Simultaneous identification of groundwater contamination source information, model parameters, and boundary conditions under an unknown boundary mode

Wang, Zibo1,2,3; Lu, Wenxi1,2,3; Chang, Zhenbo4; Bai, Yukun1,2,3; Xu, Yaning1,2,3

2024-08-01

10.1007/s00477-024-02795-z

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT   影响因子和分区

1436-3240

1436-3259

Boundary conditions play a crucial role in groundwater contamination source identification (GCSI), but they may be complex and reliable estimates are difficult to obtain in advance in actual situations. If the estimated values deviate significantly from the actual situation, the GCSI results will be inaccurate. However, very few studies have attempted to identify the boundary conditions in GCSI, and even when they are identified, they are often considered too simple. The boundary mode (B-mode) is assumed to be known, but in reality, it is often unknown and is more complex than initially assumed. Previous practices based on this assumption may not accurately reflect actual situations. Therefore, this study focused on the concentration boundaries, and the boundary conditions were also considered unknown variables, along with contamination source information and model parameters. To alleviate the problem of identifying the boundary conditions under an unknown B-mode, we proposed for the first time to treat the B-mode as an unknown variable. Thus, the source information, model parameters, B-mode, and corresponding parameters in the boundary concentration (BC) function were identified simultaneously. The Differential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM((ZS))) algorithm and a Kriging surrogate model were used as the primary means of solution. We designed four different synthetic cases to test the effectiveness of the above ideas. When identifying the B-mode, the obtained BC mostly fitted well with the true BC. It was therefore considered feasible for identifying the B-mode. The performance of the DREAM((ZS)) algorithm was found to be superior to the traditional DREAM algorithm and was more efficient.

Groundwater contamination Complex boundary conditions Boundary mode DREAM((ZS)) algorithm Surrogate model

SCI ; EI

英语

通讯

Engineering ; Environmental Sciences & Ecology ; Mathematics ; Water Resources

Engineering, Environmental ; Engineering, Civil ; Environmental Sciences ; Statistics & Probability ; Water Resources

WOS:001303241200001

SPRINGER

ENGINEERING

Web of Science

1.Jilin Univ, Key Lab Groundwater Resources & Environm, Minist Educ, Changchun 130021, Peoples R China
2.Jilin Univ, Jilin Prov Key Lab Water Resources & Water Environ, Changchun 130021, Peoples R China
3.Jilin Univ, Coll New Energy & Environm, Changchun 130021, Peoples R China
4.Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen, Peoples R China

Wang, Zibo,Lu, Wenxi,Chang, Zhenbo,et al. Simultaneous identification of groundwater contamination source information, model parameters, and boundary conditions under an unknown boundary mode[J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT,2024.

Wang, Zibo,Lu, Wenxi,Chang, Zhenbo,Bai, Yukun,&Xu, Yaning.(2024).Simultaneous identification of groundwater contamination source information, model parameters, and boundary conditions under an unknown boundary mode.STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT.

Wang, Zibo,et al."Simultaneous identification of groundwater contamination source information, model parameters, and boundary conditions under an unknown boundary mode".STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2024).