L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting
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Updated: Feb 11, 2026

In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
W T Crow1, F Chen1,2, R H Reichle3
1USDA Hydrology and Remote Sensing Laboratory, Beltsville, MD.
Abstract:
Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.
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