Global estimates of land surface water fluxes from SMOS and SMAP satellite soil moisture data

Morteza Sadeghi, Ardeshir Ebtehaj, Wade T. Crow, Lun Gao, Adam J. Purdy, Joshua B. Fisher, Scott B. Jones, Ebrahim Babaeian, Markus Tuller

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

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 parsi-monious, 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.

Original languageEnglish (US)
Pages (from-to)241-253
Number of pages13
JournalJournal of Hydrometeorology
Volume21
Issue number2
DOIs
StatePublished - Feb 2020

ASJC Scopus subject areas

  • Atmospheric Science

Fingerprint Dive into the research topics of 'Global estimates of land surface water fluxes from SMOS and SMAP satellite soil moisture data'. Together they form a unique fingerprint.

  • Cite this

    Sadeghi, M., Ebtehaj, A., Crow, W. T., Gao, L., Purdy, A. J., Fisher, J. B., Jones, S. B., Babaeian, E., & Tuller, M. (2020). Global estimates of land surface water fluxes from SMOS and SMAP satellite soil moisture data. Journal of Hydrometeorology, 21(2), 241-253. https://doi.org/10.1175/JHM-D-19-0150.1