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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #345521

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements

Author
item REICHLE, R. - Goddard Space Flight Center
item DE LANNOY, G. - University Of Leuven
item LIU, Q. - Goddard Space Flight Center
item ARDIZONNE, J. - Goddard Space Flight Center
item COLLIANDER, A. - Jet Propulsion Laboratory
item CONATY, A. - Jet Propulsion Laboratory
item Crow, Wade
item Jackson, Thomas
item JONES, L. - University Of Montana
item KIMBALL, J. - University Of Montana
item KOSTER, R. - Goddard Space Flight Center
item MAHANAMA, S.P. - Goddard Space Flight Center
item SMITH, E. - Goddard Space Flight Center
item BERG, A. - University Of Guelph
item BIRCHER, S. - University Of Toulouse
item Bosch, David - Dave
item CALDWELL, T. - University Of Texas At Austin
item Cosh, Michael
item GONZALEZ-ZANORA, A. - University Of Salamanca
item Holifield Collins, Chandra
item Livingston, Stanley
item LOPEZ-BAEZA, E. - University Of Valencia
item MARTINEZ-FERNANDEZ, J. - National Center For Agriculture And Forestry Technologies (CENTA)
item MCNAIRN, H. - Agriculture And Agri-Food Canada
item MOGHADDAM, M. - University Of Michigan
item PACHECO, A. - Agriculture And Agri-Food Canada
item PELLARIN, T. - Universite Grenoble Alpes
item Prueger, John
item ROWLANDSON, T. - University Of Guelph
item Seyfried, Mark
item Starks, Patrick - Pat
item SU, Z. - University Of Twente
item THIBEAULT, M. - Consejo Nacional De Investigaciones Científicas Y Técnicas(CONICET)
item ULDALL, F. - Technical University Of Denmark
item VAN DER VELDE, R. - University Of Twente
item WALKER, J. - Monash University
item WU, X. - Monash University
item ZENG, Y. - University Of Twente

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/15/2017
Publication Date: 12/15/2017
Citation: Reichle, R., De Lannoy, G., Liu, Q., Ardizonne, J., Colliander, A., Conaty, A., Crow, W.T., Jackson, T.J., Jones, L., Kimball, J., Koster, R., Mahanama, S., Smith, E., Berg, A., Bircher, S., Bosch, D.D., Caldwell, T., Cosh, M.H., Gonzalez-Zanora, A., Holifield Collins, C.D., Livingston, S.J., Lopez-Baeza, E., Martinez-Fernandez, J., McNairn, H., Moghaddam, M., Pacheco, A., Pellarin, T., Prueger, J.H., Rowlandson, T., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Uldall, F., van der Velde, R., Walker, J., Wu, X., Zeng, Y. 2017. Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements. Journal of Hydrometeorology. 18(10):2621-2645. https://doi.org/10.1175/JHM-D-17-0063.1.
DOI: https://doi.org/10.1175/JHM-D-17-0063.1

Interpretive Summary: Information about root-zone soil water availability is critical for a range of applications including: agricultural drought monitoring, irrigation scheduling and the optimization of fertilizer application. The current state-of-the-art for estimating root-zone soil moisture is based on combining surface soil moisture information obtained from satellite sensors with a soil water balance model via a process called data assimilation. This paper describes the validation of a new data assimilation system which utilizes observations from the NASA Soil Moisture Active Passive (SMAP) satellite mission to globally estimate root-zone soil moisture availability. It represents the first attempt to continuously generate hourly estimates of root-zone soil moisture in near-real-time. The validation results presented here demonstrate that the data assimilation system is working as expected and producing accurate estimates of root-zone soil moisture. These results represent an important step forward in the application of these new technologies to improve the sustainability of agricultural water use.

Technical Abstract: The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real-time) and provides 3-hourly, global, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach and product assessment versus in situ measurements. Core validation sites provide surface (root-zone) soil moisture measurements for 43 (17) reference pixels at 9-km and 36-km grid-cell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root-zone) soil moisture at 401 (297) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 m3 m-3 or better. The ubRMSE for L4_SM surface (root-zone) soil moisture is 0.038 m3 m-3 (0.028 m3 m-3) at the 9-km scale and 0.034 m3 m-3 (0.024 m3 m-3) at the 36-km scale. The L4_SM estimates improve (significantly for surface soil moisture) over model-only estimates, which have a 9-km surface (root-zone) ubRMSE of 0.043 m3 m-3 (0.031 m3 m-3) and do not benefit from the assimilation of SMAP brightness temperature observations. The same relative performance was found for the time series correlation metric. The sparse networks results corroborate these findings over a greater variety of climate and land cover conditions.