低影响开发
计算机科学
比例(比率)
最优化问题
多目标优化
水准点(测量)
过程(计算)
选择(遗传算法)
管理科学
风险分析(工程)
环境资源管理
运筹学
环境科学
雨水
工程类
生态学
业务
地表径流
人工智能
雨水管理
地理
机器学习
算法
地图学
大地测量学
生物
操作系统
作者
Xiaoyue Zhang,Haifeng Jia
标识
DOI:10.1016/j.resconrec.2022.106861
摘要
The complexity of urban stormwater management has helped position low impact development (LID) optimization as one of the leading-edge research areas worldwide. Some literature reviews have provided valuable background on a specific LID optimization part, such as tools, objectives or planning, etc. However, a systematic review covering a complete optimization process remains lacking. In this study, a comprehensive optimization framework involving seven steps was first constructed. Eighty-eight research papers were retrieved and thoroughly analyzed. Results showed a growing trend about large-scale optimization on numerous small-scale achievements, which would alter optimization objectives (society, environment or ecology, etc.) and furtherly determine tool selection. Nonetheless, large-scale optimization is challenging due to theoretical and technical limitations. Besides, most studies focused on a single scale, of which objective quantification and related multi-scale matching may be problematic. Coupled green-grey optimization is the common conduction for better benefits (average 61% and 54% runoff volume and pollution reduction). Nevertheless, water body (blue) responses have not been fully incorporated into optimization and assessment. Therefore, objectives downscaling decomposition and schemes up-scaling theory were proposed to integrate green-grey-blue system for multi-scale optimization. This study complemented review through an optimization process, contributing to explore future perspectives of this field more comprehensively.
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