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Yakov Pachepsky
Yakov Pachepsky
Agricultural Research Service
Environmental science
Random forest
Irrigation
Spatial variability
Water quality
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Persistent Patterns of E. coli Concentrations in Two Irrigation Ponds from 3 Years of Monitoring
2021
Water Air and Soil Pollution
Matthew D. Stocker
Yakov Pachepsky
Jaclyn E. Smith
Billie Morgan
Robert L. Hill
Moon S. Kim
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In-stream Escherichia Coli Modeling Using high-temporal-resolution data with deep learning and process-based models
2021
Hydrology and Earth System Sciences Discussions
Ather Abbas
Sang-Soo Baek
Norbert Silvera
Bounsamay Soulileuth
Yakov Pachepsky
Olivier Ribolzi
Laurie Boithias
Kyung Hwa Cho
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AI4Water v1.0: An open source python package for modeling hydrological time series using data-driven methods
2021
Geoscientific Model Development Discussions
Ather Abbas
Laurie Boithias
Yakov Pachepsky
Kyunghyun Kim
Jong Ahn Chun
Kyung Hwa Cho
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The site-specific selection of the infiltration model based on the global dataset and random forest algorithm
2021
Vadose Zone Journal
Seongyun Kim
Gülay Karahan
Manan Sharma
Yakov Pachepsky
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Accuracy and reliability of predictions of E. coli concentrations in water of irrigation ponds from drone-based imagery as affected by parameters of the random forest algorithm
2021
Billie J. Morgan
Matthew D. Stocker
Yakov Pachepsky
Moon S. Kim
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