Application of Google Earth Engine in Iran's Water Resources: A Review of Recent Progress and Localization Issues

Water resources management in Iran faces major challenges due to its arid climate, limited in-situ data, and climate change impacts. Google Earth Engine (GEE), a cloud-based geospatial processing platform, provides broad access to satellite observations and advanced analytical tools, offering a promising approach for hydrological analysis. This review examines recent applications of GEE in Iran, including runoff estimation using the SCS-CN method, soil erosion assessment via the RUSLE model, groundwater monitoring with GRACE data, vegetation analysis using NDVI, and rainfall-runoff modeling. Evidence from the literature shows that GEE enables the generation of spatio-temporal hydrological maps and analyses, particularly in data-scarce regions such as the Birjand Plain and Nehbandan Wetland. Nevertheless, challenges such as variable satellite data accuracy, limited access to national datasets, and insufficient technical training hinder its full potential. Opportunities including the integration of local datasets, development of user-friendly localized interfaces, and the application of machine learning techniques can significantly enhance GEE's effectiveness. Overall, this review highlights that localization and strengthened institutional collaboration are key to advancing sustainable water resources management in Iran.

Keywords:

Google Earth Engine , Water resources , Iran , Hydrology , Localization , Satellite data