Abstract

Global climate change and escalating water demand are exacerbating the burden on watershed management. In pursuit of a resilient water management framework, supportive of local economic growth and social stability, it is prudent for watershed management authorities to sequentially address the intricacies. The foremost step involves resolving supply–demand conflicts stemming from the seasonal ebb and flow before embarking on the development of an optimal dynamic allocation strategy. Therefore, this study has crafted a dynamic, seasonally responsive, multi-objective, multi-period water allocation system that harmonizes three pivotal objectives: economic efficiency, equity, and utilization efficiency. Then, to effectively mitigate the economic risks associated with uncertainty, the dynamic allocation framework incorporates the VaR and accounts for uncertainties in available surface water resources. Employing the improved adaptive self-constrained NSGA-III algorithm, we endeavored to simulate the optimal equilibrium solution in the face of various risks and facilitate a tradeoff between these objectives through a multi-period interaction mechanism. This iterative process displayed convergence within the range of 1.75 × 104 and 2.45 × 104 iterations. The proposed model was implemented to address the pressing issue of unsustainable water allocation within the MRB system in western China. Its validity and practicability were confirmed, and water allocation strategies were simulated across three distinct risk scenarios: high, medium, and low. Significantly, these findings have highlighted Chengdu as the focal area for considerable water apportionment. In light of this revelation, an emergency cooperation system has been established to address water shortages and uncertainties. Furthermore, some policy recommendations designed to guide watershed managers in the effective allocation of water resources.

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