基于改进粒子群算法的榆林市榆阳区水资源供需平衡分析和优化配置
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陕西省重点研发计划项目资助(2024SF-YBXM-589);国家重点研发计划专项课题(2023YFF1305100)


Analysis of water resources supply-demand balance and optimal allocation in Yuyang district, Yulin city, based on improved particle swarm optimization algorithm
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    摘要:

    针对陕北黄土高原典型区域榆林市榆阳区水资源空间分布不均、供需矛盾突出的问题,基于2005-2020年多源数据,结合InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)模型、定额法和空间分析方法,分析水资源供需的时空演变规律。并引入矮猫鼬优化算法(Dwarf Mongoose Optimization Algorithm, DMOA)来改进传统粒子群算法(Particle Swarm Optimization, PSO),结合第二代非支配排序遗传算法(NSGAⅡ)构建了基于DMOA-PSO-NSGAⅡ混合算法的多目标优化模型对榆阳区2035年各部门的用水进行预测和配置。结果表明:(1)2005-2020年榆阳区水资源供给量呈增长趋势(年均增长率6.7%),空间上呈现"南高北低"分布格局。整体用水量持续上升,其中农业与工业用水增长速率较快,且每年用水量在四个部门中占比较大。2005-2020年供需平衡状况逐步改善,高风险区面积缩减至8%,但城镇密集区仍存在缺水风险。(2)改进的DMOA-PSO-NSGAⅡ算法在解集多样性与收敛性上优于传统方法,通过实例证明它是一种可行的对干旱半干旱地区水资源进行优化配置的方法。(3)将供水来源分为地表水、地下水和非常规水,用水来源分为农业用水、工业用水、生活用水、生态用水,通过优化模型求解,得到2035年榆阳区的水资源配置方案。本算法模型与研究结果不仅可以为实现榆阳区水资源的合理配置提供科学依据,也可以为其他小尺度干旱区域的水资源管理提供参考。

    Abstract:

    This study addressed the pressing challenges of uneven spatial distribution of water resources and the acute supply-demand imbalance in Yuyang District, Yulin City. The district represents a typical and representative region of the Loess Plateau in northern Shaanxi. Drawing on a comprehensive dataset covering the period from 2005 to 2020, the research employed a multifaceted analytical framework that integrated the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model, the quota method, and spatial analysis techniques to examine the spatiotemporal evolution of water supply-demand dynamics in the study area.To improve the accuracy and robustness of water resource allocation forecasting, this study introduced the Dwarf Mongoose Optimization Algorithm (DMOA) to enhance the traditional Particle Swarm Optimization (PSO) approach. A hybrid DMOA-PSO-NSGAⅡ model, incorporating the second-generation non-dominated sorting genetic algorithm (NSGAⅡ), was constructed to optimize water allocation across sectors in Yuyang District with projections to 2035. The empirical analysis yielded several key findings: (1) Between 2005 and 2020, Yuyang District experienced a steady increase in water supply, with an average annual growth rate of 6.7%. A clear geographical gradient was observed, with higher supplies concentrated in the southern areas and lower supplies in the north. At the same time, total water consumption showed a continuous upward trend, primarily driven by growing agricultural and industrial demands, which accounted for the majority of annual water use. Although the overall supply-demand balance improved-reducing high-risk areas to only 8% of the district-densely populated urban centers continued to face persistent water scarcity risks. (2) The proposed DMOA-PSO-NSGA-II algorithm outperformed conventional methods in terms of solution diversity and convergence speed, confirming its effectiveness and adaptability for optimizing water allocation in arid and semi-arid regions. (3) Water supply sources were categorized into surface water, groundwater, and unconventional water, while water use was classified into agricultural, industrial, domestic, and ecological water use. Through the optimization model, the water resource allocation scheme for Yuyang District in 2035 was obtained. This plan prioritized the safeguarding of water for living and ecological purposes, strengthened the utilization of unconventional water sources, and proposed comprehensive management strategies for the sustainable utilization and high-quality development of water resources in Yuyang District.This research provided a solid scientific foundation for achieving rational and sustainable water resource allocation in Yuyang District. Furthermore, it offered valuable insights and a replicable reference model that can inform water management strategies in other small-scale arid regions.

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屈宇萌,李君轶,梁伟,吴颖欣,廖逸文.基于改进粒子群算法的榆林市榆阳区水资源供需平衡分析和优化配置.生态学报,2026,46(6):3236~3250

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