Integrating Geostatistics and the Standardized Precipitation Index for Enhanced Drought Risk Management in a Data-Scarce Region

Drought is one of the most significant natural disasters, imposing severe environmental, economic, and social consequences worldwide. Understanding drought patterns and predicting their spatial variability are vital for sustainable water resource management. This study examines the frequency, intensity, and spatial distribution of drought in the Sefidrud watershed, situated in the eastern part of Kurdistan Province, Iran, from 1984 to 2013. Using precipitation data from 30 synoptic and rain-gauge stations, the Standardized Precipitation Index (SPI) was calculated and mapped using geostatistical interpolation methods, including Ordinary Kriging (OK), Simple Kriging (SK), and Inverse Distance Weighting (IDW) with powers 1 and 2. Results indicate that approximately 3% of the basin area experienced moderate to severe drought, while about 95% remained under normal conditions throughout the study period. The most intense droughts occurred in 1998, 1999, 2005, and 2008, primarily affecting the western lowlands due to their lower elevation and higher evapotranspiration rates. Comparative performance assessment based on RMSE values showed that IDW with power two consistently outperformed Kriging methods, suggesting its suitability for areas with relatively uniform station distribution and limited spatial autocorrelation. A strong positive correlation (r = 0.97) between SPI and groundwater level was observed at the Saghez station, confirming the hydrological significance of meteorological drought. These findings provide a practical framework for integrating SPI-based IDW mapping into regional drought monitoring and water-resource management to enhance resilience in semi-arid basins.