Fast assessment model for rainfall-induced shallow landslide hazard and application

被引:0
|
作者
Guo Z. [1 ]
He J. [1 ]
Huang D. [1 ]
Zhou Y. [2 ]
Zhu Y. [3 ]
机构
[1] School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin
[2] State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Hubei, Wuhan
[3] Faculty of Engineering, China University of Geosciences(Wuhan), Hubei, Wuhan
基金
中国国家自然科学基金;
关键词
deterministic model; hazard assessment; probability of failure; rainfall; shallow landslides; slope engineering; stochastic parameters;
D O I
10.13722/j.cnki.jrme.2022.0605
中图分类号
学科分类号
摘要
The existing deterministic models that can consider rainfall effects have disadvantages such as high computational cost and inability to solve the uncertainty of geotechnical parameters when assessing regional-scale landslide hazard. To address this problem,the fast shallow landslide assessment model(FSLAM) was proposed,which can be used for rapid assessment of rainfall-induced shallow landslide hazard. The FSLAM model can consider both antecedent effective and event rainfall conditions to calculate slope groundwater and stochastic parameters were used in the model to calculate probability of failure to reflect landslide hazard. A homogeneous slope was used to do sensitivity analysis of parameters of the model. The results showed that soil cohesion,friction angle,and vegetation root cohesion were the most important input parameters of the model. The engineering application of the FSLAM model for regional landslide hazard assessment was carried out by taking the landslides induced by typhoon Megi in Wenzhou City of Zhejiang Province in 2016 as an example. The analysis results indicated that the FSLAM model can accurately capture the effect of rainfall on the probability of failure of shallow landslides,and the accuracy of receiver operating characteristic curve reached 76.4%. The model can effectively reduce the uncertainty of geotechnical parameters and improve the accuracy by using stochastic parameters. Since the simplified SCS-CN method was used to calculate the vertical flow of groundwater instead of the complex Richards equation,the computational efficiency at the regional scale of the FSLAM model is 25 times better than the TRIGRS model,and the accuracy of the TRIGRS was only 69.8%. © 2023 Academia Sinica. All rights reserved.
引用
收藏
页码:1188 / 1201
页数:13
相关论文
共 42 条
  • [1] BAUM R L, GODT J W., Early warning of rainfall-induced shallow landslides and debris flows in the USA[J], Landslides, 7, pp. 259-272, (2010)
  • [2] LI Ning, QIN Yazhou, Research on calculation model for stability evaluation of rainfall-induced shallow landslides[J], Rock and Soil Mechanics, 33, 5, pp. 1485-1490, (2012)
  • [3] SHOU K J, YANG C M., Predictive analysis of landslide susceptibility under climate change conditions—A study on the Chingshui River Watershed of Taiwan[J], Engineering Geology, 192, pp. 46-62, (2000)
  • [4] GUO Zizheng, LIU Qingli, Et al., Rainfall warning of creeping landslide in Yunyang County of Three Gorges Reservoir region based on displacement ratio model[J], Earth Science, 45, 2, pp. 673-684, (2020)
  • [5] FELL R, COROMINAS J, BONNARD C, Et al., Guidelines for landslide susceptibility,hazard and risk zoning for land use planning[J], Engineering Geology, 102, 3, pp. 85-98, (2008)
  • [6] GUZZETTI F,, CARRARA A, CARDINALI M,, Et al., Landslide hazard evaluation:a review of current techniques and their application in a multi-scale study,Central Italy[J], Geomorphology, 31, 1, pp. 181-216, (1999)
  • [7] SEZER E A, OSNA T., An expert-based landslide susceptibility mapping(LSM) module developed for Netcad Architect Software[J], Computers and Geosciences, 98, pp. 26-37, (2017)
  • [8] RUFF M, CZURDA K., Landslide susceptibility analysis with a heuristic approach in the Eastern Alps(Vorarlberg , Austria)[J], Geomorphology, 94, 3, pp. 314-324, (2008)
  • [9] ZEZERE J L,, PEREIRA S, MELO R, Et al., Mapping landslide susceptibility using data-driven methods[J], Science of the Total Environmental, 589, pp. 250-267, (2017)
  • [10] CHANG K T, CHIANG S H., An integrated model for predicting rainfall-induced landslides[J], Geomorphology, 105, 3, pp. 366-373, (2009)