Investigating the causes of water scarcity in the gavkhoni basin through dynamic cellular automata models and landsat satellite imagery

Water scarcity in Iran’s Gavkhoni Basin has intensified due to accelerated land-use change and ineffective water management. This study employs a spatially explicit Cellular Automata (CA) model to analyze drought-related transformations from 2010 to 2020 and to forecast conditions through 2030. Using Landsat 7 and 8 imagery, three remote sensing indices—the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI)—were derived to monitor vegetation health, surface water availability, and urban expansion at a 30-meter resolution. Three modeling scenarios, each with distinct transition rules and calibration strategies, were tested to simulate land cover dynamics. Scenario 3, based on expert-informed rules and refined parameter tuning, yielded the lowest RMSE values (NDVI: 0.041, NDWI: 0.041, NDBI: 0.075) and was selected for projection.Results indicate a projected 54% decline in surface water and a 53% reduction in vegetation cover by 2030, driven primarily by unsustainable agricultural practices and urban sprawl. The expansion of built-up areas, particularly around Isfahan, coincides with ecological degradation in the basin’s eastern zones. These findings underscore the dominant role of anthropogenic pressures intensifying regional drought and offer actionable insights for land-use planning, water policy reform, and sustainable development in arid regions.