Idnetification of High Spatiotemporal Resolution Parameters in the Tau-Omega Model for UAS-Based Passive Microwave Soil Moisture Retrieval

The use of coarse scale and temporally static effective roughness and single scattering albedo parameters in the Soil Moisture Active Passive (SMAP) operational algorithms falls short in achieving high spatial resolution in soil moisture (SM) retrieval. To address this issue, this study leverages in-situ SM measurements from 2016 to 2018 at the SMAP core validation sites to derive monthly parameters. These parameters were then applied to estimate SM for subsequent periods. Our findings suggest that SM retrievals from these monthly-adjusted parameters exhibit a marginal improvement in mean absolute error relative to the standard SMAP retrievals. This scheme will be applied to develop high spatiotemporal resolution parameters for passive microwave SM retrieval from instruments aboard uncrewed aerial systems (UAS). The proposed method also allows for these parameters to be tailored to targeted agricultural and forested areas for applications ranging from precision agriculture to intelligent wildfire management. This adaptation promises to refine our ability to retrieve SM with greater accuracy and resolution.