ISPRS-Annals ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprs-annals-X-4-W8-2025-33-2026 Evaluation of Satellite Soil Moisture Products Against Long-Term In-Situ Observations in Southern Iran Afrasiabikia Peyman 1 Parvaresh Rizi Atefeh https://orcid.org/0000-0003-0793-6728 1 Brocca Luca https://orcid.org/0000-0002-9080-260X 2 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran Director of Research, Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy 29 05 2026 X-4/W8-2025 33 38 Copyright: © 2026 Peyman Afrasiabikia et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-annals.copernicus.org/articles/X-4-W8-2025/33/2026/isprs-annals-X-4-W8-2025-33-2026.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/X-4-W8-2025/33/2026/isprs-annals-X-4-W8-2025-33-2026.pdf

Soil moisture is vital for agricultural water management in semi-arid regions facing water scarcity. This study evaluated four satellite-based soil moisture products—SMAP Enhanced L3 Radiometer (9 km), SMAP 1 km downscaled (NSIDC), ASCAT SWI v3.0 (~11 km), and a custom Random Forest downscaled product (SMAP1km RS)—against long-term in-situ data from Zarghan Agricultural Research Station in southern Iran. Performance was assessed at daily, 10-day, 15-day, and 30-day intervals using R, RMSE, MAE, and NSE metrics. Results showed strong scale dependency: daily retrievals had significant discrepancies, but temporal aggregation greatly improved accuracy. At the 30-day scale, SMAP 1 km performed best (R=0.95, NSE=0.91), followed closely by SMAP 9 km and SMAP1km RS. ASCAT consistently underperformed. The custom SMAP1km RS showed promise but did not exceed the official SMAP 1 km dataset. SMAP 1 km is the most reliable source in this semi-arid area, and temporal aggregation effectively reduces retrieval noise, supporting irrigation water use monitoring in the region.