DOI: 10.11908/j.issn.0253-374x.20542

作者:

作者单位: 同济大学 环境科学与工程学院，上海 200092


作者简介: 尹海龙（1976―），男，教授，博士生导师，工学博士，主要研究方向为水环境系统工程与智慧水务。 E-mail： yinhailong@tongji.edu.cn


通讯作者: 徐祖信（1956―），女，教授，博士生导师，工学博士，主要研究方向为水环境系统工程与智慧水务。 E-mail： xzx@tongji.edu.cn

中图分类号:


基金项目: 上海市优秀技术带头人项目（20XD1430600）




Review of Intelligent Decision-Making Technologies for Urban Drainage System
Author:

Affiliation: College of Environmental Science and Engineering， Tongji University， Shanghai 200092， China


Fund Project:




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摘要:智慧决策是智慧水务的核心关键技术。围绕城市排水系统的提标增效，从管网诊断评估、城市内涝防治和雨天溢流污染控制3个方面，对城市排水系统智慧决策的实现模式进行了评述。在管网诊断评估方面，综述了基于水量、水质特征因子分区监测的水量来源溯源定位方法；在城市内涝防治方面，综述了基于数值化模型的内涝风险精细化模拟评估和机器学习模型的降雨实时预报、局部积水深度快速预报实现模式；在溢流污染控制方面，综述了基于多目标优化算法、数值模型和机器学习相结合的排水系统优化调度实现模式。模型系统的可靠性是智慧排水决策的关键，应重视管网水量来源定量解析和排水系统内涝风险预警、优化运行调度的融合。



Abstract:Smart decision-making is the key technology of smart water systems. This paper reviews the realization of intelligent decision-making of urban drainage systems from pipe network diagnosis and evaluation， urban waterlogging prevention and control， and overflow pollution control in rainy days. For drainage pipe detection and assessment， the technical methods for source flow tracking based on water flow and chemical markers monitoring at divided sub-catchments were evaluated. For urban flooding control， the techniques of elaborate simulation of flooding risk area using numerical model， and the real-time forecast of precipitation and local flooding depth using machine-learning method were reviewed； for the drainage overflow pollution control， the optimal control of urban drainage system based on the integration of multi-objective algorithm， numerical model， and machine-learning were discussed. It is proposed that the reliability of the modeling system is the key for smart decision-making in urban drainage systems. Therefore， attention should be paid to the integration of quantitative analysis of water sources in the pipe network and waterlogging risk early warning and optimal operation scheduling of drainage systems.





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