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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2017, Vol. 11 Issue (2) : 7    https://doi.org/10.1007/s11783-017-0912-z
RESEARCH ARTICLE
Estimation and optimization operation in dealing with inflow and infiltration of a hybrid sewerage system in limited infrastructure facility data
Mingkai Zhang,He Jing,Yanchen Liu(),Hanchang Shi
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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Abstract

Inflow and infiltration of a sewage system was estimated by synthetic model.

Homological feature of catchments was recognized by self-organizing map.

Occurrence risk index was proposed to assess catchment operation problem.

Optimal strategy was used to reduce surcharge events and improve effluent quality.

Inflow and infiltration (I/I) are serious problems in hybrid sewerage systems. Limited sewerage information impedes the estimation accuracy of I/I for each system catchment because of its unknown distribution. A new method proposed to deal with I/I of a large-scale hybrid sewerage system with limited infrastructure facility data is presented in this study. The catchment of representative pump stations was adopted to demonstrate the homological catchments that have similar wastewater fluctuation characteristics. Homological catchments were clustered using the self-organizing map (SOM) analysis based on long-term daily flow records of 50 pumping stations. An assessment index was applied to describe the I/I and overflow risk of representative pump stations in the catchment based on the hourly wastewater quality and quantity data. The potential operational strategy of homological catchments was generated by the assessment index of representative pump stations. The simulation results of the potential operational strategy indicated that the optimized operation strategy could reduce surcharge events and significantly improve the quality of wastewater treatment plant effluent.

Keywords Hybrid sewerage system      Wastewater treatment plant      Optimization operation      Inflow      Infiltration     
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Corresponding Author(s): Yanchen Liu   
Issue Date: 17 March 2017
 Cite this article:   
Mingkai Zhang,He Jing,Yanchen Liu, et al. Estimation and optimization operation in dealing with inflow and infiltration of a hybrid sewerage system in limited infrastructure facility data[J]. Front. Environ. Sci. Eng., 2017, 11(2): 7.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-017-0912-z
https://academic.hep.com.cn/fese/EN/Y2017/V11/I2/7
Fig.1  Schematic of the sewer system and the Lucun WWTP (located southeast of the Wuxi City, Jiangsu Province, China). J, L, M, X, Y represents Jintang, Liqiao, Meihulu, Xianliqiao, Yonglelu pump station respectively
Fig.2  Typical variation pattern of (a) dry weather flow and wet weather flow, (b) average daily flow, (c) spectrum analysis
Fig.3  Influence of rainfall on (a) wastewater flowrate, (b) SCOD, and (c) ammonia
pump station ANOVA analysis of the flow fluctuation (Fflow) ratio of rain derived infiltration ratio of rain derived inflow
Yugang 15.15 0.3392 1.7755
Lixi 64.55 0.2879 0.5269
Meihulu 70.71 0.2041 0.1863
Liqiao 0.70 0.6357 0.7585
Hongxing 12.81 0.2114 1.9634
Jiangjian 5.47 0.1117 0.2818
Xianliqiao 3.43 0.1725 0.1502
Tonglongli 18.93 0.1248 0.2537
Chaoyang 24.93 0.1412 0.4372
Jintang 0.26 0.0783 0.1476
Yonglelu 0.09 0.0737 0.2471
WWTP Inflow 32.60 0.0875 0.1149
Tab.1  Rain-induced inflow and infiltration of representative catchments
pump station Fflow FSCOD FNH4-N FPO4-P
WWTP Inflow 32.60 0.57 11.6 12
Jintang 0.26 13.6 21.2 24.4
Liqiao 0.70 0 0.41 3.4
Meihulu 70.71 5.7 7.9 0.27
Xianliqiao 3.43 1.6 7.5 0.84
Yonglelu 0.09 2.9 30.1 23.9
Tab.2  ANOVA analysis of the influence of inflow and infiltration on wastewater quality fluctuation
pump station flow conductivity pH SS NH4+–N PO43–P SCOD Pinf./inflow Poverflow
WWTP Inflow 0.423 ﹣0.198 ﹣0.107 0.107 ﹣0.083 ﹣0.029 0.064 0.704 ﹣0.141
Jintang ﹣0.108 ﹣0.328 0.143 ﹣0.002 ﹣0.060 ﹣0.090 ﹣0.119 0.280 0.496
Liqiao ﹣0.402 ﹣0.015 ﹣0.025 ﹣0.205 0.024 0.079 0.157 ﹣0.411 0.393
Meihulu 0.191 ﹣0.078 0.009 0.255 ﹣0.051 0.158 ﹣0.019 0.321 ﹣0.062
Xianliqiao 0.127 0.082 0.124 0.211 ﹣0.094 0.232 ﹣0.021 0.139 ﹣0.114
Yonglelu ﹣0.022 ﹣0.436 ﹣0.227 0.063 ﹣0.324 ﹣0.338 ﹣0.125 0.737 0.782
Tab.3  Correlation analysis of rainfall with regard to wastewater quality and quantity
Fig.4  Neural network clustering and classification of 50 pumping stations
Fig.5  Comparison of influent flow rate variation of WWTP before and after optimal control scenario
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