Inversion of multiple parameters for river pollution accidents using emergency monitoring data

被引:10
作者
Jing, Pingfei [1 ]
Yang, Zhonghua [1 ]
Zhou, Wugang [1 ]
Huai, Wenxin [1 ]
Lu, Xinhua [1 ]
机构
[1] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
curve fitting; parameter inversion; river pollution accident; source identification; CONTAMINANT SOURCE; SOURCE IDENTIFICATION; POINT-SOURCE; COEFFICIENT; DISPERSION; LOCATION; MODEL;
D O I
10.1002/wer.1099
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study presented a new inversion algorithm on the basis of least squares method for river point pollution sources. A series of numerical experiments was conducted to verify the accuracy of the proposed inversion algorithm. The general solution of the one-dimensional (1D) pollutant transport equation is the governing equation of this method. Pollutant concentrations at various hypothetical monitoring points should be observed at two moments to obtain the point pollution source parameters, namely, velocity, longitudinal dispersion coefficient, emission moment of the pollution source, emission location, and emission intensity. Monitoring error was considered a random noise in the numerical experiments. The inversion result error was 3.69% when the monitoring error was 5%. Although the monitoring error reached 20%, the maximum error of inversion parameters was 8.58%. In addition, the effects of river flow velocity, contaminant decay rates, monitoring point setting, and time intervals between two sampling groups were analyzed in hypothetic cases. Practitioner points Present a new inversion algorithm for river point pollution sources. Multiple parameters can be obtained by inversion. The unknown river velocity does not affect the result of parameter inversion. Different levels of pollutant concentration monitoring errors are considered. (C) 2019 Water Environment Federation
引用
收藏
页码:731 / 738
页数:8
相关论文
共 26 条
[11]   Location and release time identification of pollution point source in river networks based on the Backward Probability Method [J].
Ghane, Alireza ;
Mazaheri, Mehdi ;
Samani, Jamal Mohammad Vali .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2016, 180 :164-171
[12]   IDENTIFYING SOURCES OF GROUNDWATER POLLUTION - AN OPTIMIZATION APPROACH [J].
GORELICK, SM ;
EVANS, B ;
REMSON, I .
WATER RESOURCES RESEARCH, 1983, 19 (03) :779-790
[13]  
[郭建青 GUO Jianqing], 2007, [水力发电学报, Journal of Hydroelectric Engineering], V26, P61
[14]   Longitudinal dispersion in sinuous channel with changes in shape [J].
Guymer, I .
JOURNAL OF HYDRAULIC ENGINEERING-ASCE, 1998, 124 (01) :33-40
[15]   Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis [J].
Jiang, Jiping ;
Han, Feng ;
Zheng, Yi ;
Wang, Nannan ;
Yuan, Yixing .
FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING, 2018, 12 (05)
[16]   Estimation of river pollution source using the space-time radial basis collocation method [J].
Li, Zi ;
Mao, Xian-Zhong ;
Li, Tak Sing ;
Zhang, Shiyan .
ADVANCES IN WATER RESOURCES, 2016, 88 :68-79
[17]  
[毛献忠 Mao Xianzhong], 2014, [清华大学学报. 自然科学版, Journal of Tsinghua University. Science and Technology], V54, P853
[18]   Mathematical Model for Pollution Source Identification in Rivers [J].
Mazaheri, Mehdi ;
Samani, Jamal Mohammad Vali ;
Samani, Hossein Mohammad Vali .
ENVIRONMENTAL FORENSICS, 2015, 16 (04) :310-321
[19]   Estimation of a contaminant source in an estuary with an inverse problem approach [J].
Parolin, Radael de Souza ;
da Silva Neto, Antonio Jose ;
Gomes Watts Rodrigues, Pedro Paulo ;
Santiago, Orestes Llanes .
APPLIED MATHEMATICS AND COMPUTATION, 2015, 260 :331-341
[20]   Ground water contaminant source and transport parameter identification by correlation coefficient optimization [J].
Sidauruk, P ;
Cheng, AHD ;
Ouazar, D .
GROUND WATER, 1998, 36 (02) :208-214