1.防灾科技学院 防灾减灾工程学院, 河北 三河 065200
2.中国地质大学(北京) 工程技术学院, 北京 100083
3.北京城建勘测设计研究院
4.有限责任公司, 北京 100083
4.成都理工大学 地球与行星科学学院, 四川 成都 610059
赵云辉(1993—),男(汉族),河北省昌黎县人,博士,讲师,主要从事地质灾害防治研究。Email:zyh@cidp.edu.cn。
马海志(1967—),男(汉族),北京市人,博士,博士生导师,教授级高级工程师,主要从事工程勘察及地质灾害防治研究。Email: mahaizhi@cki.com.cn。
收稿:2025-05-12,
修回:2025-09-09,
纸质出版:2025-12-10
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赵云辉, 马海志, 柳文涛, 等.北京市南港沟泥石流发育特征及孕灾成因[J].水土保持通报,2025,45(6):132-139.
Zhao Yunhui, Ma Haizhi, Liu Wentao, et al. Developmental characteristics and disaster-causing mechanisms of debris flow at Nangang gully, Beijing City [J]. Bulletin of Soil and Water Conservation,2025,45(6):132-139.
赵云辉, 马海志, 柳文涛, 等.北京市南港沟泥石流发育特征及孕灾成因[J].水土保持通报,2025,45(6):132-139. DOI: 10.13961/j.cnki.stbctb.2025.06.033. CSTR: 32312.14.stbctb.2025.06.033.
Zhao Yunhui, Ma Haizhi, Liu Wentao, et al. Developmental characteristics and disaster-causing mechanisms of debris flow at Nangang gully, Beijing City [J]. Bulletin of Soil and Water Conservation,2025,45(6):132-139. DOI: 10.13961/j.cnki.stbctb.2025.06.033. CSTR: 32312.14.stbctb.2025.06.033.
目的
2
研究北京市房山区南港沟泥石流的发育特征,揭示北京西南山区暴雨型泥石流的物源组成差异及孕灾机制,为当地及类似区域的泥石流防治提供理论支撑。
方法
2
以北京“23・7”暴雨后南港沟发生的泥石流灾害为研究对象,通过无人机获取地形数据,结合野外实地调查,分析地形、物源及水源条件;利用FLO-2D模型模拟泥石流动力过程,重点量化树枝状沟谷-高陡边坡地貌下的泥石流运动参数,并与现场调查结果进行验证。
结果
2
南港沟地形起伏大、沟谷深切,物源丰富且类型多样(含崩滑堆积、坡面侵蚀及沟床堆积物),大气降水为主要水源,暴雨是泥石流的主要激发因素。FLO-2D模拟显示,泥石流最大滑移速度为6.75 m/s,最大堆积深度为14.6 m,模拟结果与现场调查的误差率为3.995%,处于合理范围。综合分析确定南港沟泥石流易发等级指数为2~3,属于易发泥石流沟。
结论
2
南港沟泥石流为暴雨沟谷型稀性泥石流,其形成遵循“降雨—径流—揭底—汇聚”过程,属易发沟。
Objective
2
The development characteristics of the debris flow in Nangang gully, Fangshan District, Beijing City were analyzed to reveal the differences in material source composition and disaster-causing mechanisms of rainstorm-induced debris flow in the southwest mountainous areas of Beijing City, in order to provide theoretical support for debris flow prevention and control in the local area fand similar regions.
Methods
2
Taking the debris flow disaster that occurred in Nangang gully after the ‘23·7’ rainstorm in Beijing as the research object, topographic data were acquired using unmanned aerial vehicle (UAV), and terrain, material source, and water source conditions were analyzed in combination with field investigations. The FLO-2D model was used to simulate the dynamic process of the debris flow, with a focus on quantifying movement parameters under the dendritic gully-high and steep slope topography. The results were then validated against field investigation data.
Results
2
Nangang gully featured large topographic relief and deeply incised valleys, with abundant and diverse material sources (including landslide deposits, slope erosion deposits, and channel deposits). Atmospheric precipitation served as the main water source, and rainstorms were the primary triggering factor for debris flow. The FLO-2D simulations showed that the maximum sliding velocity of the debris flow was 6.75 m/s, and the maximum accumulation depth was 14.6 m. The error rate between the simulation and field investigation results was 3.995%, which was within a reasonable range. A comprehensive analysis confirmed that the susceptibility index of debris flow in Nangang gully was 2—3, classifying it as a debris flow-prone gully.
Conclusion
2
The Nangang gully debris flow is a typical rainstorm-induced gully-type dilute debris flow, with its formation following the process of ‘rainfall infiltration—runoff concentration—channel bed scouring—material convergence’, and the gully is classified as a debris flow-prone area. The FLO-2D simulation has been verified to be reliable.
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