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Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo

机译:东京市区流域降雨和CSO行为特征的聚类分析

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Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.
机译:来自城市地区的下水道溢流(CSO)被认为是潮湿天气期间接收水的主要污染物源。本研究试图对降雨事件和相应的CSO行为进行分类,以揭示在日本东京的Shingashi城市流域,降雨模式与CSO行为之间的关系,那里经常通过下水道系统(CSS)和CSO进行全面服务。此外,基于其年度溢流行为的排污口可以有效地管理雨水。分布式模型InfoWorks CS对2007年记录的所有117次降雨事件进行了模拟,以获取CSO行为。根据两组降雨模式参数和CSO行为对降雨事件进行分类。通过相似性分析将聚类的降雨和CSO组联系起来。结果表明,小降雨和极端降雨均与CSO行为密切相关,而中等降雨则与CSO行为之间存在弱相关性。这表明,通过降雨模式可以识别出从CSO角度来看重要而可忽略的降雨,而在估算中度降雨引起的CSO时应考虑到流域和网络的影响。此外,排污口最终分为六类,表明对环境的影响程度不同。

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