water

Article Analysis of Current and Future Water Demands in the Upper Indus Basin under IPCC Climate and Socio-Economic Scenarios Using a Hydro-Economic WEAP Model

Ali Amin 1,*, Javed Iqbal 1, Areesha Asghar 1 and Lars Ribbe 2

1 Institute of Geographical Information System, School of Civil and Environmental Engineering, National University of Sciences and Technology, Islamabad 44000, Pakistan; [email protected] (J.I.); [email protected] (A.A.) 2 Integrated Land and Water Resources Management in the Tropics and Subtropics, Technology Arts Sciences TH Köln, 50679 Köln, Germany; [email protected] * Correspondence: [email protected]; Tel.: +92-323-7295-289



Received: 12 April 2018; Accepted: 20 April 2018; Published: 24 April 2018


Abstract: Pakistan is currently facing physical and economic water scarcity issues that are further complicated by the rapid increase in its population and by climate change. Many studies have focused on the physical water scarcity using hydrological modeling and the measurement of the impact of climate change on water resources in the Upper Indus Basin (UIB). However, few studies have concentrated on the importance of the economic water scarcity, that is, the water management issue under the looming impacts of climate change and the population explosion of Pakistan. The purpose of this study is to develop a management strategy which helps to achieve water security and sustainability in the Upper Indus Basin (UIB) with the help of different socio-economic and climate change scenarios using WEAP (Water Evaluation and Planning) modeling. The streamflow data of five sub-basins (Gilgit, Hunza, Shigar, Shyok, and Astore) and the entire Upper Indus Basin (UIB) were calibrated (2006–2010) and validated (2011–2014) in the WEAP model. The coefficient of determination and Nash Sutcliffe values for the calibration period ranged from 0.81–0.96. The coefficient of determination and the Nash Sutcliffe values for the validation period ranged from 0.85–0.94. After the development of the WEAP model, the analysis of the unmet water demand and percent coverage of the water demand for the period of 2006–2050 was computed. Different scenarios were generated for external driving factors (population growth, urbanization, and living standards) and the impact of climate change to evaluate their effect on the current water supply system. The results indicated that the future unmet water demand is likely to reach 134 million cubic meters (mcm) by the year 2050 and that the external driving factors are putting more pressure on the supply service. This study further explores the importance of proposed dams (likely to be built until 2025) by WAPDA (Water and Power Development Authority). These dams will decrease the unmet water demand by 60% in the catchment. The water demands under four scenarios (the reference, moderate future-1, moderate future-2, and management scenarios) were compared. The management scenario analysis revealed that 80% of the water demand coverage could be achieved by the year 2023, which could help in developing sustainable water governance for the catchment.

Keywords: Water Evaluation and Planning (WEAP); water security; sustainable water governance; climate change; Upper Indus Basin

Water 2018, 10, 537; doi:10.3390/w10050537 www.mdpi.com/journal/water Water 2018, 10, 537 2 of 20

1. Introduction Most nations in the world will experience water shortage issues by 2025 [1]. Global reservoirs and glaciers which are sources of fresh water are drying up or melting [2], causing a water shortage within the agricultural and domestic sectors. This is a significant global issue as it affects the water resources as well as the availability of clean drinking water for the population [3]. The ever-increasing population and economic growth put much pressure on the hydrologic cycle and water resources [4]. The water consumption rate, urbanization, and rising living standards have a strong correlation, and these factors are putting more stress on the available water resources [5,6]. These stresses lead to a decrease in the per capita availability of water in cities [7]. In addition to the above factors, the hydrologic cycle is also significantly affected by climate change [8]. According to the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), climate change will have a significant effect on the availability and properties of natural water resources [4]. Earth’s climate is changing and even under the most optimistic scenarios of emissions and climate sensitivity, climate change impacts are inevitable [9,10]. Population growth, economic activities, and the impacts of climate change give rise to the scarcity of water, a condition in which the water demand grows beyond the available water supply because of its physical unavailability and an insufficient water management structure [11]. When the demand surpasses the available supply, then water allocation fails to meet the required demand which causes a decrease in the per capita water availability. This situation intensified further by increasing demands in the case of rapid urbanization and the improvement of living standards along with the impact of severe climate conditions [12]. The hydrology of Pakistan is based on a single river system: the Indus. The Major Indus River headwater lies in India and China [13]. The river system of Pakistan consists of more than 60 rivers (small and large). The Indus Basin has an area approximately 863,508 km2 and is a major drainage of the northwest Himalayas and the Karakoram mountains. The major tributaries in the upper Indus Basin include the Shingo, Shyok, Shigar, Astore, Hunza, Gilgit, and Kabul rivers. The source of these tributaries is dominated by snow and glacial meltwater [14]. The Indus River’s mean annual discharge is 6.2 × 1010 m3 [15]. The river water of the Indus is becoming insufficient to meet the country’s growing needs as the uses of the water resources are interdependent. Thus, there is a need to use the resource efficiently and to build more storage to avoid floods and the wastage of water in the form of runoffs into the sea [16]. In an arid and semiarid region like Pakistan, the sustainable water use in the domestic and agricultural sectors faces severe challenges under the changing climate, the population growth, and higher living standards. According to an estimate, 10 years into the future, nearly 2.9 billion people in 48 countries will face shortages of safe drinking water and Pakistan will be one of those countries with a water scarcity [17]. In the literature, different water management and allocations tools and software such as REALM (Resource Allocation Model) were used. REALM is a computer simulation used for the water distribution within a water supply source [18]. The Catchment Water Allocation Tool (CaWAT) was used for water resource planning; it is based on water balance accounting concerning the allocation of water into different sectors. It was developed with the AquaCrop (FAO) model in mind, mainly for the simulation of the water requirements for irrigation and crop productivity. The CaWAT also simulates the water storage, which is not only a model of the balance of water but also of fish production [19]. The WEAP (Water Evaluation and Planning) is selected for this study as it is the best option available to evaluate water resources using a scenario-based evaluation under different conditions of input variables. The WEAP is a useful model for the basin level evaluation of the water supply and demand [20]. The loss of water can be comprehensively handled using a simulation model (WEAP), which simulates the current water situation, evaluates the water quality, and manages the water supply and demand issues [21]. The WEAP model provides a set of objects and procedures that can resolve problems faced by water managers using a scenario-based approach, which works on natural watersheds, reservoirs, streams, and canals [22]. Water 2018, 10, 537 3 of 20

In the last decade, Pakistan entered from a water-stress country to water-scarce country. Several hydrological models have been applied to model the hydrological behavior of the Upper Indus Basin (UIB). For example, Tahir (2011) modeled the Hunza catchment under climate change scenarios using the snowmeltWater 2018, 10 runoff, x FOR model PEER REVIEW (SRM) and the results of the study suggested that SRM could be an3 of efficient 20 model for a glacier-fed sub-basin in UIB [23]. The soil water assessment tool (SWAT) model was also widelythe used snowmelt in climate runoff change model impact(SRM) and studies the result and fors of the the water study allocationsuggested inthat the SRM Indus could Basin be an [24 ,25]. The WEAPefficient model model has for a been glacier used-fed to sub study-basin the in impactUIB [23] of. The climate soil water change assessment on the hydrologytool (SWAT) of model the Indus was also widely used in climate change impact studies and for the water allocation in the Indus Basin Basin [26]. These previous studies failed to model the water management issues in the UIB to address [24,25]. The WEAP model has been used to study the impact of climate change on the hydrology of the freshwater scarcity. We assess the water scarcity issues in the UIB by using different socio-economic, the Indus Basin [26]. These previous studies failed to model the water management issues in the UIB management,to address andthe freshwater climate change scarcity. scenarios We assess for the the water availability scarcity is ofsues sustainable in the UIB waterby using in different the future in the UIB.socio-economic, management, and climate change scenarios for the availability of sustainable water in the future in the UIB. 2. Materials and Methods 2. Materials and Methods 2.1. Study Area 2.1. Study Area The Upper Indus Basin (UIB) is located in the northern part of Pakistan (33◦54005.48” E–37◦05027.96”The Upper E latitude Indus andBasin 72 ◦(UIB)11026.77” is located N–77 ◦in41 the050.36” northern N longitude) part of Pakistan (Figure 1(33°54). The′05.48 total″ areaE– of UIB is37°05 about′27.96 8303″ E latitude km2. The and UIB 72°11 contains′26.77″ N the–77°41 mountainous′50.36″ N longitude) terrains (Figure of the 1). Hindu The total Kush, area Karakorum, of UIB 2 and Himalayanis about 8303 ranges km . The which UIB contain are sourcess the mountainous of freshwater terrains for the of region.the Hindu The Kush, Indus Karakorum, is the main and river, Himalayan ranges which are sources of freshwater for the region. The Indus is the main river, which which flows through the basin, originating from the Tibetan Plateau in China, before flowing through flows through the basin, originating from the Tibetan Plateau in China, before flowing through the the disputed territory of Jammu and Kashmir to the Gilgit-Baltistan area (Pakistan). Its main tributaries disputed territory of Jammu and Kashmir to the Gilgit-Baltistan area (Pakistan). Its main tributaries in thein UIB the UIB are theare the Shingo Shingo River, River, the the Shyok Shyok River,River, the Shigar Shigar River, River, the the Gilgit Gilgit River River,, and andthe Astore the Astore River.River Then. Then the UIBthe UIB flows flows southward southward through through PakistanPakistan into into the the Arabian Arabian Sea Sea.. The The average average maximum maximum ◦ ◦ temperaturetemperature of the of the UIB UIB is 25.7is 25.7C °C and and the the average average minimum temperature temperature is 4.4 is 4.4°C. TheC. Thecatchment catchment receivesreceives substantially substantially varying varying rainfall rainfall from from 2000–2500 2000–2500 mm per per year. year.

FigureFigure 1. The 1 study. The study area maparea map showing showing the the locations locations of of the the stream stream flow flow gauges gauges andand the proposed proposed dam. dam.

Water 2018,, 10,, 537x FOR PEER REVIEW 4 of 20

2.2. Data Collection 2.2. Data Collection For the development of the hydro-economic WEAP model of the study area, different types of datasetFors were the development used (Table 1) of, theincluding hydro-economic the Digital WEAPElevation model Model of the(DEM) study for area, the delineation different types of the of subdatasets-basins were in UIB used (https://earthexplorer.usgs.gov/) (Table1), including the Digital Elevationand TRMM Model (Tropical (DEM) Rainfall for the Measuring delineation Mission) of the datasub-basins for the in catchments UIB (https://earthexplorer.usgs.gov/ which had no meteorological) and stations. TRMM (TropicalThe MODIS Rainfall land Measuring cover dataset Mission) was useddata forto identify the catchments the type whichand percentage had no meteorological of land cover in stations. a sub-catchment The MODIS (Figure land 2 cover). dataset was used to identify the type and percentage of land cover in a sub-catchment (Figure2). Table 1. The description and sources of the datasets used in developing the WEAP (Water Evaluation Tableand Planning) 1. The description model. and sources of the datasets used in developing the WEAP (Water Evaluation and Planning) model. Data Description Sources Digital Elevation Model for catchment Remote sensingData Description Sources delineation, land cover from MODIS, and USGS (https://earthexplorer.usgs.gov/) data Digital Elevation Model for catchment Remote sensing data TRMMdelineation, data for land precipitation cover from MODIS, USGS (https://earthexplorer.usgs.gov/) Climate data Precipitation,and TRMM dataTemperature for precipitation Pakistan Meteorological Department (2006–Climate2014) data Humidity,Precipitation, Cloudiness Temperature factor, Wind Humidity, speed Pakistan Meteorological Department Hydrological(2006–2014) data Cloudiness factor, Wind speed Water And Power Development Authority, Gauge station data, Reservoirs (2006Hydrological–2014) data WaterIndus AndRiver Power System Development Authority Authority, and PMD Gauge station data, Reservoirs (2006–2014) Land use data Indus River System Authority and PMD UrbanLand sector use data Socio-Economic Surveys (Census 1998) and PopulationUrban sector Socio-Economicgrowth Surveys rate, (Census 1998) and Demand data Population growth rate, Demand data Water use rates Irrigation Department (Pakistan) and Water use rates Irrigation Department (Pakistan) and WaterWater consumption consumption agriculture census census data data AgriculturalAgricultural sector sector

Figure 2. The land cover/use map of the Upper Indus Basin derived from the MODIS land cover data. Figure 2. The land cover/use map of the Upper Indus Basin derived from the MODIS land cover data.

Water 2018, 10, 537 5 of 20 Water 2018, 10, x FOR PEER REVIEW 5 of 20

TheThe climate, climate, precipitation, precipitation, temperature, temperature, wind wind speed, speed, cloudiness cloudiness factor, factor, and and humidity humidity data data were were acquiredacquired from from the the Pakistan Pakistan Meteorological Meteorological Department Department (PMD). (PMD). The The river river discharges discharges and and the the gauge gauge stationstation data data were were collected collected from from the the Water Water and and Power Power Development Development Authority Authority (WAPDA), (WAPDA), the the Indus Indus RiverRiver System System Authority Authority (IRSA) (IRSA),, and and PMD PMD which which were were further further used used for for the the calibration calibration an andd validation validation of of thethe catchment.catchment Demographic. Demographic data data including including the population, the population, water usewater rates, use and rates, water and consumption water consumptionwere acquired were from acquired different from socio-economic different socio surveys,-economic the surveys, Pakistan the Bureau Pakistan of Statistics, Bureau of and Statistics the Water, andand the Sanitation Water and Authority Sanitation (WASA), Authority which (WASA) helped, which to analyze helped the to analyze water demand, the water water demand, coverage, water and coverageunmet, waterand unmet demand. water The agriculturaldemand. The data agricultural were collected data from were the collected Irrigation from Department the Irrigation (Pakistan) Departmentand agriculture (Pakistan) census and data agriculture which were census acquired data which from thewere literature, acquired which from helpsthe literature in computing, which the helpswater in computing requirement the and water unmet requirement water demand and unmet for the water agricultural demand sector. for the agricultural sector.

2.3.2.3. Methodology Methodology TheThe study study focuses focuses on on the the development development of of the the WEAP WEAP model model and and the the calibration calibration and and validation validation of of the fivefive sub-catchmentssub-catchments (Gilgit,(Gilgit, Hunza,Hunza, Shigar, Shigar, Shyok, Shyok, Shingo, Shingo, and and Astore) Astore) in thein the Upper Upper Indus Indus Basin Basin(UIB). (UIB) After. After the the development development of theof the WEAP WEAP model, model three, three scenarios scenarios were were used used to predict to predict the the water waterdemands demands up toup the to yearthe year 2050. 2050. The WEAPThe WEAP model model was runwas on run a monthlyon a monthly time-step time interval.-step interval.In building In buildingthe WEAP the WEAP model, model, the 2006–2014 the 2006 period–2014 period was set was as aset baseline as a baseline for which for which the agricultural the agricultural and domestic and domesticwater demandswater demands were calculated. were calculated. The socio-economic The socio-economic scenarios scenarios used inused the in WEAP the WEAP model model include includebusiness business as usual as usual (set as (set a reference),as a reference high), high population population growth growth (HPG), (HPG), low low population population growth growth (LPG), (LPG),high high living living standards standards (HLS), (HLS) and, HPG and HPG + HLS. + HLS. The climate The climate change change scenarios scenarios were constructed were constructed using the usingdownloaded the downloaded Global ClimateGlobal Climate Model datasetModel dataset (RCP-4.5 (RCP and-4.5 RCP-8.5) and RCP to calculate-8.5) to calculate the impact the ofimpact climate of changeclimate onchange the supply–demand on the supply gap–demand by the yeargap 2050.by the Figure year3 2050.shows F theigure complete 3 shows workflow the complete and data workflowinputs forand developing data inputs the for WEAP developing model. the WEAP model.

FigureFigure 3. The 3. The study study workflow workflow and and data data input inputss in the in theWEAP WEAP model. model.

2.4.2.4. Hydro Hydro-Economic-Economic WEAP WEAP Model Model Description Description TheThe WEAP WEAP tool tool was was usedused toto represent represent the the current current water water supply supply and demand and demand in all six in catchments. all six catchments.The tool is The widely tool usedis widely in the used world in the for world water allocationfor water allocation and water and management water management [27]. It provides [27]. It an providesintegrated an integrated assessment assessment of the land of use, the hydrology, land use, climate,hydrology, water climate, allocation, water and allocation water management, and water of managementthe catchment of the [28 catchment]. The WEAP [28] model. The WEAP addresses model a number addresses of watera number issues of includingwater issues the including agricultural thesector, agricultural surface sector, and groundwater surface and sources, groundwater sectoral sources, (domestic, sectoral agricultural, (domestic, and agricultural, industrial) demand and industrialanalyses,) demand water management, analyses, water water management, allocation using water priorities, allocation conjunctive using priorities, use, reservoir conjunctive operations, use, reservoirand the operations, cost management and the by cost financial management planning by [ 22financial,29]. Based planning on the [22,29] linear. programming Based on the structure,linear programmingit solves the structure, water allocation it solves problems the water at allocation user-defined problems time-steps at user (monthly-defined or time daily)-steps [22]. (monthly or daily) [22].

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The WEAP model was used to simulate both the hydrological behavior and anthropogenic The WEAP model was used to simulate both the hydrological behavior and anthropogenic activities of water resources to analyze the water availability in the basin [30]. It is useful since it activities of water resources to analyze the water availability in the basin [30]. It is useful since it simulates the water supply and demand based on a set of scenarios like demographic changes or simulates the water supply and demand based on a set of scenarios like demographic changes or water water policies for a user-required time period [22]. These future simulations (or scenarios) are comparedpolicies for to a the user-required current (or time the baseline period [22) year.]. These Generally, future simulationsthe baseline (or is the scenarios) year for are which compared there tois the current (or the baseline) year. Generally, the baseline is the year for which there is an availability of an availability of all the input data required by the WEAP model including the streamflow, climate all the input data required by the WEAP model including the streamflow, climate data, demographic, data, demographic, and soil and land use/cover. It depicts the actual water supply condition in the catchmentand soil and, also land known use/cover. as the current It depicts account. the actual The baseline water supplyyear is selected condition because in the the catchment, model need alsos aknown current as water the current availability account. value The which baseline will year be further is selected used because for a comparison the model needs between a current the current water andavailability future water value whichavailabilities will be under further different used for socio a comparison-economic, between climate, the or current management and future scenarios water availabilities under different socio-economic, climate, or management scenarios [31]. The WEAP model [31]. The WEAP model uses five methods to simulate catchment processes on a daily or monthly basis.uses fiveThe methodssoil moisture to simulate method catchment was selected processes for this onstudy a daily because or monthly it allows basis. for the The characterization soil moisture ofmethod the impacts was selected of the for land this use study and because soil type it allowss on these for the processes characterization [22]. It is of a the 1- impactsD, 2-bucket of the water land accountinguse and soil method types on based these on processes empirical [22 ].functions It is a 1-D, that 2-bucket is used water to explain accounting the deep method percolation, based on evapotranspiration,empirical functions surface that is used runoff, to explainand interflow the deep for percolation,basin or sub evapotranspiration,-basins (Figure 4). surface runoff, and interflowThe mathematical for basin formula or sub-basins of the(Figure soil moisture4). method [28] is as follows: The mathematical formula of the soil moisture method [28] is as follows: , ( ) ( ) ( ) , , ( ) = , 2 ! 2 , , , 𝑑𝑑𝑑𝑑1 𝑗𝑗 5z − 25z𝑧𝑧1 𝑗𝑗−2𝑧𝑧1 𝑗𝑗 𝑅𝑅𝑅𝑅𝑅𝑅𝑗𝑗 (1) dz1,j 1,j 1,j RRFj 2 2
2 Rd =𝑗𝑗Pe(t) − PET𝑒𝑒 (t)k (t) 𝑐𝑐 𝑗𝑗 1 − P e (t)z𝑒𝑒 − f k z𝑗𝑗 −𝑠𝑠 𝑗𝑗 11 𝑗𝑗− f k z (1) j dt 𝑅𝑅𝑅𝑅 𝑑𝑑𝑑𝑑 𝑃𝑃 𝑡𝑡 − 𝑃𝑃𝑃𝑃𝑃𝑃c,j 𝑡𝑡 𝑘𝑘 𝑡𝑡3 � 3, , � − 𝑃𝑃1,j𝑡𝑡 𝑧𝑧1 𝑗𝑗 j −s,j 𝑓𝑓1,𝑘𝑘j 𝑧𝑧 − j s,j 1,j 2 𝑗𝑗 𝑠𝑠 𝑗𝑗 where z1,j = [1, 0] is the relative soil water storage,� − 𝑓𝑓 � 𝑘𝑘 𝑧𝑧is1 𝑗𝑗the effective precipitation (mm), ( ) is thewhere referencez1,j = [1, potential 0] is the relativeevapotranspiration, soil water storage, , Pise isthe the crop effective coefficient, precipitation and (mm), isPET the( tRunoff) is the 𝑃𝑃𝑒𝑒 𝑃𝑃𝑃𝑃𝑃𝑃 𝑡𝑡 reference potential evapotranspiration, kc,j is the crop coefficient, and RRFj is the Runoff Resistance Resistance Factor of the land cover. Higher values𝑐𝑐 𝑗𝑗 of RRFj lead to less surface runoff𝑗𝑗 ; ( ) , is 𝑘𝑘 𝑅𝑅𝑅𝑅𝑅𝑅RRFj 𝑅𝑅𝑅𝑅𝑅𝑅𝑗𝑗 theFactor surface of the runoff, land cover. Higher is the values interflow of RRF fromj lead first tosoil less layer, surface is runoff;the partitionPe(t)z coefficient1,j is the surfacerelated , , 𝑃𝑃𝑒𝑒 𝑡𝑡 𝑧𝑧1 𝑗𝑗 2 2 torunoff, the landfj k scover,j z1,j istype the, and interflow , is from the saturated first soil layer, hydraulicfj is the conductivity partition coefficient of the root related zone (mm/time). to the land 𝑓𝑓𝑗𝑗 𝑘𝑘𝑠𝑠 𝑗𝑗 𝑧𝑧1 𝑗𝑗 𝑓𝑓𝑗𝑗 cover type, and ks,j is the saturated hydraulic conductivity of the root zone (mm/time). 𝑘𝑘𝑠𝑠 𝑗𝑗

Figure 4. The conceptual diagram and equations used in the soil moisture method. Figure 4. The conceptual diagram and equations used in the soil moisture method. 2.5. Model Setup 2.5. ModelThe WEAP Setup model was developed for the Upper Indus Basin (UIB) (Figure5). TheThe WEAP model model was includes developed the following for the Upper (Figure Indus6); Basin (UIB) (Figure 5). The WEAP model includes the following (Figure 6); • The main Indus River and six small tributaries (Gilgit, Hunza. Shigar, Shyok, Shingo, and Astore)

Water 2018,, 10,, xx FORFOR PEERPEER REVIEWREVIEW 7 of 20 Water 2018, 10, 537 7 of 20 • The main Indus River and six small tributaries (Gilgit, Hunza. Shigar, Shyok, Shingo,, and • EightAstore) catchment nodes. Nine domestic demands (Gilgit, Hunza, Shigar, Shyok, Shingo, Astore, • Diamir,Eight catchment Kohistan, nodes. and the Nine below domestic besham demands streamflow (Gilgit, site), Hunza seven,, Shigar, agriculture Shyok, demand Shingo, sites, Astore, and oneDiamir, livestock Kohistan demand,, and site. the below besham streamflow site), seven agriculture demand sites, and • Eightone livestock runoff/infiltration demand site. lines. Eighteen transmission links. • Eight runoff/infiltration lines. Eighteen transmission links. • SixEight streamflow runoff/infiltration gauge stations lines. Eighteen (Doyian transmission (Astore river), links Dainyor. Br. (Hunza river), Shigar • Six streamflow gauge stations (Doyian (Astore river), Dainyor Br. (Hunza river), Shigar (Shigar (SixShigar streamflow river), Gilgit gauge (Gilgit stations river), (Doyian Yogo (Astore (Shyok river), river), Dainyor Partab Br. Br. (Hunza (Indus river), River), Shigar and Besham (Shigar river), Gilgit (Gilgit river), Yogo (Shyok river), Partab Br. (Indus River), and Besham Qila (Indus Qilariver), (Indus Gilgit river). (Gilgit river), Yogo (Shyok river), Partab Br. (Indus River), and Besham Qila (Indus river).

FigureFigure 5.5. TheThe structurestructure ofof thethethe waterwater supplysupply serviceservice inin thethe catchment.catchment.

Figure 6. A schematic diagram showing the configuration of the WEAP model for thethe demand sites Figure 6. A schematic diagram showing the configuration of the WEAP model for the demand sites in inin thethe Upper Indus Basin (UIB).. the Upper Indus Basin (UIB).

Scenario Development Scenario Development In the WEAP model, the scenarios were built based on “what if” questions [32] and compared In the WEAP model, the scenarios were built based on “what if” questions [32] and compared to the reference scenario. In this study, the scenarios were developed using external changes (that is,, to the reference scenario. In this study, the scenarios were developed using external changes (that is, population growth, living standards,, andand soso forthforth) and the impact of climate change inin orderorder to

Water 2018, 10, 537 8 of 20

Water 2018, 10, x FOR PEER REVIEW 8 of 20 populationWater 2018 growth,, 10, x FOR living PEER REVIEW standards, and so forth) and the impact of climate change in order8 to of predict20 predict the water supply–demand gap in the future. The first reference scenario constructed the water supply–demand gap in the future. The first reference scenario constructed represented represented the present water supply–demand conditions in the catchment, which acts as a baseline the presentpredict waterthe water supply–demand supply–demand conditions gap in the in thefuture. catchment, The first which reference acts scenario as a baseline constructed for further for further analysis and comparison with the other scenarios of the model. represented the present water supply–demand conditions in the catchment, which acts as a baseline analysis andTo comparisonunderstand the with effect the of other external scenarios factors ofon thethe model.future water supply–demand in the UIB, the for further analysis and comparison with the other scenarios of the model. Toscenarios understand were used the effectin the ofWEAP external model factors to simulate on the socio future-economic water activities supply–demand like high population in the UIB, To understand the effect of external factors on the future water supply–demand in the UIB, the the scenariosgrowth (HPG)were used, set to in be the 6%. WEAP Furthermore, model the to simulate low population socio-economic growth (LPG) activities rate was like set high to 1.35% population and scenarios were used in the WEAP model to simulate socio-economic activities like high population growththe (HPG), higher set living to be standards 6%. Furthermore, (HLS) was estimated the low population to change from growth 82.9 (LPG)m to 120 rate m was due set to toeconomic 1.35% and growth (HPG), set to be 6%. Furthermore, the low population growth (LPG) rate was set to 1.35% and growth and increased urbanization (Figure 7) 33 3 3 the higherthe higher living living standards standards (HLS) (HLS) was was estimated estimated toto change from from 82.9 82.9 m mto 120to 120 m mduedue to economic to economic For the climate change scenarios, the climate data was acquired using the downloaded Global growthgrowth and and increased increased urbanization urbanization (Figure (Figure7 )7) 3 3 Circulation Model (GCM) datasets [33]. There were four Representative Concentration Pathways For theFor climatethe climate change change scenarios, scenarios, the the climate climate data was was acquired acquired using using the the downloaded downloaded Global Global (RCPs), namely, RCP2.6, RCP4.5, RCP6.0, and RCP8.5. The RCP scenarios were named according to CirculationCirculation Model Model (GCM) (GCM) datasets datasets [33 [33]].. ThereThere werewere four four Representative Representative Concentration Concentration Pathways Pathways the radiative forcing target level 2100. For this study, the RCP 4.5 and RCP 8.5 scenarios were selected (RCPs),(RCPs), namely, namely, RCP2.6, RCP2.6, RCP4.5, RCP4.5, RCP6.0, RCP6.0, and and RCP8.5.RCP8.5. The The RCP RCP scenarios scenarios were were named named according according to to because of the study period time length. The RCP4.5 scenario described a stabilization of the pathway the radiative forcing target level 2100. For this study, the RCP 4.5 and RCP 8.5 scenarios were selected the radiativeafter 2100 forcing without target exceeding level 2100. 4.5 W/ Form this(~650 study, ppm theCO RCP) [34]. 4.5 The and RCP8.5 RCP scenario 8.5 scenarios corresponded were selected to because of the study period time length. The RCP4.5 scenario described a stabilization of the pathway becausethe of rising the study radiative period forcing time pathway length. leading The2 RCP4.5 to 8.5 W/ scenariom (~1370 described ppm CO a) stabilizationby 2100 [35]. This of the scenario pathway after 2100 without exceeding 4.5 W/m (~650 ppm CO )2 [34]. The RCP8.5 scenario corresponded to after 2100was withoutrelated to exceedingthe situation 4.5 with W/m no climate2 (~650 policies ppm CO and2)[ high34]. emissions The RCP8.5 of greenhouse scenario correspondedgases. to 2 m 2 CO 2 the rising radiative forcing pathway leading to 8.5 W/ 22 (~1370 ppm ) by 2100 [35]. This scenario the rising radiativeThe workflow forcing of the pathway scenarios leading is shown to 8.5 in Figure W/m2 8(~1370 below. ppm CO2) by 2100 [35]. This scenario was related to the situation with no climate policies and high emissions of2 greenhouse gases. was relatedThe to workflow the situation of the with scenarios no climate is shown policies in Figure and 8 below. high emissions of greenhouse gases. The workflow of the scenarios is shown in Figure8 below.

Figure 7. Shows the externally driven factors and climate change scenarios used in the WEAP model. Figure 7.FigureShows 7. theShows externally the externally driven driven factors factors and and climate climate change change scenarios scenarios used used inin thethe WEAP model. model.

Figure 8. An image showing the workflow of the externally driving scenarios, the impact of climate change, and the management scenarios used in the study.

Water 2018, 10, 537 9 of 20

The accuracy of the model was computed using the coefficient of determination and the Nash–Sutcliffe efficiency index [36,37].

3. Results

3.1. Model Calibration and Validation The hydrological and economic data of the UIB were used to calibrate and validate the Hydro-Economic WEAP model for the period of 2006–2014 (Figure9). To simulate the discharge data in the WEAP model crop coefficient (kc) of the land cover types, the root zone conductivity, the preferred flow direction, and the soil water capacity were calibrated manually. These values were selected based on the location of study area and the default values of the WEAP. The values for the coefficient of determination ranged between 0.82 and 0.96 with an average of 0.88, while the Nash–Sutcliffe parameter varied from 0.81 to 0.94 with an average of 0.87. The Nash–Sutcliffe efficiency ranges from −∞ to 1. An efficiency of 1 (E = 1) corresponds to a perfect match between the modeled discharge and the observed data [38]. The values of these parameters show that the hydrology of the UIB is predicted accurately by the WEAP model. In a sense, this provides a confidence that the future streamflow prediction can be accurately projected based on future scenarios. Table2 shows the range of the values used for the different parameters in order to calibrate the model.

3.2. Scenario 1: Reference/Business as Usual Figure 10 shows the results of the current/reference scenario simulation and analysis for the unmet water demand. The graph shows that in the year 2014, the average water demand coverage was 90% and that the average monthly supply delivered in the catchment was 44.3 mcm. Based on the baseline conditions, the estimation of the future water supply–demand conditions indicated that the average water demand coverage in the UIB would decrease from 90% to 75% in 2050. The unmet water demands, which were 78.9 mcm in 2014, were estimated to be 134.56 mcm in 2050. The water demands were calculated based on the per capita water consumption rate, which includes the population growth and the agricultural water requirement in the catchment. The reference scenario analysis developed was based on the assumption that if there were no changes in the water supply system of the catchment, the water coverage in the catchment would decrease by 15% in 2050. The reference scenario analysis concluded that no improvement in the water infrastructure and the supply situation would lead the catchment to a water scarcity in the future.

Table 2. The calibration parameter ranges used in the Water Evaluation and Planning (WEAP) model.

Parameters Model Range Optimal Range (for Different Land Covers) Soil water capacity 0-higher (mm) 0–1200 (mm) Root zone conductivity Default = 20 mm 10–50 (mm) 0.1-higher (mm/month) Deep conductivity Default = 20 mm Default = 20 mm Runoff resistance factor 0–1000 (default = 2) 0–100 Preferred flow direction 0–1 (default = 0.15) 0.5–1 Water 2018, 10, 537 10 of 20 Water 2018, 10, x FOR PEER REVIEW 10 of 20

Figure 9. The calibration and validation of the five sub-catchments and the entire Upper Indus Basin (UIB).

Figure 9. The calibration and validation of the five sub-catchments and the entire Upper Indus Basin (UIB).

3.3. External-Driven Factor Scenarios Result Figure 11 shows the comparison of unmet water demands under the impact of externally driven factors (population growth, urbanization, and living standards). The analysis showed that the high population growth and higher living standard scenarios have a critical impact on the water supply– demand situation. For the population growth scenario, it was assumed that if the population of the

Water 2018, 10, 537 11 of 20

3.3. External-Driven Factor Scenarios Result Figure 11 shows the comparison of unmet water demands under the impact of externally driven factors (population growth, urbanization, and living standards). The analysis showed that the highWater population 2018, 10, x FOR growth PEER REVIEW and higher living standard scenarios have a critical impact on the11 of water 20 supply–demand situation. For the population growth scenario, it was assumed that if the population ofcatchment the catchment continue continuedd to rise to with rise a with 6% growth a 6% growth rate (high rate popu (highlation population growth) growth),, it would it lead would to more lead to moreurbanization urbanization,, which which could could result result in higher in higher living living standards standards and and economic economic growth growth.. The The current current domesticdomestic water water demand demand from from the the Water Water and and Sanitation Sanitation Authority Authority (WASA) (WASA) was 82.9was m82.93 in m the in baseline the yearsbaseline and wasyears projected and was toprojected increase to to increase 120 m3 toin 120 the m scenario in the ofscenario high living of high standards living standards by the3 year by the 2050. Foryear the 2050. low populationFor the low growthpopulation (LPG) growth scenario, (LPG) the scenario, water3 demandsthe water weredemands analyzed were foranalyzed a population for a growthpopulation rate ofgrowth 1.35% rate (this of would 1.35% be(this in would the case be ofin thethe governmentcase of the government intervening intervening and stepping andup thest awarenessepping up inthe order awareness to control in order the national to control growth the national rate) (Figure growth 11 rate)). The (Figure study estimated11). The study future projectionsestimated based future on projections the external based driving on the factors external such driving as urbanization factors such (which as urbanization might lead (which to a high might water consumptionlead to a high per water capita), consumption increased per in populationcapita), increased growth, in pop highulation living growth, standards, high and living low standards population, and low population growth (Figure 12). growth (Figure 12). The worst-case scenario was developed by assuming that there was no significant improvement The worst-case scenario was developed by assuming that there was no significant improvement in the water supply condition in the catchment but an increase in the higher living standards of the in the water supply condition in the catchment but an increase in the higher living standards of the population and a higher population growth rate. This scenario was developed by the combination of population and a higher population growth rate. This scenario was developed by the combination of the high population growth rate scenario and the high living standards scenario (Figure 13). the high population growth rate scenario and the high living standards scenario (Figure 13).

FigureFigure 10. 10.The The unmet unmet water water demand demand for for thethe reference/businessreference/business as as usual usual (2014 (2014–2050)–2050) scenario scenario in inthe the UpperUpper Indus Indus Basin Basin (UIB). (UIB).

Water 2018, 10, 537 12 of 20 WaterWater 20182018,, 1010,, xx FORFOR PEERPEER REVIEWREVIEW 1212 ofof 2020

FigureFigureFigure 11. 11.11.The TheThe future futurefuture projections projectionsprojections of ofof the thethe unmet unmetunmet waterwater d demandsdemandsemands inin in thethe the UpperUpper Upper IndusIndus Indus BasinBasin Basin (UIB)(UIB) (UIB) underunder under thethethe reference, reference,reference, high highhigh population populationpopulation growth, growth,growth, and highandand high populationhigh ppopulationopulation growth growthgrowth + higher ++ higherhigher living standardslivingliving standardsstandards scenarios forscenariosscenarios the period forfor 2014–2050. thethe periodperiod 20142014––2050.2050.

FigureFigureFigure 12. 12.12.The TheThe future futurefuture projections projectionsprojections of ofof the thethe unmet unmetunmet waterwater demands demands inin in thethe the UpperUpper Upper IndusIndus Indus BasinBasin Basin (UIB)(UIB) (UIB) underunder under thethethe reference referencereference and andand low lowlow population populationpopulation growth growthgrowth scenarios. scenarioscenarioss..

Water 2018, 10, 537 13 of 20 Water 2018, 10, x FOR PEER REVIEW 13 of 20

FigureFigure 13. The 13. The future future projections projections of of the the unmet unmet waterwater demands in in the the Upper Upper Indus Indus Basin Basin (UIB) (UIB) under under the reference and high population growth + high living standards scenarios for the period 2014–2050. the reference and high population growth + high living standards scenarios for the period 2014–2050. The results in Figure 12 show that only in the LPG scenario was the unmet water demand Thesomewhat results similar in Figure to the 12reference show scenario, that only but in in theall other LPG case scenarios of external was thedriving unmet factor water scenarios, demand somewhatthe unmet similar water to demand the reference had an scenario,increasing but trend. in allIn the other high cases population of external growth driving scenario, factor the unmet scenarios, the unmetwater waterdemand demand reachedhad 136 m an increasingby the year 2050, trend. which In the would high have population severe effect growths on the scenario, water supply the unmet 3 watersystem demand if not reached improved 136 or mif3 newby water the year management 2050, which policies would are not have introduced. severe effectsThe HLS on (higher the water living standard) scenario, introduced based on the assumption of increased urbanization and supply system if not improved or if new water management policies are not introduced. The HLS economic development in the UIB, lead to the unmet water demand of 163 m by 2050. For the worst (higher living standard) scenario, introduced based on the assumption of increased urbanization and case condition scenario, the water supply–demand was estimated for the combination3 of the higher 3 economicliving development standards and in high the population UIB, lead togrowth the unmet scenario waters. The demand water demand of 163 would m by reach 2050. more For thethan worst case condition190 m for scenario, the year 2050 the, waterin this supply–demandcase (Figure 13). was estimated for the combination of the higher living standards3 and high population growth scenarios. The water demand would reach more than 190 m3.4.3 for Climate the year Change 2050, Scenarios in this case (Figure 13). The climate change scenario was constructed by using the climate data downloaded from the 3.4. Climate Change Scenarios website of the Pakistan Meteorological Department [39]. The RCP-4.5 stabilization scenario and the TheRCP- climate8.5 for extreme change conditions scenario were was used constructed to simulate by the using future the imp climateact of the data climate downloaded on the water from the websitesupply ofand the demand Pakistan conditions Meteorological (Figure 14) Department. [39]. The RCP-4.5 stabilization scenario and the RCP-8.5 for extreme conditions were used to simulate the future impact of the climate on the water 3.5. Management Scenario supply and demand conditions (Figure 14). Figure 15 shows the comparative analysis of the unmet water demands between the reference 3.5. Managementscenario and Scenariothe management scenarios. The management scenarios introduced include the supply side management and the demand side management. The supply side management scenario was Figurebuilt with 15 theshows assumption the comparative that the proposed analysis dams of (Bunji, the unmet Dasu, waterand Bhasha demands Diamir) between were functioning the reference scenarioby the and year the 2023. management The demand scenarios. side management The management included the scenarios adoption introduced of proposed include water thesaving supply side managementtechniques by andthe PCRWR the demand (Pakistan side Council management. of Research The in supply Water sideResources) management which include scenariod a was built withreduction the assumptionin the water thatwastages the proposed at domestic dams and (Bunji,agricultural Dasu, sites and and Bhasha a decrease Diamir) in the were per functioning capita by thewater year requirement. 2023. The demandThese dams side will management not only store included water for agricultural the adoption and of domestic proposed purposes water but saving techniquesthey will by also the help PCRWR to control (Pakistan the energy Council crisis in of the Research country. inFigure Water 15 shows Resources) the amount which of includedunmet a reduction in the water wastages at domestic and agricultural sites and a decrease in the per capita water requirement. These dams will not only store water for agricultural and domestic purposes but they will also help to control the energy crisis in the country. Figure 15 shows the amount of unmet Water 2018, 10, 537 14 of 20 WaterWater 2018 2018, 10, 10, x, xFOR FOR PEER PEER REVIEW REVIEW 1414 of of 20 20

water demand that can be reduced through the implementation of a water management plan via the waterwater demand demand that that can can be reducedbe reduced through through the the implementation implementation of of a awater water management management plan plan via the via the referencereference scenario. scenario. reference scenario.

FigureFigureFigure 14. The 14. 14. The unmetThe unmet unmet water water water demands demands demands in in the in the the Upper Upper Upper Indus Indus Indus Basin Basin Basin (UIB) (UIB) (UIB) underunder under thethe the reference reference scenario scenarioscenario and in theandand RCP-4.5 in in the the RCP andRCP-4.5 RCP-8.5-4.5 and and RCP RCP scenarios-8.5-8.5 scenarios scenarios for the for for period the the period period 2014–2050. 2014 2014–2050.–2050.

Figure 15. The projection of unmet water demands in the Upper Indus Basin (UIB) under the reference

and water management scenarios. Water 2018, 10, 537 15 of 20

4. Discussion We proposed a water management strategy in the UIB based on the different socio-economic, management, and climate change scenarios for the sustainable availability of future water resources in the UIB. To develop a sustainable water supply–demand system, the first step was to understand the current water supply–demand system in the study area and to evaluate the future impacts of externally driven factors and the impact of climate change on the water resources of the UIB. Then, based on the current supply–demand situation, the supply and demand side management scenarios were applied in the model in order to optimize the water management system to achieve better results (decrease the unmet water demands). In this study, the reference scenario was built and the current unmet water demand in the Upper Indus Basin (UIB) was estimated to be 134 mcm. Similar findings were reported by Chitresh Saraswat [40] who asserted that the current water demand in the Kathmandu Valley was estimated to be 388.10 MLD (million liters per day). The authors of Reference [41] performed a similar water supply–demand analysis in the Didessa sub-basin West Ethiopia and reported that the current water demand in the sub-basin was 74 mcm. The results of their study suggested that water management strategies can help resolve the water scarcity problem in the basin. In another study conducted in the Mae Kong Basin in Thailand reported that the average unmet water demand for agriculture was 62 mcm per year and 17 mcm per year for the Tha Chin sub-basin [42]. Since the proposed dam sites (supply-side management) are crucial and necessary for achieving water security in the basin, the results of this study indicate that after the completion of the proposed dams and the implementation of the necessary demand side management strategies, there is a high probability of achieving an 80% fulfillment of the unmet water demand by 2025. In this study, the WEAP modeling suggested that water management options such as reducing the losses to domestic demand sites, the reduction in the per capita water requirement, and (mainly) the construction of the proposed dams would help in retaining the water supply services in the future. The WEAP model also evaluated the externally driving factors (population growth, high living standards, and climate change) which puts immense pressure on the current water supply system and intensifies the water scarcity situation not only in the catchment but also downstream. The results of the study encourage water resources managers to adopt a management policy to resolve the water crisis or to render the unmet water demands in the Upper Indus Basin (UIB). Based on the analysis of this study, it is necessary to identify an effective management strategy. For this purpose, a comparative analysis was designed to consider the possible options and to identify an effective policy for the maintenance of the water security in the catchment (Figure 16). In the pessimistic future or reference scenario, we assume that the dams which are under construction could not be completed by 2050 due to some unforeseen reasons (the lack of funds or political issues, for example). Thus, the unmet water demands will rise to an average of 84 mcm and losses could reach up to 40%. In the moderate future-1 scenario, we assume that the various domestic water saving techniques mention by the PCRWR were applied, which could decrease the per capita water demand from 82.9 m3 to 70 m3 along with a decrease in the losses by up to 20%. In the moderate future-2 scenario which is based on the baseline conditions, we assume that the climatic condition, the river flow, and the catchment has a steady population growth. For the optimistic future, the PCRWR’s reported that water saving techniques could be applied which will help in the reduction of losses and the proposed or under construction dams will be fully functional by 2023. In the optimistic future or management scenario, the average unmet water demands could be reduced to just 25 mcm (Figure 17). Water 2018, 10, 537 16 of 20 Water 2018, 10, x FOR PEER REVIEW 16 of 20

FigureFigure 16. 16. TheThe future future water water estimation estimation under under different different management management strategies strategies of of water water in in the the UIB. UIB.

TheThe reference reference scenar scenarioio exerts exerts a a negative negative impact impact on on the the UIB UIB supply supply system, system, the the water water demands demands risrise,e, and and itit isis predictedpredicted that that it willit will be be more more than than double double by the by year the 2050year(Figure 2050 (Figure 18). This 18 rapid). This increase rapid increasein the demand in the demand is not only is not due only to anthropogenicdue to anthropogenic activities activities (urbanization, (urbanization growth, gr rate,owth and rate, so on)and butso onalso) but due also to changesdue to changes in the amount in the amount of rainfall of andrainfall itsseasonal and its seasonal distribution distribution [43]. Glaciers [43]. Glaciers in the northern in the northernregion of region Pakistan of are Pakistan a major are source a major of fresh source water of for fresh 200 million water peoplefor 200 living million downstream people living in the downstreamlower Indus Basinin the forlower domestic Indus and Basin agricultural for domestic purposes and agricultural and have a highpurposes dependency and have on itsa high GDP dependencyon agriculture on exports.its GDP Archeron agriculture suggested exports. that any Archer change suggested in the trend that ofany rainfall change or in snow the intrend winter of rainfalldue to human-inducedor snow in winter or non-human-induceddue to human-induced climate or non variability-human-induced will be reflected climate onvariability the runoff will in be the reflectedsummer seasonon the runoff [44]. The in presentedthe summer analysis season of [44] management. The presented strategies analysis for the of futuremanagement prediction strategies should forbe the considered future prediction for planning, should developing, be considered and designing for planning, a sustainable developing water, and supply designing system a sustainable (Figure 18). waterPakistan supply system is at high (Figure risk 18) regarding. the water availability situation due to its dependency on a singlePakistan river system is at high in therisk face regarding of looming the water climate availability change impacts. situation However, due to its Pakistan dependency has yeton toa singledevelop river and system implement in the itsface water of looming policy. climate Apart from change climate impacts. change However, impacts, Pakistan Pakistan has is yet facing to developrapid population and implement growth. its water With Pakistan’spolicy. Apart steadily from climate increasing change water impacts, demand Pakistan for food is facing security rapid and populationthe loss of growth. storage inWith the Pakistan’s existing water steadily resource increasing development water demand structure for food due tosecurity sedimentation and the loss and ofinter-provincial storage in the conflictsexisting onwater the developingresource development water storage structure reservoirs, due theto sedimentation Government response and inter on- provincialthese issues conflicts is fragmentary on the developing [45]. To dealwater with storage these reservoirs, issues, the the integrated Government water response management on these of issuesreservoirs, is fragmentary the construction [45]. To ofdeal new with water these infrastructure, issues, the integrated and a water water management management strategy of reservoirs, for the theagricultural construction sector of new is required. water infrastructure, The Water and and Power a water Development management Authority strategy for (WAPDA) the agricultural and the sectorProvincial is required. Irrigation The and Water Drainage and AuthoritiesPower Development (PIDA) have Authority sub-divisional (WAPDA) control and of the the Provincial reservoirs, Irrigationbut they haveand aDrainage shortage Authorities of resources (PIDA) and technical have sub support-divisional to make control the bestof the use reservoirs, of the surface but waterthey havethat isa shortage available. ofThe resources productivity and technicalper unit support of water to is make 40% lowerthe best than use in of neighboring the surface partswater of that India is available.and 50% lowerThe productivity than the United per unit States of water [46]. is 40% lower than in neighboring parts of India and 50% lower than the United States [46].

Water 2018, 10, x FOR PEER REVIEW 17 of 20 WaterWater 20182018, ,1010,, x 537 FOR PEER REVIEW 1717 of of 20 20

Figure 17. The projection of the “total unmet water demand” under four different prediction scenarios FigureFigure(2014 –17 17.2050).. TheThe projection projection of of the the “ “totaltotal unmet unmet water water demand” demand” under under fo fourur different different prediction prediction scenarios scenarios (2014(2014–2050).–2050).

Figure 18. The unmet water demand for four different futures for the years of 2015 and 2050. Figure 18. The unmet water demand for four different futures for the years of 2015 and 2050. Figure 18. The unmet water demand for four different futures for the years of 2015 and 2050. TheThe Tarbela Tarbela and and Mangla Mangla dams dams are are the the only only two two significant significant reservoirs reservoirs on on the the Indus Indus River River and and theytheyThe both both Tarbela under under degradationand degrada Manglation duedams due to to are high high the sediment sediment only two loads. loads.significant So, So, as as thisreservoirs this study study suggests,on suggests the Indus, with with River the the rapid rapidand theypopulationpopulation both under increase increase degrada coupled coupledtion withdue with to an an high increased increased sediment water water loads. requirement requirement So, as this and and study the the impact suggestsimpact of of, climatewith climate the change, change,rapid population increase coupled with an increased water requirement and the impact of climate change,

Water 2018, 10, 537 18 of 20 the construction of new major reservoirs like the Bhasha dam, Dasu dam, Bunji dam, and Kalabagh dam (downstream) is the need of the hour. Increasing water productivity could buy some time against the increasing water demand and the reducing water supply until the new reservoirs are functional. Acknowledgment of the study limitations and Future Research: In this study, the socio-economic data availability and the high-altitude climatic stations’ data scarcity were the significant constraints. This issue has been highlighted by many other studies in the literature [47]. Since we did not include the western (Kabul Basin) and lower part of the Indus Basin, we would like to recommend that future studies should include the Kabul Basin for water allocation for the managerial point of view. The WEAP model is a flexible tool for hydrological modeling, however, it does have some limitations. For example, it assumes an infinite supply of groundwater which is not the case in reality. Another limitation of the WEAP model is that there is a limited number of catchment hydrologic models (that is, the simplified coefficient method, the soil moisture method, the MABIA method, and the plant growth model method) and this can be a serious constraint if some of the parameters use different catchment models. So, the parameters should be translated from one model to another model. These limitations did not put any constraints on the current study when running the WEAP model for the UIB. However, in the literature, there were some studies that reported that these limitations make a noticeable difference. Arrans and McCartney (2007) suggested that this limitation can be overcome in two ways. Firstly, by developing part of the model externally, and secondly, by building the model separate from the WEAP in order to calculate the WEAP output for downstream [48].

Author Contributions: Ali Amin and Javed Iqbal conceived and designed the study; Ali Amin run the WEAP model and collected and analyzed all the data. Ali Amin, Javed Iqbal, Areesha Asghar wrote the paper. Javed Iqbal extensively reviewed the article. Lars Ribbe provided extensive help in providing training on WEAP modeling. Funding: This research received no external funding. Acknowledgments: The authors acknowledge the financial support of National University of Sciences and Technology (NUST), Islamabad for collecting data and Technology Arts Sciences TH Köln, Köln, Germany provided technical support to run the WEAP model. The authors also acknowledge Junaid Aziz for his support for data processing, WAPDA, IRSA and Ghulam Fareed from PMD for providing streamflow and meteorological data. Conflicts of Interest: The authors declare no conflict of interest.

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