Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan

Environ Monit Assess (2011) 173:447–457DOI 10.1007/s10661-010-1398-3

Composite use of numerical groundwater flow modelingand geoinformatics techniques for monitoring Indus Basinaquifer, Pakistan

Zulfiqar Ahmad · Arshad Ashraf · Alan Fryar ·Gulraiz Akhter

Received: 14 June 2009 / Accepted: 11 February 2010 / Published online: 7 March 2010© Springer Science+Business Media B.V. 2010

Abstract The integration of the Geographic In-formation System (GIS) with groundwater mod-eling and satellite remote sensing capabilitieshas provided an efficient way of analyzing andmonitoring groundwater behavior and its associ-ated land conditions. A 3-dimensional finite ele-ment model (Feflow) has been used for regionalgroundwater flow modeling of Upper Chaj Doabin Indus Basin, Pakistan. The approach of usingGIS techniques that partially fulfill the data re-quirements and define the parameters of existinghydrologic models was adopted. The numericalgroundwater flow model is developed to configurethe groundwater equipotential surface, hydraulichead gradient, and estimation of the groundwaterbudget of the aquifer. GIS is used for spatial

Z. Ahmad (B) · G. AkhterDepartment of Earth Sciences, Quaid-i-AzamUniversity, Islamabad, Pakistane-mail: [email protected]

G. Akhtere-mail: [email protected]

A. AshrafWater Resources Research Institute, NationalAgricultural Research Center, Islamabad, Pakistane-mail: [email protected]

A. FryarDepartment of Earth and Environmental Sciences,University of Kentucky, Kentucky, USAe-mail: [email protected]

database development, integration with a remotesensing, and numerical groundwater flow model-ing capabilities. The thematic layers of soils, landuse, hydrology, infrastructure, and climate weredeveloped using GIS. The Arcview GIS softwareis used as additive tool to develop supportivedata for numerical groundwater flow model-ing and integration and presentation of imageprocessing and modeling results. The groundwa-ter flow model was calibrated to simulate futurechanges in piezometric heads from the period2006 to 2020. Different scenarios were developedto study the impact of extreme climatic condi-tions (drought/flood) and variable groundwaterabstraction on the regional groundwater system.The model results indicated a significant responsein watertable due to external influential factors.The developed model provides an effective toolfor evaluating better management options formonitoring future groundwater development inthe study area.

Keywords Finite element modeling ·Groundwater system · Chaj Doab ·Remote sensing · GIS · Indus Basin

Introduction

Three-dimensional numerical groundwater flowmodeling, using finite element flow model Feflow

448 Environ Monit Assess (2011) 173:447–457

ver. 5.1 (WASY 2004) coupled with decision sup-port tools of geoinformatics, was used for analyz-ing the behavior of regional groundwater flow ofUpper Chaj Doab area in the Indus Basin. TheGeographic Information System (GIS) is usedfor spatial database development and integrationwith remote sensing (RS) and numerical ground-water flow modeling capabilities to simulate re-gional groundwater flow behavior. GIS facilitatesrapid transfer and assembly of various input datasets for groundwater modeling and is found ex-tremely helpful during the process of model cal-ibration and forecasting. The RS image capabilitywas used to analyze surface hydrological condi-tions and land cover/land use status in order toconceptualize the recharge/discharge sources ofaquifer (Ashraf and Ahmad 2008). It providesan economic and efficient tool for land covermapping and has its advantages in planning andmanagement of water resources for optimum use.

In the Indus Basin of Pakistan, irrigation sup-plies are mainly fulfilled through conjunctive useof surface and groundwater resources. Groundwa-ter is mainly utilized to supplement canal watersupplies where these are not adequately met, es-pecially when river discharges are at their lowest.In the last drought of 1999–2002, the ground-water abstractions have increased manifolds dueto rapid increase in the number of private tubewells for irrigation purposes. Excessive pumpageof groundwater from these wells is causing a grad-ual decline in watertable. Moreover, the devel-opment of irrigation potential with canals alsohas a negative environmental impact. In the lowrelief area of central Doab, seepage from con-veyance system and excessive irrigation in fieldshas disturbed the preexisting natural groundwa-ter balance, especially at locations where naturaldrainage is inadequate due to topographic fea-tures and retardation of soils. Accumulation ofwater causes problems of waterlogging and salin-ity which threaten the livelihood of farmers in theIndus Basin (Bhutta and Wolters 1996). There is aneed to utilize the techniques of GIS coupled withhydrological modeling to investigate environmen-tal problems related to excessive groundwater useand irrigation water supplies in the Indus Basin.The present work considers the impact of extremeclimate events, like the drought that occurred dur-

ing 1999–2002, on the groundwater developmentof Upper Chaj Doab area.

Conceptual framework of GIS–groundwatermodeling

Integration of GIS with groundwater model-ing and remote sensing capabilities provide aneffective way of analyzing and monitoring tempo-ral changes in groundwater and its associated en-vironment. Efficient management of groundwaterresource relies on a comprehensive database thatrepresents the characteristics of natural ground-water system (Josef 2004). The GIS technologyprovides suitable alternatives for handling largeand complex databases (Saraf and Choudhury1997). Arora and Goyal (2003) highlighted theuse of GIS in the development of conceptualgroundwater model. The effort to perform analy-sis of management scenarios will be substantiallyreduced by an easily accessible database, a conve-nient interface between database and groundwa-ter models, visualization, and utilities for modelinputs and results (Pillmann and Jaeschke 1990).In recent times, integration of GIS and hydro-logic models follows one of the two approaches:(a) to develop hydrologic models that operatewithin a GIS framework and (b) to develop GIStechniques that partially define the parameters ofexisting hydrologic models (Jain et al. 1997). Thelatter approach has been followed in the presentstudy.

Feflow is a fully integrated modeling environ-ment with a full-featured graphical interface andpowerful numeric engines that allow the userto perform any flow and contaminant transportmodeling (WASY 2004). The components ensurean efficient process for building the finite ele-ment model using functions and input data ofGIS for running the simulation and visualizing theresults.

Study area

Upper Chaj Doab area lies within a fertile agri-culture belt of Punjab plains, between longitudes73◦ and 74◦5′ E and latitudes 32◦ and 32◦45′ N inthe northeastern territory of Pakistan (Fig. 1). Thearea is bounded by Jhelum and Chenab Rivers in

Environ Monit Assess (2011) 173:447–457 449

Fig. 1 Location of thestudy area

the northwest and southeast and Upper Jhelumcanal and Lower Jhelum canal in the northeastand southwest, respectively. The canal system inthe area is mainly fed by water supplies of theJhelum River. The major portion of the river flowsis contributed by monsoon rainfalls and a minorportion by snow and glaciers melt water flowingdown from high mountains of the Himalayasin the north. Administratively, the area comprisesof Mandi Bahauddin and part of Gujrat dis-trict, which are subdivided into tehsils. The maintopographic features are submountainous ravines,piedmont plain in the northeast, and alluvial plainand bar-uplands in the rest of the area. Elevationin the area ranges between 200 and 238 masl.The groundwater flows in general from the north-east to southwest direction with hydraulic gradientranging from 0.4 to 1.35 m/km (PPSGDP Report2000). The drainage pattern is mainly dendritic innature.

The Chaj Doab is a part of a vast geosyn-cline lying between the Himalayan Mountainsand the central core of the Indian subcontinentwhere Quaternary alluvium has been depositedon semiconsolidated Tertiary rocks (Soil SurveyReport 1967). Test drilling has revealed that theuppermost 183 m of the alluvium consists pre-dominantly of fine to medium sand and silt. Al-luvium was encountered in test holes drilled to amaximum depth of about 457 m (1,500 ft); hence,

no information is available concerning the totalthickness of alluvium and the depth to basementcomplex in the Chaj Doab area (Kidwai 1962).The land use is predominantly irrigated agricul-ture. Most of the natural vegetation has beencleared off from the plains for agriculture farming.Uncontrolled grazing and cutting of wood havemuch damaged the density of the vegetation.

The climate is mainly subhumid in the north tosemiarid in the south. Rainfalls are erratic and arereceived in two rainy seasons; about two thirdsof annual rains are received during the monsoonseason (July to mid-September) and the remain-ing one third in the winter season (January toMarch). The mean annual rainfall is 778 mm.The mean maximum and minimum temperaturesduring summer are about 39.5◦C and 25.4◦C, re-spectively. The temperature may rise up to 47◦Cduring the month of June in summer. The meanmaximum and minimum temperatures in winterare about 21.5◦C and 5.1◦C, respectively (Qureshiet al. 2003).

Aquifer characteristics

Aquifer data of ten pump-out tests performedby the Water and Soil Investigation Division(WASID 1964) showed horizontal hydraulicconductivity values in the range of 39.6 to118.6 m/day. The transmissivity (T) values eval-


uated through pumping tests ranged between1,565.2 and 4,045.6 m2/day. The aquifer is dividedinto three layers on the basis of subsurface lithol-ogy encountered in the boreholes and pumpagedepth of different tube wells (local term usedas alternative to water well). The first layer isunconfined with free and movable surface. Sedi-ments occurring at shallow depths are composedof finer materials, i.e., silt and fine sand. Thislayer has been assumed to extend 8 m belowthe average watertable. The second layer is as-sumed to extend from 8 to 40 m depth (thick-ness 32 m) to represent groundwater withdrawalsfrom comparatively shallow tube wells. The thirdlayer extends from 40 to 107 m depth (thickness67 m) to account for abstractions from deep tubewells. The thickness of these layers is assumedconstant during the process of groundwater flowmodeling.

Aquifer recharge occurs mainly from canalseepage, rainfall, return flow of groundwaterpumpage, and percolation from drains and ponds.Discharge sources of the aquifer are: pumpagefrom shallow and deep tube wells, evapotranspi-ration (ET), outflows to the rivers and drains,and subsurface flows from one zone to another.The loss of water by ET has been adjusted inthe groundwater flow model while estimating thenet recharge of the groundwater. The availablerecharge data were used to define recharge ofdifferent stress periods in model calibration. Therecharge from large boundary link canals andinflows from adjacent areas are considered im-plicitly in the groundwater modeling by assum-ing constant head boundaries along these canals(Sarwar 1999). Some of the related studies havebeen carried out by Ahmad and Khawaja (1999),Ahmad and Serrano (2001), Ahmad et al. (1997a,b, 2009), and Ghulam and Ahmad (2007).

Material and methods

GIS database development

The base map of the study area was developedusing topography map of scale 1:250,000 acquiredfrom the Survey of Pakistan. The remote sens-

ing data of Landsat TM and Enhanced ThematicMapper (ETM) plus of periods 1990 and 2001were used for land cover/land use analysis. Thespatial resolution of the image data is 30 m exceptthe addition of an extra panchromatic band of15 m resolution in the Landsat ETM data. Thespatial data input in GIS was carried out throughscanning, digitization, and keyboard entry. Acommon coordinate system of Transverse Merca-tor was used for the development of spatial datalayers like geomorphology, soils, infrastructure,surface hydrology, cities/towns, and administra-tive boundaries in the Arcview 3.1 GIS software.Analytical functions of GIS were used to de-rive thematic map layers of elevation, slope, andbuffer zones. Theissen polygons of the rechargezones were developed for model calibration, whilewatertable depth and equipotential maps weregenerated during the postcalibration phase ofthe groundwater flow modeling. Remote sens-ing analysis was carried out through visual anddigital interpretation of the imageries to studyland cover and surface hydrological conditionslike waterlogging associated with canal network,swamps, surface moisture, etc. Such natural indi-cators were found helpful in identifying potentialrecharge sources of groundwater besides shallowgroundwater environment in the area. The imageclassification was carried out through supervisedmethod following the maximum likelihood rule inthe ERDAS imagine 8.5 software (ERDAS 2001).Six land cover classes were demarcated throughimage classification. Major land covers consist ofcrop cover (70%), soil (10.2%), grassland (8.4%),and forest (5.6%). The wastelands, which includeswamps and waterlogged areas, cover about 4%of the area, mainly in the meander flood plainof Mandi Bahauddin district. The canal irrigatedland, which can be distinguished by homogenouscrop cover in the northwestern part, forms a po-tential zone of groundwater recharge comparedwith rainfed agriculture land visible as heteroge-neous crop cover in the northeast. A low poten-tial area of groundwater recharge also exists indepressions in the central parts where drainageis poor and swamps are developed as permanentfeatures. Figure 2 shows the general methodologyfollowed in the present composite study.


Fig. 2 Flow diagram ofmethodology used in thestudy

Numerical groundwater flow modeling

A model grid consisting of five superelementmesh was drawn over the model area using thebase information of land use, landforms, anddrainage/canal network of the area. The superele-ment mesh represents the basic structure of thestudy domain. The finite element mesh was gen-erated from the superelement mesh using triangu-lation option of 6-noded prism for 3-dimensional(3-D) model. The 3-D mesh consists of a total of5,343 elements and 3,928 nodes. The model layerswere developed from point data using Akima’sbivariate interpolation method.

In order to estimate the net recharge of modeldomain, the model area was divided into fivezones or subareas (Fig. 3). The recharge zoneswere based on the hydrological setup of the area,geomorphologic characteristics, and land capabil-ity for agriculture use. The recharge of five zones

Fig. 3 Recharge zones along with locations of observationwells


was characterized by variable infiltration ratesassociated with different soil types and varyinggroundwater pumpage rates in the study area.

Model calibration

In the first phase, steady-state calibration was per-formed which was fully implicit. The groundwaterlevels of June 1985 (premonsoon period) of 28observation wells were used as initial condition.Automatic parameter estimation method was ap-plied for the calibration of the steady-state model(Doherty 1995). The previous values of hydraulicconductivities were used to develop conductivityzones using Theissen polygons for model cali-bration. The hydraulic conductivity and rechargevalues estimated previously were used as initialconditions in the steady-state calibration. The val-ues were adjusted during calibration runs until thecalculated head values were close to the observedheads. Similarly, specific yield zones were devel-oped using field data in transient-state calibration.The model was rerun for a 6-month period, i.e.,April–September 1985, for transient-state calibra-tion. The scattergram plots of steady-state andtransient-state calibration outputs are shown inFig. 4. The mean residuals of observed and cal-culated heads in steady-state and transient-statecalibrations are 0.06 and 0.002 m with variancesof 1.46 and 1.86 m, respectively. The calibrationresults indicated a reasonable agreement betweenthe calculated and observed heads.

The sensitivity of the model results were thenevaluated to variations in hydrologic parametersand modeling assumptions. The sensitivity analy-sis of the steady-state model indicated the sen-

sitivity of the model to any change in hydraulicconductivity. High imbalance in water budget wasobserved against lower and higher conductivityvalues. Similarly, the model was found sensitiveto recharge also. The sensitivity analysis of thetransient-state model indicated model sensitivityto both higher and lower values of the specificyield.

Results and discussion

Prestress and poststress behavior of groundwater

The strategy of management for the prestress pe-riod and poststress period was developed on thebasis of availability of observed data until 2005and projected hypothetical data for the period2006 to 2020. Time series records of previouslyobserved data of precipitation, annual recharge,and withdrawals from tube wells were examined,which formed the basis to generate projecteddata for the simulation of future groundwaterbehavior. The predictive period of 15 years, i.e.,2006–2020, was chosen to perceive the long-termimpact of droughts/floods on regional ground-water system. Based on the annual incrementalincrease/decrease in recharge and/or groundwa-ter pumpage, recharge for various stress periodswas adjusted for calibration of groundwater flowmodel.

The steady-state calibrated model was run forthe prestress period of variable time steps until2005. The average watertable values (the spatialaverage over the whole region) was used to fore-see the overall effect of the watertable in model

Fig. 4 Scatter gram plotof a steady-statecalibration andb transient-statecalibration


domain. During the calibrated period 1985–2005,the watertable had shown a total decline of 0.96 mat the rate of 0.05 m/year. The watertable indi-cated a rising trend from 1988 to 1999 followedby a gradual decline onward. The initial rise maybe attributed to record rainfalls that had oc-curred in Muzaffarabad and Jhelum during period1997–1998 (Siddiqi 1999). Those rainfalls exagger-ated the problem of waterlogging, especially inPhalia tehsil of Mandi Bahauddin district. A ma-jor breakthrough of groundwater depletion wasobserved in the year 1999 when the last droughtprevailed for over 3–4 years in Doab area. Thedeclining trend of groundwater levels continuedin the remaining calibration period. During thedrought period, the shortages in canal water sup-plies resulted in low recharge from canals seepageand overexploitation of groundwater for irrigationuse. The situation had affected the extent of wa-terlogging which was reduced significantly in someparts of the area. The groundwater behavior inthe model domain was studied for base year 2005at tehsil level (Fig. 5). The watertable depth ofrange <1.5 m is seen in distributed patches inMalakwal, Phalia, and part of Kharian tehsils.Quantitative analysis of the groundwater aquiferwas performed using geoprocessing tools of Ar-cview 3.2. Results showed a maximum head dropof about 21 m in Phalia tehsil, while a mini-mum head drop of 14 m was shown in Gujratduring 2005 (Table 1). The head variation in3-D is shown in Fig. 6. Maximum velocity rangeof 0.006–0.09 m/day was observed in MandiBahauddin, while minimum velocity range of

Fig. 5 Variations of watertable depth in different tehsils(base year 2005)

0.003–0.035 m/day was observed in Kharian tehsil.The velocity variation in model domain is shownin Fig. 7. Overall, minor variations in groundwaterlevels were observed in Gujrat compared withMandi Bahauddin district.

The calibrated model was rerun to predict thefuture changes in piezometric heads for the period2006–2020. The predictive model showed an av-erage decline of 0.81 m in the watertable. Duringprestress and poststress periods, variation in headvalues varies between 196 and 234 masl. In theupper reaches of the model domain, fluctuationin heads is low due to the presence of less ex-tensive alluvial deposits in the piedmont plain.The comparison in coverage of watertable depth

Table 1 Variation of groundwater levels and velocities in different tehsils (2005)

District Tehsil Nodes Area (km2) Heads (m) Velocity (m/day)Min Max Mean Min Max Mean

M.B.Din M.B.Din 220 807.8 207.28 226.05 216.06 0.006 0.090 0.027Malakwal 159 658.4 195.70 213.12 207.78 0.000 0.068 0.017Phalia 289 1,159.4 196.17 217.48 209.17 0.013 0.080 0.039

Gujrat Gujrat 75 309.3 216.52 230.73 221.95 0.001 0.038 0.005Kharian 93 328.2 217.09 234.13 225.43 0.003 0.035 0.016

Minimum 75 309.3 195.70 213.12 207.78 0.000 0.035 0.005Maximum 289 1,159.4 217.09 234.13 225.43 0.013 0.090 0.039Mean 206.55 224.30 216.08 0.005 0.062 0.021Total 836 3,263.0


Fig. 6 Equipotential surface in 3-D view (base year 2005)

of base year 2005 and predictive year 2020 indi-cated a noticeable reduction in watertable <1.5 mdepth range from 226.9 km2 in 2005 to 73.8 km2

in 2020 (Table 2). Similarly, the coverage ofdepth range 1.5–3.0 m indicated a decrease from1,299.4 km2 in 2005 to 1,104.8 km2 in year 2020.The variations in watertable depth were mappedon decadal basis to observe the trend of the wa-tertable during prestress and poststress periods

Fig. 7 3-D view of velocity variations in 2005

(Fig. 8). The watertable depth of ranges <1.5 and1.5–3.0 m showed an initial increase in coveragesduring 1990–2000. The changes were significant inthe Malakwal and Phalia tehsils. The watertabledepth <3.0 m indicates a declining trend in cover-age during the period 2000–2020 which may helpin reducing the extent of waterlogging in ChajDoab area. On the other hand, watertable depth>4.5 m is indicating a gradual increase in coverageduring the same period.

Development of future scenarios

The calibrated model was used to predict futurescenarios based on variability of influential factorsand parameters related to groundwater develop-ment in the model area. The impact of the climaticvariability generated by persistent drought/floodconditions during prestress period was used to de-velop the hypothesis for the poststress period. Thebasic idea is to consider rainfall extremes of thedrought/flood events in the area for the develop-ment of future climate scenarios. In the first sce-nario, severe drought condition was assumed toprevail for the 5-year period 2006–2010. The rain-fall data of the severe drought that occurred dur-ing 1999–2002 was used as reference in developingthe scenario. The hypothetical simulation indi-cated a mean decline of 0.7 m in watertable depthfrom that of the base year 2005 (Table 3). In thesecond scenario, extreme wet condition was as-sumed to prevail for a period of 5 years from 2011to 2015. The scenario was based on the referencerainfall data of the wet period 1997–1998 whenintense rainfalls occurred in Jhelum area. It indi-cated a mean decline of 0.42 m in the watertablefrom that of the base year. In order to examine theeffect of groundwater withdrawals on the under-lying aquifer, scenarios of varying pumpage rateswere developed. In the third scenario, pumpagefrom 33 deep tube wells was assumed to con-tinue at a constant rate of 5,000 m3/day for aconsecutive 3-year period 2006–2008. At the endof the discharge period, the watertable exhibiteda mean decline of 1.63 m. In the fourth scenario,an increase of 60% in discharge (8,000 m3/day) ofthe tube wells was assumed to continue for a con-secutive 3-year period (2006–2008). It indicated amean decline of 2.23 m in the watertable at the


Table 2 Change in area coverage (in square kilometers) of different watertable depths during 2005–2020

Tehsil 2005 2020

<1.5 m 1.5–3.0 m 3.0–4.5 m 4.5–6.0 m 6.0–12.0 m <1.5 m 1.5–3.0 m 3.0–4.5 m 4.5–6.0 m 6.0–12.0 m

M.B.Din 0.0 119.3 482.2 206.3 0.0 0.0 25.5 473.8 308.5 0.0Malakwal 60.5 114.4 344.9 128.2 10.4 0.0 39.3 222.8 308.6 87.7Phalia 125.1 781.2 200.6 51.5 1.0 39.7 775.4 262.9 75.8 5.6Gujrat 0.0 223.2 74.0 12.0 0.0 0.0 201.4 93.8 14.0 0.0Kharian 41.3 61.2 98.2 79.2 48.2 34.1 63.2 97.7 81.0 52.0Total 226.9 1,299.4 1,199.8 477.2 59.7 73.8 1,104.8 1,151.0 788.0 145.4

Fig. 8 Variations inwatertable depth(1990–2020)

Table 3 Watertable behavior in different scenarios (WT depth in 2005 = 2.95 m)

Scenario Description Simulation period Net change inwatertable depth (m)

1 Extreme drought prevails for a 5-year period 2006–2010 0.72 Wet condition prevails for a 5-year period 2011–2015 0.423 Pumpage from tube wells continue for a 3-year period 2006–2008 1.634 60% increase in pumpage from tube wells 2006–2008 2.23


end of the discharge period. The high pumpageof the groundwater can be utilized to minimizewaterlogging problem in waterlogged areas.

Conclusion

The results of this composite study show the long-term impact of factors like extreme climate con-ditions and overexploitation of groundwater onregional groundwater system. The high pumpageof groundwater on a long-term basis may result inunsafe decline of watertable though it would beuseful for areas facing the problem of waterlog-ging. GIS facilitates rapid transfer and assembly ofvarious input data sets for groundwater modelingand is found extremely helpful during the processof model calibration and forecasting. The capa-bility of remote sensing technology can be uti-lized to identify potential sources of groundwaterrecharge for model conceptualization. The devel-oped model provides an effective tool for evaluat-ing better management options for the sustainableuse of groundwater and its future monitoring inthe Indus Basin area.

Acknowledgements We thank Prof. Dr. Qasim Jan, ViceChancellor University of Quaid-i-Azam, Islamabad, forthe initial review of this paper and giving useful sugges-tions for its improvement. The data support by Water andPower Development Authority (WAPDA) and the techni-cal/material support of the National Engineering ServicesPakistan (NESAK) for carrying out this work are gratefullyacknowledged.

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Composite use of numerical groundwater flow modeling and geoinformatics techniques for monitoring Indus Basin aquifer, Pakistan