Corrigendum to "Comparative efficiency of the SWAT model and a deep learning model in estimating nitrate loads at the Tuckahoe creek watershed, Maryland" [Sci. Total Environ. 954 (2024) 176256].
Jiye Lee, Dongho Kim, Seokmin Hong, Daeun Yun, Dohyuk Kwon, Robert L Hill, Feng Gao, Xuesong Zhang, Kyung Hwa Cho, Sangchul Lee, Yakov Pachepsky
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期刊介绍：
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.
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