A novel approach to recognize the long-term spatial-temporal pattern of dry and wet years over Iran

• Published in: Physics and chemistry of the earth. Parts A/B/C 2023-10, Vol.131, p.103426, Article 103426
• Main Authors: Modabber-Azizi, Sajjad, Salarijazi, Meysam, Ghorbani, Khalil
• Format: Article
• Language: English
• Subjects: Annual series; Bayesian quantile regression; Iran; Rainfall variations; Spatial distribution; Temporal variation
• ISSN: 1474-7065; 1873-5193
• DOI: 10.1016/j.pce.2023.103426

More studies in estimating rainfall variations have focused on examining the change in the series' mean/median, which does not lead to the analysis of wet and dry conditions. Variations in wet and dry years, equivalent to changes in the upper and lower quantiles, have critical effects on human, environmental, and ecological activities. This study investigated variations in wet and dry years compared to the normal years in Iran using long-term data (1966–2019) from 41 synoptic stations. The Bayesian quantile regression model was used to study variations in annual rainfall quantiles. In addition, the spatial-temporal distribution of variations was analyzed. The results reveal that the intensities of wet years (Q90) variations are significantly higher than dry years (Q10) and normal years (Q50). In addition, wet and dry years show decreasing and increasing behaviors in most parts of Iran. Wet and dry years variations in the western, north-western, and northern regions of Iran have been more severe than the rest of the country. Moreover, the results reveal that disregarding variations in wet and dry years can lead to inappropriate inferences about water-related activities. •Variations in wet and dry years in Iran were investigated using long-term data sets.•Intensities of variations in wet years are significantly higher than in dry years.•In most parts of Iran, wet and dry years show decreasing and increasing behaviors.•Variations are severe in Iran's western, northwestern, and northern regions.