Integrating climatic projections and geographical variables to predict road accident risks based on insights from the Khorramabad pole Zal axis under RCP scenarios

The increasing number of car accidents is attributed to the effects of climate change, such as heavy rain, snow, heatwaves, avalanches, and tornadoes. This study focuses on assessing the vulnerability of the Khorramabad–Pol-e-Zal axis road transport network in the context of climate change. The research employed the double mass test, temporal-spatial analysis using GIS software, and forecasting under RCP scenarios with a global climate model over a 30-year statistical period. The analysis of temporal and spatial data, using a weighting approach, yielded valuable insights. Linear regression was utilized to explore the correlation between climate factors and road accidents. The study identified maximum monthly rainfall and cold days as the most influential climatic parameters along this axis in Lorestan province. These parameters exhibit varying trends along the axis, with decreasing trends in the middle and end sections and an increasing trend in central regions, directly impacting accident rates. A statistically significant regression model for the axis underscores the significance of climatic factors, particularly maximum one-day rainfall and cold days. The results clearly demonstrate distinct trends in road accidents between the two climate scenarios, RCP 4.5 and RCP 8.5. RCP 4.5 shows a consistent increase in accidents leading up to 2065, with a notable spike between 2051 and 2058. In contrast, RCP 8.5 indicates a significant decrease in accidents, presenting a contrasting pattern. This disparity underscores the influence of climate change and adaptation strategies on road safety in the Khorramabad-Pol-e-Zal region. The study highlights significant variations in accident rates between the RCP 4.5 and RCP 8.5 climate scenarios. Under RCP 4.5, accidents are projected to increase by 1.5–5% per month, peaking between 2051 and 2058. Conversely, RCP 8.5 forecasts a decline in accidents during the same period, with reductions of up to 0.5% in certain years. This emphasizes the importance of implementing climate adaptation and mitigation strategies.