Study on Flood Characteristics under Different Rainfall Mechanisms

methods the annual maximum flood (AMF) and the peak over threshold (POT) methods, and applies extreme value theory to analyze the flood data. In the AMF method, the statistical characteristics of flood peaks are described by fitting a Gumbel distribution; in the POT method, the tail behavior of flood events exceeding a set threshold is modeled using the Generalized Pareto Distribution (GPD). Additionally, rainfall intensity, duration, and frequency are statistically analyzed, and the Mann-Kendall non-parametric trend test, which accounts for autocorrelation effects, is used to reveal significant changes in the spatiotemporal distribution and extreme value characteristics of floods. The results show that, since 1990, the peak flood month in the XF watershed has shifted from July to June, while flood events in August have significantly increased in the HJT watershed. Furthermore, the temperature has shown a significant upward trend, consistent with the theoretical expectation of increased atmospheric water vapor and intensified extreme rainfall. Although a single trend test is insufficient to directly prove the causal effect of climate change, the combined changes in extreme value distribution parameters provide solid statistical evidence for the potential impact of climate change on flood extremes and their spatiotemporal distribution. The findings of this study offer scientific support for regional flood management, infrastructure design, and future climate-adaptive flood risk management.