Spatiotemporal trend and variability of precipitation across Iran: A multi-stage homogeneity adjustment and autocorrelation-corrected framework

Study Region Iran, an arid and semi-arid country, was assessed using precipitation records from 75 synoptic stations over 1979–2019; 75 stations met the predefined retention criteria after homogeneity screening. Study Focus The study provides an integrated assessment of precipitation homogeneity, serial dependence, variability, and trends at annual and seasonal scales. Four homogeneity tests were combined with lag-1 autocorrelation testing. The Mann–Kendall (MK) test was used for series without significant autocorrelation, and trend-free pre-whitening MK (TFPW-MK) for autocorrelated series. Sen's slope quantified trend magnitude, and the coefficient of variation (CV) characterized relative variability. Benjamini–Hochberg false discovery rate (FDR) adjustment was additionally applied separately to the 75 station-level tests within each temporal scale. New Hydrological Insights for the Region Annual precipitation CV averaged 35.3% (15.4–73.3%) and increased from northwest to southeast. Summer had the highest mean CV (222%). At the nominal 5% level, 12 stations showed significant annual trends (9 decreases, 3 increases), while winter had 14 significant decreases. Mean Sen's slopes were −0.48 mm/year annually and −0.78 mm/year in winter. Significant winter decreases were concentrated in southwestern and central Iran. After FDR adjustment, only two station–time-scale trends remained significant, indicating more limited evidence for widespread statistical significance under multiple testing. These results provide a structured basis for regional water-resource and climate-adaptation planning.