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Cambridge Prisms. Coastal Futures|June 22, 2026
Toward transferable models for efficient spatiotemporal flood prediction across coastal-estuarine systemsSamuel Daramola, David F Muñoz, Chaopeng Shen
Water Research|November 2, 2022
Nitrate concentrations predominantly driven by human, climate, and soil properties in US riversKayalvizhi Sadayappan, Devon Kerins, Chaopeng Shen, et al.
The Science of the Total Environment|March 19, 2023
A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watershedsGourab Kumer Saha, Farshid Rahmani, Chaopeng Shen, et al.
Journal of Environmental Management|April 8, 2026
Analyzing the deep learning approach-based modeling framework to understand the critical environmental factors of predicting daily nitrate concentrationsGourab Kumer Saha, Farshid Rahmani, Ashok Jacob, et al.
Environmental Science & Technology|February 3, 2021
From Hydrometeorology to River Water Quality: Can a Deep Learning Model Predict Dissolved Oxygen at the Continental Scale?Wei Zhi, Dapeng Feng, Wen-Ping Tsai, et al.
Scientific Data|April 8, 2026
A Community Dataset for Large-Scale River Nitrogen Modeling in the United StatesShuyu Y Chang, Doaa Aboelyazeed, Kamlesh Sawadekar, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 18, 2024
Increasing phosphorus loss despite widespread concentration decline in US riversWei Zhi, Hubert Baniecki, Jiangtao Liu, et al.
Nature Communications|October 14, 2021
From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modelingWen-Ping Tsai, Dapeng Feng, Ming Pan, et al.
Environmental Science & Technology|May 29, 2014
Pore-scale controls on calcite dissolution rates from flow-through laboratory and numerical experimentsSergi Molins, David Trebotich, Li Yang, et al.
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