Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed, China-Reference-Cited by-同舟云学术

Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed, China

Published:2019-03 Issue: Volume:77 Page:115-129
ISSN:1001-0742
Container-title:Journal of Environmental Sciences
language:en
Short-container-title:Journal of Environmental Sciences

Author:

Qiao Pengwei,Lei Mei,Yang Sucai,Yang Jun,Zhou Xiaoyong,Dong Nan,Guo Guanghui

Funder

Hi-Tech Research and Development Program (863) of China

Beijing Postdoctoral Research Foundation

Project of Heavy Metal Risk Warning and Phytoremediation in Mining Concentrated Area

Special Fund for Environment Protection Research in the Public Interest

Study on Heavy Metal Accumulation Risk and Early Warning in Typical Ore Concentration Area

Publisher

Elsevier BV

Subject

General Environmental Science,General Medicine,Environmental Chemistry,Environmental Engineering

Reference71 articles.

1. Sensitivity analysis of SWAT model to the spatial rainfall distribution and watershed subdivision in streamflow simulations in the Mediterranean context: a case study in the Joumine watershed;Aouissi,2013

2. Role of watershed subdivision on modeling the effectiveness of best management practices with SWAT;Arabi;J. Am. Water Resour. Assoc.,2006

3. Large area hydrologic modeling and assessment. Part I: model development;Arnold;J. Am. Water Resour. Assoc.,1998

4. A regional GIS-based model to predict long-term responses of soil and soil water chemistry to atmospheric deposition: Initial results;Bilaletdin;Water Air Soil Pollut.,2001

5. Effect of watershed subdivision on simulation runoff and fine sediment yield;Bingner;Trans. ASAE,1997

Cited by 35 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China;J ENVIRON SCI;2025

2. Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China;Journal of Environmental Sciences;2025-01

3. Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications;Ecotoxicology and Environmental Safety;2024-09

4. Identifying interactive effects of spatial drivers in soil heavy metal pollutants using interpretable machine learning models;Science of The Total Environment;2024-07

5. Distribution Characteristics and Assessment of Heavy Metal Pollution in Sediments of Fengyuan River, Guangdong;Environmental Forensics;2024-07