HYDROGEOLOGY OF BANDUNG BASIN: MODELING, … · (b) THE CONCEPT 1: Change in groundwater flow...

Ahmad TAUFIQ

HYDROGEOLOGY OF BANDUNG BASIN:MODELING, HYDROGEOCHEMISTRY, AND NITRATE CONTAMINATION

WEBINAR, JULY 22, 2020

1

Outline of presentation

I. Introduction (background and concept)

II. Study area (geology, hydrogeology)

III. Data (groundwater flow system: potential, in-situ test, major ions, CFCs)

IV. Results 11) Hydrogeochemistry result

2) Groundwater modeling

3) Groundwater mixing ratio

V. Result 21) Controlling factors of nitrate contamination

2) Driving mechanisms of nitrate contamination

2

GROUNDWATER AND THE CITY

An intimate relationship (Foster et al, 2010)

The impacts: (Jago-on et al, 2009)

• quantity: significant groundwater drawdown and quality: degradation of groundwater quality

3

(Hendrayana et al, 2008

(http://water.usgs.gov/edu/gwdepletion.html) http://sd.water.usgs.gov/nawqa/pubs/factsheet/fs114.95/fig2.gif

INTRODUCTION

Three different depression areas:1. Cimahi (CMHI) 2. Rancaekek (RCK)3. Dayeuhkolot (DHYK)

BACKGROUND 1:Groundwater drawdown

4

Rosadi R, 2004

5

BACKGROUND 2

(b)

THE CONCEPT 1:

Change in groundwater flow dynamics

• Hydrogeochemistry methodoCFC-12 tracer and C-14 (ratio)

• A vertical flux by numerical modeling

• Estimation the mixing ratio 6

• Understanding these processes, it is an important task for effective groundwater management because such changes

can cause unexpected problems, such as groundwater quality degradation and the disturbance of regional

groundwater flow systems

• Nitrate (NO3−) is a primary groundwater

contaminant (Xue et al., 2009; Zhang et al., 2015)

• Very stable

• Soluble

• Mobile

• A widespread concern and particularly important in environmental problem (Rivet et al., 2008;

Xue et al., 2009; Hosono et al., 2013; Zhang et al., 2015)

THE CONCEPT 2:

7

• The 4TH biggest

country of the

WORLD by

population (±216

million)

• ± 53.4 % of the

population is urban

• ± 60% of the

population live in

java island

Capital city of West Java province

Centre of textile industry

People: 8.5 million; 2.300 km2

https://www.worldofmaps.net/typo3temp/images/bevoelkerungsdichte-indonesien.png

Study area

Geological and hydrogeological setting

• Shallow groundwater system

• By dug well <20 m; domestic

• Kosambi Formation (Akuitard)

• Deep groundwater system

• By drilled well > 80 m; industry)

• Middle and Lower Cibereum Formation

9

Thick

(m)

Aluvial river Uncolidated material; clay, sand, gravel, boulder

Holosen (0.01

Ma)KOSAMBI Fm (Ql) 80

Lake deposit; unconsolidated clay, sand;

interconnected laterally and vertically with young

volcanic sand, tuff, breccia

Late Pleistosen

(0.7 Ma)

CIBEREUM Fm

(Qyd)80

Volcanic products; ocarse grain, breccia, conglomerat,

tuff, obsidian,andesit, basalt; inter-bedded

pyroclastic; dark brown

Pleistosen -

Pliosen (1.8 Ma)

CIKAPUNDUNG

Fm (Qyu)350

Old volcanic product; aglomerat, breccia, sandy tuff

with lava intercalation (Qob)

Upper Miosen

(12 Ma)Tertiary Vulcanic ?

Undifferentiated volcanic prducts; breccia, balastic

lava

Middle Miosen

(15 Ma)

RAJAMANDALA

Fm? Limestone, napal, clay, quartz sandstone

TE

RS

IE

R

AGE Stratigraphy Lithological desciption

QU

AR

TE

RN

AR

Y

PLIOCENE (1,8 Ma)

LATE PLEISOTOCENE

(0.7 Ma)

HOLOCENE

(0.01 Ma)

Source: Geological map compiled by Hutasoit (2009)

Source: compiled by Hutasoit (2009)

•The shallow groundwater:•Groundwater abstracted by dug well in Upper Kosambi

and Upper Cibereum Formation

•The deep groundwater:•Groundwater abstracted by drilled well in Middle and

Lower Cibereum Formation

The Assumptions

10

• Shallow groundwater flows from theperipheral of basin to the center of thebasin

• The deep groundwater: three depressionzones in the industrial area

Data 1 - Groundwater potential map

11

Data 2 - Distribution map of ORP value

• Shallow groundwater: high ORP value

12

• Deep groundwater: low ORP

Data 3 - Distribution map of water type

• The shallow groundwater: Ca-HCO3

• On center of basin: Na-HCO3 type13

• The deep groundwater: Na-HCO3 type

• No pattern in depression area

The geological cross section adapted from an) by the

Office of Energy and Mineral Resources -West Java Province

and LPPM–ITB (2004)

• The deep groundwaterindicates more progression• The enrichment of Na+ > Ca2+

• The enrichment of mNa/Ca

• The increasing Na, an indicatorof strong rock interaction

• The cation exchange reaction(Ca2+ <->Na+) (Appelo and Postma, 2005).

Redox boundary

14

• The shallow groundwater: high CFC-12 concentration • The deep groundwater: some points in the cone of depression area has

high CFC-12 concentration.

Result 1 - Rejuvenation processes Distribution map of CFC-12 concentration ( as a tracer of hydrogeohemistry method)

• The three depression areas

Result 1 - Rejuvenation processes > Observed CFC-12 concentration

16

Result 1- Rejuvenation age processesCarbon-14 concentration in monitoring wells

• The 14C conc: getting higher or getting younger

• The CMHI area: the highest rejuvenation ratio

17

R = REJUVENATION AGE RATIO

R = 𝑅𝑚 −𝑅𝑜

𝑅𝑜X 100

Well no, area Result of 14C (in pmC)

2008a 2012b

Well 1, CMHI areac 0.3 0.5

Well 6, RCK area 48.8 64.7

Well 8, DHYK area 71.5 81.5 a data after Wahyudin and Matahelumual (2008)

b data from Satrio et al (2012) c Areas: Cimahi (CMHI), Rancaekek (RCK), Dayeuhkolot

(DHYK)

Result 2 - Groundwater modeling

•The stages:1) Updating data of wells (water discharge and head)

2) Constructing a hydrogeological model 3) Setting the boundary condition4) Adjusting the hydraulic parameter data5) Calibrating the model 6) Calculating the groundwater fluxProgram : A numerical software: Modflow V10

18

1) Updating data of wells (water discharge and head)

• The authority on this basin: Office of Energy and Mineral Resources

• A simplified form of data in one grid represented by a well point

19

2) Constructing a hydrogeological model

3) Setting the boundary condition

• Description of the groundwater system is divided into two systems

• No-flow boundary conditions: • the bottom and

the outer sides of the model.

20

4) Adjusting the hydraulic parameter data

• Divided into two system

• The initial parameters was from previous study (Hutasoit, 2009)

• Then had been calibrated up to 2016

Property Set up

Grid size 0.5 x 0.5 km2

Number of grids 130 rows and 130 columns

Layer structure and their

parameters (K, T)

Zone S : Shallow groundwater system

Zone S consists of 3 layers (L1, L2 and L3)

Layer L1 (4 x 10-5 m/s, 44 m2/day)

Layer L2 (1 x 10-5 m/s, 30 m2/day)

Layer L3 (8 x 10-7 m/s, 2 m2/day)

Zone D : Deep groundwater system

Zone D consists of 3 layers (L4, L5 and L6)

Layer L4 (1 x 10-5 m/s, 47 m2/day)

Layer L5 (5 x 10-5 m/s, 75 m2/day)

Layer L6 (1.2 x 10-5 m/s, 50 m2/day)

Computation period 1950 – 2015

Top boundary Flexible head

Bottom boundary No-flow

Initial condition Steady-state, without groundwater pumping

Natural groundwater flow (1950)

Calibration data Groundwater potential observations for

1994-2015 at ten representative observation

wells 21

5) Calibrating the model

• Adjusted to best fit the long-term fluctuations of groundwater potential between monitoring and modeling result, with simultaneously the calculated pumping volumes22

5) Calibrating the model

• Comparison head in contour between monitoring result and modeling result

23

1995 2005 2015

6) Calculating the groundwater flux

• The budget zone analysis based on the zone of layer.

• To calculate the vertical downward flux from Zone S to Zone D

24

Evaluation:

• The calculated volumes were up to 14 times higher than the official volumes• Similar anomalies were found in the Asian big cities• These anomalies might be caused

• by unregistered wells• many of the pumping volumes have not been reported in official documents.

• Therefore, this finding regarding under-reported pumping volumes could provide valuable information for improving monitoring and modeling.

25

Result 3 - The comparison of three depression areas

• To increase our understanding of the mixing process

• To further proof that there was groundwater mixing

• To further evaluation of groundwater mixing

26

• Estimate the TOTAL mixing ratio,Rueedi et al (2005) can beeliminated:• to reduce the error of estimation,

• to reduce uncertainties and

• to make the result becomesconsistent.

Result 3 - The total mixing ratio

MAJOR IONS and STABLE ISOTOPES (Ca, Na, K, Mg, HCO3, Cl, SO4, δ18O, δ 2H)

27


Selection of end-members:

• A pure chemical compound regarded as a natural water

• Representing based on all available information (geology, hydrogeology, spatial distribution hydro-geochemistry)• End-member 1 (C1): the shallow groundwater

• elevated concentrations of CO2− and HCO3

−, lowCl− - and low SO4

− ; elevated concentration ofCa2+

• End-member 2 (C2): the deep groundwater.

• elevated concentrations of Cl− and HCO3− ;

elevated concentration of Na2+, low ORP and lowDO

• The spatial distribution map: higher mixing ratios are found close to the center of the depression cone, • the mixing ratio gradually decreases towards the edges of the area


29

Discussion 1- Hydrogeochemical vs Numerical modeling

• The modeling result confirmed with the results obtained from the hydrogeochemistry techniques:• by observed high concentration of CFC-12 conc

• by estimating the R of C-14 activity

30

b)

• The correlations by the modeling looks more clearly than the chemical parameter (CFC-12 conc) • The CMHI area has the largest total mixing ratio with the highest coefficient of correlation

Discussion 2 - Hydrogeochemical vs Numerical modeling

31

1. The groundwater flow dynamic due to excessive pumping:• The observed of CFC-12 concentration• The rejuvenation ratio (R) of C-14• A ‘vertical downward flux’ in depression area

2. The correlation:• A positive correlation among total mixing ratios and modeled vertical flux, • no correlation with CFC-12 concentration

3. The largest drawdown area: • the highest magnitude of CFC-12, R, vertical fluxes and total mixing ratio

4. The approaching methods:• A hydrogeochemical method (CFC-12) is a good tracer to identify the rejuvenation

processes, • The modeling is an effective tool to calculate the rejuvenation process

32

Conclusion

1. to reveal the controlling factors of nitrate contamination

2. to identify the main driving mechanisms of nitrate contamination

3. to test whether nitrate can be a mixing tracer as well as a contaminant tracer

OBJECTIVES 2

33

Groundwater Nitrate Contamination

34

Groundwater mappingInsitu test

Hydrogeochemistry Nitrate isotopes

Nitrate mixing ratio

Controlling factor of Nitrate contamination

SURVEY ANDSAMPLING

Driving factors of Nitrate contamination

Literature review

Laboratory test

LABORATORY ANALYSIS

CFC age tracer

Socio-economic data

PCA analysis

ANALYSIS AND DISCUSSION #1


Conclusion


1. The controlling factor of nitrate contamination

35

1. paddy fields 33.11%2. urban areas 28.34% 3. plantations 16.16% 4. forests 12.36%

5. reservoirs and rivers 10.02%

(Bakosurtanal, 2009) 36

LAND USE

• The stable isotope ratio of nitrogen and oxygen in nitrate

• A powerful tracer revealing concealed contaminant sources

Kendall (1998) and Singleton et al (2007)

NITRATE ISOTOPES

37

• Nitrate in shallow groundwater >> nitrate in deep groundwater

RESULT: DISTRIBUTION MAP OF NITRATE CONCENTRATION

38

(b)

Statistically significant differences between the nitrate and ammonium concentrations

NO3− were significantly higher than NH4

+

Category Observed

differences Significant

level Annotation

Shallow groundwater

plantation [NO3-] > [NH4

+] P > 0.05 Non Significant

urban area [NO3-] > [NH4

+] P < 0.05 Significant

paddy Field [NO3-] > [NH4


Deep groundwater

natural [NO3-] > [NH4


contaminated [NO3-] > [NH4


1

39

•DETERMINING THE POSSIBLESOURCES• plantations: fertilizer

• urban areas: septic waste

• paddy fields: fertilizer

Kendall. 1998 and Singleton et al, 2007

THE CONTROLING FACTORS: SHALLOW GROUNDWATER

40

• DETERMINING THE POSSIBLE SOURCES• Contaminated deep groundwater : septic waste

• Natural deep groundwater: fertilizer, denitrification

THE CONTROLING FACTORS: DEEP GROUNDWATER

41Kendall. 1998 and Singleton et al, 2007

Zone A: Plantation areaZone C: Urban and industria l area Zone B: urban area

cc'

DHYK area

-200-100

0100200300400500

OR

P (

mV

)

0

2

4

6

8

10

DO

0

2

4

6

8

10

NO

3 (m

g/l)

0 5 10 15 20 25 30

0 5 10 15 20 25 30Shallow groundwater Deep groundwater

0

10

20

30

40

50

δ1

5N

(0/ 0

0)

-10

0

10

20

30

40

50

δ1

5O

(0/ 0

0)

Denitrification

MixingDilution

• Zone A:• Decrease slightly along the flow direction

• Dilution

• Zone B:• Denitrification

• Zone C• Groundwater mixing

NITRATE IN GROUNDWATER FLOW SYSTEM

42

1. The nitrate concentrations:•Some of shallow groundwater exceed theIndonesia standard limit

2. Source of nitrate in groundwater:•Anthropogenic activities

1. Septic waste2. Chemical fertilizer

CONCLUSION #1

43

3. The groundwater starts:• contaminated in the recharge area• attenuated along the flow, then• enters to an unconfined and to a confinedaquifer.

4. There is a vertical nitrate flux from theshallow to deep groundwater

CONCLUSION #1

44

2. The driving mechanism of nitrate contamination

45

YOUNG AGE TRACER

• Chlorofluorocarbon (CFCs) and air-mixing ratios (Busenberg and Plummer, 1992; Plummer et al., 2000; 2001; USGS, 2010). 46

The shallow groundwater: high CFC-12

concentration

The deep groundwater: some points in the cone of depression area

have high CFC-12 concentration.

RESULT: DISTRIBUTION MAP OF CFC-12 CONCENTRATION

CFC-12 concentration concentration (pptv) >> residence time (year)

Nitrate

NO3-

pptvresidence time

(year)mg/l

1 249 1976 5.04

2 437 1987.5 5.04

3 230 1975 12.09

4 769 Contam. 2.28

5 579 Contam. 9.97

6 327.29 1981 3.87

7 502 1991 3.99

9 768 Contam. 10.43

9 767.92 Contam. 10.43

10 646.69 Contam. 1.67

11 192.67 1973.5 9.02

12 12 1952.5 0.97

13 40 1961 4.78

13 40 1961 4.78

16 85 1966.5 5.75

18 1132.00 Contam. 3.87

19 250.33 1976 3.33

20 21 1956 1.08

23 56 1963.5 1.65

24 12 1952.5 1.97

26 1.06

27 595 Contam. 3.95

28

28 1.30

29 7.62

30 20.69

31 164 1972 4.00

31 1276.19 Contam. 3.00

11a 646.69 Contam. 9.02

15d 692.75 Contam. #REF!

21a 58 1963.5 1.25

30a 21 1956 1.08

6a 9.06 1951 1.42

a 346 1982 4.08

a1 346 1982 1.67

b 149 1970 5.99

c 225.50 1975 2.13

c1 368.64 1983.5 4.29

d 676.16 Contam. 2.63

d1 368.64 Contam. 3.99

e 179.25 1972.5 0.36

f 365.73 1983 3.09

g 540.85 1998.5 5.64

b) Deep groundwater

Nitrate and Nitrate isotopes

NO3-

pptvresidence time

(year)mg/l

10 405.2 1985.5 1.3

1 0.0 1.6

1 0.0 3.0

2 321.6 1980.5 1.1

3 129.5 1970 1.1

4 243.0 1975.5 1.1

5 314.7 1980 1.9

6 292.7 1979 3.2

7 143.1 1970.5 4.1

8 0.0 4.0

9 0.0 1.4

11 0.0 2.0

12 2.8

12 2.8

13 0.0 3.8

15 255.3 1976.5 0.2

17 46.0 1962 2.6

18 0.0 0.2

19 156.8 1971.5 0.3

20 48.3 1962.5 2.0

21 100.3 1967.5 2.1

22 302.1 1979 4.0

23

24 11.7 1952.5 0.5

25 238.4 1975.5 0.5

27 0.0 0.1

28 0.0 6.6

29 285.1 1978 1.1

30 269.5 7.4

31 363.8 1.1

32 98.2 7.8

33 39.1 1960.5 0.1

34 0.0 0.4

40 17.7 5.7

41 0.0 2.4

42 130.5 1970 2.4

43 0.0 6.6

44 300.6 1979 1.1

45 0.0 1.7

46 0.0 0.3

47 23.2 1957 0.4

11a 224.0 1974.5 0.6

12a 3.0

12d 0.0 3.0

12d 0.0 3.0

12f 0.0 3.0

12f 0.0 3.0

15a 116.6 1969 2.6

18a 27.9 1958 0.2

19b

19c 68.1 1965 0.3

20a 38.6 1960.5 0.6

22a 120.7 1969 2.0

24b 105.7 1968 0.2

28a 0.0 5.7

29a 1.3

2a 0.0 0.2

30a 0.0 0.9

31a 225.0 2.4

33a 234.8 1975.5 0.4

39b 0.0 2.5

4a 0.0 1.1

5a 0.0 3.0

6a 80.0 1966 0.2

6b 117.9 1969 1.2

6c 186.3 1973 1.2

7a 86.7 1966.5 3.6

7b 126.6 1969.5 3.6

7c 169.2 1972 5.3

Sampling No

(Sx)

CFC-12

Sampling No

(Sx)

CFC-12

0

3

6

9

12

15

0 50 100 150 200 250 300 350 400 450 500 550

NO

3co

nce

ntr

atio

n (

mg/

L)

CFC-12 concentration (pptv)

0

3

6

9

12

15

1940 1950 1960 1970 1980 1990 2000 2010

NO

3co

nce

ntr

atio

n (

mg/

L)

Year

48

PCA (Principle Component Analysis)

•PCA :• a dimension-reduction

tool that can be used to reduce a large set of variables to a small set that still contains most of the information in the large set.

• Loading factor and Eigen value

49

•Socioeconomic data for the basin for the period ofgroundwater young age (1950–2015) were compiled

•The data were taken from Book of West JavaProvince in Figure (BPS) such as:• permanent population (PP),

• population density (PD),

• monthly gross domestic product (GDP),

• industrial growth value (IG),

• built-up urban area (BUA),

• green area (GA), and

• chemical fertilizer use (CF).

PCA (Principle Component Analysis)

50

Socio economic parameter(Source: BPS)

• Permanent Population (PP),• Population Density (PD),• Monthly Gross Domestic

Product (GDP),• Industrial Growth (IG),• Built-up Urban area (BUA),• Green area (GA), and• Chemical Fertilizer Use (CF).

NO3-

PD PP GDP IG BUA GA CF

mg/l people/km2 people IDR number ha ha ton

1953 0.97 11,544 2,770,001 5,177 9 64,054 144,010 1,890

1956 1.08 12,255 3,010,999 8,829 19 64,957 143,559 1,984

1961 4.78 14,485 3,476,410 12,481 42 65,659 143,108 2,050

1964 1.25 15,367 3,688,156 17,891 61 65,921 142,837 2,074

1967 5.75 16,250 3,890,000 23,302 79 66,201 142,566 2,075

1970 5.99 17,426 4,182,230 30,516 98 66,765 142,205 2,084

1972 4.00 17,716 4,251,867 38,188 114 66,966 142,055 2,001

1974 9.02 18,006 4,321,504 45,861 131 67,167 141,905 2,800

1975 12.09 18,151 4,356,000 49,697 139 67,167 141,829 2,900

1976 5.04 18,896 4,535,141 53,533 147 67,368 141,754 3,100

1982 1.67 20,367 4,800,050 76,550 204 67,971 141,303 4,253

1991 3.99 23,308 5,593,872 201,552 288 68,876 140,401 5,185

NO3-

PD PP GDP IG BUA GA CF

mg/l people/km2 people IDR number ha ha ton

1953 0.54 11,544 2,770,001 5,177 9 64,054 144,010 1,890

1957 0.35 13,015 3,123,000 8,829 23 64,957 143,559 2,010

1958 0.15 13,382 3,200,001 9,742 27 65,107 143,446 2,030

1961 0.62 14,485 3,476,410 12,481 42 65,559 143,108 2,050

1962 2.58 14,779 3,546,992 14,284 48 65,680 143,017 2,057

1963 2.03 15,073 3,617,574 16,088 54 65,800 142,927 2,060

1965 0.34 15,661 3,700,001 19,695 67 66,042 142,747 2,075

1966 0.17 15,956 3,760,010 21,498 73 66,162 142,656 2,073

1967 3.63 16,250 3,890,000 23,302 79 66,201 142,566 2,075

1968 2.09 16,642 3,994,012 25,707 86 66,443 142,446 2,078

1969 1.21 17,034 4,088,121 28,111 92 66,604 142,326 2,066

1970 3.63 17,426 4,182,230 30,516 98 66,765 142,205 2,084

1971 4.07 17,671 4,248,881 34,352 106 66,865 142,130 2,092

1972 0.26 17,716 4,251,867 38,188 114 66,966 142,055 2,106

1973 1.20 18,161 4,358,686 42,024 123 67,066 141,980 2,114

1975 0.56 18,151 4,359,500 49,697 139 67,267 141,829 2,439

1976 1.07 18,896 4,535,141 53,533 147 67,368 141,754 3,100

1977 0.20 19,141 4,590,000 57,369 155 67,468 141,679 2,922

1978 1.13 19,387 4,652,778 61,205 163 67,569 141,604 3,653

1979 3.16 19,632 4,750,596 65,041 172 67,669 141,529 4,085

1980 1.89 19,877 4,770,414 68,877 180 67,770 141,453

1981 1.05 20,122 4,829,233 72,714 192 67,870 141,378

1986 1.31 21,347 5,100,005 91,894 252 68,372 141,002

a) Shallow groundwater

residence

time (year)

b) Deep groundwater

residence

time (year)

51

PCA analysis

Relationships between nitrate concentration for the shallow and contaminated deep groundwater with permanent population (PP), population density (PD), monthly gross domestic product (GDP), industrial growth (IG), built-up urban area (BUA), green area (GA) and chemical fertilizer use (CF)

y = 0.0002x + 0.7869R² = 0.1534, P < 0.01

y = 1E-04x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

5000 10000 15000 20000 25000

NO

3co

nce

ntr

ati

on

(mg/

L)

PD (people/km2)

y = -0.0012x + 180.14R² = 0.132, P < 0.01

y = -0.0003x + 44.559R² = 0.0367, P < 0.01

0

3

6

9

12

15

140,000 140,500 141,000 141,500 142,000 142,500 143,000 143,500 144,000 144,500

NO

3co

nce

ntr

ati

on

(mg/

L)

GA (ha)

y = 0.001x - 59.282R² = 0.1409, P < 0.01

y = 0.0002x - 12.998R² = 0.0357, P < 0.01

0

3

6

9

12

15

63,000 64,000 65,000 66,000 67,000 68,000 69,000 70,000

NO

3co

nce

ntr

ati

on

(mg/

L)

BUA (ha)

y = 5E-06x + 4.3783R² = 0.0074, P < 0.01

y = 4E-06x + 1.3056R² = 0.0054, P < 0.01

0

3

6

9

12

15

0 50,000 100,000 150,000 200,000 250,000

NO

3co

nce

ntr

ati

on

(mg/

L)

GDP (IDR)

y = 0.0002x + 4.1122R² = 0.0036, P < 0.01

y = 0.0002x + 0.9477R² = 0.0096, P < 0.01

0

3

6

9

12

15

1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500

NO

3co

nce

ntr

ati

on

(mg/

L)

CF (ton)Shallow groundwater Deep groundwater

Linear (Shallow groundwater) Linear (Deep groundwater)

y = 0.0104x + 3.4804R² = 0.0605, P < 0.01

y = 0.0023x + 1.2025R² = 0.0132, P < 0.01

0

3

6

9

12

15

0 50 100 150 200 250 300

NO

3co

nce

ntr

ati

on

(mg/

L)

IG (number)

y = 1E-06x - 1.1897R² = 0.1124, P <0.01

y = 4E-07x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

2,000,000.00 4,000,000.00 6,000,000.00

NO

3co

nce

ntr

ati

on

(mg/

L)

PP (people)

y = 0.0002x + 0.7869R² = 0.1534, P < 0.01

y = 1E-04x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

5000 10000 15000 20000 25000

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

PD (people/km2)

y = -0.0012x + 180.14R² = 0.132, P < 0.01

y = -0.0003x + 44.559R² = 0.0367, P < 0.01

0

3

6

9

12

15

140,000 140,500 141,000 141,500 142,000 142,500 143,000 143,500 144,000 144,500

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

GA (ha)

y = 0.001x - 59.282R² = 0.1409, P < 0.01

y = 0.0002x - 12.998R² = 0.0357, P < 0.01

0

3

6

9

12

15

63,000 64,000 65,000 66,000 67,000 68,000 69,000 70,000

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

BUA (ha)

y = 5E-06x + 4.3783R² = 0.0074, P < 0.01

y = 4E-06x + 1.3056R² = 0.0054, P < 0.01

0

3

6

9

12

15

0 50,000 100,000 150,000 200,000 250,000

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

GDP (IDR)

y = 0.0002x + 4.1122R² = 0.0036, P < 0.01

y = 0.0002x + 0.9477R² = 0.0096, P < 0.01

0

3

6

9

12

15

1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500

NO

3c

on

ce

ntr

ati

on

(m

g/L

)



y = 0.0104x + 3.4804R² = 0.0605, P < 0.01

y = 0.0023x + 1.2025R² = 0.0132, P < 0.01

0

3

6

9

12

15

0 50 100 150 200 250 300

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

IG (number)

y = 1E-06x - 1.1897R² = 0.1124, P <0.01

y = 4E-07x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

2,000,000.00 4,000,000.00 6,000,000.00

NO

3c

on

ce

ntr

ati

on

(m

g/L

)

PP (people)

y = 0.0002x + 0.7869R² = 0.1534, P < 0.01

y = 1E-04x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

5000 10000 15000 20000 25000

NO

3co

nce

ntr

ati

on

(mg/

L)

PD (people/km2)

y = -0.0012x + 180.14R² = 0.132, P < 0.01

y = -0.0003x + 44.559R² = 0.0367, P < 0.01

0

3

6

9

12

15

140,000 140,500 141,000 141,500 142,000 142,500 143,000 143,500 144,000 144,500

NO

3co

nce

ntr

ati

on

(mg/

L)

GA (ha)

y = 0.001x - 59.282R² = 0.1409, P < 0.01

y = 0.0002x - 12.998R² = 0.0357, P < 0.01

0

3

6

9

12

15

63,000 64,000 65,000 66,000 67,000 68,000 69,000 70,000

NO

3co

nce

ntr

ati

on

(mg/

L)

BUA (ha)

y = 5E-06x + 4.3783R² = 0.0074, P < 0.01

y = 4E-06x + 1.3056R² = 0.0054, P < 0.01

0

3

6

9

12

15

0 50,000 100,000 150,000 200,000 250,000

NO

3co

nce

ntr

ati

on

(mg/

L)

GDP (IDR)

y = 0.0002x + 4.1122

R² = 0.0036, P < 0.01

y = 0.0002x + 0.9477

R² = 0.0096, P < 0.01

0

3

6

9

12

15

1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500

NO

3co

nce

ntr

ati

on

(mg/

L)



y = 0.0104x + 3.4804R² = 0.0605, P < 0.01

y = 0.0023x + 1.2025R² = 0.0132, P < 0.01

0

3

6

9

12

15

0 50 100 150 200 250 300

NO

3co

nce

ntr

ati

on

(mg/

L)

IG (number)

y = 1E-06x - 1.1897R² = 0.1124, P <0.01

y = 4E-07x - 0.2389R² = 0.0411, P < 0.01

0

3

6

9

12

15

2,000,000.00 4,000,000.00 6,000,000.00

NO

3co

nce

ntr

ati

on

(mg/

L)

PP (people)

52

a) Shallow Groundwater

Parameter Principal components

PC1 PC2

PP 0.857 0.113

PD 0.834 0.116

GDP 0.898 -0.223

IG 0.980 -0.047

BUA 0.974 0.090

GA -0.987 -0.078

CF 0.304 0.838

eigenvalue 5.615 1.521

%total variance 70.191 19.008

Cumulative % 70.191 89.199

b) Deep Groundwater (contaminated)


PC1 PC2

PP 0.966 0.240

PD 0.965 0.240

GDP 0.986 0.033

IG 0.991 0.089

BUA 0.962 0.237

GA -0.967 -0.235

CF 0.234 0.714



Cumulative % 75.384 89.568

1



PC1 PC2

PP 0.857 0.113

PD 0.834 0.116

GDP 0.898 -0.223

IG 0.980 -0.047

BUA 0.974 0.090

GA -0.987 -0.078

CF 0.304 0.838



Cumulative % 70.191 89.199



PC1 PC2

PP 0.966 0.240

PD 0.965 0.240

GDP 0.986 0.033

IG 0.991 0.089

BUA 0.962 0.237

GA -0.967 -0.235

CF 0.234 0.714



Cumulative % 75.384 89.568

1

PCA analysis

53

•PC1 :The IG, GDP, PD, PP, BUA and GA had very strong loading indices, indicating that primary industrial and population growth was a primary driving force.



PC1 PC2

PP 0.857 0.113

PD 0.834 0.116

GDP 0.898 -0.223

IG 0.980 -0.047

BUA 0.974 0.090

GA -0.987 -0.078

CF 0.304 0.838



Cumulative % 70.191 89.199



PC1 PC2

PP 0.966 0.240

PD 0.965 0.240

GDP 0.986 0.033

IG 0.991 0.089

BUA 0.962 0.237

GA -0.967 -0.235

CF 0.234 0.714



Cumulative % 75.384 89.568

1

•PC2 indicated that fertilizer use is the secondary driving force



PC1 PC2

PP 0.857 0.113

PD 0.834 0.116

GDP 0.898 -0.223

IG 0.980 -0.047

BUA 0.974 0.090

GA -0.987 -0.078

CF 0.304 0.838



Cumulative % 70.191 89.199



PC1 PC2

PP 0.966 0.240

PD 0.965 0.240

GDP 0.986 0.033

IG 0.991 0.089

BUA 0.962 0.237

GA -0.967 -0.235

CF 0.234 0.714



Cumulative % 75.384 89.568

1

54

•The period of groundwater residence time is 1950 - 2000

•PCA results:•The primary: industrial and population growth•The secondary: chemical fertilizer use

•The results indicate that nitrate in groundwater is a good indicator the growth of study area.

CONCLUSION #2

55

•The period of groundwater residence time is 1950 - 2000

•PCA results:•The primary: industrial and population growth•The secondary: chemical fertilizer use

•The results indicate that nitrate in groundwater is a good indicator the growth of study area.

CONCLUSION #2

56

LIST OF PUBLICATIONS

• Refereed Articles

• Taufiq, A., Hosono, T., Ide, K., Kagabu, M., Iskandar, I., Effendi, A. J., Hutasoit, L. M., Shimada, J (2017).Impact of Excessive Groundwater Pumping on Rejuvenation processes in the Bandung Basin(Indonesia) as Determined by Hydrogeochemistry and Modeling. Hydrogeology Journal. Onlinepublished on December 14, 2017. DOI: 10.1007/s10040-017-1696-8

• Taufiq, A., Hosono, T., Iskandar, I., Effendi, A. J., Hutasoit, L. M (2017). Estimating Groundwater MixingRatios Using Hydrogeochemistry Parameters and Nitrate Concentration due to Excessive GroundwaterPumping in the Bandung Basin, Indonesia. Geologia Croatica Journal. ID. 816. Status: Under reviewingprocess on 22/11/2017

• Taufiq, A., Effendi, A. J., Iskandar, I., Hosono, T., Hutasoit, L. M (2018). Factors Controlling andMechanisms Driving Nitrate Contamination in Groundwater of Bandung Basin (Indonesia), A RapidlyDeveloping Region“. Under reviewing process on Water Research Journal. Number: WR42611. Underreviewing process on 06/05/2018

• Conference Submission

• Taufiq, A., Hosono, T., Iskandar, I., Effendi, A. J., Hutasoit, L. M (2017). Estimating Groundwater MixingRatios Using Hydrogeochemistry Parameters and Nitrate Concentration due to Excessive GroundwaterPumping in the Bandung Basin, Indonesia. 44th International Association of Hydrogeologists (IAH)’sAnnual Congress, 2017

• Taufiq, A., Hosono, T., Iskandar, I., Effendi, A. J., Hutasoit, L. M (2018). Subsurface EnvironmentalProblems Due To A Rapid Industrialization and Population Growth In Bandung Basin, Indonesia. 45th

International Association of Hydrogeologists (IAH)’s Annual Congress, 2018 (submitted) 57

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HYDROGEOLOGY OF BANDUNG BASIN: MODELING, … · (b) THE CONCEPT 1: Change in groundwater flow...

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