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Simulation and optimization of water supply and demand balance in Shenzhen: A system dynamics approach

机译:深圳市供需平衡的模拟与优化:系统动力学方法

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As a typical rapid urbanization area and an emerging scientific and technological creative center, Shenzhen is confronted with the pressure of balancing water supply and demand. Based on clarifying the whole water cycle of the city, a system dynamics model was constructed to investigate the complex interactions throughout the water cycle within the social-economic-ecological system. Water supply and demand in Shenzhen City was simulated from 2015 to 2030. The results show that the water supply and demand (WSDR) of Shenzhen will steadily decline in future years, which indicates a serious scarcity of water resources and conflicts between water supply and demand in this region. Based on the sensitivity analysis, six parameters were identified as the most influential factors on water supply and demand in Shenzhen. They are the growth rate of secondary industry, the growth rate of tertiary industry, the utilization rate of surface water resources, the comprehensive utilization rate of wastewater, the per capita domestic water demand and the water consumption per unit of value of added industrial output. To avoid water resource shortages in the future, a scenario analysis was conducted using these parameters as control variables. The values of these control variables were set with integrated social and economic development targets. The results showed that water supply and demand (WSDR) will increase from 0.89 in the baseline scenario to 1.04 in the optimized scenario in 2020 and from 0.64 to 1.05 in 2030. (C) 2018 Elsevier Ltd. All rights reserved.
机译:作为典型的快速城市化地区和新兴的科技创新中心,深圳面临着平衡供需的压力。在阐明整个城市水循环的基础上,建立了系统动力学模型,以研究整个社会经济生态系统中整个水循环的复杂相互作用。以2015年至2030年为例,对深圳市的供需情况进行了模拟。结果表明,未来几年深圳市的供需将稳步下降,这说明水资源严重短缺和供需矛盾。在这个地区。在敏感性分析的基础上,确定了六个参数对深圳的水供需影响最大。它们是第二产业的增长率,第三产业的增长率,地表水资源的利用率,废水的综合利用率,人均家庭需水量和单位工业增加值的用水量。为了避免将来水资源短缺,使用这些参数作为控制变量进行了情景分析。这些控制变量的值是根据综合的社会和经济发展目标设定的。结果显示,供水和需求(WSDR)将从基准情景中的0.89增加到2020年最佳情景中的1.04,到2030年从0.64增加到1.05。(C)2018 Elsevier Ltd.保留所有权利。

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