The 12th International Symposium on Southeast Asian Water
Environment (SEAWE12)
28 - 30 November 2016, Hanoi Vietnam
WEPA Session
Groundwater Pollution Control - to Prevent and Mitigate Impacts ofIndustrial Activities

Overview of GroundwaterContamination in Malaysia
Ismail Tawnie1, Anuar Sefie1, Azrul Normi Idris1, Mohd Khairul Nizar
Shamsuddin1, Azuhan Mohamed2
1Researcher, Hidrogeology Research Center, National Hydraulic Research Institute of

Malaysia (NAHRIM)
2Director General, National Hydraulic Research Institute of Malaysia (NAHRIM

INTRODUCTION - MALAYSIA• Area of about
329,750 km2• Climate is oftropical type,receiving over
2800 mm ofrainfall annually.
• The humidity
and temperature
ranges between
80–90% and 2132°C

INTRODUCTION
Water Resources in Malaysia(Azuhan, 2009)

INTRODUCTION
4 categories of potential:• The most productive aquifers are thealluvium (sand and gravel), yield from50 to 100 m3/h/well• The most productive aquifer in hardrock is in limestone, yield up to 50
m3/h/well. Sinkhole may occur indeveloped areas• Fractured sandstone, their
metamorphic equivalent and volcanic
rock aquifers can yield up to
30m3/h/well• The least productive type of aquifer ismade up of fractured igneous rocks,
yield 20 m3/h/well.

GROUNDWATER MONITORING
Groundwater monitoring is being carried out by:
•
•
•
•
•
•

Minerals and Geoscience Department (JMG)
Department of Environment
Local Councils
Water agencies
Universities (special projects)
NAHRIM (research and modelling)GROUNDWATER MONITORING BYMINERALS AND GEOSCIENCE
DEPARTMENT (JMG)
Objectives:• To detemine ambient/background water quality
and regional water quality trends• To meet regulatory requirements• To detemine the contamination/pollution effects ofa facility discharging to the groundwater• To determine the effect of a particular activity to
the groundwater environment• To provide early warning of onset of contamination

O

100 00'K
J

104 00'M
L

P.Langkawi

Km

PERLIS
Kangar0

Kota Bharu

O

6 0

00'
U

KEDAH
+++++

+ ++

++

++

Georgetown
PULAU
PINANG

P. Redang

+

+

B

+

Kuala Terengganu

+

+++++

PERAK
++

+

+

++

+++

+++

+++

+++

++

+

++

+ ++

+

N

++

00'

Km

A

Alor Setar

++

6

O

O

102 00'+

Laut

TERENGGANU++KELANTAN

China
SelatanIpoh

CP. Pangkor

40

40

00'

D

PAHANG

00'

Kuantan

H
F
E

SELANGOR
K. Lumpur

I

Shah Alam

Selat

NEGERISEMBILAN

MelakaP

P.Tioman

G

SerembanGemencheh, N.S.

MELAKA
Melaka

2 0

JOHOR

2 0

00'

00'
U

LegendJohor
Baharu++ + + ++

++

++++

++

++

++

Railway
State boundry
International boundry

+

O

100

00' T

O

102

O

00'

LegendGroundwater contamination studies

Groundwater monitoring sites
A
B
C
D
E
F
G
H

- Kota Bharu, Kelantan (Rangkaian)- Kg. Kepong, K. Terengganu, Terengganu- Kg. Sg. Ular, Kuantan, Pahang- Kg. Padang, Kuantan, Pahang- Nenasi, Pekan, Pahang- Nenasi - Pekan, Pahang (Rangkaian)- K. Rompin, Rompin, Pahang- Kg. Pulau Manis, Pekan, Pahang

I
J
K
L
M
N
O
P

- Kg. Bohor Bharu, Temerloh, Pahang- Arau, Perlis- Alor Semadong, Perlis- Chuping, Perlis- Rimba Mas, Perlis- Bukit Kemoja, Langkawi, Kedah- Bukit Dundong, Langkawi, Kedah- Telok Datuk-Olak Lempit, Banting

104

00' T

PENINSULAR
MALAYSIAGROUNDWATERMONITORINGSTATIONS (JMG)

110°E

5°
N

4°
N

111°E

112°E

113°E

A. ZON BARATB. ZON TENGAH
BAHAGIAN KUCHINGBAHAGIAN SARIKEI
1. Kampung Sampadi
9. Belawai (JKR)
2. Sg. China
10. Paloh (JKR)
3. Rambungan
11. Penibong
4. Loba
12. Jemoreng
5. Kuala Sampadi-Kuala Gelugor 13. Igan (JKR)
6. Bako National Park
BAHAGIAN SIBU
14. SRK Senau, Mukah
BAHAGIAN SRI AMAN
7. Pusa
15. Oya (JKR)
8. Kabong (JKR)
16. SMK Three Rivers, Mukah
17. Jebungan

114°E

115°E

C. ZON UTARABAHAGIAN BINTULU
18. Kuala Tatau (JKR)
19. Sg. Mas
20. Sebauh
21. Kuala Nyalau

24

23

5°
N
LAWAS

LIMBANGBAHAGIAN MIRI
22. Kuala Sibuti
MIRI

BAHAGIAN LIMBANG
23. Sg. Bangat, Lawas 21
24. Kuala Lawas (JKR)

22
MARUDI
Be ke nu

4°N

Sibuti

NiahLong Lama

Suai

20

18

19

BINTULU

13 14 15 16 17

3°
N

Tubau

3°
N

Balingian

12

Oya

MUKAH

TATAU

Igan
DALAT

MATU

11

BELAGA

DARO

10

SIBU
9

BINTANGORSARIKEI2°N

5KANOWITSONGMERADONG

8

Julau

6
Sematan

1

2

3

4

2°
N

KAPIT

7
SARATOK

LUNDU

Disediakan oleh:
1. Zamzuri Ghazalee
2. Sulong Enjop
Program Perkhidmatan Geologi
Jabatan Mineral & Geosains,
Sarawak.
10 Oktober 2000

KUCHINGSe bu ya u

SIMUNJAN
KOTA
SAMARAHAN

BAU

Be ton g

SRI AMAN
PadawanEngkilili

SERIAN

1°
N

Scale

LUBOK ANTU

0

30

60

90

120

150 kmd:\zuri\mzr\bas.ds4

110°E

111°E

112°E

113°E

114°E

115°E

SARAWAK GROUNDWATER MONITORINGSTATIONS

1°N

GROUDWATER QUALITY
MONITORING BY DOE• To establish groundwater quality status within the country• To develop a Malaysian Standard for groundwater quality• To identify locations that necessitates necessary intervention• To initiate remedial action at sites identified as contaminatedareas

GROUNDWATERMONITORING(DOE)
PENINSULAR
MALAYSIA• 122 monitoring
wells (79 mw at 47
sites in P. Malaysia)• 15 landuses• Potential areas ofcontamination:industrial, animalburial, agricultural,
urban & rural

RESULTSMONITORING RESULTS - DOE• Iron: generally Fe above acceptable level (36 - 75%), it comes from theaquifer itself• Mercury: exceed benchmark of agriculture (10%), landfill (9%),
industrial site (6%).
• Arsenic: exceed benchmark of agriculture (9%), landfill (27%), industrialsite (11%).
• Other metals & coliform- not exceed limit.
• Phenolic cpds: exceed benchmark of landfill (8%), ind. site (10%), golfcourse (11%).
• Nitrate: Exceed benchmark of landfill (8%), ind. site (9%), rural site(50%) ((fertilizer & sewage seepage))• Gw quality at 9 industrial sites > contaminated than other site types.

GROUNDWATER MONITORING BYMINERALS AND GEOSCIENCE
DEPARTMENT (JMG)

RESULTSGROUNDWATERMONITORING(JMG)
LOCATION: KOTA
BHARU

79
monitoring
wellsHydrogeologicalfence diagram of
the northern
KelantanSampling locations(contamination
study)

Results of nitrateconcentration(study)Distribution ofammonia values inthe study area
(1998)

Distribution of oil
and grease values
in the study area
(1998)

Distribution ofdetergent values inthe study area
(1998)

Variations of chloride
and ironconcentrations inmonitoring wells at
Tg. Mas Waterworks(1) Kelantan

Nitrate concentration in groundwater samples
from the shallow aquifer in relation to the landuse

Nitrate concentration in groundwater samples
from the deep aquifer in relation to the landuse

Fluctuation of nitrate concentration in monitoring wells
40
35

Nitrate, mg/l

30

KB48
KB50

25

KB52
KB53

20

KB56
KB59

15

KB60
KB67

10
5
0
Feb

May

Jul
1989

Sep

Apr

Aug
1990

Feb

Sep

1991

Feb

Sep

1992

Feb

Aug

1993

Jan

Aug

1994

Fluctuation of nitrate concentration in monitoringwells

Nitrate, mg/l
0

40

80

120

0

Depth, m

40

80

120

Nitrate concentration:
Number of data points used = 753
Average X = 4.90mg/l
160

Relationship between nitrate concentration and depth

Ammonium, mg/l
0

4

8

12

0

Depth, m

40

80

120

Ammonium concentration:
Number of data points used = 722
Average X = 0.54mg/l
160

Relationship between ammonium concentration and depth of monitoring wells

Summary of nitrate and ammonium
concentrations
Nitrate concentration
Aquifer/well type

Minimum(mg/l)

Maximum(mg/l)

Average(mg/l)

Dug well

3.00

47. 00

8.33

Shallow
aquiferDeepaquifer

3.00

37.00

5.84

3.00

88.00

4.44

Ammonium concentration
Aquifer/well type

Minimum(mg/l)

Maximum(mg/l)

Average(mg/l)

Dug well

0.02

14.36

0.47

Shallow
aquifer
Deep aquifer

0.02

9.50

0.60

0.02

17.00

0.62

Pollution from household

Sources of Nitrate
A number of anthropogenic nitrate sources can be identified in the study. These are:i.
Fertilisers
The extensive agricultural activities use extremely high amounts of fertilisers to optimise theagricultural production capacity. Padi and tobacco are the major fertilised crops in the area.
The vertical movement of the contaminant is through the sandy soil with the help of rainfall
and irrigation water.
ii.
Septic tanks
There is no central sewerage system in the study area. Hence, most of the households use
septic tanks for human waste disposal. In many suburban areas of the Kota Bharu, the septic
tanks are normally unlined at the bottom (no concrete lining at the bottom or concrete
culvert often used) and hence the wastes are in direct contact with the aquifer.
iii.
Waste water
Domestic waste water could also be one of the major contributors to high nitrateconcentrations. Other sources could be factory, school and hospital/clinic. The waste water isnormally discharged directly to the open drain or purpose built collector well for discharging
liquid waste from the households.
iv.
Other sources
Other sources of nitrate could be from the in-situ sources such as landfill or animalhusbandry/poultry shed, and in the village areas where garbage collection is not carried out,
most households use rubbish pits to dispose of the domestic solid wastes.

Other Contaminants
AmmoniumThe occurrence of ammonium is normally associated with contaminationfrom human activities or domestic waste disposal sites, and may indicate theexistence of a relatively reducing environment in the aquifer.
Pesticides
A study in selected agricultural areas cultivated with padi and tobacco inNorth Kelantan indicated strong evidence of pesticides contamination.
Groundwater samples was found to contain endosulphane and is mostwidespread in the padi area compared to tobacco, resulting from theextensive use of pesticide for pest control. Other pesticides have been
detected in both types of agrosystems.
Microbial
A preliminary study indicated significant contamination by coliforms in the
groundwater resources from the shallow aquifer. Samples were collected in
dug wells and also piezometers. The contamination could be related tohuman and animal wastes (grazing animals and poultry shed).

GROUNDWATER MONITORING
LOCATION: KUALA LANGAT, SELANGOR

1400
MWD 5

1200

1000

800

600

400

200

0
35886

35916

MWD5 - Na

MWD10 - Na

36039

36069
MWD12 - Na

36100
MWD5 - Cl

36342
MWD10 - Cl

Variation of chloride concentration in monitoring wells
at Telok Datuk, Selangor

36373
MWD12 - Cl

Location of Nenasi Water Treatment Plant, Pekan, PahangGroundwater quality
variations (bicarbonate,chloride dan iron) inmonitoring wells in Nenasi
Water Treatment, Pahang

OTHER CASE STUDIESRESULTSMIGRATION OF POLLUTANTS IN
GROUNDWATER AT A DOMESTICLANDFILL IN MALAYSIA.
A Case Study: Pollutants
Distribution and groundwater
quality in Gemencheh Landfill

Drinkingwater
standard(WHO)

Range ofgroundwater
quality at thesite*

Range ofgroundwater
backgroundvalue**

6.5-8.5

3.4-7.4

5.1-7.0-60-2670

44-64

Sodium200

3.6-228

6.0-6.8

Potassium-

0.7-209

2.2-3.8

Calcium-

0.9-154

0.2-11

Magnesium

150

0.2-61<0.1-0.5

Carbonate

-

<1.0

<0.1

Bicarbonate-<1.0-179

10-46

Sulphate

250<3.0-686<3-5

Chloride

250

6-648

2-7

Nitrate50<0.5-226<0.5-1.3

Iron

0.3

0.2-215

0.2-4

Manganese

0.5<0.1-23<0.1

Nickel

0.02

<0.1

<0.1

Lead

0.01

<0.01-1.26<0.01-0.13

Zinc

3.0

<0.1-0.9<0.1

Cadmium

0.003<0.01-0.1<0.01

Chromium

0.05<0.01-1.0<0.01-0.03

Copper1.0<0.1-0.7<0.1-1.0

Mercury (μg/l)

1.0<0.2-4.1<0.2-0.8

Parameter

pH
Electric
conductivity(μS/cm)Groundwater quality analysis
Note:
All unit in mg/l except those inbrackets
WHO-Drinking Water Standard ofWorld Health Organisation*Range of groundwater quality
from other than borehole SP8** Range of groundwater quality
from borehole SP8

20-year WHPA

NAHRIM CASE STUDYAPPLICATION OF CHEMOMETRICSTECHNIQUES IN HYDROGEOLOGICALASSESSMENT

Chemometrics
The use of mathematical and statistical methods to improve theunderstanding of chemical information and to correlate quality
parameters or physical properties to analytical instrument data

Application of Chemometrics Techniques for
the Aquifer Classification and Characterisationof Groundwater Quality in Lower Kelantan
Basin, Kelantan, Malaysia

Introduction• Groundwater is the main source of Kelantan Lower Basin
where almost 100% of domestic water supply and industrial
purposes in Kota Bharu comes from groundwater• Therefore, the sustainable management, maintaining andprotecting groundwater resources are the major concern as
about 75% of the population live in this area
• About 9.875 MLD or 6.8% of total groundwater production isabstracted from Tanjung Mas• The demand for clean water is estimated to increase at apace of 2.5% per year

Objectives
To classify and differentiate confined aquifer
as well as to determine the extent of saline
2nd aquifer based on groundwater quality andlithology log

To identify the significant variables indiscriminating the well locations

Methodology
Study Area

carried out for theconfined aquifers (2ndaquifer) and below which
depth approximately 20 m
at 3 different locations(Pengkalan Chepa,
Tanjung Mas and Jalan
Merbau)-Lower Kelantan
Basin
19 monitoring wellFigure: Location of well stations in Lower Kelantan basin

Geological log of KB 15(Jalan Merbau), KB 06 (TanjungMas) and KB 01 (Pengkalan Chepa)
Jalan Merbau

Tanjung Mas

Pengkalan Chepa

Monitoring well at the study area
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.

Location

Pengkalan Chepa

Tanjung Mas

Jalan Merbau

Well
KB 01
KB 02
KB 03
KB 04
KB 05
KB 06
KB 07
KB 08
KB 09
KB 10
KB 11
KB 12
KB 13
KB 14
KB 15
KB 16
KB 17
KB 18
KB 19

Latitude(RSO)
478112478109478106478104478103475211475211475210475212475174475122475215475111475232472560472573473300472572472569Longitude(RSO)
681482681481681481681481681483678945678947678949678949678991678959678949678894678875678352678341678500678339678337

ScreenDepth (m)98.5-100.0
85.5-87.0
67.0-68.5
58.0-59.5
23.0-24.5
127.5-129.0
97.5-99.0
78.5-80.0
54.0-55.5
30.0-31.5
30.5-32.0
30.5-32.0
30.0-31.5
30.5-32.0
125.0-126.5
108.5-110.0
83.5-85.0
64.0-65.5
27.0-28.5

Depth
(m)
101.0
88.0
69.5
60.5
25.5
130.0
100.0
81.0
56.5
32.5
33.0
33.0
32.5
33.0
127.5
111.0
86.0
66.5
29.5

Methodology
The chemometrics techniques employed were:• Agglomerative Hierarchical Cluster (AHC) and• Discriminate Analysis (DA)Methodology
Data Preparation and Analysis

Data Pretreatment

Statistical
Analysis•Secondary groundwater quality data → 16 parameters(Minerals and Geoscience Department, Malaysia)•19 well stations•May 1989 to Dec 2012
•Missing data → average values fromcorresponding datasets•Values below limit → set to half•Normality test (XLSTAT 2012.3)•Normalize → centering, standardisation andlog-scaling methods•Univariate analysis → mean + standard deviation•Agglomerative hierarchical cluster (AHC)•Discriminant analysis (DA)Multivariate
analysisDatacollection

Methodology
Agglomerative Hierarchical Cluster (AHC)• Ward’s linkage method• Euclidean distance as a measure of similarity to determine thenumber of clusters

Methodology

Discriminant models• Formed using water quality
variables (independent
variables) & clusters(dependent variables)• Standard, stepwise forward
and stepwise backward modes

Confirm cluster membership• Successful if high correct
percentage
Observations (axes F1 and F2: 100.00 %)
10
8
6
4

F2 (6.50 %)Discriminant Analysis-10

1st aquifer

2

2nd aquifer

2nd aquifer-8-6

1st aquifer 0
-4
-2
0
-2
-4
-6
-8

F1 (93.50 %)2

4 aquifer
6
3rd

8

3rd aquifer
Centroids

Result & Discussion
Dendrogram (Pengkalan
Chepa)

Dendrogram (Tanjung Mas)
14000000

80000000

12000000
2nd aquifer

Dissimilarity

50000000
40000000

3rd aquifer

30000000

8000000
3rd aquifer

6000000
4000000

20000000

Dendrogram (Jalan Merbau)

160000140000

2nd aquifer

100000

3rd aquifer

80000
60000
40000

KB 17

KB 15

0

KB 16

20000
KB 19

Dissimilarity

120000

KB 13

KB 12

KB 14

KB 11

KB 10

KB 09

KB 08

0

KB 07

KB 02

KB 01

KB 04

KB 03

KB 06

2000000

100000000

2nd aquifer

10000000

KB 1860000000

KB 05

Dissimilarity

70000000

Observations (axes F1 and F2: 100.00 %)50
40

Pengkalan Chepa

30
20

F2 (0.00 %)Result & Discussion

2nd Aquifer

10
3rd Aquifer

3rd Aquifer

2nd Aquifer

0
-30

-20

-10

0

10

20

30

40

50

60

Centroids

-10
-20
-30

Observations (axes F1 and F2: 100.00 %)F1 (100.00 %)Observations (axes F1 and F2: 100.00 %)
5.6

4.8

Tanjung Mas

4.8

3.2

F2 (0.00 %)

-6.4

-4.8

-3.2

2nd Aquifer

2nd Aquifer-1.6

0-1E-14

1.6

-1.6
-3.2
-4.8

3.2

4.8

6.4

3rd Aquifer
Centroids

F2 (0.00 %)

2.4

1.6
3rd Aquifer

Jalan Merbau

4

3.2

2nd Aquifer

1.6
3rd Aquifer

0.8

0-4.8 -4 -3.2 -2.4 -1.6 -0.8 0-0.8

2nd Aquifer
0.8 1.6 2.4 3.2

-1.6
-2.4
-3.2
-4

-6.4

F1 (100.00 %)-4.8

F1 (100.00 %)4

3rd Aquifer
4.8 5.6

Centroids

Cross section Jalan Merbau –Pengkalan Chepa (correlation)
Jalan Merbau

Tanjung Mas

Peng. Chepa

1st aquifer
2nd aquifer

3rd aquifer

Result & Discussion

Descriptive statistics of groundwater quality from 2nd and 3rd aquifer(Pengkalan Chepa, Tanjung Mas and Jalan Merbau)
AquiferUnit

2nd (second) aquifer
Min

Max

Mean

3rd (third) aquifer
SD

Min

Max

Mean

SD

pH

-

3.20

8.90

6.26

1.08

2.00

8.50

6.63

0.68

EC

µS/cm

41

6150

1792

1548

14

970

278

235

TS

mg/l

38.00 9240.00 1223.95 1218.25

34.00 696.00 213.01 177.87

DS

mg/l

20.00 2736.00

988.82753.882.00 960.00 174.12 149.57

Ca2+

mg/l

2.10

157.00

36.67

19.23

0.25 140.00

15.14

15.64

Mg2+

mg/l

0.80

75.00

27.47

12.01

0.25

40.00

9.17

8.69

Na2+

mg/l

1.00 1028.00

243.66279.35

0.20

90.00

16.90

13.10

K+

mg/l

1.30

37.00

12.65

6.46

0.05

86.00

7.79

5.48

CO3

mg/l

0.50

8.00

0.58

0.56

0.50

7.00

0.55

0.39

HCO3

mg/l

0.50

156.00

44.09

50.12

5.00 167.00

44.87

19.66

Cl-

mg/l

0.50 1778.00

528.40459.721.00 281.00

58.53

70.40

SO4

mg/l

0.50

26.00

1.86

1.84

0.50

22.00

2.19

1.61

NO3

mg/l

0.25

43.00

2.99

4.74

0.25

34.00

1.90

2.34

NH4

mg/l

0.01

19.00

1.14

1.91

0.01

6.40

0.44

0.54

Fe2+

mg/l

0.05

48.00

24.51

10.84

0.05

58.00

12.07

6.54

Mn+

mg/l

0.05

0.90

0.52

0.25

0.05

2.00

0.21

0.17

Result & Discussion
Univariate Analysis• Groundwater parameter variation of pH, EC, TS, DS, Ca2+, Mg2+, Na+, K+,
HCO3-, Cl-, SO42-, NO3-, NH4+, Fe2+, Mn+ from 2nd and 3rd aquifer

Classification matrix for DA of groundwateraquifer variations
Aquifer

Depth assigned by DA
2nd aquiferStandard mode
2nd aquifer
221
3rd aquifer
13
Total
234
Stepwise forward mode
2nd aquifer
223
3rd aquifer
13
Total
236
Step wise backward mode
2nd aquifer
220
3rd aquifer
16
Total
236

Total

% Correct

52
380
432

273
393
666

80.95%
96.69%
90.24%

50
380
430

273
393
666

81.68%
96.69%
90.54%

53
377
430

273
393
666

80.59%
95.93%
89.64%

3rd aquifer

Result & Discussion
Discriminant Models (DA)ModeStandard
Stepwise forward

Stepwise backward

Correct
Assignation (%)

Significant
Variables

90.24(12 variables) pH, Cond., Tot. Solid, Diss.
Solid, Ca, Mg, Na, K, Cl, NH4, Fe, Mn

90.54(7 variables) pH, Diss. Solid, Na, K, Cl, Fe,
Mn

89.64

(7 variables) pH, Cond., Diss. Solid, K, Cl,
NH4, Fe, Mn

DA →confirmed the number of aquifer determined by the CA

Conclusion• Application of cluster analysis (AHC) based on 19 monitoring well –classify groundwater aquifer into 3 aquifer; 1st, 2nd and 3rd aquifer(only 2nd &3rd aquifer analysed-no data/1st aquifer)• The results were supported by DA. Discriminating models created in
all modes were approximately 90% correct assignation of theclassification data set. That mean, all the aquifers are completely
separated by impermeable layer of clay (no leakage)• However, there are similar/overlapping water quality value indifferent aquifer due to groundwater movement from upstream -will
dilute the gw concentration (saline 2nd aquifer)• Extent of saline 2nd aquifer could be as far as 10 km from coast line
(there is still has segregation/discriminant of water quality in Jalan
Merbau)-inundated in the past, support the previous study finding (6km from beach) using hydrogeochemical and geophysical method(Samsudin et. al, 2008)• Multivariate techniques served as excellent exploratory tools inanalysis for understanding spatial variations (horizontal and vertical)of groundwater quality in Lower Kelantan Basin.
• The use of these methods will prove to be useful in reducing cost andtime of sampling as number of monitoring well reduced

TERIMA KASIH
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Alamat: Institut Penyelidikan Hidraulik Kebangsaan Malaysia(NAHRIM)
Kementerian Sumber Asli dan Alam Sekitar (NRE)
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Theme:MANAGING WATER FOR SUSTAINABLE DEVELOPMENT –Learning from the Past for the FutureTechnical visits #1 (SMART Tunnel)

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Genting Highlands

Food HeavenKeynotes Speakers

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MANAGEMENTTHEME 2: FLOOD MANAGEMENTHYDRAULICS AND
Prof. Ing. Silke Wieprecht
Prof. Roger A. Falconer
INDUSTRIAL FLOWS(University of Stuttgart, Germany)(Cardiff University, UK)
Prof. Shahbaz Khan
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Indonesia)

THEME 4: COASTAL,
THEME 4: COASTAL,ESTUARIES AND LAKESESTUARIES AND LAKESMANAGEMENTMANAGEMENT
Prof. Stephen MonismithProf. Pengzhi Lin(Stanford University,(Sichuan University, China)
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THEME 5: URBAN WATERMANAGEMENT
Prof. Dragan A. Savić(University of Exeter, UK)

THEME 5: URBAN
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Prof. Farhad Yazdanoost(K N Toosi University ofTechnology, Iran)

THEME 6: WATERRESOURCESMANAGEMENT
Prof. Jorg Imberger(University of Miami,
Florida, USA)

THEME 7: HYDRO-INFORMATICS/ COMPUTATIONAL METHODSAND EXPERIMENTAL METHODS
Dr. Ahn Jae-Young(ETRI, Republic of Korea)

THEME 6: WATERRESOURCESMANAGEMENT
Prof. Jun Xia(Wuhan University,
China)

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