This current study explores satellite-based soil moisture downscaling approaches and applies them to common passive microwave retrievals. Three variations of a second-order polynomial regression were tested based on the surface temperature/greenness index concept and merged information from higher spatial resolution moderate-resolution imaging spectroradiometer with soil moisture active passive (SMAP) and soil moisture and ocean salinity (SMOS) products to obtain soil moisture estimates at higher resolutions (1 km). Downscaled products were evaluated at the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Results show slight differences in performance among the three downscaling methods and little improvement between original low-resolution products and downscaled (1 km) products. Spatial analysis over WGEW demonstrates downscaled products were able to decipher small-scale heterogeneities in surface soil moisture, though spatial variability remains low compared to observations with a difference of only 0.06    m 3 /m 3 in spatial standard deviation between observations and the mean between downscaling techniques. Results demonstrate the ability of both SMOS and SMAP to represent soil moisture accurately on the point scale without applying downscaling techniques in the region under study.