摘要
随着城市化进程的加快,水资源供需不平衡成为影响地区经济发展的"瓶颈"。科学的需水预测是规划区域未来发展的重要条件之一。基于系统动力学模型的需水预测将复杂的社会用水系统分解成多个子系统,可以清晰地展示出各用水子系统的需水动态过程,得到较精确的需水预测结果。以成都青白江区为例,结合区域用水结构和产业结构,介绍了系统动力学模型用作需水预测时的建模流程。通过青白江区的用水现状和参数敏感性分析结果,设计出现状发展方案、农业节水方案、工业改良方案和综合发展方案4种需水方案。通过对4种方案模拟结果的对比分析,并考虑"三条红线"指标,选择综合发展方案作为青白江区未来需水预测的最佳方案。模拟结果为:青白江区2020年、2025年的总需水量分别为3.95亿m^3、3.99亿m^3。通过合理性分析验证模拟结果的可靠性,并提出了保障方案实施的建议措施,以期为青白江区未来的水资源规划提供依据。
The imbalance between water supply and demand due to the fast urbanization has become the bottleneck of regional economic development. Thus, predicting water demand in scientific way is one of the prerequisites for the planning of regional development; and when predicting water demand, it is possible to decompose a complicated social system into several subsystems using the system dynamics model, and therefore the dynamic water demand process of each subsystem, as well as more accurate water demand prediction results are obtained. This paper elaborates on the modeling process when system dynamics model was used as water demand forecast combined with the structures of regional water consumption and industries with a case study in Qingbaijiang District of Chengdu City. With the results of analyzing the current water supply/consumption in the District and the relevant parameter sensitivity, four kinds of scheme are designed regarding the status quo water utilization, agricultural water-saving, industrial improvement and comprehensive development; and finally the comprehensive development scheme is selected as the best scheme for prediction of water demand in the District, the reliability of simulation result is verified through the analysis of the rationality test. As a result, the total water demand of the District is 395 million m^3 in 2020 and 399 million m^3 in 2025. In addition, suggestions for implementation of the comprehensive development scheme are put forward.
出处
《环境科学与技术》
CAS
CSCD
北大核心
2017年第4期200-205,共6页
Environmental Science & Technology
基金
国家重点基础研究发展计划(2015CB452701)
国家自然科学基金面上项目(51579161)
关键词
系统动力学模型
需水预测
敏感性分析
方案比选
system dynamics model
water demand prediction
sensitivity analysis
scheme comparison
