Global warming is altering the water cycle, driving changes in the intensity, seasonality and timing of hydro-climatic extremes such as flooding and extreme precipitation. These shifts have significant implications for soil erosion, landslides, and debris flow, requiring a comprehensive analysis of historical trends and future projections. This research integrates historical observations, advanced statistical techniques, and climate model projections to assess large-scale changes in hydro-climatic extremes. Results reveal notable shifts in the timing and seasonality of extreme precipitation, with future projections indicating an intensification of rarest events. These findings highlight the need for improved downscaling techniques and bias correction methods to enhance predictions at finer spatial and temporal scales. This research underscores the critical role of robust statistical frameworks in understanding and mitigating the impacts of extreme events in a changing climate. Particularly as a key driver of hydrological prediction, and understanding how representing precipitation extremes translates to hydrological response.
