Analyzing water resources with sector characteristics in Fujian Province utilizing S2-DR-BIMCCP model integrated with the Gini coefficient

作     者：Bai, Ruolin Jin, Lei Fan, Yurui Zhang, Xi Yin, Ruoyu Wei, Yi 

作者机构：Xiamen Univ Technol Coll Environm Sci & Engn Xiamen 361024 Fujian Peoples R China Brunel Univ London Dept Civil & Environm Engn Uxbridge UB8 3PH Middx England 

出 版 物：《JOURNAL OF CLEANER PRODUCTION》 (J. Clean. Prod.)

年 卷 期：2025年第490卷

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 

基　　金：Fujian Natural Science Foundation [2021J011176] Xiamen University of Technology National Natural Science Foundation Key Project [XPYM2408] 

主　　题：Bi-level multi-objective programming Double-sided stochastic chance-constrained Urban agglomerations Water resources allocation Gini coefficient 

摘      要：Water resource challenges faced by region encompass the entire spectrum of resource development and utilization, including resource stress and imbalances among diverse social users. To address these challenges, an innovative S2-DR-BIMCCP model incorporating the Gini coefficient was developed. This approach presents a linearized formulation and a comprehensive set of incremental solutions for reconciling interval issues in bi-level multi-objective programming models. The S2-DR-BIMCCP model was applied to address water scarcity and uneven water resource programming for three distinct water-use sectors within an urban agglomeration comprising nine cities. The findings indicate that as the risk of breaching system constraints escalates, the validity of the model resulted in an increase in the system benefit from [2075.95, 8148.68] x 109 Chinese Yuan (CNY) to [2457.03, 9979.98] x 109 CNY. Simultaneously, water equity in the system gradually increases, resulting in a decrease in the Gini coefficient from [0.1618, 0.2338] to [0.0948, 0.2383]. The model predicted a gradual increase in livestock water allocation under varying circumstances, ultimately reaching a projected total water supply of 2.63 x 109 m3 in 2030. The conclusion was obtained that Fujian Province should further optimize the spatial layout and production structure of animal husbandry to enhance the competitiveness of animal husbandry. Finally, a comparative analysis demonstrated that the S2-DR-BIMCCP model effectively balanced the perspectives of multiple decision-makers across different levels. It considered the overall system benefits and equity, integrated the uncertainty factors. Stochastic uncertainty expressed as intervals and probability distributions is carefully handled, significantly improving the ability to handle uncertainty in fuzzy optimization problems, and offered the flexibility to adjust risks related to violating system constraints. This capability, along with multi-scenario analyses, can