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浙江大学学报(工学版)  2022, Vol. 56 Issue (11): 2313-2320    DOI: 10.3785/j.issn.1008-973X.2022.11.022
土木工程     
基于耦合模拟的污水管网入流入渗定量识别
胡鸿昊1(),李秀娟2,于俊锋2,张清周2,柳景青1,*()
1. 浙江大学 建筑工程学院,浙江 杭州 310058
2. 浙江大学 滨海产业技术研究院,天津 300457
Quantitative identification of inflow and infiltration of sanitary sewer system based on coupling simulation
Hong-hao HU1(),Xiu-juan LI2,Jun-feng YU2,Qing-zhou ZHANG2,Jing-qing LIU1,*()
1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2. Binhai Industrial Technology Research Institute , Zhejiang University, Tianjin 300457
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摘要:

为了准确有效地识别降雨引起的污水管网入流和入渗,提出了一个基于土壤蓄水量、产流过程和单位过程线耦合率定的识别模型,并且考虑到不同降雨强度工况对模型参数率定的影响. 模型被应用于H市乡镇地区污水管网2个断面上游的入流入渗过程的负荷分析,采用指数移动平均法(EMA)对15场降雨事件的校准结果进行处理,得到大、中、小3类降雨的最优参数集,用另外6场降雨来验证模型的有效性,纳什效率系数为0.65~0.86. 结果表明:研究区域内入流入渗占区域总降雨量的5%~22%,其中入流量占比为3%~9%,入渗量占比为1%~13%,随着降雨量的增大,入渗占比逐渐增加. 不同于成本较高的管道勘探,所提出的识别模型充分利用降雨数据和管网水力监测数据,可用于污水管网入流入渗的定量识别.

关键词: 污水管网入流入渗定量识别耦合模型遗传算法    
Abstract:

A recognition model based on the calibration of soil moisture content, runoff-yield and instantaneous unit hydrograph was proposed to quantify rainfall derived infiltration and inflow (RDII) accurately and effectively in sanitary sewer networks. The effects of different rainfall intensity conditions on the calibration of model parameters were also considered. The model was applied to the load analysis of the infiltration process in the upstream of two sections of the sewage pipe network in a rural area of H city. The exponential moving average (EMA) was used to process the calibration results of 15 rainfall events. The optimal parameter sets for heavy, medium and light rainfall events were obtained. The other 6 rainfall events were used to validate model with Nash efficiency coefficients from 0.65 to 0.86. The results showed that the RDII accounts for 5%~22% of the precipitation in the study area, of which the inflow accounts for 3~9% and the infiltration accounts for 1%~13%. As the rainfall intensity getting high, the proportion of infiltration increased gradually. Different from high cost pipeline exploration, the proposed identification model makes full use of rainfall data can be used for quantitaive identification of RDII in sanitary sewer networks.

Key words: sanitary sewer system    rain derived infiltration and inflow    quantitative identification    coupling model    genetic algorithm
收稿日期: 2021-12-08 出版日期: 2022-12-02
CLC:  X 143  
通讯作者: 柳景青     E-mail: johnkeatinghhh@zju.edu.cn;liujingqing@zju.edu.cn
作者简介: 胡鸿昊(1997—),男,硕士生,从事污水管网入流入渗研究. orcid.org/ 0000-0003-1726-2931. E-mail: johnkeatinghhh@zju.edu.cn
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引用本文:

胡鸿昊,李秀娟,于俊锋,张清周,柳景青. 基于耦合模拟的污水管网入流入渗定量识别[J]. 浙江大学学报(工学版), 2022, 56(11): 2313-2320.

Hong-hao HU,Xiu-juan LI,Jun-feng YU,Qing-zhou ZHANG,Jing-qing LIU. Quantitative identification of inflow and infiltration of sanitary sewer system based on coupling simulation. Journal of ZheJiang University (Engineering Science), 2022, 56(11): 2313-2320.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2022.11.022        https://www.zjujournals.com/eng/CN/Y2022/V56/I11/2313

图 1  研究区域示意图
检查井编号 静压液位计 超声液位计 流速计 雨量计
28
23
45
21
15
表 1  监测设备分布情况
图 2  本研究技术路线
图 3  No.23监测断面旱季日流量聚类示例
图 4  旱季流量日变化标准化均线
图 5  研究区域入流入渗过程示意图
${f_{\rm{c}}}$ ${W_{\rm{m}}}$ ${W_i}$ ${E_{\rm{m}}}$ $C/10^{-5}$
H 7.52 61.66 17.74 0.08 4.0
M 6.55 63.10 15.05 0.06 5.2
L 5.81 65.48 14.72 0.02 1.3
${N_{{{\rm{RDI,A}}}}}$ $ {K_{{{\rm{RDI,A}}}}} $ ${R_{{{\rm{RDI,A}}}}}$ ${N_{{{\rm{RII,A}}}}}$ $ {K_{{{\rm{RII,A}}}}} $ ${R_{{{\rm{RII,A}}}}}$
H 2.77 13.39 0.35 7.67 55.63 0.94
M 2.90 10.53 0.35 16.20 56.93 0.39
L 1.03 8.13 0.74 10.27 59.43 0.02
${N_{{{\rm{RDI,B}}}}}$ $ {K_{{{\rm{RDI,B}}}}} $ ${R_{{{\rm{RDI,B}}}}}$ ${N_{{{\rm{RII,B}}}}}$ $ {K_{{{\rm{RII,B}}}}} $ ${R_{{{\rm{RII,B}}}}}$
H 3.11 3.95 0.11 8.08 57.44 0.20
M 4.52 4.85 0.28 9.80 31.84 0.52
L 1.28 12.12 0.48 5.46 22.26 0.70
表 2  大、中、小降雨事件最优参数集
降雨
事件
Ptotal/mm 区域
编号
RateRDI/% RateRII/% E RMSE/
(m3/h?1)
L1 17.2 A 8.03 3.02 0.86 0.60
B 3.21 1.47 0.80 0.35
L2 16.6 A 7.92 3.40 0.89 0.90
B 3.08 1.78 0.75 0.52
M1 45.4 A 8.02 6.33 0.81 1.47
B 4.41 3.86 0.85 0.61
M2 41.2 A 8.16 5.00 0.85 2.19
B 4.74 2.66 0.79 0.72
H1 73.8 A 9.04 12.70 0.73 0.99
B 4.81 6.42 0.78 0.74
H2 223.2 A 8.10 12.5 0.65 2.92
B 3.92 6.03 0.79 0.74
表 3  测试集降雨事件验证结果
图 6  入流入渗量计算结果示例
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