Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model.

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第一作者： Iliana E,Mladenova

第一单位： NASA GSFC, Hydrological Sciences Lab (617), Greenbelt, MD, United States.;UMD, Earth System Science Interdisciplinary Center, College Park, MD, United States.

作者： Iliana E,Mladenova ^[1] ; John D,Bolten ^[2] ; Wade,Crow ^[3] ; Nazmus,Sazib ^[4] ; Curt,Reynolds ^[5]

作者单位： NASA GSFC, Hydrological Sciences Lab (617), Greenbelt, MD, United States.;UMD, Earth System Science Interdisciplinary Center, College Park, MD, United States. ^[1] NASA GSFC, Hydrological Sciences Lab (617), Greenbelt, MD, United States. ^[2] USDA ARS, Hydrology and Remote Sensing Lab, Beltsville, MD, United States. ^[3] NASA GSFC, Hydrological Sciences Lab (617), Greenbelt, MD, United States.;Science Application International Corporation, Lanham, MD, United States. ^[4] USDA FAS, Washington, DC, United States. ^[5]

关键词 SMAP agricultural drought data assimilation hydrologic modeling soil moisture

DOI 10.3389/fdata.2020.00010

PMID 33693385

发布时间 2021-03-12

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Frontiers in big data

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Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model.

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Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model.

Frontiers in big data

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Frontiers in big data

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