Projection of future non-stationary intensity-duration-frequency curves using the pooled CMIP6 climate models

Abstract

Extreme precipitation events can cause severe floods that pose significant risks to human lives, properties, and ecosystems. Therefore, understanding how climate change may affect the characteristics of these events is crucial for developing effective adaptation and mitigation strategies. In this study, we investigated the effect of climate change on the extreme characteristics through the concept of Intensity-Duration-Frequency curves. For this purpose, annual maximum precipitation series derived from five climate models from Coupled Model Intercomparison Project phase 6 were used to develop the historical (1965–2014) and future (2051–2100) curves for 12 major cities in Iran. By applying the pooling data method, the changes in intensity and frequency of the extreme precipitation with duration of 24-h, 48-h, and 72-h were assessed for three scenarios of SSP1-2.6, SSP2-4.5, and SSP3-7.0. The results indicate that most stations will experience more intense (up to 20%) and frequent (up to 8 times) extreme precipitation events under projected climate change scenarios, especially for the SSP3-7.0 scenario. However, these results varied across cities. The findings of this study provide valuable insights into the potential impacts of climate change on flood risk management in Iran and suggest the need for appropriate adaptive strategies.