Project Impacts

Through this project a high-resolution land data assimilation system was developed to integrate soil moisture information obtained from thermal infrared and radar remote sensing into a 30-m soil water balance model. Specifically, evapotranspiration retrievals acquired from multiple thermal infrared satellite sensors were combined to obtain the fused ET retrievals at 30-m and daily resolution via the ALEXI/DisALEXI surface energy balance system.

These ET retrievals represent the root-zone soil moisture availability. Meanwhile, sub-field-scale surface soil moisture data derived from Sentinel-1 radar observations were also integrated into the soil water balance model via the Ensemble Kalman filter. The data assimilation system, designed to assimilate both thermal infrared and radar soil moisture information, can be deployed to continuously monitor root-zone soil moisture conditions at a fine scale. This system has been operationally run over multiple California vineyard sites for 2020 and 2021 growing seasons.

Using this data assimilation system, continuous fine-scale profile soil moisture information was obtained at 30-m resolution, facilitating the monitoring of crop status and soil water availability for decision support. Particularly, root-zone soil moisture imageries were generated in a near-real-time scheme and delivered to our end user (E&J Gallo Winery). By providing this new source of fine-scale soil moisture information, we aimed to improve the water use efficiency, quality, and economic value of their grape harvests. Moreover, this system can be enhanced and expanded for more vineyards and orchards.