Water resources allocation considering water supply and demand uncertainties using newsvendor model-based framework
A novel newsvendor model-based framework for regional industrial water resources allocation that considers uncertainties in water supply and demand was proposed in this study. This framework generates optimal water allocation schemes while minimizing total costs. The total cost of water allocation consists of the allocated water cost, the opportunity loss for not meeting water demand, and the loss of the penalty for exceeding water demand. The uncertainties in water demand and supply are expressed by cumulative distribution functions. The optimal water allocation for each water use sector is determined by the water price, the unit loss of the penalty and opportunity loss, and the cumulative distribution functions. The model was then applied to monthly water allocation for domestic, industrial, and agricultural water use in two counties of Huizhou City, China, whose water supply mainly depends on Baipenzhu Reservoir. The water demand for each water use sector and the monthly reservoir inflow showed good fits with the uniform and P-III distributions, respectively. The water demand satisfied ratio for each water use sector was stable and increased for the optimal water allocation scheme from the newsvendor model-based framework, and the costs were lower compared with the actual water allocation scheme. The novel framework is characterized by less severe water shortages, lower costs, and greater similarity to actual water use compared with the traditional deterministic multi-objective analysis model, and demonstrates strong robustness in the advantages of lower released surplus water and higher water demand satisfied ratio. This novel framework yields the optimal water allocation for each water use sector by integrating the properties of the market (i.e., determining the opportunity loss for not meeting water demand) with the government (i.e., determining the water price and the loss of the penalty for exceeding water demand) under the strictest water resources management systems.
Natural Science Foundation of Guangdong Province[2021A1515010723];National Key Research and Development Program of China[2022YFC3202204];National Natural Science Foundation of China;National Natural Science Foundation of China;
|WOS Research Area|
Science & Technology - Other Topics
|WOS Accession No|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||School of Environmental Science and Engineering|
1.Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds,Institute of Environmental and Ecological Engineering,Guangdong University of Technology,Guangzhou,510006,China
2.Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Guangzhou,511458,China
3.Guangzhou Franzero Water Technology Co.,Ltd.,Guangzhou,510663,China
4.State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
5.School of Civil Engineering,Sun Yat-Sen University,Zhuhai,519082,China
|Corresponding Author Affilication||School of Environmental Science and Engineering|
He，Yanhu,Zheng，Yanhui,Chen，Xiaohong,et al. Water resources allocation considering water supply and demand uncertainties using newsvendor model-based framework[J]. Scientific Reports,2023,13(1).
He，Yanhu,Zheng，Yanhui,Chen，Xiaohong,Liu，Binfen,&Tan，Qian.(2023).Water resources allocation considering water supply and demand uncertainties using newsvendor model-based framework.Scientific Reports,13(1).
He，Yanhu,et al."Water resources allocation considering water supply and demand uncertainties using newsvendor model-based framework".Scientific Reports 13.1(2023).
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