María Florencia Degano, Sabrina Beninato, José Pasapera, Mauro Holzman, Raúl Eduardo Rivas
Soil moisture (SM) is a key variable for assessing plant water availability, especially in rain-fed systems where imbalances strongly affect crop development. Satellite missions such as SMAP provide global SM estimates, though representing vertical SM variability remains challenging. This study evaluates the performance of SMAP Level 4 Global 3-hourly 9 km grid EASE-Grid Surface and Root-Zone Soil Moisture Geophysical Data (SPL4SMGP, version 7 and the new and scarcely evaluated version 8) using field observations from the Argentine Pampas, a region dominated by Typic Argiudolls soils (~16 million ha). The analysis covered normal-wet and dry conditions across several crop seasons. Surface (SSM, ~5 cm) and root zone (RZSM, 0–100 cm) soil moisture were compared against field data using Pearson’s correlation (r), bias, and unbiased root mean square deviation (ubRMSD). Both SSM and RZSM achieved ubRMSD values close to the SMAP accuracy target (≈0.04 m3/m3). SSM correlated moderately with observations (r = 0.57–0.72) and showed a consistent negative bias (−0.08 ± 0.05 m3/m3). In contrast, RZSM exhibited low sensitivity to soil profile variability and a narrow dynamic range. Version 8 showed similar performance to version 7, with a tendency toward overestimation, mainly during dry periods. Overall, SPL4SMGP products effectively capture SSM dynamics but show limited skill in representing root zone variability in Typic Argiudolls.