:A brief review on SWAT applications in the Great Lakes Watersheds论文

:A brief review on SWAT applications in the Great Lakes Watersheds论文

本文主要研究内容

作者(2019)在《A brief review on SWAT applications in the Great Lakes Watersheds》一文中研究指出:Soil and Water Assessment Tool(SWAT)is an efficient model to simulate hydrology and water quality in large watersheds. During the past decades, SWAT has been used as a decision support tool to evaluate environmental effects of land usage change, BMPs, and hydraulic structures in Great Lakes watersheds. In addition, it has been increasingly used to predict water resources under different climate change scenarios. This paper briefly reviewed SWAT applications in various watersheds draining into the Great Lakes and intended to provide readers with insights regarding water quality issues in the Great Lakes concerned by researchers and capability of SWAT in dealing with those problems. Future development of SWAT with respect to dealing with cold region climate and vegetation conditions was also discussed.

Abstract

Soil and Water Assessment Tool(SWAT)is an efficient model to simulate hydrology and water quality in large watersheds. During the past decades, SWAT has been used as a decision support tool to evaluate environmental effects of land usage change, BMPs, and hydraulic structures in Great Lakes watersheds. In addition, it has been increasingly used to predict water resources under different climate change scenarios. This paper briefly reviewed SWAT applications in various watersheds draining into the Great Lakes and intended to provide readers with insights regarding water quality issues in the Great Lakes concerned by researchers and capability of SWAT in dealing with those problems. Future development of SWAT with respect to dealing with cold region climate and vegetation conditions was also discussed.

论文参考文献

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  • 论文详细介绍

    论文作者分别是来自林业与环境科学的,发表于刊物林业与环境科学2019年03期论文,是一篇关于,林业与环境科学2019年03期论文的文章。本文可供学术参考使用,各位学者可以免费参考阅读下载,文章观点不代表本站观点,资料来自林业与环境科学2019年03期论文网站,若本站收录的文献无意侵犯了您的著作版权,请联系我们删除。

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