薛晴,杨侃

• 1:河海大学水文水资源学院

摘要(Abstract)：

为量化调控指标对水资源承载力未来发展态势的影响程度，以优化配置水资源并充分发挥其综合效益，以江苏省为研究对象，构建系统动力学(SD)预测模型，对现状延续下2019—2030年江苏省水资源承载力进行动态模拟。在此基础上耦合遗传算法(GA)改进的Back Propagation人工神经网络(ANN)模型，对水资源承载力进行评分。同时进行障碍度诊断，分析在未来社会经济发展中影响江苏省水资源承载力的障碍因子，依此筛选调控指标。运用情景分析法，针对调控指标设置五种调控方案，分析污废水排放总量、氨氮排放量、化学需氧排放量(COD)、生产用水量和居民生活用水量5个反映用水水量和排放水水质的量质要素的变化趋势以及水资源承载力评分走势，结果表明：江苏省水资源承载力不断恶化，较2019年、2030年水资源承载力评分下降9.61%,氨氮排放量提高6.82%,总用水量提高23.94%,难以满足未来经济社会发展的需要。方案1、方案2及方案4从降低用水总量角度出发，方案3从控污角度出发，都有效改善了水资源承载力，但均无法逆转水资源承载力在2019—2030年的下降态势；方案5统筹考虑节流、调整产业结构和水污染处理调控措施，较2019年、2030年水资源承载力评分提高3.15%,氨氮排放量下降44.13%,总用水量下降9.90%,有效缓解水资源供需压力、改善水环境质量，实现了江苏省水资源承载力在未来年份中的稳步提升，为优化水资源调控提供建设性依据。

关键词(KeyWords)： 水资源承载力;系统动力学;BP神经网络;障碍度模型;调控指标;情景分析

Abstract:

Keywords:

基金项目(Foundation): 山西省水利科学技术研究与推广资助项目(2017DSW02);; 国家重点基础研究发展计划(973计划)资助项目(2012CB417006);; 国家科技支撑计划资助项目(2009BAC56B03)

作者(Author): 薛晴,杨侃

DOI: 10.13928/j.cnki.wrahe.2022.11.009

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