Spatiotemporal differentiation characteristics of extreme precipitation evolution in China's mountainous areas

Extreme precipitation in mountainous areas is the primary driver of flash floods, landslides, and debris flows. Understanding the evolutionary patterns of extreme precipitation is therefore crucial for enhancing disaster prevention and mitigation systems in these areas. Using hourly precipitation records from 800 meteorological stations located in China's mountainous regions (average slope ≥ 2°) from 1971 to 2024, this study defined extreme precipitation at each station as values above the 95th percentile of precipitation events exceeding 1 mm. The Mann-Kendall test and Theil-Sen slope estimation were then applied to systematically analyze the temporal trends in both the magnitude and frequency of extreme precipitation across China's mountainous areas. The results indicate the following: ① At the national scale, both the magnitude and frequency of extreme precipitation in mountainous areas have shown increasing trends, with average decadal increases of 0.6 mm and 0.3 events, respectively; ② In terms of spatial distribution, the most pronounced increases occurred in East China and Northwest China, followed by Northeast China and Central China, whereas South China and Southwest China exhibited relatively smaller increases, and North China showed negligible changes in frequency; ③ A 30-year sliding window analysis revealed distinct regional developmental patterns of extreme precipitation trends. Projections suggest that Northeast China, North China, and Northwest China will experience accelerated increases in both magnitude and frequency, with Northwest China showing the most pronounced growth. East China is expected to follow a decelerating upward trend, while South China and Central China may stabilize or even decline, and Southwest China will likely exhibit greater variability. Overall, this study highlights the spatiotemporal differentiation of extreme precipitation evolution in China’s mountainous areas, offering scientific evidence to support regional disaster risk prevention and control.