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Integrated Simulation-Optimization Framework for Water Allocation Based on Sustainability of Surface Water and Groundwater Resources
The aim of this study is to develop a framework for the optimal conjunctive use of surface and groundwater in a case study of the Zayandehrud river basin in Iran. The basis of the framework is an integrated simulation-optimization model that can be used to optimize a number of decisions, including (1) the operation of a reservoir, (2) allocations of water to irrigation canals, and (3) withdrawals from the river and groundwater sources. A water evaluation and planning system (WEAP) model is coupled with the nondominated sorting genetic algorithm II (NSGA-II) optimization algorithm to optimize the following two criteria: (1) a fuzzy sustainability criterion, and (2) the normalized shortfall of supply compared to demand. Each point on the generated Pareto front corresponds to a set of releases from the reservoir and allocations from surface and groundwater resources to the various agricultural regions. A compromise solution is selected from the Pareto front using an established method. The total sustainability of the compromise solution is 26% higher than that obtained previously by using the simulation model alone. It also represents an increase in the sustainability of the reservoir by 37% and the sustainability of the aquifers by 16%.
Integrated Simulation-Optimization Framework for Water Allocation Based on Sustainability of Surface Water and Groundwater Resources
The aim of this study is to develop a framework for the optimal conjunctive use of surface and groundwater in a case study of the Zayandehrud river basin in Iran. The basis of the framework is an integrated simulation-optimization model that can be used to optimize a number of decisions, including (1) the operation of a reservoir, (2) allocations of water to irrigation canals, and (3) withdrawals from the river and groundwater sources. A water evaluation and planning system (WEAP) model is coupled with the nondominated sorting genetic algorithm II (NSGA-II) optimization algorithm to optimize the following two criteria: (1) a fuzzy sustainability criterion, and (2) the normalized shortfall of supply compared to demand. Each point on the generated Pareto front corresponds to a set of releases from the reservoir and allocations from surface and groundwater resources to the various agricultural regions. A compromise solution is selected from the Pareto front using an established method. The total sustainability of the compromise solution is 26% higher than that obtained previously by using the simulation model alone. It also represents an increase in the sustainability of the reservoir by 37% and the sustainability of the aquifers by 16%.
Integrated Simulation-Optimization Framework for Water Allocation Based on Sustainability of Surface Water and Groundwater Resources
Chakraei, Iman (author) / Safavi, Hamid R. (author) / Dandy, Graeme C. (author) / Golmohammadi, Mohammad H. (author)
2021-01-06
Article (Journal)
Electronic Resource
Unknown
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