Irrigation Supply and Demand, Land Use/Cover Change and Future Projections of Climate, in Indus Basin Irrigation System, Pakistan

Sustainable management of canal water through optimum water allocation is the need of the modern world due to the rapid rise in water demand and climatic variations. The present research was conducted at the Chaj Doab, Indus Basin Irrigation System (IBIS) of Pakistan, using the WEAP (Water Evaluation and Planning) model. Six different scenarios were developed, and the results showed that the current available surface water is not sufficient to meet crop water demands. The Lower Jhelum Canal (LJC) command area is more sensitive to water scarcity than the Upper Jhelum Canal (UJC). The future (up to 2070) climate change scenarios for RCP 4.5 and 8.5 showed a decrease in catchment reliability up to 26.80 and 26.28% for UJC as well as 27.56 and 27.31% for LJC catchment, respectively. We concluded that scenario 3 (irrigation efficiency improvement through implementation of a high efficiency irrigation system, canal lining, reduction and replacement of high delta crops with low delta crops) was sufficient to reduce the canal water deficit in order to optimize canal water allocation. Improvement in the irrigation system and cropping area should be optimized for efficient canal water management.


Introduction
Pakistan's economy primarily depends on irrigated agriculture, and it uses more than 95% of its total fresh water resources to irrigate 80% of the cultivatable land, which generates 90% of nutrition and fodder [1]. The agriculture sector's contribution to the GDP of Pakistan is almost 19%, and it provides jobs for 42% of people [2]. Therefore, in Pakistan, water is under stress with susceptible irrigation, and its availability directly influences the socioeconomic situation of the country. An increase in future food demands more water to produce food, but no additional water is available [1]. Globally, water scarcity has risen in preventing plant development as a necessary constraint of the environment in most regions [3,4]. More than 30 countries in arid and semi-arid regions of the world study area altitude varies from 150 to 250 m above mean sea level. The total area of Chaj Doab is 5854 km 2 , covering four districts, i.e., Gujrat, Mandi Bahauddin, Sargodha, and some parts of Jhang. It has mostly flat topography having overall slope from south to west. The dominant soil type is coarse soil with texture between medium to moderate. Silt and sand with a range from fine to medium are mostly present in the upper 183-m part of the soil named alluvium soils. The northeast area has a semi-humid climate while the southwest has a semiarid climate. The summer in this area is very hot, but the winter season is cool. It has a mean annual temperature of 24 • C, while the range is 3 to 27 • C in winter and very hot weather with 20 to 42 • C temperature in summer. The value of the mean annual rainfall is around 600 mm while the value of reference evapotranspiration (ET ref ) is around 1600 mm. The monsoon rainfall contributes a large share in total annual precipitation. The irrigation system of Chaj Doab is primarily composed of two main canals, namely Upper Jhelum Canal (UJC) and Lower Jhelum Canal (LJC). Two branch canals, such as Gujrat branch and Phalia, offtake from UJC, while six branch canals offtake from LJC (Shahpur branch, Northern branch and feeder, Southern branch, Southern Sulki branch, and Khadir feeder). Rice, sugarcane, wheat, citrus, and fodder are the main crops grown in this area [39]. CCSM4 (Community Climate System Model Version 4) data provided by IPCC (Intergovernmental Panel on Climate Change) in 5th Assessment report (AR5) were downscaled for RCP4.5 and RCP 8.5 on resolutions of grid size 25 km.
The present study area is bounded by the rivers Jhelum and Chenab, known as Chaj Doab, within the Indus Basin Irrigation System (IBIS) of Pakistan, as shown in Figure 1. It ranges between longitudes 72°10′E to 74°22′E and latitudes 31°11′ N to 32°58′N. The study area altitude varies from 150 to 250 m above mean sea level. The total area of Chaj Doab is 5854 km 2 , covering four districts, i.e., Gujrat, Mandi Bahauddin, Sargodha, and some parts of Jhang. It has mostly flat topography having overall slope from south to west. The dominant soil type is coarse soil with texture between medium to moderate. Silt and sand with a range from fine to medium are mostly present in the upper 183-m part of the soil named alluvium soils. The northeast area has a semi-humid climate while the southwest has a semiarid climate. The summer in this area is very hot, but the winter season is cool. It has a mean annual temperature of 24 °C , while the range is 3 to 27 °C in winter and very hot weather with 20 to 42 °C temperature in summer. The value of the mean annual rainfall is around 600 mm while the value of reference evapotranspiration (ETref) is around 1600 mm. The monsoon rainfall contributes a large share in total annual precipitation. The irrigation system of Chaj Doab is primarily composed of two main canals, namely Upper Jhelum Canal (UJC) and Lower Jhelum Canal (LJC). Two branch canals, such as Gujrat branch and Phalia, offtake from UJC, while six branch canals offtake from LJC (Shahpur branch, Northern branch and feeder, Southern branch, Southern Sulki branch, and Khadir feeder). Rice, sugarcane, wheat, citrus, and fodder are the main crops grown in this area [39]. CCSM4 (Community Climate System Model Version 4) data provided by IPCC (Intergovernmental Panel on Climate Change) in 5th Assessment report (AR5) were downscaled for RCP4.5 and RCP 8.5 on resolutions of grid size 25km For RCP 4.5 and RCP 8.5, two climatic parameters, i.e, precipitation and rainfall are showing wide variations up to 2070. The mean annual rainfall will decline to around 270 mm and mean annual temp will decrease by 29 °C, respectively both for RCP 4.5 and RCP 8.5.  For RCP 4.5 and RCP 8.5, two climatic parameters, i.e., precipitation and rainfall are showing wide variations up to 2070. The mean annual rainfall will decline to around 270 mm and mean annual temp will decrease by 29 • C, respectively both for RCP 4.5 and RCP 8.5.

WEAP Model Development
The Water Evaluation and Planning (WEAP) model developed by Stockholm Environment Institute was used to achieve the research objectives [26]. The WEAP model is used for integrated water resources management and planning strategies that consider the land use/cover, hydrology of the watershed/region, etc. [26]. The WEAP model was used to simulate the impact of various climate changes, land use/cover and irrigation schemes. The WEAP model is used as a tool for modeling, planning, and management of water resources all over the world [41][42][43]. GIS-based shapefiles of the Chaj Doab irrigation system were added into the WEAP model and schematic created to simulate the required objectives as shown in Figure 3.

WEAP Model Development
The Water Evaluation and Planning (WEAP) model developed by Stockholm Environment Institute was used to achieve the research objectives [26]. The WEAP model is used for integrated water resources management and planning strategies that consider the land use/cover, hydrology of the watershed/region, etc. [26]. The WEAP model was used to simulate the impact of various climate changes, land use/cover and irrigation schemes. The WEAP model is used as a tool for modeling, planning, and management of water resources all over the world [41][42][43]. GIS-based shapefiles of the Chaj Doab irrigation system were added into the WEAP model and schematic created to simulate the required objectives as shown in Figure 3.  The WEAP-MABIA method [44][45][46][47] was used for simulation, which involves the daily basis simulation for different parameters, i.e., irrigation water demand, evapotranspiration, crop growth, irrigation scheduling, crop yield, and also elements such as calculation of soil water capacity and reference evapotranspiration. This method uses the dual 'Kc' method, where Kc value consists of two components [47,48], including basal crop coefficient (Kcb) and soil evaporation Ke. The formula for actual ETa is given in Equation (1) (1) where ETref is reference evapotranspiration, and Ks is soil stress co-efficient. Total available water or available water capacity can be determined by subtracting a wilting point from field capacity, and it can be represented by the Equation (2) as: . .
where TAW stands for total available water, and W.P is named as a wilting point while F.C represents the field capacity of the soil. For reference evapotranspiration, the following Equation (3) was used: where, ETref represents reference evapotranspiration in mm/day, Rn is a net radiation at the crop surface in MJ/m^2/day, G is the soil heat flux density in MJ/m^2/day which can be ignored (G=0), Tmean is the mean air temperature with unit in (°C), u2 represents wind speed at 2 m height in m/s, es shows the saturation vapor pressure in kPa, ea is an actual vapor pressure in kPa, es−ea is the saturation vapor pressure deficit in kPa, Δ is the slope vapor pressure curve measured in kPa/°C, and G is the psychrometric constant in kPa/°C The WEAP-MABIA method [44][45][46][47] was used for simulation, which involves the daily basis simulation for different parameters, i.e., irrigation water demand, evapotranspiration, crop growth, irrigation scheduling, crop yield, and also elements such as calculation of soil water capacity and reference evapotranspiration. This method uses the dual 'K c ' method, where K c value consists of two components [47,48], including basal crop coefficient (K cb ) and soil evaporation K e . The formula for actual ET a is given in Equation (1) where ET ref is reference evapotranspiration, and K s is soil stress co-efficient. Total available water or available water capacity can be determined by subtracting a wilting point from field capacity, and it can be represented by the Equation (2) as: where TAW stands for total available water, and W.P is named as a wilting point while F.C represents the field capacity of the soil. For reference evapotranspiration, the following Equation (3) was used: where, ET ref represents reference evapotranspiration in mm/day, R n is a net radiation at the crop surface in MJ/mˆ2/day, G is the soil heat flux density in MJ/mˆ2/day which can be ignored (G = 0), T mean is the mean air temperature with unit in ( • C), U 2 represents wind speed at 2 m height in m/s, es shows the saturation vapor pressure in kPa, ea is an actual vapor pressure in kPa, es−ea is the saturation vapor pressure deficit in kPa, ∆ is the slope vapor pressure curve measured in kPa/ • C, and G is the psychrometric constant in kPa/ • C [16]. The detailed research layout is shown in Figure 4.

Scenarios Developed in WEAP Modeling Framework
WEAP works on what-if type of scenarios and provides a good comparison between reference and future scenarios [26,49,50]. The impact of six different scenarios (Table 2) was tested on unmet demand and reliability of the system against the reference scenario. The current account year was 2006, and it was extended up to 2070 to simulate the reference scenario for the purpose of comparison, analysis and evaluation of other future scenarios. All the scenarios were created under the reference scenario in the WEAP model for comparison with future scenarios. The efficiency of different irrigation systems was considered as follows: drip irrigation efficiency 80-91% and sprinkler 54-80%. In scenario 2, the area of high delta crops was reduced and replaced with crops that have low water requirements. The 50% area of rice crop was reduced while keeping in mind the importance of rice demand, and this percent was added or given to maize, sorghum and very small percent to cotton although it requires much water, but water requirement of cotton is less than rice.
In scenario 4, the canals are operating at less than design discharge because of addition of silt and other debris materials that continuously decrease its capacity. By proper maintenance and silt removal the canal capacity will be increased. Canal capacity is enhanced by increasing diversions from river into the canals, which ultimately results in more water supplies to catchment. The inflows to the canals were increased by allocating 20% more water to the canal from the Jhelum River to use it as an allocation plan. So by allocating more water through diversion, unmet demand could be decreased, but this percent is minute.

Scenarios Developed in WEAP Modeling Framework
WEAP works on what-if type of scenarios and provides a good comparison between reference and future scenarios [26,49,50]. The impact of six different scenarios (Table 2) was tested on unmet demand and reliability of the system against the reference scenario. The current account year was 2006, and it was extended up to 2070 to simulate the reference scenario for the purpose of comparison, analysis and evaluation of other future scenarios. All the scenarios were created under the reference scenario in the WEAP model for comparison with future scenarios. The efficiency of different irrigation systems was considered as follows: drip irrigation efficiency 80-91% and sprinkler 54-80%. In scenario 2, the area of high delta crops was reduced and replaced with crops that have low water requirements. The 50% area of rice crop was reduced while keeping in mind the importance of rice demand, and this percent was added or given to maize, sorghum and very small percent to cotton although it requires much water, but water requirement of cotton is less than rice. In scenario 4, the canals are operating at less than design discharge because of addition of silt and other debris materials that continuously decrease its capacity. By proper maintenance and silt removal the canal capacity will be increased. Canal capacity is enhanced by increasing diversions from river into the canals, which ultimately results in more water supplies to catchment. The inflows to the canals were increased by allocating 20% more water to the canal from the Jhelum River to use it as an allocation plan. So by allocating more water through diversion, unmet demand could be decreased, but this percent is minute.
where Qo represents observed flow and Qs shows simulated flow,Qs is mean of the simulated flow and n is the number of observations.

Model Calibration and Validation
The WEAP model was subjected to calibration from years 2006 to 2010 and for validation from 2011 to 2016, as presented in Figure 6. The statistical parameters such as R2, NSE co-efficient, PBIAS were tested to observe model calibration and validation on observed and simulated average monthly streamflow. For calibration of UJC, the monthly values for observed flows (m 3 /s) from January to December were 52,145,157,192,205,199,201,186,189,172,197

Model Calibration and Validation
The WEAP model was subjected to calibration from years 2006 to 2010 and for validation from 2011 to 2016, as presented in Figure 6. The statistical parameters such as R2, NSE co-efficient, PBIAS were tested to observe model calibration and validation on observed and simulated average monthly streamflow. For calibration of UJC, the monthly values for observed flows (m 3 /s) from January to December were 52,145,157,192,205,199  The negative sign indicates that the simulated flow is lower than the observed flow. For the satisfactory performance of the model, the values of PBIAS should be in the range of ±25% in the case of streamflow. NSE should be >0.50, and the range for R2 (0-1), with 1 is an indication of a perfect match between simulated and observed flows and vice versa [51]. The resulted statistical values are clearly showing a good match between the measured and simulated flows.

WEAP Model Simulations to Estimate Canal Water Deficit
The WEAP model simulated results for required irrigation water and water supply for UJC and LJC command areas are presented in Figure 7 for the entire study period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). The overall water demand of both the canal command areas of UJC and LJC was 4086 million cubic meters (MCM) and 10,607 million cubic meters (MCM), respectively. LJC has more culturable command areas as compared to UJC and thus has more  The negative sign indicates that the simulated flow is lower than the observed flow. For the satisfactory performance of the model, the values of PBIAS should be in the range of ±25% in the case of streamflow. NSE should be >0.50, and the range for R2 (0-1), with 1 is an indication of a perfect match between simulated and observed flows and vice versa [51].
The resulted statistical values are clearly showing a good match between the measured and simulated flows.

WEAP Model Simulations to Estimate Canal Water Deficit
The WEAP model simulated results for required irrigation water and water supply for UJC and LJC command areas are presented in Figure 7 for the entire study period (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). The overall water demand of both the canal command areas of UJC and LJC was 4086 million cubic meters (MCM) and 10,607 million cubic meters (MCM), respectively. LJC has more culturable command areas as compared to UJC and thus has more water demand. The volume of water supplied to UJC and LJC command areas was 1888.8 MCM and 2066.4 MCM, respectively. It is evident from these graphs that the supplied volume of water is not enough to fulfill water demands for both canal commands. However, the demands for irrigation water are higher in the Kharif (Summer) crops (i.e., rice and sugarcane) as compared to Rabi (Winter) crops (i.e., wheat and fodder); see Figure 7. water demand. The volume of water supplied to UJC and LJC command areas was 1888.8 MCM and 2066.4 MCM, respectively. It is evident from these graphs that the supplied volume of water is not enough to fulfill water demands for both canal commands. However, the demands for irrigation water are higher in the Kharif (Summer) crops (i.e., rice and sugarcane) as compared to Rabi (Winter) crops (i.e., wheat and fodder); see Figure 7.  The mean annual unmet demand (i.e., water deficit) for the UJC and LJC command areas were 2197.2 MCM and 8540.6 MCM, respectively. Unmet demand gets a peak value in June-August although supplies are greater in these months. The high evapotranspiration rate with rise in temperature in these months (June-August) creates demands for more water [52]. Moreover, the rice and sugarcane water requirement is significantly high. Therefore, the unmet demand is higher in the months of June, July and August.

Canal Catchment Reliability
The simulated results of the WEAP model showed that the reliability of canal command is decreasing, for example, 61.15% in the Upper Chenab Canal command and 46.41% in the Lower Jhelum Canal command. The relatively smaller percentage of relia- The mean annual unmet demand (i.e., water deficit) for the UJC and LJC command areas were 2197.2 MCM and 8540.6 MCM, respectively. Unmet demand gets a peak value in June-August although supplies are greater in these months. The high evapotranspiration rate with rise in temperature in these months (June-August) creates demands for more water [52]. Moreover, the rice and sugarcane water requirement is significantly high. Therefore, the unmet demand is higher in the months of June, July and August.

Canal Catchment Reliability
The simulated results of the WEAP model showed that the reliability of canal command is decreasing, for example, 61.15% in the Upper Chenab Canal command and 46.41% in the Lower Jhelum Canal command. The relatively smaller percentage of reliability shows more water shortage in those canal command areas for irrigation water. Water supply reliability is largely affected by water demand, water storage and changes in inflow caused by climate variabilities.

Future Water Allocation Scenarios
The scenario analysis as described in Table 2 was performed in the WEAP model to optimize the allocated water to the demand sites in order to reduce canal water deficit. The effect of these scenarios was checked on the reliability of the demand sites. Demand site reliability for all the scenarios was compared with the reliability of the reference scenario (Figures 8 and 9). The results showed that with the implementation of the first scenario, the reliability of the UJC command area could be increased from 61% to 75%. On the other hand, LJC command area reliability would improve from 46% to 50%. ainability 2021, 13, x FOR PEER REVIEW 12 o

Future Water Allocation Scenarios
The scenario analysis as described in Table 2 was performed in the WEAP mode optimize the allocated water to the demand sites in order to reduce canal water defi The effect of these scenarios was checked on the reliability of the demand sites. Dema site reliability for all the scenarios was compared with the reliability of the reference s nario (Figures 8 and 9). The results showed that with the implementation of the first s nario, the reliability of the UJC command area could be increased from 61% to 75%. the other hand, LJC command area reliability would improve from 46% to 50%.   The results of the percentage reliability change between the reference and other s narios are presented in Table 4. Results showed that by simulating the second scena reliability of the UJC and LJC commands could be enhanced from 61 to 71% and 46 51%, respectively. In Scenario 3, results highlighted that the demand site reliability for UJC command could be maximized up to 84% from 61% showing a 23% increase in re bility. For the LJC command, the reliability would increase from 46% to 54%, an 8% crease. Thus, this strategy seems very effective, especially in the UJC area. Under scena 4, results showed that after water allocation, the reliability for the UJC demand site wo be increased from 61 to 64%, while for LJC it would increase from 46 to 47%. Results scenario 5 showed that the demand site reliability for the Upper Chaj Doab would crease from 61 to 34.36%, while for Lower Chaj Doab it would also decrease from 46 18.8%. Results for scenario 6 also showed a decrease in reliability for both catchment are in UJC from 61 to 34.87% and in LJC 46 to 19.10%.  The results of the percentage reliability change between the reference and other scenarios are presented in Table 4. Results showed that by simulating the second scenario, reliability of the UJC and LJC commands could be enhanced from 61 to 71% and 46 to 51%, respectively. In Scenario 3, results highlighted that the demand site reliability for the UJC command could be maximized up to 84% from 61% showing a 23% increase in reliability. For the LJC command, the reliability would increase from 46% to 54%, an 8% increase. Thus, this strategy seems very effective, especially in the UJC area. Under scenario 4, results showed that after water allocation, the reliability for the UJC demand site would be increased from 61 to 64%, while for LJC it would increase from 46 to 47%. Results for scenario 5 showed that the demand site reliability for the Upper Chaj Doab would decrease from 61 to 34.36%, while for Lower Chaj Doab it would also decrease from 46 to 18.8%. Results for scenario 6 also showed a decrease in reliability for both catchment areas, in UJC from 61 to 34.87% and in LJC 46 to 19.10%.

Discussion
The present study simulated the water demand, several irrigation water allocations practices and future climatic scenarios that were taken into consideration for development of sustainable management of canal water in Chaj Doab, within the Indus Basin Irrigation System (IBIS). Results showed a large gap between water supply and demand in the study area. The water supply in canals is greater in Kharif months (April-October) as compared to the Rabi months (October-March) because of the monsoon season, which results in more rainfall. However, the monsoon season (July-September) and western disturbances contribute a major part of the annual rainfall [53,54]. There are two pairs of months in a year that are recognized as dry periods (April-June and October-November), but mainly two months, October and November [53][54][55]. On the other hand, temperature records are very high in summer months, particularly in June and July [40,56,57]. In Kharif season, the evapotranspiration is greater due to high temperatures, which results in more water demand in these months and hence, water requirement is not satisfied [57,58]. The irrigation water requirement shows a rising trend due to maximum ET in Kharif months from May-August and a low trend in Rabi months during December-January. This large gap is due to less water availability for the crops as compared to their actual water requirement [57][58][59]. The calculation of agricultural water demand highly depends upon the determination of evapotranspiration (ET) [19]. As ET has a direct relationship with crop water demand, the water demand gets a peak value in June, July, August and up to the middle of September because of high temperature, which results in more evapotranspiration.
The unmet demand is greater in November-January because this month's water supply decreases while cropping intensity increases. Unmet demand decreases in April because Rabi crops are harvested in this month mostly [57,58]. It is of paramount importance to strategically manage the current water resources in order to understand and forecast the hydrological response of this complicated system [39,60]. Scenarios were developed on the basis of water management strategies as well as future climatic variations to optimize the water allocation. Demand site management strategies include water use efficiency improvement, irrigation technology adaptation and a shift towards low water-intensive crops [57][58][59]. Supply management strategies include water supply enhancement by developing storage, inter-region transfer and modifying current operational rules to fulfill water demand [40,58]. Increments in water-use efficiency involve a shift towards a more effective system, for example, sprinkler and drip irrigation instead of less-effective flood and furrow irrigation [52,61]. Shifting towards irrigation technologies was incorporated [62], and that was found to be efficient in increasing irrigation efficiency. A scenario of management through irrigation technology was conceptualized [63], which resulted in fulfilling water demand of crops with less water application. Water conservation techniques such drip and sprinkler irrigation were employed in the WEAP model and their impact on demand site reliability were predicted [64]. The inefficient canal irrigation system of Pakistan results in a large loss of water quantity before it reaches the field crops [39,65,66]. In unlined canals, seepage rates are usually four times greater than lined canals' seepage rates. Although there very little seepage losses from lined canals, however, about 60 to 80 % of water losses can be saved as compared to unlined canals.
The canal-lining scenario for improvement of conveyance efficiency was analyzed by [52,64]. The scenario analysis indicates that the adaptation of high-water requiring crops, i.e., sugarcane must be replaced with crops that consume less water for demand reduction and that will in turn save water [14,67,68]. A combination of alteration in cropping patterns and irrigation-system improvement is necessary and more effective in reducing irrigation water demand [38,69]. Similar research shows that an increase in irrigation efficiency with a change in cropping patterns is essential for attaining agricultural as well as environmental sustainability, and this strategy also increases reliability [52]. Lining of canals and application of a sprinkler irrigation system maximize system reliability up to 17% and 25%, respectively [64]. Water supplies can be enhanced by increasing diversion from the river into main canals, and more water can be allocated to reduce the unmet demand of water. Maintenance of canals can also increase water supplies.
Future climate change is expected to exaggerate the water shortage. For climate change scenarios, the water shortage difference primarily arises when water use rate is highest. Climate change largely effects water use, but it has comparatively small effects on irrigation water supply as well as its availability [69]. Multiple studies have predicted the impact of climate change on irrigation water demand or possible climate change adaptation pathways [63]. Variations in patterns of snow, precipitation and glacier melting may change the flow timings [1]. Variation in flows and changes in the climate have been going to affect irrigated-agriculture productivity with a significant change in net benefits. However, crop yields are expected to decrease because of climate change [70,71]. Under climate change scenarios, it has been clearly shown by the results that unmet demand will rise in the future as compared to the reference scenario [72]. Results also displayed that unmet water demand is higher under the climate change scenario with RCP 4.5 as compared to the climate change scenario with RCP 8.5 [73]. Demand site water management approaches, i.e., variable cropping structure and improved irrigation systems, will be effective in reducing adverse climate change impacts [69].

Proposed Strategies and Conclusions
Based on the findings of the current study and scenario analyses, different strategies are proposed for efficient and effective utilization of the present water resources. Scenario 3, which includes the combined application of improving irrigation systems and reducing and replacing high-water requiring crops with lower-water consuming crops, should be practically implemented. Operate canals at full supply levels, and proper maintenance should be enforced. Rainwater should be harvested, particularly in the monsoon season, by building small storage reservoirs or ponds for dry-period use. Based on future climate change, respective alternate water regulation policies should be revised and replanned based on the crop types, the area covered, and on-field water requirements for efficient water allocation. The main findings of this study are listed below: 1.
The annual water demand for the UJC and LJC canal catchment was found to be 4086, and 10,607 million cubic meters (MCM), and the yearly water shortage was found to be 2197.2 and 8540.6 MCM with catchment reliability of 61 and 46%, respectively. Currently, available surface water is not sufficient to meet the demand for agricultural water; 2.
The LJC command area is more sensitive to water scarcity, as this area is more than twice the UJC command area with less LJC design discharge as compared to UJC; 3.
It is concluded that by adopting scenario 3 (irrigation efficiency improvement through implementation of high-efficiency irrigation systems, canal lining, reduction and replacement of high delta crops with low delta crops), the system reliability can be maximized up to 84% and 54% for the UJC and LJC command areas, respectively;