Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S

Abstract

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U.S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m/m for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent Manuscript received April 2, 2011; revised June 24, 2011 and August 4, 2011; accepted August 31, 2011. Date of publication October 21, 2011; date of current version April 18, 2012. T. J. Jackson, R. Bindlish, M. H. Cosh, and T. Zhao are with the Hydrology and Remote Sensing Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD 20705 USA (e-mail: tom.jackson@ars.usda.gov; rajat.bindlish@ars.usda.gov; michael.cosh@ ars.usda.gov; tianjie.zhao@ars.usda.gov). P. J. Starks is with the Grazinglands Research Laboratory, Agricultural Research Service, U.S. Department of Agriculture, El Reno, OK 73036 USA (e-mail: patrick.starks@ars.usda.gov). D. D. Bosch is with the Southeast Watershed Research Center, Agricultural Research Service, U.S. Department of Agriculture, Tifton, GA 31793 USA (e-mail: david.bosch@ars.usda.gov). M. Seyfried is with the Northwest Watershed Research Center, Agricultural Research Service, U.S. Department of Agriculture, Boise, ID 83712 USA (e-mail: mark.seyfried@ars.usda.gov). M. S. Moran and D. C. Goodrich are with the Southwest Watershed Research Center, Agricultural Research Service, U.S. Department of Agriculture, Tucson, AZ 85719 USA (e-mail: susan.moran@ars.usda.gov; dave.goodrich@ ars.usda.gov). Y. H. Kerr and D. Leroux are with Centre d’Etudes Spatiales de la BIOsphère (CESBIO), 31401 Toulouse, France (e-mail: yann.kerr@cesbio.cnes.fr; delphine.leroux@cesbio.cnes.fr). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TGRS.2011.2168533 rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expected that the SMOS estimates will improve.

DOI: 10.1109/TGRS.2011.2168533

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@article{Jackson2012ValidationOS, title={Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S}, author={Thomas J. Jackson and Rajat Bindlish and Michael H. Cosh and Tianjie Zhao and Patrick J. Starks and David D. Bosch and Mark Seyfried and Mary Susan Moran and David C. Goodrich and Yann Kerr and Delphine J. Leroux}, journal={IEEE Trans. Geoscience and Remote Sensing}, year={2012}, volume={50}, pages={1530-1543} }