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Remote Sens. 2018, 10(3), 427; https://doi.org/10.3390/rs10030427

A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability

1
Forschungszentrum Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3), 52428 Jülich, Germany
2
Instituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, 37185 Salamanca, Spain
*
Author to whom correspondence should be addressed.
Received: 12 January 2018 / Revised: 27 February 2018 / Accepted: 8 March 2018 / Published: 9 March 2018
(This article belongs to the Special Issue Retrieval, Validation and Application of Satellite Soil Moisture Data)
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Abstract

Several studies currently strive to improve the spatial resolution of coarse scale high temporal resolution global soil moisture products of SMOS, SMAP, and ASCAT. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. We use this information for the prediction of the sub-grid soil moisture variability for each SMOS, SMAP, and ASCAT grid cell. The approach is based on a method that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean, available at https://doi.org/10.1594/PANGAEA.878889. The resulting data set helps identify adequate regions to validate coarse scale soil moisture products by providing a measure of representativeness of small-scale measurements for the coarse grid cell. Moreover, it contains important information for downscaling coarse soil moisture observations of the SMOS, SMAP, and ASCAT missions. In this study, we present a simple application of the estimated sub-grid soil moisture heterogeneity scaling down SMAP soil moisture to 1 km resolution. Validation results in the TERENO and REMEDHUS soil moisture monitoring networks in Germany and Spain, respectively, indicate a similar or slightly improved accuracy for downscaled and original SMAP soil moisture in the time domain for the year 2016, but with a much higher spatial resolution. View Full-Text
Keywords: SMOS; SMAP; ASCAT; SoilGrids; soil moisture variability; scaling; soil texture SMOS; SMAP; ASCAT; SoilGrids; soil moisture variability; scaling; soil texture
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

  • Externally hosted supplementary file 1
    Doi: 10.1594/PANGAEA.878889
    Link: https://doi.org/10.1594/PANGAEA.878889
    Description: Sub-grid soil moisture variability of SMAP, SMOS and ASCAT predicted on basis of soil texture
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Montzka, C.; Rötzer, K.; Bogena, H.R.; Sanchez, N.; Vereecken, H. A New Soil Moisture Downscaling Approach for SMAP, SMOS, and ASCAT by Predicting Sub-Grid Variability. Remote Sens. 2018, 10, 427.

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