High Spatio-Temporal Resolution Soil Moisture for Agricultural Applications in the Western United States

Soil moisture is one of the critical variables that controls near-surface water and heat fluxes. Accurate soil moisture will enhance agricultural management practices (such as irrigation and planting schedule), and may provide valuable information for crop yield prediction. Accessibility of accurate soil moisture estimates is particularly important over agricultural regions of western United States due to scarcity of available water. Global soil moisture monitoring missions, such as Soil Moisture Active Passive (SMAP), provide soil moisture estimates at a spatial resolution of ~36 km with a temporal repeat cycle of ~2-3 days. However, the SMAP radiometer spatial resolution (~36 km) may not be adequate for precision agriculture due to high spatial heterogeneity in agricultural domains. Various efforts have been made on disaggregating the satellite soil moisture products to finer spatial resolution. One of the proposed methodologies uses thermal flux variation to disaggregate coarse resolution soil moisture by using higher resolution land surface temperature (LST) observations from thermal sensors. A thermal flux approach was implemented based upon the thermal inertial theory using LST and NDVI from MODIS to estimate wetness variation at fine scale (1 km). However, non-coincident satellite revisits and cloud cover result in missing data or gaps in the disaggregated soil moisture products.

This study improves the disaggregated soil moisture algorithm by combining the thermal flux approach with a soil drainage-based approach to enhance the spatio-temporal scale of soil moisture. The soil drainage approach uses soil retention curve and field capacity derived from soil texture information to estimate the soil moisture distribution at 1 km. This soil drainage approach provides contiguous estimates at high resolution and can be used to fill the gaps. The two disaggregation approaches are combined based upon temperature. At higher temperatures the heat transport is stronger so the wetness from thermal flux approach is weighted higher. The results from this approach are validated using in situ observations.