the poor,
CENPs can be value added by introducing LCADRC components and also
represented in national LCADRC steering committee (SC). Appropriate
examples of CENPs are Program Nasional Pemberdayaan Masyarakat ofIndonesia, Gawad Kalinga of the Philippines, The Learning Institute of
Cambodia, etc.
As a shared local platform, the cooperatives will deliver geospatial
and decisionsupport tools and products to coordinate action of local
communities, NGOs, government agencies, donors, and others. LCADRCs
will also strengthen the capacity of local governments and communities tosupport implementation of the governments’ national plan for disaster risk
reduction and climate adaptation. At the national level, the LCADRC
steering committee will form partnerships with local governments to form
local LCADRC partnerships and to establish the core functions and services
within the institutional framework of local governments and administrative
structure of CENPs. Internationally, LCADRCs will collaborate with
regional and international partners to obtain scientific and technical support
for a wide range of CA-DR activities tailored to local priorities and needs.
3. TECHNOLOGICAL SUPPORTRegional geospatial Earth observation capability is a powerful and essential
tool to achieve CA-DR via environmental management. However, there
exists a very limited Asian network of national geospatial centers andtherefore no exchange of regional expertise takes place. A geospatial
information sharing tool (GIST) is hence envisioned. GIST is a hardwaresoftware and applications framework that facilitates geospatial information
sharing and technical coordination/support issues in addressing regional
climate adaptation, disaster resilience, and other environmental challenges.
A motivating example of a model platform is SERVlR (www.servir.net), an
earth observation, monitoring, and visualization system (NASA-USAID).
Established in 2008, SERVIR integrates satellite and other geospatial data
Integrated climate
landscape cooperatives
Integrated
climate adaptation
adaptation andand disasterdisasterresilience
resilience−- aa landscapecooperatives paradigm
paradigm

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for improved scientific knowledge and decision-making by managers,
researchers, students, and the general public including local communities.
SERVIR decision support tools and data are currently used to address issues
related to climate change, disasters, ecosystems, biodiversity, health, andwater in the Central America and Africa. In 2010, the first Asian SERVIR
node was introduced in the Himalayas through the International Center for
Integrated Mountain Development (ICIMOD).
Networking of National Spatial Data Infrastructures (NSDI) in
Southeast Asia is encouraged as a testing ground for GIST, conceptuallymodeled after SERVIR. The NSDIs can provide a backbone for the regional
cooperation with the creation of a regional geospatial hub, bringing together
partners through collaborations among national and regional atmospheric,meteorological, and geophysical bureaus. There is also a necessity to
explore and better understand mechanisms of strengthening specific policy,
governance, and capabilities of national geospatial mapping centers(Philippine’s
PAGASA,
Thailand’s
GISTDA,
Indonesia’s
BAKUSORTANAL, etc.) to best support information sharing for planningand coordination of climate adaptation activities at the local and national
levels through GIST in the LCADRC framework. Baseline needs
assessment must be undertaken to address a multitude of relevant spheresfor which GIST is critically important. The established GIST framework
will (i) provide a common web-based platform for sharing geospatial
information, maps, and satellite data among LCADRCs; (ii) provide acommon web-based platform for sharing weather related data, including
meteorological data gathered from sensors installed in target landscapes;(iii) tap state universities to serve as regional service centers for training andcapacity building in geospatial applications for development; and (iv)provide decision support tools and data to address issues related to disasters,
ecosystems, health, water, weather, and climate change.
4. POLICY ADVOCACY
Strategic environmental assessment (SEA) is an approach formainstreaming and ‘upstreaming’ environmental sustainability in thedecision-making hierarchy, addressing the issue of environmental
sustainability as early as possible in the decision making process (OECD,2006). SEA has emerged due to the shortcoming of conventional
environmental assessment approaches (e.g. environmental assessment or
EIA) to tackle increasingly complex environmental issues, including theirintegration with economic and social issues at the highest levels of planningand decision making (Partidário, 2004). A major advantage of an SEA
framework is setting a strategic context for project environmental
assessment, making the latter more efficient (Stinchcombe and Gibson,
2001). As Figure 3 shows, SEA for flood control is a tiered planning process.

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Figure 3: Tiered decision making for water and flood control development,
adapted and modified from Jones et al. (2005).
Although some developing Asian countries very recently introduced
SEA as a legal requirement for newly proposed development planning at thenational and local levels, implementation is constrained by weaknesses intechnical capacity to apply the SEA framework in policy, planning, andimplementation at the local and national levels. Building capacity for SEA
provides an opportunity for strategic planning to apply “CA-DR lens” to thedevelopment scenarios (OECD, 2008a, b). Mechanisms such as stakeholder
seminars and participatory rural appraisals will be applied to help bridge
macro-level (SEA-based) and micro-level (landscape/community-based)
environmental management. With micro-level currently a neglected area,such mechanisms will provide a feedback loop for addressing local
grassroots issues to better inform strategic planning at and national level.
Actively engaging local communities in the strategic planning process willlead to an increased acceptance of the SEA concepts at district and local
community levels. Introducing SEA into CA-DR, and, vice versa, will beviewed as a novel feature and good practice among LCADRCs.

Figure 4: R-SEA framework, adapted and modified from Gunn and Noble(2009).
Also a recently explored “futures-oriented” approach in regional
development planning, regional SEA (R-SEA, Figure 4), emphasizes
alternative development scenarios and the means of achieving these (Gunnand Noble, 2009). In the RSEA approach, developed in Canada andendorsed by the Canadian Council of Ministers of Environment (2009),

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emphasis is placed on ensuring the sustainability of a region and a desired
level of environmental or socio-economic quality, rather than solely on
impact mitigation. It facilitates a more proactive and integrated approach to
SEA, and one that explicitly operates at the regional scale so as to facilitate
the assessment of cumulative environmental effects of multiple initiatives
within a relevant region (river basin, etc). A major feature of R-SEA iscumulative effects assessment (CEA) to account for the complex nature andpace of interventions related to climate adaptation and water, rather than
primarily focus on program/plan/policy approval. Of particular concern are
cumulative effects of development on the environment which are criticallyimportant but problematic to integrate into environmental assessment. An
illustrative example is water scarcity which, in the face of competing
cumulative demands for food production, domestic, industrial, energy andenvironmental purposes, reduces community resilience to disasters. Freshwater is such a limited resource that scarcity leads to a potential for user
conflicts (USAID-OFDA, 2009). The need to increase community resilienceto droughts and water scarcity through programs that promote efficientwater management practices (water harvesting, treatment and conservation)is thus prominent. Furthermore, small-scale disasters in aggregate frequently
affect more people and cause greater economic damage than less frequent,large-scale disasters. Developing communities often fail to comprehend thesignificance of cumulative effects or see the long-term accumulation of
impacts by drivers of change. This therefore calls for serious considerationin strategic development planning in the context of LCADRCs.
5. COMMUNITY-DRIVEN INTERVENTIONS
Ecological engineering (EE) offers a nature-based, robust and sustainableapproach to deal with multiple cumulative effects of climate change,
disasters and poverty reduction. In the case of wetland landscape forexample, the multifunctional wetlands approach based on EE appears to be
most appropriate (Wickramasinghe et al., 2009) way to tackle the challenges
while generating cobenefits such as livelihoods, carbon sequestration, green
energy, health, and wellbeing, etc. EE systems are becoming progressively
more established, although due to various reasons some are still underused(many issues remain to be researched). These include (i) bio-geochemicaland ecological mechanisms (that is where reverse engineering is helpful)underlying ecosystem processes and (ii) social mechanisms of acceptanceby communities and political buy-in. An approach that looms large inaddressing the issues is the one dealing with a bottom-up perspective incommunity-driven activities, which is particularly relevant for climatechange-dependent scenarios.
Environmental management (EM) based on the “sufficiency economy
philosophy”, originating from Thailand, is another ecologically friendly
approach that assists communities to withstand, apart from climate change,
disasters, other pressures such as economic insecurity caused by trade
globalization and market price fluctuations. Capacity building centers serve
as “learning by doing” hubs on

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natural agriculture and local knowledge, green energy, surplus food storagefor economic gain, household product and earth-house making, soil andwater management, tree planting, charcoal making, bio-diesel production,etc. Interventions are desirably linked up with the envisioned Southeast
Asian alliance of LCADRCs which relates with local communities in theregion.
Climate change, moreover, is viewed by the local communities as only
one contributory factor impacting their development (Mercer, 2010). It
therefore appears inappropriate to solely address climate change without
focusing on other underlying factors, such as poverty, social deprivation,
gender imbalance, lack of resources and poor education with a view to
reducing community vulnerabilities. Undertaking community-driven pilot
projects based on EE and EM systems will require study by reverse ecoengineering and improved appropriate, locally preferred water, green energy,
sanitation, health, food security-related interventions by participatory
methodologies. Lessons learned and good practices of how the integrated
CA-DR-EE-EM and poverty reduction approaches help the communities
adapt to climate change and cope with disasters will be documented andmade available to communities via a network of GIST-interlinked
LCADRCs.
6. CONCLUDING REMARKS
Landscape climate adaptation and disaster resilience cooperatives(LCADRCs) are envisioned to contribute to the sustainability of ecosystemservices for climate and disaster proofing of vulnerable communities indiverse Asian tropical conditions (i.e. landscapes). By mainstreaming the
integrated climate adaptation, disaster resilience, ecological engineering,
environmental management, and poverty reduction approaches indevelopment planning, the socio-economic vulnerability to climate change
and related disasters is appropriately addressed. To enhance capacity for
integration, LCADRCs are proposed to be embedded into existing
community empowerment alliances and to be studied and fine tuned with aview to regional replication. Geospatial information sharing tool (GIST)
will provide technological support for decision-makers through thecooperatives. Policy advocacy for improved environmental management ofrisks and vulnerabilities will be carried out through a developed system
based on regional strategic environmental assessment (R-SEA), including
cumulative effects assessment. LCADRCs will promote a bottom-up,
gender sensitive approach to ensure a buy-in and commitment bycommunities and administrations.
REFERENCES
Ahmed, A. K. 2010. Linking disaster risk reduction to climate change
adaptation: Evolving regional perspectives in Asian countries. In ADPC and
BDPC (organizers), Climate Change and Extreme Cyclones, Regional

Integrated climate
landscape cooperatives
Integrated
climate adaptation
adaptation andand disasterdisasterresilience
resilience−- aa landscapecooperatives paradigm
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Conference on Disaster Risk Reduction and Emergency Response in a
Rapidly Changing World, Dhaka, Bangladesh, 17−18 February 2010.
Gunn, J., and Noble, B., 2009. A conceptual basis and methodologicalframework for regional strategic environmental assessment (R-SEA).
Impact Assessment and Project Appraisal 27, 258–270.
IFRCRCS, 2006. What is VCA: an introduction to vulnerability andcapacity assessment. International Federation of Red Cross and Red
Crescent Societies, Geneva, Switzerland.
IPCC, 2007. Climate Change 2007: Impacts, Adaptation, andVulnerability. In Parry, M. L., Canziani, O. F., Palutikof, J. P., van der
Linden, P. L., and Hanson, C. E. (editors), Contribution of Working GroupII to the Fourth Assessment Report of the Intergovernmental Panel on
Climate Change.
Cambridge University Press, Cambridge. UNISDR, 2004. Living With
Risk: A Global Review of Disaster Reduction Initiatives. United Nations
International Strategy for Disaster Reduction Secretariat, Geneva,
Switzerland.
Jones, C., Baker, M., Carter, J., Jay, S., Short, M., and Wood, C.,(eds.), 2005. Strategic Environmental Assessment and Land Use Planning:
An International Evaluation. Earthscan, London.
Mercer, J., 2010. Disaster risk reduction or climate change adaptation:
are we reinventing the wheel? Journal of International Development 22,
247–264.
OECD, 2006. Applying Strategic Environmental Assessment toDevelopment Cooperation. Organization for Economic Co-operation andDevelopment(OECD). Paper No. 12. World Bank, Washington DC.
OECD, 2008a. Applying Strategic Environmental Assessment and
Adaptation to Climate Change. Organization for Economic Cooperation andDevelopment, Paris, France.
OECD, 2008b. Strategic Environmental Assessment and Disaster Risk
Reduction. Organization for Economic Cooperation and Development, Paris,
France.
Partidário, M.R., 2004. Strategic Environmental Assessment (SEA) –current practices, future demands and capacity building needs. Course
Manual, IAIA Training Courses, International Association for Impact
Assessment (IAIA).
Romieu, E., Welle, T., Schneiderbauer, S., Pelling, M., and Vinchon,C., 2010. Vulnerability assessment within climate change and natural hazard
contexts: revealing gaps and synergies through coastal applications.
Sustainability Science 5, 159–170.
Schipper, L., and Pelling, M., 2006. Disaster risk, climate change andinternational development: scope for, and challenges to, integration.
Disasters 30, 19−38.
SELA, 2010. Climate Change Adaptation and Disaster Risk
Reduction Institutional and Policy Landscape in Asia and Pacific. Sistema
Económico Latinoamericano y del Caribe, Caracas, Venezuela.
Stinchcombe, K., and Gibson, R.B., 2001. Strategic environmental
assessment as a means of pursuing sustainability: ten advantages and ten

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challenges. Journal of Environmental Assessment Policy and Management 3,
343–372.
Tearfund. 2008. Linking Climate Change Adaptation and Disaster
Risk Reduction. Tearfund, London.
Thomalla, F., Downing, T., Spanger-Siegfried, E., Han, G., andRockström J., 2006. Reducing hazard vulnerability: towards a common
approach between disaster risk reduction and climate adaptation. Disasters
30, 39−48.
USAID-OFDA, 2009. Asia Strategy Development, Exercise for the
Period of 2009-2011. USAID Office of Foreign Disaster Assistance(OFDA).
USAID-RDMA, 2008. Global Climate Change in the Asia-PacificRegion. An Analysis and road map for the USAID Regional Development
Mission for Asia (RDMA). Bangkok, Thailand.
USFWS. 2009. Conservation in Transition: Leading Change in the
21st Century. US Fish and Wildlife Service.
Wamsler, S., 2009. Urban Risk Reduction and Adaptation. How topromote resilient communities and adapt to increasing disasters andchanging climatic conditions? VDM Verlag, Saarbrücken.
Wickramasinghe, S., Borin, M., Kotagama, S., Cochard, R., Anceno,A., and Shipin, O., 2009. Multi-functional pollution mitigation in arehabilitated mangrove conservation area. Ecological Engineering 35, 898–
907.

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landscape cooperatives
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adaptation andand disasterdisasterresilience
resilience−- aa landscapecooperatives paradigm
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884

New Technologies for Urban Safety of Mega Cities in Asia‘Urban environment climate maps
(UECM)’ for supporting ‘Urban planningwith urban climate’: trial for mitigatingurban heat island in Shanghai, China
Kaoru MATSUO1, Takahiro TANAKA2
1
Graduate Student, Graduate School of Engineering,
Hiroshima University, Japan
cafeaulait.2125@gmail.com
2
Associate Professor, Hiroshima University, Dr. Eng., Japan
ABSTRACTIn Shanghai, they have an originally hot and humid climate. The inhabitantsof the city are exposed to the more severe climate caused by urbanization,
because Shanghai is growing and urban heat island is becoming severe.
Therefore they must take countermeasures to urban heat island for
comfortable life of inhabitants and reduction of energy consumption.
Therefore, it is thought that urban planning that considers urban heat island
mitigation is necessary in Shanghai.
Consequently, this study aims at analyzing urban heat island phenomenonin Shanghai by using meso-scale meteorological model and measurement
data, and making Urban Environmental Climate Maps (UECM). UECM is
made for urban planning with urban climate and environmental policy
making. The role of this map is to provide some information and advices(hints) from the view of urban heat island mitigation to the place of decision
making. Actually, UECM consists of a Climate Analysis Map (CAM) and a
Hint Map for Urban Planning (HM). The role of CAM is representing
actual climate conditions. That of HM is presenting some advices (hints) for
urban planning.
Keywords: Urban Environmental Climate Map, Shanghai, WRF, Urban
Heat Island
1. INTRODUCTION
1.1 BackgroundIn recent years, Asian countries have continued their rapid economic
growth. Urban development in large cities is especially remarkable. It isapparent that the urban heat island phenomenon is remarkable in thosemajor cities because they have always had hot and humid climates.
Especially in China, rapid population growth is thought to have worsened
the urban heat island phenomenon. Reportedly, the severe urban heat island

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phenomenon engenders temperatures in downtown area of Shanghai that are
higher than in other large cities in China1). Therefore, Shanghai needs urban
planning incorporating mitigation of the urban heat island phenomenon. The
authors intend to produce Urban Environmental Climate Maps of Shanghai
as the ultimate objective of this study.
1.2 Previous Studies and Objective
Although the urban heat island phenomenon is regarded as a problem
in Japan, few examples exist for which planners (or stakeholders) consider
urban heat island phenomenon mitigation based on scientific knowledge intheir planning processes. That is true apparently because the urban climate
phenomenon is difficult to understand for stakeholders: residents, local
government officials, designers, and planners. Urban Environmental
Climate Maps (UECMs) are therefore proposed as a tool supporting urban
planning. Trial UECMs incorporating urban heat island mitigation2), havebeen made for Tokyo3) and Osaka4). Those maps, which show the present
climate conditions of the object area (e.g. wind patterns), are thought to beeffective in elucidating present climate conditions. However, when trying to
produce an urban plan that incorporates urban heat island phenomenon
mitigation, practical countermeasures are difficult for many people tounderstand. Urban environmental climate maps should therefore include
recommendations for urban planners5). Some maps presenting
recommendations have been made at the district level, showing some
proposals from a climatic environment perspective. However, such maps
showing recommendations for entire city areas are needed. Because
stakeholders must incorporate various elements in their process when theyplan the whole city area, the map should show issues to be considered inplanning processes and climatic resources, rather than only actual proposals.
Therefore, indicating zones that are classified from a climatic perspective isthought to be effective. This study analyzes the urban heat island
phenomenon in Shanghai using a meso-scale meteorological model andmeasurement data, yielding a climate zoning based on the analyses, with amap providing hints for planning.
2. RESEARCH OUTLINE
2.1 Overview of the Targeted Area
For this study, Shanghai in China is selected as a targeted area (Figure.
1). Shanghai is at north latitude 31°14′, which is approximately the same
latitude as Japan’s Kagoshima Prefecture. Shanghai, which faces the East
China Sea on the east, has an urban area extending along the lower Huangpu
River, which runs north–south through central Shanghai. Basic information
related to Shanghai is given below.
・Resident population: 19,213,200 (2009)
・Family registered population: 14,007,000 (2009)
・Area: 6,340.5 [km2]2886

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・Population density: 29,030.49 [persons/ km2]

䎵䏈䏓䏘䏅䏏䏌䏆䎃䏒䏉䎃䎮䏒䏕䏈䏄

䎭䏄䏓䏄䏑

䎦䏋䏌䏑䏄
��������
䎨䏄䏖䏗䎃䎦䏋䏌䏑䏄䎃䎶䏈䏄0

125 250500 kmFigure 1: Position in Shanghai±

2.2 Method
This study progressed by the following steps.
1) Analyzing the urban heat island phenomenon using measurement
data2) Simulating the urban heat island phenomenon for all of Shanghai
using a meso-scale meteorological model, and analyzing theurban heat island phenomenon using simulation results.
3) Discussion based on results of analyses 1) and 2).
4) Climate zoning for all of Shanghai
3. ANALYSES USING MEASUREMENT DATA
3.1 Outline of Measurement Data
Measurement data of the National Climate Data Center (July 2008)
were used. Two measurement stations (Hongqiao and Pudong) are shown in
Figure. 2. Hongqiao is located in the urbanized city center; Pudong islocated in a coastal area.

HONGQIAO
PUDONG

±

0

25 50

100 kmFigure 2: Measurement stations

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3.2 Temperature
The average temperature for each hour (July 2008) is depicted in
Figure 3, which clarifies that the temperature in Hongqiao is higher than thatin Pudong throughout the day. Hourly differences in average temperaturesof the two stations (July 2008) are portrayed in Figure 4, which shows thatthe difference is 2.0°C or more between the city center and suburb at around
13:00. Although it is necessary to analyze details to know the causes, thedifference of temperatures is presumably influenced by wind because thedaytime temperature is strongly influenced by wind in general10). However,the difference between city center and suburban temperatures is 0.5–1.0°C
at night. Presumably, that temperature difference is influenced bysurrounding land cover because the nighttime temperature is strongly
influenced by surrounding land cover10).
36

Temperature（℃）

34
32
30

HONGQIAO
PUDONG

28
26
24
0時 2時 4時 6時 8時 10時12時14時16時18時20時22時

Figure 3: Average Temperature for Each Hour (July 2008)

Temperature difference(℃）
Center of a city－a suburb

2.5
2
1.5
1
0.5
0

0時

3時

6時

9時

12時

15時

18時

21時

Figure 4: Hourly Differences in Average Temperatures (July 2008)
3.3 Wind Speed and Direction
Wind roses of the two stations are presented in Figure 5, showing thatprevailing winds come from the south or south–southeast all day long
during summer in Shanghai. Still, according to Figure 3, the temperaturerise in Pudong stopped at about 12:00, but the rise in temperature in
Hongqiao continued to about 14:00. Considering this tendency and Figure 5

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together, Pudong, which is near from a sea and located windward, is
probably influenced earlier by sea breezes.
NNW 40%N

NW

NNW 40%

NNE

30%
20%

WNW

NW

NE
ENE

WNW

E

W

ESE

WSW

NNE
NE

20%

10%
W

N

30%

ENE

10%

0%

WSW
SW

SE
SSW

SSE

E

0%

ESE
SW

SE
SSW

S

SSE
S

Day（6:00－18:00）

Left：PUDONG

Night（19:00－5:00）

Right：HONGQIAO

Figure 5: Wind Rose (July.2008)
4. CALCULATION CONDITIONS AND RESULTS
4.1 Outline of a Meso-scale Meteorological Model WRF
Weather Research & Forecasting (WRF), a meso-scale meteorologicalmodel developed by the National Center for Atmospheric Research (NCAR),
is an advanced version of meteorological model MM5.
4.2 Calculation Conditions
The authors used WRF-ARW ver. 3.0 in this study. The calculation
object domain on this study is depicted in Figure 6. A nesting technique isused: Domain 1 is a 120 × 120 grid with spatial resolution of 3 km. Domain
2 is a 103 × 103 grid with a spatial resolution of 1 km. Analyses of Domain
2 is conducted. Table 1 presents the conditions of calculations, which weredone for three days (July 23–25, 2008).
Figure 7 shows the inputted land cover data. The land cover data aremade from the Normalized Vegetation Index (NVI) map, which is derived
from satellite remote sensing data and Land Cover data of International
Steering Committee for Global Mapping. In addition, satellite remotesensing data were obtained: ALOS AVNIR-2 in 2009.
Domain1

Domain2

0 25 50

100 km±Figure 6: Calculation Object Domain
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Table 1: Calculation Condition
PeriodJuly 23-25. 2008

Vertical grid28 layers (Surface ～ 100hPa)

Horizontal grid

Domain1：3 ㎞（dimension 120×120） Domain2：1 ㎞（dimension 103×103）

Meteorological data
Elevation
Land data

Land cover

Microphysics
Radiation

GTOPO30
International Steering Committee for Global Mapping Land Cover data,
Satellite remote sensing data acquired by ALOS AVNIR-2 (2009)
Purdue Lin schemeLong wave

Rapid Radiative Transfer Model (RRTM) Longwave

Short wave

MM5(Dudhia) Shortwave

PBL scheme
Surface scheme

NCEP Re-analysis global objective analysis data（every 6 hour, 1° Grid, 17 layers）

Urban area
Nonurban area

Mellor-Yamada-Janjic PBL
Urban Canopy Model (UCM)
Noah LSM

Cumulus parameterization

none

FDDA

none

Land
被 Cover
A：Urban(High density)(222)
B：Urban(Medium density)(1526)
C：Urban(Low density)(4014)
4：Cropland and Pasture(Dry)(345)
5：Cropland and Pasture(Irrigation)(903)
6：Herbaceous(4)7：Mixed forest(121)
8：Water bodie(3474)

Figure 7: Land Cover Data (Mesh number in parentheses)

24℃

36℃

Figure 8(Left): Distributionof Daytime Temperature at
2.0 m Height(14:00, July 25, 2008)

6
890

21℃

28℃

Figure 9(Right): Distributionof Night Temperature at
2.0 m Height(4:00, July 25, 2008)

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4.3 Results and Discussion
Figure 8 shows some results: distribution of daytime temperatures at
2.0 m height (14:00; July 25, 2008). Furthermore, Figure 9 shows the
distribution of nighttime temperature at 2.0 m height (4:00; July 25, 2008).
The authors considered distributions of daytime and night temperatures as
the following. 1) Distribution of daytime temperature First, it seems certainthat the temperatures of the urbanized area and the surroundings are high.
This is apparently true because the heat island phenomenon occurs in thisurban area. Additionally, the temperature of the northwest zone in Shanghai
is high, just as it is in the city. Apparently it takes much time for wind fromthe south or from the south–southeast to reach this zone in the daytime. The
temperature of the southeast coastal zone tends to be low, probably becauseof the influence of a sea breeze blowing on this zone. 2) Distribution ofnighttime temperatures First, temperatures of the urbanized areas and thesurroundings are higher in the daytime, apparently because heat island
phenomenon occurs (by heat storage on surfaces, etc.) in urban areas. Also,
temperatures are lower according to distance from the urban area. The
temperatures of the southeast coastal zone are lower still, probably because
the south wind blows there at night, just as it does in the daytime. Results
show that the temperature difference between the urbanized area andsoutheast coastal zone during the day and the daytime temperature
difference are greater than the nighttime temperature difference. Thistendency resembles the change of the temperature difference between
Pudong in the southeast coastal zone and Hongqiao in the city center during
the day, as reported in Section 3.
5. CLIMATE ZONING
Daytime and nighttime climate zoning was done using temperature andwind distribution results obtained during daytime and nighttime (Figures. 10,11). For daytime, the whole Shanghai area was first classified according totemperature based on the temperature distribution. Concretely, the zone of
35°C or more, where the temperature is the highest, is a zone for which thehighest necessity of the measure of heat island in daytime, a zone of lessthan 35°C is classified at intervals of 1°C, 34°C, 33°C, 32°C, 31°C, andevery 30°C. The zone where the temperature is low does not require heatisland measurements in the daytime relatively. Then the zone of less than
30°C is assumed to be a zone with little necessity of heat island
measurements during the daytime. Next, the whole area of Shanghai isclassified into zones that are affected and unaffected by the sea breeze by
overlaying the wind distribution on this classification map. Then, the urban
planning proposal that considers heat island measures is attempted for zones
such as those affected and unaffected by the sea breeze.
For nighttime temperatures, as for the daytime, first, the whole area of
Shanghai was classified according to temperatures based on the temperature
distribution. Concretely, the zone of 28°C, where the temperature is highest,is made a zone where it was the highest necessity of the measure of heat
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island in the night, the zone of less than 35°C is classified at intervals of 1°C,
27°C, 26°C, 25°C, and every 24°C. The zone in which the temperature is
low has low necessity of the heat island measure in the night. The zone ofless than 25°C is assumed to be a zone where the necessity of the heat island
measures during the night is small. The subsequent procedure resembles thatused for daytime.
⓪:Less than 30℃ (The necessity ofheat island measure is small)
Zone B

Low

①:30℃
②:31℃

The necessity ofheat island
measure

③:32℃
④:33℃
⑤:34℃
⑥:35℃ or moreHigh

Zone A:The zone where sea breeze reach
Zone B:The zone where sea breeze don’t reach
Zone AUrban Planning
Zone A

Making wind road

Zone B

Greening
Create shadow

Figure 10: Recommendation Map (Daytime)⓪:Less than 25℃(The necessity ofheat island measure is small)
Low
①:25℃

Zone B③:27℃

The necessity ofheat island
measure

④:28℃

High

②:26℃

Zone A:The zone where sea breeze reach
Zone B:The zone where sea breeze don’t reach
Zone AUrban Planning
Zone A

Making wind road
Greening

Zone B

Greening

Figure 11: Recommendation Map (Night)
6. SUMMARY
This study was undertaken to analyze the urban heat island phenomenon in
Shanghai using a meso-scale meteorological model and measurement data,
producing a climate zoning with that analysis, and making a
recommendation map. As the next step, the authors will advance analyses ofmeasurement data and results to improve detailed climate zoning, ultimately
producing Urban Environmental Climate Maps.
REFERENCES
Bai Y., and Mikami T., 2007. Measuring and Mitigating Urban Heat
Island in Summer in Shanghai. China. Environmental Information Science,

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No.21, 387-392.
AlJ. 2000. Klima Atlas of Urban Environment: Urban planning withusing the climate information. Gyosei.
Chairman: Toshio OJIMA. Supervision (Learning Community for
Promoting Coo-City Eco-City 2010). THE COOL CITY strategy of heatisland mitigation :Architecture and Urban planning utilizing green, water
and wind, Building technology.
Tanaka T., and Moriyama M., 2004. Making and Using of "Urban
Environmental Climate Map" for Supporting Urban Planning which is
Adapted for Climate. Papers and Proceedings of the Geographic
Information Systems Association, Vol.13, 391-394.
Moriyama M., 2004. Measures and technology of heat island.
Gakugei Shuppan.
Working Group for Practical Use of Klimaatlas, Environment
Planning Sub-committee in Architectural Institute of Japan, Study Group of
Klimaatlas. 2001. Study on Practical Use of Klimaatlas: A Trial to Make the
Recommendation Map by Workshop. AIJ Journal of Technology and
Design, No.14, 207-210.
Working Grope for Practical Use of Klimaatlas Environment Planning
Sub-committee in Architectural Institute of Japan. 2003. Study on PracticalUse ofKlimaatlas (Part2): A Trial to Make the Climate Analysis Map and the
Recommendation Map by Kitakyushu workshop. AIJ Journal of Technology
andDesign, No.18, 203-206.
Working Group for Practical Use of Klimaatlas Sub-committee in
Architectural Institute of Japan. 2004. A Trial to Make the Climate Analysis
Map and the recommendation Map by Workshop for Sendai City Region:
Study on Practical Use of Klimaatlas (Part 3). AIJ Journal of Technology
and Design, No.20, 183-186.
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Urban environment climate maps (UECM)” for supporting “urban planning with urban climate”: trial for‘Urban environment climate maps (UECM)’ for supporting ‘Urban planning with urban climate’:mitigating urban heat island in shanghai, China
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trial for mitigating urban heat island in Shanghai, China

October 2011, Chiang Mai, Thailand

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New Technologies for Urban Safety of Mega Cities in Asia