Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model

Siyu Zhu; Bingxin Liu; Sinuo Li; Linus Zhang; Eldon R. Rene; Weifang Ma

doi:10.1016/j.jenvman.2024.123484

journal article Jan 01, 2025

Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model

Siyu Zhu Bingxin Liu

Sinuo Li Linus Zhang

Eldon R. Rene Weifang Ma

Journal of Environmental Management Vol. 373 pp. 123484 · Elsevier BV

View at Publisher Save 10.1016/j.jenvman.2024.123484

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Details

Published: Jan 01, 2025
Vol/Issue: 373
Pages: 123484
License: View

Authors

Polymer Science Group, Department of Chemical Engineering, The University of Melbourne, Parkville, VIC 3010, Australia

d Department of Water Resources Engineering, Lund University, Lund 22100, Sweden

E

Eldon R. Rene

IHE Delft Institute for Water Education

W

Weifang Ma

Funding

National Natural Science Foundation of China

Beijing Forestry University

National Fund for Fostering Talents of Basic Science Award: 51678052

Cite This Article

Siyu Zhu, Bingxin Liu, Sinuo Li, et al. (2025). Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model. Journal of Environmental Management, 373, 123484. https://doi.org/10.1016/j.jenvman.2024.123484

Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model

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