Modeling and statistical extrapolation of drought dynamics in Northern Iran using pixel-based spatiotemporal framework

Drought is a critical hydro-climatic hazard with profound implications for water resources, ecosystems, and food security. This study investigates the spatiotemporal dynamics of drought and extrapolates its future evolution across the northern half of Iran using an Integrated Markov Chain–Cellular Automata (IMC–CA) framework. Climatic records from 21 meteorological stations covering the period 1967–2024 were utilized to compute the Standardized Precipitation Evapotranspiration Index (SPEI). Due to the non-normal distribution of the dataset, spatial interpolation was conducted using the Inverse Distance Weighting (IDW) method, followed by discretization into a 20 km 2 pixel grid (40,482 cells). The IMC–CA model was then employed to simulate drought class transitions for the period 2025–2040 by integrating temporal transition probabilities with spatial neighborhood effects. Long-term trends were assessed using Spearman’s Rho (SpR) for both historical (1967–2024) and extended (1967–2040) periods. Model performance was validated using Concordance Correlation Coefficient (CCC), coefficient of determination (R 2 ), and Mean Absolute Error (MAE), confirming high reliability of both interpolation and prediction procedures. The results indicate that near-normal conditions are expected to dominate the study area during the projection period, while wet classes become increasingly limited and spatially confined. Despite this apparent stability, trend analysis reveals a persistent and widespread drying signal, with significant decreasing trends detected across 70.59% of the region during 1967–2024 and projected to remain dominant (61.73%) through 2040. These findings highlight a transition toward a drying normal regime, suggesting long-term aridification despite reduced extreme anomalies. The most important finding is that although extreme drought events are projected to become less frequent, more than 60% of the region is expected to remain under statistically significant long-term drying trends, indicating a persistent process of regional aridification.