This study adopts an applied, descriptive–analytical research design to spatially model and analyze climate resilience to water scarcity in Boyer-Ahmad County, Iran. In the first stage, to identify the key dimensions and determinants influencing watershed resilience under water-stress conditions, a comprehensive set of 23 spatial indicators was compiled and classified into six major categories, namely climatic, hydrological, topographical, environmental, demographic, and geological factors. These indicators were identified through a systematic review of the international literature and subsequently validated in accordance with the geomorphological and environmental characteristics of the study area.

To determine the relative importance of the selected indicators while minimizing subjective bias in the weighting process, the Method based on the Removal Effects of Criteria (MEREC) was employed. Following the estimation of criterion weights, the standardized spatial layers were integrated within a Geographic Information System (GIS) using a weighted overlay approach to generate the final climate resilience map of Boyer-Ahmad County.

Subsequently, spatial statistical analyses were conducted to identify spatial clustering patterns and evaluate the statistical significance of the spatial distribution of resilience levels using the Getis–Ord Gi* local spatial autocorrelation statistic. This method enables the identification of statistically significant hotspots and cold spots, where hotspots represent areas characterized by a high concentration of climate vulnerability and low resilience to water scarcity, whereas cold spots indicate relatively resilient areas with lower levels of vulnerability and greater adaptive capacity.