1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China 2. Binhai Industrial Technology Research Institute , Zhejiang University, Tianjin 300457
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.
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.
Fig.3Example of dry weather daily flow clustering at monitoring section No.23
Fig.4Average normalized curve of dry weather flow
Fig.5Schematic presentation of inflow and Infiltration in study area
${f_{\rm{c}}}$
${W_{\rm{m}}}$
${W_i}$
${E_{\rm{m}}}$
$C/10^{-5}$
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
Tab.2Best parameters sets for heavy, medium and light rainfall events
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
Tab.3Validation results of rainfall event in test set
Fig.6Example of calculation results of RDI and RII
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