A four-dimensional soil moisture product: closing the soil profile gap with a SCAT-SAR-SMAR high spatiotemporal resolution approach

Accurate soil moisture (SM) information at a high spatiotemporal resolution related to the soil profile could represent an added value for monitoring and managing climate-related natural hazards and resources. In this study, we addressed this challenge using a two-step integrated approach. First, we combined two active-microwave satellite datasets, namely the Advanced SCATterometer and Copernicus Global Land Service Sentinel-1 data, to obtain surface soil moisture information at a daily temporal resolution and a spatial resolution of 1 km. Then, we applied the physically based soil moisture analytical relation (SMAR) to enhance SM prediction along the entire soil profile, achieving SCAT-SAR-SMAR data. We tested the SCAT-SAR-SMAR model in two gauged basins (that strongly differ in terms of soil characteristics) in the Alento area (Campania Region, southern Italy), where in-situ SM information was available for the 2017-2022 period. The obtained products showed good performance (in terms of root mean square difference and correlation coefficient) for comparison with in-situ data and another well-known literature approach in recognising SM spatiotemporal patterns, indicating the potential of SCAT-SAR-SMAR for a better understanding of soil moisture dynamics.