Effect of Rainfall Events on SMAP Radiometer-Based Soil Moisture Accuracy Using Core Validation Sites

Author:

Colliander Andreas1,Jackson Thomas J.2,Berg Aaron3,Bosch D. D.4,Caldwell Todd5,Chan Steven1,Cosh Michael H.2,Collins C. Holifield6,Martínez-Fernández Jose7,McNairn Heather8,Prueger J. H.9,Starks P. J.10,Walker Jeffrey P.11,Yueh Simon H.1

Affiliation:

1. a Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

2. b USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, Maryland

3. c University of Guelph, Guelph, Ontario, Canada

4. d USDA ARS Southeast Watershed Research, Tifton, Georgia

5. e USGS Nevada Water Science Center, Carson City, Nevada

6. f USDA ARS Southwest Watershed Research, Tucson, Arizona

7. g University of Salamanca, Salamanca, Spain

8. h Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada

9. i USDA ARS National Laboratory for Agriculture and the Environment, Ames, Iowa

10. j USDA ARS Grazinglands Research Laboratory, El Reno, Oklahoma

11. k Monash University, Melbourne, Victoria, Australia

Abstract

AbstractSoil moisture retrieval is particularly challenging during and immediately after precipitation events because of the transient movement of water in the shallow subsurface. Conventional L-band microwave radiometer–based soil moisture products use algorithms that assume a static state and a constant vertical soil moisture distribution. This study assessed the retrieval performance of a SMAP radiometer-based soil moisture product during and immediately after rain events. The removal of the rain event samples systematically improved the unbiased root-mean-square error (ubRMSE) from 0.037 (all measurements) to 0.028 m3 m−3 (transitory measurements screened out), while the magnitude of the bias became larger (from −0.005 to −0.014 m3 m−3); RMSE improved from 0.047 to 0.042 m3 m−3, and the Pearson correlation saw a minor positive change from 0.813 to 0.824. The results indicate that removing samples during the transitional period causes the comparison to improve, but also suggests that the true bias may be larger than the one estimated using all the samples. Furthermore, the results revealed that the effect was stronger for areas with high clay content. An assessment of the performance of the product during the rain events (overpass within 3 h from the start of the rain) showed that the ubRMSE degraded from the benchmarked 0.036 m3 m−3 (during no rain events at all) to 0.043 m3 m−3 (during rain). The results also showed that the bias became wetter, which is expected because SMAP sensed the water on the surface before propagating to the in situ sensors. SMAP maintains its soil moisture sensitivity even during rain events and screening of rain events may not be necessary to ensure sufficient soil moisture retrieval quality.

Funder

National Aeronautics and Space Administration

Publisher

American Meteorological Society

Subject

Atmospheric Science

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