Diagnosis of road drainage inlets’ abnormal condition using multi-hydrological data association analysis

doi:10.3785/j.issn.1008-973X.2021.01.007

Journal of ZheJiang University (Engineering Science)

2021, Vol. 55

Issue (1): 55-61 DOI: 10.3785/j.issn.1008-973X.2021.01.007

Diagnosis of road drainage inlets’ abnormal condition using multi-hydrological data association analysis

Gong CHEN1(

),Chun-hua ZHENG2,Xian-ming WENG2,Baustani HAMEED1,Hong-hao HU1,Xiao-yu MA2,Jing-qing LIU1,*(

)

1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2. Wenzhou Drainage Limited Company, Wenzhou 325000, China

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Abstract

A method of using monitored hydrological data to assess the degree of inlet blockage was proposed in order to quantitatively analyze the uncertainty of the drainage system. The correlation between the monitored hydrological data and the blocked area of the inlet was obtained by describing the physical model of the road drainage inlet under flooding. The average clogged area of the inlet under each independent water accumulation event was calculated and defined as the index of inlet’s blockage degree. The moving average method was used to process the calculation results in order to visually analyze the degree of inlet’s blockage. The method was applied to an eastern coastal city, and the inlet cleanup records were used to verify the calculation results. Results show that 83% of inlet blockage can be well identified, of which the accuracy of the points diagnosed as cleared is 75%, the accuracy of the points diagnosed as uncleared is 89%. Errors in the calculation results are mostly caused by incomplete records. Some branch pipes may be gradually cleaned up after the inlet is cleared, which interferes with the calculation results.

Key words： urban flooding urban drainage system road drainage inlet blockage diagnosis time series analysis

Received: 29 July 2020 Published: 05 January 2021

CLC:

X 143

Corresponding Authors: Jing-qing LIU E-mail: 21812068@zju.edu.cn;liujingqing@zju.edu.cn

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	Gong CHEN
	Chun-hua ZHENG
	Xian-ming WENG
	Baustani HAMEED
	Hong-hao HU
	Xiao-yu MA
	Jing-qing LIU

Cite this article:

Gong CHEN,Chun-hua ZHENG,Xian-ming WENG,Baustani HAMEED,Hong-hao HU,Xiao-yu MA,Jing-qing LIU. Diagnosis of road drainage inlets’ abnormal condition using multi-hydrological data association analysis. Journal of ZheJiang University (Engineering Science), 2021, 55(1): 55-61.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2021.01.007 OR http://www.zjujournals.com/eng/Y2021/V55/I1/55

基于多水文数据关联分析的雨水口异常诊断

为了定量探究排水系统的不确定性，基于监测水文数据提出雨水口堵塞程度的评估方法. 通过描述雨水口淹没入流状态下的物理模型，获得监测水文数据与雨水口堵塞面积的关联；计算每次独立积水事件下雨水口平均堵塞面积，作为雨水口堵塞程度评估指标；使用移动平均法对评估指标进行处理，能够直观分析出雨水口的堵塞程度. 将该方法应用于东部沿海城市研究区域，用雨水口清理记录进行验证. 结果表明，有83%研究点位的雨水口堵塞情况可以被很好地鉴别出来，其中诊断为堵塞并被清理的点位准确率为75%，诊断为堵塞但未被清理的点位准确率为89%. 预测失败的点位多由雨水口清理记录不全造成，雨水口侧支管堵塞疏通的延后性会对计算结果造成干扰.

关键词： 城市内涝, 城市排水系统, 雨水口, 堵塞评估, 时间序列分析

Fig.1 Structure of ultrasonic water depth sensor

Fig.2 Locations of hydrological sensor

Tab.1 Flood intervention records from June 2019 to October 2019

Fig.3 Examples of rainfall and water depth data collected by sensors

Fig.4 Study flow of drainage inlets analysis scheme

Fig.5 Sketch of outflow modes of inlet discharging

Fig.6 Duration of urban flooding

Fig.7 Example of calculation result of clogging degree of drainage inlets

Fig.8 Comparison of predicted dredged interval and real dredged interval

Fig.9 Example of calculation result of uncorrected severity of stormwater outlet blockage


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