Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data
Author
Sadeghi, MortezaEbtehaj, Ardeshir
Crow, Wade T.
Gao, Lun
Purdy, Adam J.
Fisher, Joshua B.
JONES, Scott B.
Babaeian, Ebrahim
Tuller, Markus
Affiliation
Univ Arizona, Dept Environm SciIssue Date
2020-02-10
Metadata
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AMER METEOROLOGICAL SOCCitation
Sadeghi, M., Ebtehaj, A., Crow, W., Gao, L., Purdy, A., Fisher, J., . . . Tuller, M. (2019). Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data. Journal of Hydrometeorology, D-19-0150.1.Journal
JOURNAL OF HYDROMETEOROLOGYRights
Copyright © 2020 American Meteorological Society.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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 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.Note
6 month embargo; published online: 10 February 2020ISSN
1525-755XVersion
Final published versionae974a485f413a2113503eed53cd6c53
10.1175/jhm-d-19-0150.1
