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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 #364917
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Global estimates of land surface water flux from SMOS and SMAP satellite soil moisture data

Author
item SADEGHI, M. - University Of Montana
item EBTENAJ, A. - University Of Minnesota
item Crow, Wade
item GAO, L. - University Of Minnesota
item PURDY, A. - Jet Propulsion Laboratory
item FISHER, J. - Jet Propulsion Laboratory
item JONES, S. - University Of Utah
item TULLER, M. - University Of Arizona

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/15/2020
Publication Date: 2/20/2020
Citation: Sadeghi, M., Ebtenaj, A., Crow, W.T., Gao, L., Purdy, A., Fisher, J., Jones, S., Tuller, M. 2020. Global estimates of land surface net water flux from SMOS and SMAP satellite soil moisture data. Journal of Hydrometeorology. 21:241–253. https://doi.org/10.1175/JHM-D-19-0150.1.
DOI: https://doi.org/10.1175/JHM-D-19-0150.1

Interpretive Summary: Understanding long-term changes to groundwater resources requires accurate tracking of net water flux into (and out of) the earth’s surface. Net water flux can be calculated using a water balance approach and available estimates of precipitation, evapotranspiration, and runoff fluxes; however, the accumulated impact of errors in each individual flux component are magnified when they are summed to estimate their net effect. Here, we describe a novel approach for estimating global net water flux using only satellite-based surface soil moisture retrievals. Results are well-matched with independent estimates of groundwater storage change obtained from other approaches. Application of our technique will provide a valuable new tool for assessing the global impact of irrigation agricultural on groundwater resources.

Technical Abstract: Monitoring global patterns and dynamics of land surface net water flux (NWF) is crucial to quantify the depletion and recharge of groundwater resources. Conventional estimates of NWF, as a residual of individual surface flux components, suffer from substantial mass conservation errors due to accumulated uncertainties in the individual fluxes. Here, for the first time, we provide direct estimates of global NWF based on near-surface soil moisture products derived from the Soil Moisture Ocean Salinity and Soil Moisture Active Passive satellite missions, which are fed into a novel analytical model derived from Richards’ Equation. The model is parsimonious, mass-conservative and yields unbiased estimates of long-term cumulative NWF that are tightly correlated to the long-term groundwater recharge and Gravity Recovery and Climate Experiment mass change fields. Additionally, together with existing global precipitation and evapotranspiration data, the derived NWF estimates provide a new approach to mapping of global infiltration and runoff.