Abstract
This research uses the simulation–optimization approach for the conjunctive use of surface and underground water in climate change conditions. For this purpose, Multi-Objective Invasive Weed Optimization Algorithm (MOIWOA) is developed for three benchmark functions in order to verify the algorithm and its results in the form of Pareto Front with MOPSO and NSGA-II were compared. Then, developed MOIWOA is applied for optimal water allocation to drinking-industry and agricultural needs in order to (1) maximize reliability index of water supply system, and (2) maximize resiliency index of a water supply system(from a failure period due to lack of water supply). The findings show that the model effectively reduces failure periods and allocates water resources efficiently to consumption sectors during hot months. The highest increase in reliability and resiliency indexes is observed in the RCP85 climate change scenario (as pessimistic scenario) for time period 2070–2099, with an 11% increase in reliability and a 66% increase in resiliency. In this research, Gray Relationship Analysis (GRA) is used to select the best solution from the set of Pareto solutions. Also, multi-objective solutions are prioritized and ranked based on Gray Relational Grade (GRG).
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Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Mahdieh Kalhori developed the theory and performed the computations. Seyedeh Hadis Moghadam verified the analytical methods. Parisa-Sadat Ashofteh and Seyedeh Hadis Moghadam encouraged Mahdieh Kalhori to investigate a specific aspect. Parisa-Sadat Ashofteh supervised the findings of this work, and Seyedeh Hadis Moghadam. All authors discussed the results and contributed to the final manuscript. Parisa-Sadat Ashofteh wrote the manuscript. Parisa-Sadat Ashofteh conceived the original idea.
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Kalhori, M., Ashofteh, PS. & Moghadam, S.H. Development of the Multi-Objective Invasive Weed Optimization Algorithm in the Integrated Water Resources Allocation Problem. Water Resour Manage 37, 4433–4458 (2023). https://doi.org/10.1007/s11269-023-03564-3
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DOI: https://doi.org/10.1007/s11269-023-03564-3