Flood Seasonality Analysis in Iran: A Circular Statistics Approach

This is the authors' abstract. We don't add key points for this paper.

Flood seasonality (FS) analysis is a key to delineating hydrologically homogenous regions and better understanding flood risk, especially for arid regions. Although Iran has undergone heavy floods in current decades, a quantitative spatially distributed overview of the flood seasonality and the its affected mechanisms is currently unavailable. This study aimed in seasonality analysis of annual maximum flood with average recurrence of 2 to 500 years in 291 continuous hydrometric stations across Iran having sufficient recorded flood data (>20 years, total of 9,565 events) using a circular statistics approach. Moreover, the relationships of recurrence season of floods with eight natural and human-induced factors including catchment area, catchment perimeter, mean catchment slope, normalized difference vegetation index (NDVI), elevation of station, mean slope of river, and latitude were examined. Findings showed that flooding in Iran presents strong seasonality, with 32% and 41% of the total events occurring during winter and spring, and mostly during April (24%). Although summer floods (∼11%) are more frequent in the northern parts, winter floods present higher percentages in the south. A significant difference in flood seasonality (2 to 500 years) was identified between the northern and southeastern regions. This study suggests that the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other considered factors in shaping flood seasonality. Results can serve as a foundation for enhancing the scientific understanding of the flood seasonality across Iran, which can provide useful insights for flood prevention planning and future changes projected by models.