中国水土保持科学2026，Vol.24Issue(2)：39-51,13.DOI:10.16843/j.sswc.2025121
"23·7"极端暴雨门头沟区滑坡分布与主要影响因素
Spatial distribution and main influencing factors of landslides in Mentougou district during the extreme rainstorm"23·7"
摘要
Abstract
[Objective]From July 30 to August 1,2023,the Mentougou district of Beijing experienced an unprecedented extreme rainfall event,later termed the"23·7 Catastrophic Basin Flood".This event,driven by the remnants of Typhoon Doksuri and the West Pacific Subtropical High,brought cumulative rainfall exceeding 1 000 mm in some locations.Unlike typical flash floods in the region,the"23·7"event triggered extensive shallow landslides and soil-driven debris flows,highlighting a rare but increasingly significant hazard pattern in the semi-humid,semi-arid climate zone of North China.The event's uniqueness lies in its compound triggering mechanism:a combination of prolonged antecedent rainfall and short-duration,high-intensity precipitation episodes.[Methods]This study integrated high-resolution BJ-2 satellite imagery and UAV photogrammetry to identify 7 011 shallow landslides across Mentougou.A total of nine environmental variables-including slope,aspect,NDVI,lithology,land use,and distances to roads,rivers,and faults-were analyzed using kernel density estimation and a random forest model.High-accuracy DEM data from UAV coverage(151.82 km2)was used to extract refined terrain metrics for 1 995 landslide samples.The random forest algorithm was employed to evaluate the relative importance of each variable in shaping landslide spatial patterns,while kernel density mapping provided insights into distributional clustering.[Results]1)The rainfall event exhibited dual-peak characteristics with extreme intensities.Cumulative rainfall exceeded 1 000 mm over 66 hours,with hourly maxima surpassing 130 mm.These values exceeded the 100-year return period thresholds and met both key triggering conditions for shallow landslides:prolonged saturation and peak-hour intensities far above regional thresholds.2)Landslides showed strong spatial clustering along river valleys,especially in areas near the Yongding River and its tributaries.High-density zones(up to 88 events per km2)were concentrated in towns such as Zhaitang and Yanhecheng.Landslide density decreased with distance to rivers,highlighting the significant role of valley morphology and river erosion in landslide initiation.3)Random forest analysis revealed that slope(17.5％),NDVI(17.0％),and aspect(14.9％)were the dominant factors controlling landslide distribution.Southeast-facing slopes and slope gradients between 40° and 50° were particularly prone to failure.Anthropogenic variables such as distance to roads(11.2％)and nighttime light intensity(10.8％)contributed significantly,indicating a strong influence from human activity.4)Slope,vegetation,and aspect interacted in controlling landslide behavior.On slopes less than 40°,high NDVI values(＞0.7)were associated with larger landslide areas,likely due to higher soil water retention.On steeper slopes(40°-70°),NDVI had a stabilizing effect,with higher values linked to smaller landslide areas,reflecting enhanced root cohesion and surface protection.5)Comparison of slope data from 12.5 m DEM and UAV-derived DEM showed deviations of up to 20°,with coarser data significantly underestimating slope steepness.This highlighted the critical need for high-resolution topographic data in landslide susceptibility mapping,especially in complex mountain terrains.[Conclusions]The"23·7"rainfall event demonstrates a compound hazard mechanism that triggers a rare,widespread outbreak of shallow landslides in northern China's mountainous terrain.The landslides exhibit distinct spatial clustering,closely tied to topographic,hydrological,vegetative,and anthropogenic variables.Slope,vegetation cover,and aspect are identified as dominant controls,while road construction and urban development also exacerbate local susceptibility.The findings underscore the critical importance of high-resolution elevation data in such analyses and provide a valuable foundation for improving early warning systems and hazard mitigation planning in similar environments under a changing climate.关键词
浅层滑坡/极端降水/滑坡密度/随机森林/环境因素Key words
shallow landslide/extreme precipitation/landslide density/random forest/environmental factors分类
天文与地球科学引用本文复制引用
姚皓译,方子杰,马超,杨瑞杰,顾杰,毛紫毅.."23·7"极端暴雨门头沟区滑坡分布与主要影响因素[J].中国水土保持科学,2026,24(2):39-51,13.基金项目
国家自然科学基金青年科学基金项目"北方土石山区低粘度泥石流起动机理研究"(41702369) （41702369）
北京市科技计划课题"北京市沟道侵蚀泥石流多元预警阈值模型研究及示范工程"(Z191100001419015) National Natural Science Foundation of China"Research on the Initiation Mechanism of Low Viscosity Debris Flow in Northern Earth and Rocky Mountainous Areas"(41702369).Beijing Science and Technology Program"Research and Demonstration Project of Multiple Early Warning Thresholds for Channel Erosion and Debris Flow in Beijing"(Z191100001419015) （Z191100001419015）
