Technology for Flood Forecasting System

1) Objective and concept of GFAS
GFAS--Streamflow and IFAS
by Kazu FUKAMI
2) Major features and functions of IFAS for poorlypoorly-gauged
river
i
b
basinsiby Jun MAGOME
Hydrologic Engineering Research Team,International Centre for Water Hazard and Risk Management (ICHARM)
Public Works Research Institute (PWRI)Flood disaster is still increasing…
•
•
•
•
•
Average numbers of people affected by natural disasters(1973-2002)•

Source: “World Disaster Report
p 2004”
International Federation of Red Cross and Red Crescent Societies••

Aug. 2007: Nepal-IndiaBagladesh
Nov 2007: Cyclone Sidr
Nov.
(Bangladesh)
May 2008: Cyclone Nargis(Myammar)July-Sep. 2008: Many guerrillastorms (Japan)
Aug. 2008: Mississippi River(USA)
Aug. 2008: Hurricane Gustav(Caribbean countries)
Sep. 2008: Hurricane Ike(Caribbean countries)
Etc…..

Priority actions
January, 2005
UN World Conference on Disaster Reduction (Kobe)
H
Hyogo
F
Frameworkk ffor A
Actionti
2005--2015
2005
2015::-Building Resilience of Nations
andd CommunitiesC
iti tot DisastersDisastersDit1) Ensure that disaster risk reduction is a nationalandd a llocall priority
i it with
ith a strongtiinstitutional
tit tilbasis for implementation.
2) Identify,y, assess and monitor disaster risks andenhance early warning.
3) Use knowledge, innovation and education tobuild a culture of safety and resilience at alllevels.
4) Reduce the underlying risk factors.
5) Strengthen disaster preparedness for effective
response at all levels.

Flood disaster mitigation
with floodfforecastingfand warning systems
1. Monitoring of meteorological & hydrologicalconditions
2. Flood – runoff modeling-

Building rainfall forecasts & runoff analysis

3. Analysis of forecasts and judgments on the degree of
hazards and risk
4. Dissemination of warnings
5. Crisis management- migration of residents and livestock,- re-planningpg of agriculturalgschedule ((seedings,
g ,fertilizing, harvesting, etc.)- flood fighting, evacuation, etc.

Flood disaster mitigation
with flood forecasting and warning systems（Typical situations in developing countries)

1. Monitoring of meteorological & hydrological conditions

×Low density of gauging stations, low sustainability of maintenance of observatories, etc.
2. Flood – runoff modeling×Lack of hydrological and geophysical data for modeling×Lack of budget and capacity to construct and run the forecasting & warning system
3. Analysis of forecasts and judging risks

×Lack of real
real--time hydrologic data
×No information to identify reliability and uncertainty
×Lack of capacity to maintain and improve the system with new accumulated data and changing
situations
4. Dissemination of warning

×Lack of disasterdisaster-managementgcommunity
y and communication network,,
×Incomp
Incompatibility
atibility of flood information with local society and needs, etc.
5. Crisis management

×Improper governance and preparedness
×Insufficientffi i t institutional
i tit til cooperation,
ti
etc.
t

Recordable Gauges

Data source: WMO

Technical issues
for flood forecasting in poorly gauged or ungauged basins•

How can we prepare necessaryy (historical(and real-time)) hydrologicyg andgeophysical data for rainfall-runoff modeling as the basis for flood
forecasting and warning systems in poorly-gauged river basins,
especially in developing countries?

•

What kind of hydrologic (rainfall-runoff) model is suitable for “worldwide
applicable” flood forecasting system under the condition of very limited(hydrologic & geophysical) in-situ data availability?

•g necessity
y to ppreparepanyy easyy and efficient tool jjust fit to theBig
objective above, with user-friendly interfaces and minimal cost to
implement?

•

How should the system be to sustain the effectiveness and reliability of
the implemented system under changing situations?

Technical issues
for flood forecasting in poorly gauged or ungauged basins•

How can we prepare necessaryy (historical(and real-time)) hydrologicyg andgeophysical data for rainfall-runoff modeling as the basis for flood
forecasting and warning systems in poorly-gauged river basins,
especially in developing countries?

•

What kind of hydrologic (rainfall-runoff) model is suitable for “worldwide
applicable” flood forecasting system under the condition of very limited(hydrologic & geophysical) in-situ data availability?

•g necessity
y to ppreparepanyy easyy and efficient tool jjust fit to theBig
objective above, with user-friendly interfaces and minimal cost to
implement? Enhancement of Global Flood Alert•

System (GFAS) concept of IFNet

How should the system be to sustain the effectiveness and reliability of○ GFAS
Rainfallsituations?
the implemented system
under–changing● GFAS – Streamflow

Technical issues
for flood forecasting in poorly gauged or ungauged basins•

How can we prepare necessaryy (historical(and real-time)) hydrologicyg andgeophysical data for rainfall-runoff modeling as the basis for flood
forecasting and warning systems in poorly-gauged river basins,
especially in developing countries?

•

What kind of hydrologic (rainfall-runoff) model is suitable for “worldwide
applicable” flood forecasting system under the condition of very limited(hydrologic & geophysical) in-situ data availability?

•g necessity
y to ppreparepanyy easyy and efficient tool jjust fit to theBig
objective above, with user-friendly interfaces and minimal cost to
implement?

•

How should the system be to sustain the effectiveness and reliability of
the implemented system under changing situations?

Technical issues
for flood forecasting in poorly gauged or ungauged basins••

How can we prepare necessaryy (historical(and real-time)) hydrologicyg andDevelopmentofneweffective
tool
geophysical data for rainfall-runoff modeling as the basis for flood
towarning
realizesystems
GFAS-Streamflow
forecasting andin poorly-gauged river basins,
especially in developing
conceptp incountries?
developingp g countries:“Integrated
Flood Analysis
What kind of hydrologic(rainfall-runoff)model isSystem”
suitable for “worldwide
applicable” flood forecasting(IFAS) system under the condition of very limited(hydrologic & geophysical) in-situ data availability?

•g necessity
y to ppreparepanyy easyy and efficient tool jjust fit to theBig
objective above, with user-friendly interfaces and minimal cost to
implement?

•

How should the system be to sustain the effectiveness and reliability of
the implemented system under changing situations?

Original GFAS concept includes both rainfall alert andbasin-scale
basin
scale flood forecasting using satellite information
Rainfall information

Heavy rain around theUpstream of ○○ RiverA
Aroundd th
the downstreamdt
off ○○ riveri

Observation satellite

石塘
樋門
It is heavy rain in the upstream of XXX River.
There is a possibility to occur a flood in X hour.
Please evacuate to safe places

Flood Alert
Groundstations

Organization in charge of meteorology
and disaster prevention
Raw
Data

Flood Forecasting System
・Data for climate forecasts (real time/near real time data)
・Run-off calculation

Rainfall prediction,
Flood prediction

Directions to overcome technical issues (1/2)< Global Flood Alert System
y((GFAS)) – Streamflow >• To acquire historical & real-time hydrologic information anywherei thin
the worldld→ Application of satellite-derived rainfall data and runoff reanalysis with those dataex.) NASA-3B42RT (GFAS-rainfall), JAXA-Real-time GSMaP• To secure the availabilityy of flood-runoff ((hydrologic)yg ) model
anywhere in the world→Applying a practical & distributed-parameter hydrologic
model the parameters of which can be estimated on basis
model,of globally available GIS data sets.
Upper tankex.) BTOP model,
PWRI-PDHM Ver.2, etc.
Lower tank

Example of satellite-based rainfall products
TRMM (Tropical Rainfall Measuring Mission) and 3B42
42RTRT(1) Current System

Launch of Tropical Rainfall Measuring Mission (TRMM(TRMM))
satellite in 1997
Near
N
reall titime datad t “3B42RT“3B42RT”” sincei2002 from
f
TRMM
TRMM,
orbital satellites and geostationary satellites(2) Features

3-dimensional analysis of rainfall structure.
structure
No influence of topography.
Global coverage including oceans(3) Data Specifications of “3
“3B42
42RT”
42RT
RT”
RT





Mesh Size: 0.25 degrees of latitude and longitude(rectangle of about 30
30km
km by 2020km
km on 40
40N)
N)
Coverageg Area: between 60N
60N and 60
60S
S latitude
Data Delivery: every 3 hours (not hourly)
Near--real
Nearreal--time basis with several hours time lag

ftp://trmmopen.gsfc.nasa.gov/pub/merged/mergeIRMicro/

Global Flood Alert System (GFAS) – Rainfall by IFNet

You can select 1 or 33-day
rainfall from pullpull-downmenu here.

Latest 1 day rainfall in theworld is displayed on theinitial page.

Downloadthe data intext format

Then, click here fordisplay.

http://gfas.internationalfloodnetwork.org/gfas--web/
http://gfas.internationalfloodnetwork.org/gfas

Contents of GFAS - Rainfall

Real--time precipitation Map
Real(every 3 hour)Pre--analyzed rainfall distribution
Pre
exceeding 1010--year return period

E-mail alarm forhheavy
rainfalli f llReal--time estimation of rainfall areas
Real
Exceeding 10
10-- (or 5-) Year Return Period

Real-Time
R
l Ti
GSMaP
JAXA
JAXA,
JST-CREST(Prof. Ken’ichi OKAMOTO,
Osaka Pref.
Pref Univ.
Univ et alal.))

ICHARM/PWRIGGSMaP4.6(MVKK) Precipitation ((mm/h)

42

Y1

36

Y2
Y3

30

Y4
Y5

GSMaP4.6(MVK)

3h basin averaged
rainfalli f ll datad t (mm/h)
(
/h)

Y6
T1
T2

24

For major storm events

T3

18

at Tone River & Yoshino River.,
Japan

12
6
0
0.0

6.0

12.0

18.0

24.0

30.0

36.0

42.0

Gauged Precipitation (mm/h)
42

Y1
Y2

3B42RT P
Precipitation (mmm/h)

CMORPH Precipitation (mmm/h)

CMORPH

Y3

36

Y4
Y5

30

Y6
T1

24

T2
T3

18
12

42

Y1

36

Y2
Y3

30

Y4
Y5

24

Y6
T1
T2

12
6

0

0
6.0

12.0

18.0

24.0

30.0

Gauged Precipitation (mm/h)

36.0

42.0

T3

18

6

0.0

3B42RT

0.0

6.0

12.0

18.0

24.0

30.0

Gauged Precipitation (mm/h)

36.0

42.0

Developing of the correction method for satellite rainfall
Slow movement

Rapid movement
現在

現在
＋

＋

１時間後

１時間後
＋

＋

２時間後
＝

＝

２時間後

３時間累加

３時間累加

The proposal of the correction method considering rainfall movement !
250.0

beforeAverage error ratio＝
A
ti
69.8%

200 0
200.0
GSMaP_ddata(mm/6h)

1
2
3
4
5
6
7
8
9

150.0

100.0

50.0

250.0

1
2
3
4
5
6
7
8
9

after

200.0
GSMaP__data(mm/6h)※6hour additional rainfall

Average error ratio＝
A
ti
16.5%

150.0

100.0

50.0

0.0

0.0

0.0

50.0

100.0

150.0

Gauged_data(mm/6h)

200.0

250.0

0.0

50.0

100.0

150.0

Gauged_data(mm/6h)

200.0

250.0

Verification in the Awash River Basin, Ethiopia
sate llite- Rainfall(mm/day)

50

3B42RT+ VS Observation

40

30

3B42RT

20

10

0
0

10

50

20
30
observation(mm/day)

40

50

satellite
e-Rainfall(mm/day)

GSM PMVK+ VS Observation
GSMaPMVK+
Ob
ti

40

30

GSMaP

20

10

0
0

10

20
30
observation(mm/day)

40

50

observation

2
A=10,391km,

Daily rainfall
d i JJuly
duringl anddAugust of 2004

sate llite - Rain fall((m m / day)

50

GSMaPMVK+(correction) VS Observation

GSMaP(correction)

40

30

20

10

0
0

10

20
30
observation(mm/day)

40

50

Global Precipitation Measurement(GPM)

zScheme for reports on global precipitation every 3 hours with main satellite and 8

constellation satellites

zJapan’s contribution: Development of dual precipitation data and launch of H2
H2-A Rocket
Constellation
Core Satellite
Dual--Frequency RadarDual
S t llit
Satellites
Multi Frequency Radiometer

Satellites with Microwave
Radiometers

Observation of rainfall with moreaccuracy and higher resolution

More frequent observation

Adjustment of data fromconstellation satellites
JAXA (Japan)

Cooperation ：NOAA(US) NASA(US) ESA(EU)NOAA(US),NASA(US),ESA(EU),
China, Korea and others

Dual--frequency radar, rocket
Dual

NASA(US)
Satellite bus, Microwave measurement

E th heating
Earth
h ti
phenomenahStudy of climate change
Improvement of forecasting system

Global Observation
every 3 hours

IWRM
Flood forecasting
Forecasting of crop productivity

Directions to overcome technical issues (2/2)< Integratedg
Flood AnalysisySystemy(IFAS)) >～To realize the concept of GFAS – Streamflow ～For local engineers in developing countries•••

To enable the implementation of flood forecasting system with global
real-time satellite-based rainfall data and other GIS databases, without
much cost and a priori high-tech capacity, anywhere in developing
countries,ti
andd
To enable local engineers to easily improve the accuracy and reliabilityof the system by combining with in-situ local data
→ User-friendlyfinterfaces
fusing state-of-the-art
ftechnology,
including modules to use satellite-based data
and to analyze GIS data for building hydrologic models
To enable local administrators and engineers to utilize IFAS effectively
by themselves with the sense of local ownership.
→ Both technical training and dissemination activities are jointly
promoted

Developing countries can utilize advanced technology
as easily, effectively and autonomously as possible
with the sense of local ownershipDevelopment of IFASforo flood
ood runoffu o analyses
a a yses oon a rivere basbasin sca
scalee
• IFAS (Integrated Flood Analysis System)
The software package for the flood runoff analysis equipped with GUI
Rainfall data

Software package

Flood forecasting

Disaster mitigation

RainfallSurface flow of water
Flow intoriver channels
Flow of water in the ground

DEM data

River basin• Developed by joint research (FY2005-2007)
ICHARM / Public Works Research Institute (PWRI),
Infrastructure Development Institute (IDI / Secretariat of IF-Net),and nine major
j civil-engineeringgg consulting
g companiesp22• Distribution of executables, free of charge

River channel network

Global Flood Alert System (GFAS) - Streamflow- Toward prompt implementation of flood forecasting / warning systems with the sense ofownership of local users in developing countries g

IFAS(A basis for flood forecasting/warning system)
Real-time input: Satellite & ground rainfall
GIS data input for setting parameters
GIS analysisGy to build runoff model
Runoff analysis and flood simulation
User-friendly interfaces for output
Grid No:482

250

20

200

25

150

30

100

35

50

40

上流域平均雨量

河道流量 (G482)○○実績河道流
雨量

152007/7/9 20:00

300

2007/7/9 19:00

10

2007/7/9 18:00

5

2007/7/9 16:00

Prompt & efficient implementation
No need to develop original core system
Step by step improvement of accuracy with
Step-by-stephydrological observational network

Date Time:2007/7/9

2007/7/9 14:00

After the application of IFAS:

Project:ABCDEFG

400

2007/7/9 12:00

流量

450

350

2007/7/9 8:00

Despite of the needs for flood forecasting/warning,No rainfall, GIS data, nor analytical toolsÆ Required much money & time for implementation

2007/7/9 6:00

Current situation

Data download throughInternet, free of charge

2007/7/9 10:00

Flood
disasterprevention &mitigation

Other GIS data for runoff mode((Land use,, soil,, etc.))

2007/7/9 4:00

Ex.)) IFNet-GFAS,E
IFN t GFAS NASANASA
3B42RT, JAXA-GSMaPTopographic data

2007/7/9 2:00

Satellite-basednear real-time
rainfalli f ll ddatat

2007/7/9 0:00

Global observation of rainfall
by earth observation satellites

Plan to promote the implementation of flood forecasting
systemyusing
g GFAS-Streamflow with IFAS
• First Phase ( - FY
FY20082008))• To implement the method to utilize newest global satellitesatellite-based rainfall products with auto
auto--correction
algorithm for heavy rainfall• To implement the method to utilize global climatic and geophysical datasets available through theInternet• To implement the method to utilize statestate-ofof--thethe-art numerical weather forecast and hydrologic modelingtechnology with GIS analytical tools• Effective dissemination of flood forecasts and warnings with universal and graphical visualization→ Realization of flood forecasting and warning system even in poorlypoorly-gauged river basins• Second Phase (FY2008(FY2008 - )• To implement the method to improve the performance of the flood forecasting system by the integration
with local inin--situ hydrohydro--meteorological data
• To implement the method to attain higher accuracy and efficiency of numerical weather prediction andhydrologic simulation models• To make the IFAS system compatible with universal platforms such as CommonMP
CommonMP,, OpenMI,
OpenMI, MMS, etc.
• To hold educational and training seminars and workshops for local administrators/engineers on thetheoretical background, usage and maintenance of the IFAS
• To
T enhancehlocal
ll pilot
il t studiest di• Third Phase (FY(FY20092009 -)• Consultation and/or proposal on the arrangement of meteo
meteo--hydrological inin--situ observation networkand flood forecasting system, the improvement of the system, alternatives for flood control and/or
integrated flood management, etc. on the basis of experiences of local pilot studies

Technology for
Flood Forecasting System-MajorMajor features and functions of IFAS forpoorly-gauged river basins –International Center for Water Hazard and Risk Management
under the auspices of UNESCO （ICHARM） hosted by PWRI

Jun MAGOME

-- Key Features -1. Utilization of satellite
satellite-based
based rainfall
2. Multi run-off analysis engines
3 Automatic model creation
3.
4. Visualization of flood forecasting results
5. Free distribution

Rainfall data

Satellite-based rainfall data
Ground-based rainfall data

Modeling

Creation of a river channel
Estimation of parameters

Distributed model

RunoffR
ff analysis
l i BTOP model

Display of results

Rainfall Data : Current Functions1 ) Satellite-based rainfall data
TMPA-3B42RT (NASA)()•

QMORPH/CMORPH (NOAA)•

GSMaP (JST/CREST, OPU,JAXA etc.)
Gl b l coverage : between
Globalb t
60N 60S llatitude
60N-60S
tit d
Mesh size: 0.25 degrees (25km) or 0.1 degree (10km)

Automatic Data Extraction for area of interest
Provided by NASA, NOAA, JAXA and IFNet-GFAS through the Internet for free2) Ground-based
Ground based rainfall data
• Observed Own data
(L
(LocallO
Ownership)
hi )

3) In
ntegraation(Correctio
on of R
Rainfaall)•Rainfall Data : Rainfall Correction

Key : rainfall movement
250.0

GSMaP
P_data(mm/6h)

200.0

150.0

1
2
3
4
5
6
7
8
9

beforeAverage error ratio＝
A
ti
69.8%

100 0
100.0

50.0

250.0

1
2
3
4
5
6
7
8
9

after

200.0
GSMaP_data(mm/6h)※6hour additional rainfall

Average error ratio＝
A
ti
16.5%

150.0

100 0
100.0

50.0

0.0

0.0
0.0

50.0

100.0

150.0

Gauged_data(mm/6h)

200.0

250.0

0.0

50.0

100.0

150.0

200.0

250.0

Gauged_data(mm/6h)

Siraishi et. al, 2008 (Submitted)

Rainfall data

Satellite-based rainfall data
Ground-based rainfall data

Modeling

Creation of a river channel
Estimation of parameters

Distributed model

RunoffR
ff analysis
l i BTOP model

Display of results

Modelingbasin boundary

Extraction of DEM

River network
L a n d C o v e r C la s sific a tio n ( G L C C )U rb a n a n d B u ilt- U p L a n d
D ry la n d C ro p la n d a n d P a st u re
Irrig a te d C ro p la n d a n d P a s tu re
M ix e d D ry la n d /Irrig a t e d C ro p la n d a n d P a st u re
C ro p la n d /G ra s sla n d M o s a ic
C ro p la n d /W o o d la n d M o s a ic
G ra ss la n d
S h ru b la n d
M ix e d S h ru b la n d /G ra s sla n dSavannaD e c id u o u s B ro a d le a f F o re st
D e c id u o u s N e e d le le a f F o re s t
E v e rgg re e n B ro a d le a f F o re st
E v e rg re e n N e e d le le a f F o re s t
M ix e d F o re st
W a te r B o d ie s
H e rb a c e o u s W e tla n d
W o o d e d W e t la n d
B a rre n o r S p a rs e ly V e g e ta te d
H e rb a c e o u s T u n d ra
W o o d e d T u n d ra
M ix e d T u n d ra
B a re G ro u n d T u n d ra
S n o w o r Ice

I F A S C la s sific a t io n
U rb a n a re a
W e tla n d

G ra ss la n d

F o re s t

parameter

W a te r B o d ie s
W e tla n d

G ra ss la n d

W a te r B o d ie s

“Automatic” Model creation & parameter estimation

Rainfall data

Satellite-based rainfall data
Ground-based rainfall data

Modeling

Creation of a river channel
Estimation of parameters

Distributed model

RunoffR
ff analysis
l i BTOP model

Display of results

Runoff Analysis
PWRI--Distributed Hydrological ModelPWRI(PDHM) Suzuki et.al, 1996 ~Ver. 2.0

YHyM/BTOP Model

Ao et.
et al
al, 1998 ~Ver. 1.4 (Coming Very Soon)C
Core
moduled l anddM
Multi-Module
lti M d l
• Easy parameter calibration• Developed and tested at many basins• Jointly Developed

Applied well more than 100 river basins

Multi Runoff Analysis Engine

Rainfall data

Satellite-based rainfall data
Ground-based rainfall data

Modeling

Creation of a river channel
Estimation of parameters

Distributed model

RunoffR
ff analysis
l i BTOP model

Display of results

Display Results (IFAS-PDHM)
Hydro
Hydroy -g
graphpPlan view of river dischargegGraph of tank water level and discharge

Plan view of satellitesatellite-based rainfall

Display Results (IFAS-PDHM)
Mambermo River Basin in Republic of Indonesia

Sameura dam River Basin in Japan
A=472km2

50
Ground-based rainfall data
Satellite-based rainfall data

(mm/h)

hourly rainfall

40

A=78,992km2

30
20
10

Un-gauged basin

0
0:00

12:00

0:00

2004/10/18

Pasig River Basin in Republic of the Philippines

12:00

0:00

12:00

2004/10/19

2004/10/20 (GMT)

0:00

0:00

0:00

4,000
3 500
3,500

3,000

0
3,000

20
30

2,000

Satellite rainfall(mm)Ground rainfall(mm)Measured discharge(m3/s)
Results Ground rainfall
Results Satellite rainfall

1,500

40
50
60

1,000

70
80

500

90
0
12/4 13:00

12/4 1:00

12/3 13:00

12/3 1:00

12/2 13:00

12/2 1:00

12/1 13:00

12/1 1:00

11/30 13:00

11/30 1:00

11/29 13:00

11/29 1:00

11/28 13:00

11/28 1:00

A=499km2

100

Rainfall（mmm）

Discharge（m3
3/s）

2,500

Discharge(m3/s)

10

2,500
2,000
1,500
1,000
500
0:00

12:00
2004/10/19

12:00
2004/10/20
Time(GMT)

12:00
2004/10/21

0:00

Measured discharge
Calculated discharge (using ground-based rainfall, calibrated parameter)
Calculated discharge (using satellite-based rainfall, calibrated parameter)

Further Developmentpfor ppoorlypoorlyy-g
gaugedg basins•“Satellite-based rainfall corrections”
with/without ground-based rainfall data
•Real time flood forecasting•Real-time•Integration of flood inundation model•Enhanced Visualization using freeware (Google Earth/Map)•Incorporation of numerical weather forecastex.) Global forecast with 20km-mesh by JMA•Consideration on uncertainty of forecasting
Ensemble forecast•Statistical analysis tools to identify flood risks•Downscale technology for hydrologic forecastingex.) Weather Research and Forecasting (WRF) Model)

“Real-time” Flood Alert Systemyat AnywhereyE
Examplel : BTOP ModelM d l + TMPA 3B42RT
Magome, 2008

Integration of “Flood Inundation Model”
t Distributedto
Di t ib t d H
Hydrologicald l i lM
Modeld lHai, Magome, 2008

Enhanced & Easyy Visualization

Tone River (Japan) analysis
for case of levee breach in Tokyo Area
Hai, Magome, 2008

Lower Mekong River Basin((Zoom : Northwest of Tonle Sap
p Lake))Contact

Thank you very much