A novel framework for estimating probable maximum precipitation events by integrating extreme value theory and storm transposition

Study region Beijing Municipal Administrative Center (Beijing MC), China. Study focus To improve the applicability of Probable Maximum Precipitation (PMP) in urban flood protection, this study proposes the concept of Potential Probable Maximum Precipitation Events (PMPE) and develops a dual-pathway estimation framework. Based on rainfall-pattern classification, Extreme Value Theory (EVT) is used to derive statistical extreme-rainfall scenarios, while the WRF model transposes historical extreme storms from neighboring regions to generate physically consistent scenarios. By integrating statistical extremity and atmospheric-process consistency, the most adverse scenario in terms of peak intensity and total rainfall is selected for each rainfall pattern as the final PMPE. New hydrological insights for the region Extreme rainfall in the Beijing MC exhibits strong rainfall-pattern dependence, with historical storms classified into six patterns. The most hazardous PMPE features a short-duration, high-intensity structure, with a total rainfall of 326.2 mm, a maximum 1-hour intensity of 84.8 mm, and a duration of 7 h. EVT and storm transposition exhibit complementary strengths, with the former better capturing statistical extremes and the latter producing more severe scenarios when atmospheric dynamics and topographic effects dominate. These findings indicate that urban precipitation extremes arise from both statistical and physical mechanisms. PMPE therefore extends traditional design rainfall estimates to physically plausible extreme-rainfall processes, providing a more reliable basis for urban flood-risk assessment and infrastructure resilience planning.