High-Resolution SMAP Soil Moisture in Agriculture: Capturing Field-Scale Variability in Soil Moisture and Evapotranspiration in the San Luis Valley
Abstract
A newly developed downscaling algorithm produces a 400 m resolution soil moisture (SM) product from native 36 km Soil Moisture Active Passive (SMAP) observations. The objective of this research is to demonstrate that this downscaled SM product provides enhanced field-scale discrimination of SM variability compared with the existing 9 km SMAP product in the San Luis Valley in Colorado. We demonstrate that the 400 m product exhibits greater sensitivity to differences in irrigation type, crop type, evapotranspiration (ET) and planting/harvesting dates. The high-spatial-resolution SM correlates well with Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) precipitation, and Moderate Resolution Imaging Spectroradiometer (MODIS) ET. MODIS ET correlates better with the 400 m product than the 9 km product (0.457 versus 0.392) and better discerns differences between crop types. We also find that SM and precipitation have a stronger correlation in crops requiring less irrigation and that sprinkler-irrigated fields have lower ET and SM than flood-irrigated fields. Our rotated empirical orthogonal function (REOF) analysis shows that unlike the 9 km product, the 400 m soil moisture product can detect field-scale trends consistent with seasonal water management. Both products detect basin-wide changes, including SM responses to snowmelt and increasing SM at higher elevations in recent years. Rotated principal component analysis of the 400 m SM product and MODIS ET revealed seasonal patterns concentrated over irrigated fields, lower values during dry years, and increased runoff following winters with high snow water equivalent.