• Energy Research

Water sector planning and policy making in arid and semi-arid regions are challenging because many drivers and decision criteria require consideration. In this study, a multi-period mixed-integer linear programming model was developed to integrate and economically evaluate water management options for water supply in arid regions. The applicability of the proposed approach was demonstrated through a case study in the Emirate of Abu Dhabi (EAD), United Arab Emirates. The model was programmed in general algebraic modeling system (GAMS) and solved using the Cplex solver. The model determined the optimal economic and environmental costs, capacity expansion of treatment plants and water transmission systems, and other environmental aspects including the carbon footprint and brine discharge. Results show that the capacity contribution of reverse osmosis for desalination is expected to increase from 5.1% in 2021 to 18.1% in 2050. Based on the model's results for the case study, it was concluded that even with moderate consideration of environmental aspects, desalination plants in the EAD need a major technology transformation from thermal desalination to reverse osmosis The proposed model is proved to be effective for integrated water resources management and infrastructure planning in the EAD, and has the potential for effective application in other arid or semi-arid countries.

Water sector planning and policy making in arid and semi-arid regions are challenging because many drivers and decision criteria require consideration. In this study, a multi-period mixed-integer linear programming model was developed to integrate and economically evaluate water management options for water supply in arid regions. The applicability of the proposed approach was demonstrated through a case study in the Emirate of Abu Dhabi (EAD), United Arab Emirates. The model was programmed in general algebraic modeling system (GAMS) and solved using the Cplex solver. The model determined the optimal economic and environmental costs, capacity expansion of treatment plants and water transmission systems, and other environmental aspects including the carbon footprint and brine discharge. Results show that the capacity contribution of reverse osmosis for desalination is expected to increase from 5.1% in 2021 to 18.1% in 2050. Based on the model's results for the case study, it was concluded that even with moderate consideration of environmental aspects, desalination plants in the EAD need a major technology transformation from thermal desalination to reverse osmosis The proposed model is proved to be effective for integrated water resources management and infrastructure planning in the EAD, and has the potential for effective application in other arid or semi-arid countries.

Study region: Abu Dhabi, United Arab Emirates (UAE) Study focus: Water demand in the Emirate of Abu Dhabi (EAD) has increased significantly over the last few decades. Hence, a main challenge for the EAD water policy makers is to develop long-term resilient water resources strategies. This study evaluates future water supply-demand condition in the EAD and identifies water management strategies that support a sustainable future. A dynamic water budget modelling framework is used to evaluate future water demand as affected by population growth, economic growth, proposed water related policies, consumption patterns, and climate change. The Abu Dhabi Dynamic Water Budget Model (ADWBM) is used to construct future water scenarios and assess the status of the EAD water system until 2050 in terms of water supply-demand balance. This study presents four suites of water scenarios, namely: Business as Usual (BAU), Policy First (PF), Sustainability by Conservation (SC), and Rainfall Enhanced Sustainability (RES) scenarios. New hydrological insights: Simulation results indicate that both SC and RES scenarios achieved balanced water budget without any shortage throughout the entire period until 2050. The RES scenario is recommended for adoption because of the reasonable and achievable proposed consumption reductions needed in the different demand sectors. The obtained results should be valuable for devising appropriate strategies to prevent potential future water shortages in the Emirate.

Study region: Abu Dhabi, United Arab Emirates (UAE) Study focus: Water demand in the Emirate of Abu Dhabi (EAD) has increased significantly over the last few decades. Hence, a main challenge for the EAD water policy makers is to develop long-term resilient water resources strategies. This study evaluates future water supply-demand condition in the EAD and identifies water management strategies that support a sustainable future. A dynamic water budget modelling framework is used to evaluate future water demand as affected by population growth, economic growth, proposed water related policies, consumption patterns, and climate change. The Abu Dhabi Dynamic Water Budget Model (ADWBM) is used to construct future water scenarios and assess the status of the EAD water system until 2050 in terms of water supply-demand balance. This study presents four suites of water scenarios, namely: Business as Usual (BAU), Policy First (PF), Sustainability by Conservation (SC), and Rainfall Enhanced Sustainability (RES) scenarios. New hydrological insights: Simulation results indicate that both SC and RES scenarios achieved balanced water budget without any shortage throughout the entire period until 2050. The RES scenario is recommended for adoption because of the reasonable and achievable proposed consumption reductions needed in the different demand sectors. The obtained results should be valuable for devising appropriate strategies to prevent potential future water shortages in the Emirate.

Water demand forecasting plays an important role in the sustainable management of water resources, especially in countries facing water scarcity challenges, such as the United Arab Emirates (UAE). Al-Ain, the second-largest city within the Emirate of Abu Dhabi and the fourth largest in the UAE, faces the dual challenge of anticipated population growth and forthcoming development initiatives. These factors are set to exert added pressure on the city’s water resources. Hence, Al-Ain City requires an immediate assessment of future water demands as a critical step toward achieving sustainable development. The main objective of this study is to conduct a systematic analysis of historical consumption patterns and other relevant factors to predict future water demand and to present a water demand forecasting model to project the water requirements of Al-Ain City up to the year 2030. The proposed “Linear Forecast Model” for Al-Ain City is developed using the IWR-MAIN software (Version 6.0), with its core code developed by the U.S. Army Corps of Engineers’ Institute for Water Resources. The results of this model suggest that the total water demand is projected to increase by 45% by the year 2030. Among the sectors, the residential sector is expected to have the highest water demand, accounting for approximately 61% of the total water demand by 2030. The governmental and agricultural sectors are estimated to contribute 20% and 10% to the total demand, respectively, with the remaining 9% distributed across the other four sectors.

Water demand forecasting plays an important role in the sustainable management of water resources, especially in countries facing water scarcity challenges, such as the United Arab Emirates (UAE). Al-Ain, the second-largest city within the Emirate of Abu Dhabi and the fourth largest in the UAE, faces the dual challenge of anticipated population growth and forthcoming development initiatives. These factors are set to exert added pressure on the city’s water resources. Hence, Al-Ain City requires an immediate assessment of future water demands as a critical step toward achieving sustainable development. The main objective of this study is to conduct a systematic analysis of historical consumption patterns and other relevant factors to predict future water demand and to present a water demand forecasting model to project the water requirements of Al-Ain City up to the year 2030. The proposed “Linear Forecast Model” for Al-Ain City is developed using the IWR-MAIN software (Version 6.0), with its core code developed by the U.S. Army Corps of Engineers’ Institute for Water Resources. The results of this model suggest that the total water demand is projected to increase by 45% by the year 2030. Among the sectors, the residential sector is expected to have the highest water demand, accounting for approximately 61% of the total water demand by 2030. The governmental and agricultural sectors are estimated to contribute 20% and 10% to the total demand, respectively, with the remaining 9% distributed across the other four sectors.