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Volume 22, issue 9 | Copyright
Hydrol. Earth Syst. Sci., 22, 4935-4957, 2018
https://doi.org/10.5194/hess-22-4935-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Sep 2018

Research article | 25 Sep 2018

Development of soil moisture profiles through coupled microwave–thermal infrared observations in the southeastern United States

Vikalp Mishra1,2, James F. Cruise1, Christopher R. Hain3, John R. Mecikalski4, and Martha C. Anderson5 Vikalp Mishra et al.
  • 1Earth System Science Center, The University of Alabama in Huntsville, Huntsville, AL, USA
  • 2NASA-SERVIR, Marshall Space Flight Center, Huntsville, AL, USA
  • 3NASA Marshall Space Flight Center, Earth Science Branch, Huntsville, AL, USA
  • 4Atmospheric Science Department, University of Alabama in Huntsville, Huntsville, AL, USA
  • 5Hydrology and Remote Sensing Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA

Abstract. The principle of maximum entropy (POME) can be used to develop vertical soil moisture (SM) profiles. The minimal inputs required by the POME model make it an excellent choice for remote sensing applications. Two of the major input requirements of the POME model are the surface boundary condition and profile-mean moisture content. Microwave-based SM estimates from the Advanced Microwave Scanning Radiometer (AMSR-E) can supply the surface boundary condition whereas thermal infrared-based moisture estimated from the Atmospheric Land EXchange Inverse (ALEXI) surface energy balance model can provide the mean moisture condition. A disaggregation approach was followed to downscale coarse-resolution ( ∼ 25km) microwave SM estimates to match the finer resolution ( ∼ 5km) thermal data. The study was conducted over multiple years (2006–2010) in the southeastern US. Disaggregated soil moisture estimates along with the developed profiles were compared with the Noah land surface model (LSM), as well as in situ measurements from 10 Natural Resource Conservation Services (NRCS) Soil Climate Analysis Network (SCAN) sites spatially distributed within the study region. The overall disaggregation results at the SCAN sites indicated that in most cases disaggregation improved the temporal correlations with unbiased root mean square differences (ubRMSD) in the range of 0.01–0.09m3m−3. The profile results at SCAN sites showed a mean bias of 0.03 and 0.05 (m3m−3); ubRMSD of 0.05 and 0.06 (m3m−3); and correlation coefficient of 0.44 and 0.48 against SCAN observations and Noah LSM, respectively. Correlations were generally highest in agricultural areas where values in the 0.6–0.7 range were achieved.

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Multiple satellite observations can be used for surface and subsurface soil moisture estimations. In this study, satellite observations along with a mathematical model were used to distribute and develop multiyear soil moisture profiles over the southeastern US. Such remotely sensed profiles become particularly useful at large spatiotemporal scales, can be a significant tool in data-scarce regions of the world, can complement various land and crop models, and can act as drought indicators etc.
Multiple satellite observations can be used for surface and subsurface soil moisture...
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