IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2022)

Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

  • Pang-Wei Liu,
  • Rajat Bindlish,
  • Peggy O'Neill,
  • Bin Fang,
  • Venkat Lakshmi,
  • Zhengwei Yang,
  • Michael H. Cosh,
  • Tara Bongiovanni,
  • Chandra Holifield Collins,
  • Patrick J. Starks,
  • John Prueger,
  • David D. Bosch,
  • Mark Seyfried,
  • Mark R. Williams

DOI
https://doi.org/10.1109/JSTARS.2022.3165644
Journal volume & issue
Vol. 15
pp. 4072 – 4092

Abstract

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A thermal hydraulic disaggregation of soil moisture (THySM) algorithm was implemented to downscale NASA's soil moisture active passive (SMAP) enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in soils. Relative soil wetness values were estimated using land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both models were then combined by using weighting functions whereby the spatial distribution of SM was governed more by thermal fluxes during times of strong heat transport and infiltration during moisture abundant soil conditions. THySM values were evaluated using in situ SM measurements from SMAP Core Validation Sites (CVS), the US Department of Agriculture Soil Climate Analysis Network, and the National Oceanic and Atmospheric Administration Climate Reference Network over CONUS. THySM shows higher accuracy than the SMAP / Sentinel-1 (SPL2SMAP_S) 1 km SM product when compared to in situ measurements. The accuracy of THySM is 0.048 m3/m3 based on unbiased root mean square error (ubRMSE), outperforming SPL2SMAP_S by 0.01–0.02 m3/m3. The ubRMSE of THySM 1 km SM over the SMAP grassland/rangeland-dominated CVS sites is better than 0.04 m3/m3, which meets the SMAP mission SM accuracy requirement applied at 9 and 36 km.

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