托普西斯
地表径流
环境科学
雨水
雨水管理模型
多准则决策分析
低影响开发
计算机科学
环境工程
运筹学
雨水管理
工程类
生态学
生物
作者
Bo Luan,Ruixue Yin,Peng Xu,Xin Wang,Xiaomin Yang,Lan Zhang,Xiaoyan Tang
标识
DOI:10.1016/j.jclepro.2019.03.028
摘要
Abstract The dramatic changes in Land-Use and Land-Cover (LULC) in urbanizing areas have led to problems such as urban flooding and water pollution. Green Stormwater Infrastructure (GSI) has become a new approach to mitigate these problems. The comprehensive assessment of GSI strategies and their combinations is the foundation for decision making regarding GSI implementation. Using the rapidly developing Western New City of Zhuhai in China as an example, this study applies Storm Water Management Model (SWMM) to evaluate Single and Combined GSI strategies. Four indicators—runoff volume control, peak flow reduction, pollutant removal, and economic cost—are selected to conduct a Multi-Criteria Decision Analysis with the use of Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The performance evaluation of Single and Combined GSIs suggests that: (i) there may exist linear or nonlinear relation between the efficiency of a Single GSI and the size of its implementation. (ii) the optimal LULC-cost effective range may be identified for certain GSI, and (iii) Distributed-Centralized Combined GSIs are superior to other strategies in regard to reduction of runoff, TSS and peak flow. The TOPSIS assessment indicates that the cost weight ( w c ) has significant impact on the multi-criteria decision-making, and all strategies may be classified into three categories: effectiveness, cost, and stability. The results of TOPSIS show that the Distributed-Centralized Combined GSIs (scenarios S3, S5) are the best options if w c is not an important factor, while the Centralized Single GSI (S6) is the best option if w c becomes more important. Furthermore, this study can provide the well-informed alternative stormwater management plans and GSI decisions for local planners and water resource managers in the rapidly urbanizing sponge cities.
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