Machine‐Learning Based Multi‐Layer Soil Moisture Forecasts—An Application Case Study of the Montana 2017 Flash Drought

Machine‐Learning Based Multi‐Layer Soil Moisture Forecasts—An Application Case Study of the Montana 2017 Flash Drought

Abstract Soil moisture (SM) is an essential climate variable, governing land‐atmosphere interactions, runoff generation, and vegetation growth and productivity. Timely forecasts of SM spatial distribution and vertical profiles are needed for early detection and prediction of potential droughts. Howe...

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Bibliographic Details
Main Authors: J. Du, J. S. Kimball, K. Jencso, Z. Hoylman, C. Brust, D. Ketchum, Y. Xu, H. Lu, J. Sheffield
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Water Resources Research
Subjects:
flash drought
machine learning
soil moisture
remote sensing
Mesonet
forecast
Online Access:https://doi.org/10.1029/2023WR036973
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https://doi.org/10.1029/2023WR036973

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