Spatio-Temporal Extreme Value Modeling of Extreme Rainfall over the Korean Peninsula Incorporating Typhoon Influence

This study models the spatiotemporal heterogeneity of extreme rainfall over the Korean Peninsula using the generalised additive extreme value models (EVGAM) to address the limitations of traditional stationary approaches under climate change. Analyzing 30 years of daily precipitation data (1995–2024), we conducted a comparative analysis between typhoon-inclusive and non-typhoon scenarios to isolate the meteorological drivers of extremes. The results revealed distinct covariate dependencies: while spatial location (latitude and longitude) governs rainfall variability in non-typhoon conditions, elevation emerged as the critical determinant for the scale parameter during typhoon events, highlighting the role of orographic effects. Furthermore, the shape parameter exhibited multi-decadal oscillations corresponding to climate variability indices. To ensure local accuracy, a dual fitting strategy was implemented, supplementing EVGAM with standalone generalized extreme value (GEV) estimation for stations exhibiting poor goodness-of-fit. The resulting 50-year and 100-year return level maps quantify regional risks, identifying the southern coast as a high-vulnerability zone driven by typhoons, while inland basins benefited from orographic shielding. This comprehensive framework provides a robust scientific basis for adaptive water resource management and infrastructure design.