吉林大学学报(地球科学版) ›› 2015, Vol. 45 ›› Issue (6): 1781-1788.doi: 10.13278/j.cnki.jjuese.201506201

• 地质工程与环境工程 • 上一篇    下一篇

基于小流域的地震扰动区降雨型滑坡泥石流危险性评价方法

王萌, 姜元俊, 黄栋, 李倩倩   

  1. 中国科学院水利部成都山地灾害与环境研究所山地灾害与地表过程重点实验室, 成都 610041
  • 收稿日期:2014-02-20 发布日期:2015-11-26
  • 作者简介:王萌(1980),女,副研究员,博士,主要从事滑坡风险评价及预警报研究,E-mail:wm@imde.ac.cn。
  • 基金资助:

    国家青年科学基金项目(41301592);中国科学院山地灾害与地表过程重点实验室自主支持基金项目(2013年度);长江科学院开放研究基金项目(CKWV2015228/KY);国家科技部重点国际合作项目(2013DFA21720)

Hazard Assessment on Rainfall-Triggered Landslide and Debris Flow in the Seismic Disturbance Area at Watershed Level

Wang Meng, Jiang Yuanjun, Huang Dong, Li Qianqian   

  1. Key Laboratory of Geo-Surface Process and Mountain Hazards, Institute of Mountain Hazards and Environment, Chinese Academy of Science, Chengdu 610041, China
  • Received:2014-02-20 Published:2015-11-26

摘要:

地震扰动区存在大量震裂松散坡体,在持续或者密集的降雨条件下极易转化为滑坡灾害。同时,滑坡又会给泥石流提供大量松散固体物质,增加泥石流的危险性。因此,在震区,灾害通常以"链"的形式出现,比单一灾种危害性大。为了更有效地对地质灾害危险性进行评价,笔者将滑坡、泥石流作为灾害链,综合地加以分析和研究。选择5·12汶川大地震中受灾严重的都江堰市白沙河流域的17条泥石流沟作为研究区,建立滑坡-泥石流危险性评价耦合模型,研究24 h不同降雨量条件下小流域滑坡泥石流危险性的变化。耦合模型包括了坡体稳定性评价模型,水文模型及以泥石流规模、发生频率、流域面积、主沟长度、流域高差、切割密度、不稳定斜坡比为评价因子的泥石流危险性评价统计模型。研究结果表明:随着降雨量的增大,参与泥石流活动的松散物质方量持续增加,但当24 h降雨量超过200 mm后,泥石流沟的危险度等级不再发生变化;17条泥石流沟中4条为中危险度,12条为高危险度,1条为极高危险度。这说明研究区地质灾害问题相当严峻,在多雨季节存在泥石流群发的可能性,直接威胁到居住在泥石流沟附近的人民群众生命财产安全;因此,对于有直接危害对象的高危险度及其以上的泥石流沟,应该按照高等级设防标准进行工程治理及发布预警报。同时也说明,将滑坡、泥石流作为灾害链研究具必要性和可行性。

关键词: 小流域, 地震扰动区, 滑坡, 泥石流, 危险性评价

Abstract:

There are many loose slopes existed in the seismic disturbance area. Landslides and debris flow can be easily induced by a heavy or concentrated rainfall. The hazards often occur in a form of chain in an earthquake region with a severer harm than the one caused by a single disaster. In order to evaluate the geological hazards effectively, we regard the landslide and debris flow as a disaster chain and conduct the analysis synthetically. A coupled model has been developed to assess the hazard degree of debris flow induced by the different 24 h precipitation at watershed level in Baishahe watershed of Dujiangyan City in Sichuan Province. The model comprises of a landslide susceptibility evaluation model, a stability model, a hydrological model to predict unstable slopes and determine the amount of landslides to be involved, and a statistical model to evaluate the hazard degree of debris flow gully by selecting debris flow volume, frequency, basin area, main gully length, height difference, cutting density, and the ratio of unstable gully bed as the evaluation parameters. The results show that the volume of loose material involved in debris flow increase with the intensity of rainfall. However, when 24 h rainfall is over 200 mm, the hazard degree of debris flow does not change any more. Among the 17 debris flows,four debris flows are middle hazardous, twelve debris flows are high hazardous, and one debris flow is very high. It indicates that the potential geological hazard is quite serious in the study area. During the rainy season, 17 debris flows might concentratedly outbreak; which would directly threaten the nearby human lives and properties. The protection engineering and early-alert should be set to eliminate the hazards caused by the debris flows in comply with the high level fortification standard. By the way, it's necessary to take landslide and debris flow as a disaster chain to make the hazard assessment.

Key words: watershed, seismic disturbance area, landslide, debris flow, hazard assessment

中图分类号: 

  • P642.22

[1] Jibson R W, Harp E L, Michael J A.A Method for Producing Digital Probabilistic Seismic Landslide Hazard Maps[J]. Engineering Geology, 2000,58: 271-289.

[2] 崔鹏,韦方强,何思明,等.5·12汶川地震诱发的山地灾害及减灾措施[J].山地学报,2008,26(3):280-282. Cui Peng, Wei Fangqiang, He Siming,et al. Mountain Disasters Induced by the Earthquake of May 12 in Wenchuan and the Disasters Mitigation[]. Journal of Mountain Science, 2008,26(3): 280-282.

[3] Rajakumar P, Sanjeevi S, Jayaseelan S,et al. Lan-dslide Susceptibility Mapping in a Hilly Terrain Using Remote Sensing and GIS[J]. Journal of the Indian Society of Remote Sensing, 2007, 35(1): 31-42.

[4] Wang M, Qiao J P, He S M. GIS-Based Earthquake-Triggered Landslide Hazard Zoning Using Contributing Weight Model[J]. Journal of Mountain Science, 2010, 7:339-352.

[5] Lee C T, Huang C C, Lee J F,et al. Statistical Approach to Earthquake-Induced Llandslide Susceptibility[J]. Engineering Geology, 2008, 100:43-58.

[6] Carrara A, Pike R J. GIS Technology and Models for Assessing Landslide Hazard and Risk[J]. Geomorphology, 2008, 94: 257-260.

[7] 兰恒星,伍法权,周成虎,等.GIS支持下的降雨型滑坡危险性空间分析预测[J].科学通报,2003,48(5): 507-512. Lan Hengxing, Wu Faquan, Zhou Chenghu ,et al. Rainfall-Induced Landslide Hazard Spatial Analyze and Prediction Based on GIS[J]. Chinese Science Bulletin, 2003,48(5): 507-512.

[8] Muntohar A, Liao H. Rainfall Infiltration: Iinfinite Slope Model for Landslides Triggering by Rainstorm[J]. Natural Hazards, 2010, 54(3): 967-984.

[9] Baum, R L, Savage W Z, Godt J W. TRIGRS :A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope Stability Analysis[J]. US Geological Survey Open-File Report,2002,424: 38.

[10] 庄建琦,彭建兵,张利勇. 不同降雨条件下黄土高原浅层滑坡危险性预测评价[J].吉林大学学报:地球科学版,2013,43(3):867-876. Zhuang Jianqi, Peng Jianbing, Zhang Liyong. Risk Assessment and Prediction of the Shallow Landslide at Different Precipitation in Loess Plateau[J]. Journal of Jilin University:Earth Science Edition, 2013, 43(3): 867-876.

[11] Montogery D R, Dietrich W E. A Physically Based Model for the Topographic Control on Shallow Landsliding[J]. Water Resources Research, 1994, 30:1153-1171.

[12] O'Loughlin E M. Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis[J]. Water Resources Research, 1986, 22:794-804.

[13] Griswold J P, Iverson R M. Mobility and Statistics and Automated Hazard Mapping for Debris Flows and Rock Avalanches[R]. Reston, VA:U S Geological Survey. Scientific Investigations Report 2007-5276,2008:22.

[14] 刘希林,莫多闻.泥石流风险评价[M].成都:四川科学技术出版社,2003:17-22. Liu Xilin, Mo Duowen. Debris Flow Risk Assessment[M]. Chengdu: Sichuan Science and Technology Press,2003:17-22.

[15] 刘希林,唐川.泥石流危险性评价[M].北京:科学出版社,1995:1-93. Liu Xilin, Tang Chuan. Debris Flow Risk Assessment[M]. Beijing: Science Press, 1995:1-93.

[16] Guzzetti F, Ardizzone F, Cardinali M,et al. Lan-dslide Volumes and Landslide Mobilization Rates in Umbria, Central Italy[J]. Earth and Planetary Science, 2009, 279:222-229.

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