2022 Vol. 41, No. 4
Article Contents

ZHOU Yue, WANG Yunsheng, ZHAO Xun, WANG Guokang, SU Yi, BI Yangyang, XIANG Chao. Susceptibility assessment of debris flow in Dimaluo River, branch of Nujiang River[J]. Geological Bulletin of China, 2022, 41(4): 702-712. doi: 10.12097/j.issn.1671-2552.2022.04.014
Citation: ZHOU Yue, WANG Yunsheng, ZHAO Xun, WANG Guokang, SU Yi, BI Yangyang, XIANG Chao. Susceptibility assessment of debris flow in Dimaluo River, branch of Nujiang River[J]. Geological Bulletin of China, 2022, 41(4): 702-712. doi: 10.12097/j.issn.1671-2552.2022.04.014

Susceptibility assessment of debris flow in Dimaluo River, branch of Nujiang River

More Information
  • The research on debris flow in Nujiang River mostly focused on the influence of tributary debris flow on the main stream, but ignored the tributary debris flow.Dimaluo river is a tributary on the left bank of Nujiang River.It is representative in the upper reaches of Nujiang River(Yunnan)because of its convex slope landform, distribution of metamorphic soft rock, fault shear failure and abundant provenance caused by intermittent uplift of Neotectonic movement.Field investigation shows that debris flow can be divided into three types, gully type, slope type and composite type.Based on the hydrological response unit, 8 evaluation factors are selected.This paper analyzes the susceptibility of different types of debris flow by using AHP and information method.The results show that the areas with high and extremely high susceptibility to all kinds of debris flow are mainly weak strata such as Cd and Ce, and they are mainly distributed along the areas with strong human engineering activities, such as road construction, with the closer to the fault zone, the higher the susceptibility.The AUC of all types of debris flow reaches 83.34%, 90.07% and 84.39%, so the evaluation results are reasonable, which can provide scientific basis for the prevention and control planning and prediction of debris flow in Nujiang River, and provide theoretical and technical reference for disaster prevention and mitigation of mass debris flow in southwest deep canyon metamorphic soft rock area.

  • 加载中
  • [1] Guzzetti F, Reichenbach P, Cardinali M, et al. Probabilistic landslide hazard assessment at the basin scale[J]. Geomorphology, 2005, 72(1/4): 272-299.

    Google Scholar

    [2] 任敬, 范宣梅, 赵程, 等. 贵州省都匀市滑坡易发性评价研究[J]. 水文地质工程地质, 2018, 45(5): 165-172.

    Google Scholar

    [3] 王高峰, 杨强, 田运涛, 等. 泥石流易发性评价模型的构建——以白龙江流域石门乡羊汤河段为例[J]. 干旱区研究, 2019, 36(3): 761-770.

    Google Scholar

    [4] Jiang W G, Rao P Z, Cao R, et al. Comparative evaluation of geological disaster susceptibility using multi-regression methods and spatial accuracy validation[J]. Journal of Geographical Sciences, 2017, 27(4): 439-462. doi: 10.1007/s11442-017-1386-4

    CrossRef Google Scholar

    [5] Sun J, Qin S, Qiao S, et al. Exploring the impact of introducing a physical model into statistical methods on the evaluation of regional scale debris flow susceptibility[J]. Natural Hazards, 2021, 106: 881-912. doi: 10.1007/s11069-020-04498-4

    CrossRef Google Scholar

    [6] Qing F, Zhao Y, Meng X, et al. Application of Machine Learning to Debris Flow Susceptibility Mapping along the China-Pakistan Karakoram Highway[J]. Remote Sensing, 2020, 12(18): 2933-2933. doi: 10.3390/rs12182933

    CrossRef Google Scholar

    [7] Chen Y, Qin S, Qiao S, et al. Spatial Predictions of Debris Flow Susceptibility Mapping Using Convolutional Neural Networks in Jilin Province, China[J]. Water, 2020, 12(8): 2079-2079. doi: 10.3390/w12082079

    CrossRef Google Scholar

    [8] 毛佳睿, 李铁锋, 田运涛, 等. 基于物源特征的白龙江流域泥石流易发性评价[J]. 科学技术与工程, 2020, 20(28): 11479-11490. doi: 10.3969/j.issn.1671-1815.2020.28.012

    CrossRef Google Scholar

    [9] 蔡定昆. 兼顾发展权与可持续性的怒江流域开发模式研究[D]. 西南财经大学博士学位论文, 2011.

    Google Scholar

    [10] 梁馨月, 徐梦珍, 吕立群, 等. 基于地貌特征的青藏高原边缘泥石流沟分类[J]. 地理学报, 2020, 75(7): 1373-1385.

    Google Scholar

    [11] 张杰, 李世凯, 甘云兰, 等. 云南贡山8·18特大泥石流灾害调查分析与启示[J]. 工程地质学报, 2015, 23(3): 373-382.

    Google Scholar

    [12] 吕立群, 王兆印, 徐梦珍, 等. 怒江泥石流扇地貌特征与扇体堵江机理研究[J]. 水利学报, 2016, 47(10): 1245-1252.

    Google Scholar

    [13] 李树德. 滑坡型泥石流形成机理[J]. 北京大学学报(自然科学版), 1998, (4): 3-5.

    Google Scholar

    [14] 杨涛, 唐川, 常鸣, 等. 基于数值模拟的小流域泥石流危险性评价研究[J]. 长江流域资源与环境, 2018, 27(1): 197-204.

    Google Scholar

    [15] Lyons N J, Mitasova H, Wegmann K W. Improving mass-wasting inventories by incorporating debris flow topographic signatures[J]. Landslides, 2014, 11(3): 385-397. doi: 10.1007/s10346-013-0398-0

    CrossRef Google Scholar

    [16] 梁馨月, 曾璐, 葛永刚, 等. 川西高原鲜水河断裂带炉霍-道孚段泥石流分布特征[J]. 地质通报, 2021, 40, 319(12): 2061-2070.

    Google Scholar

    [17] 张书豪, 吴光, 张乔, 等. 基于子流域特征的泥石流易发性评价[J]. 水文地质工程地质, 2018, 45(2): 142-149.

    Google Scholar

    [18] Melton M A. The Geomorphic and Paleoclimatic Significance of Alluvial Deposits in Southern Arizona: A Reply[J]. The Journal of Geology, 1966, 74(1): 102-106. doi: 10.1086/627147

    CrossRef Google Scholar

    [19] 熊德清, 崔笑烽. 喜马拉雅山脉地震带主要地质灾害与地形地貌关系——以西藏日喀则地区为例[J]. 地质通报, 2021, 40(11): 1967-1980. doi: 10.12097/j.issn.1671-2552.2021.11.014

    CrossRef Google Scholar

    [20] 周超. 集成时间序列InSAR技术的滑坡早期识别与预测研究[D]. 中国地质大学博士学位论文, 2018.

    Google Scholar

    [21] 梁丽萍, 刘延国, 唐自豪, 等. 基于加权信息量的地质灾害易发性评价——以四川省泸定县为例[J]. 水土保持通报, 2019, 39(6): 176-182, 321.

    Google Scholar

    [22] 孙长明, 马润勇, 尚合欣, 等. 基于滑坡分类的西宁市滑坡易发性评价[J]. 水文地质工程地质, 2020, 47(3): 173-181.

    Google Scholar

    [23] 胡芹龙, 王运生. 基于GIS的川西地貌过渡带滑坡灾害易发性评价[J]. 成都理工大学学报(自然科学版), 2018, 45(6): 746-753. doi: 10.3969/j.issn.1671-9727.2018.06.10

    CrossRef Google Scholar

    [24] 杨盼盼, 王念秦, 郭有金, 等. 基于加权信息量模型的临潼区滑坡易发性评价[J]. 长江科学院院报, 2020, 37(9): 50-56.

    Google Scholar

    [25] Singh K, Kumar V. Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya[J]. Journal of Mountain Science, 2018, 15(4): 808-824. doi: 10.1007/s11629-017-4634-2

    CrossRef Google Scholar

    [26] 赵鹏大, 胡旺亮, 李紫金. 矿床统计预测[M]. 北京: 地质出版社, 1983.

    Google Scholar

    [27] 张以晨, 秦胜伍, 翟健健, 等. 基于信息量的长白山地区泥石流易发性评价[J]. 水文地质工程地质, 2018, 45(2): 150-158.

    Google Scholar

    [28] 宁娜, 马金珠, 张鹏, 等. 基于GIS和信息量法的甘肃南部白龙江流域泥石流灾害危险性评价[J]. 资源科学, 2013, 35(4): 892-899.

    Google Scholar

    [29] 张欣, 王运生, 梁瑞锋. 基于GIS的小江断裂中北段滑坡灾害危险性评价[J]. 地质与勘探, 2018, 54(3): 623-633. doi: 10.3969/j.issn.0495-5331.2018.03.018

    CrossRef Google Scholar

    [30] 许冲, 戴福初, 姚鑫, 等. 基于GIS与确定性系数分析方法的汶川地震滑坡易发性评价[J]. 工程地质学报, 2010, 18(1): 15-26. doi: 10.3969/j.issn.1004-9665.2010.01.003

    CrossRef Google Scholar

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(8)

Tables(6)

Article Metrics

Article views(1005) PDF downloads(72) Cited by(0)

Access History

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint