4.5 Article

Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data

Journal

JOURNAL OF HYDROMETEOROLOGY
Volume 21, Issue 2, Pages 241-253

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-19-0150.1

Keywords

Remote sensing; Satellite observations; Hydrologic models

Funding

  1. National Aeronautics and Space Administration (NASA) [80NSSC18K152, 80NSSC18K0742]
  2. National Science Foundation (NSF) [1521469, 1521164]
  3. University of Arizona (UA) College of Agriculture and Life Sciences (CALS) Innovation Venture Investment Project (iVIP)
  4. NASA
  5. Division Of Earth Sciences
  6. Directorate For Geosciences [1521164] Funding Source: National Science Foundation

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In-depth knowledge about the global patterns and dynamics of land surface net water flux (NWF) is essential for quantification of depletion and recharge of groundwater resources. Net water flux cannot be directly measured, and its estimates as a residual of individual surface flux components often suffer from mass conservation errors due to accumulated systematic biases of individual fluxes. Here, for the first time, we provide direct estimates of global NWF based on near-surface satellite soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites. We apply a recently developed analytical model derived via inversion of the linearized Richards' equation. The model is parsimonious, yet yields unbiased estimates of long-term cumulative NWF that is generally well correlated with the terrestrial water storage anomaly from the Gravity Recovery and Climate Experiment (GRACE) satellite. In addition, in conjunction with precipitation and evapotranspiration retrievals, the resultant NWF estimates provide a new means for retrieving global infiltration and runoff from satellite observations. However, the efficacy of the proposed approach over densely vegetated regions is questionable, due to the uncertainty of the satellite soil moisture retrievals and the lack of explicit parameterization of transpiration by deeply rooted plants in the proposed model. Future research is needed to advance this modeling paradigm to explicitly account for plant transpiration.

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