Natural Hazards

, Volume 97, Issue 3, pp 1151–1173 | Cite as

Risk assessment of snowmelt-induced landslides based on GIS and an effective snowmelt model

  • Fasheng Miao
  • Yiping WuEmail author
  • Linwei Li
  • Kang Liao
  • Longfei Zhang
Original Paper


In early 2008, southern China experienced a severe freezing snow event, causing many geological disasters (such as landslides). Based on combining the infinite slope model and the snowmelt effect, an effective snowmelt model (ESM) is proposed to calculate the stability of landslides. The geological mechanics model of snowmelt-induced landslides is established with the Enshi area as a case study. The landslide susceptibility in the Enshi area is evaluated based on the set pair analysis and analytical hierarchy process. Then, the hazard grade of snowmelt-induced landslides is predicted and classified by the calculation results of ESM. And the warning grade of Enshi is determined based on the landslide susceptibility and the hazard grade. The results indicate the following: (1) High-susceptibility areas in Enshi are mainly concentrated in the regions of Badong County and Lichuan County. (2) The snowmelt hazard in the rock group with a high susceptibility is considered a medium-level hazard and the other areas are low-level hazards. (3) A total of 94.73% of the study region is a no-warning area, and the levels 3 and 4 warning zones account for 1.04% and 4.23%, respectively. (4) The increases in the slope gradient α and the slip zone depth Z lead to a decreasing initial stability and decreased influence of snowmelt water infiltration. (5) The snowmelt threshold can be calculated by the ESM model, and different snowmelt risk levels can be classified according to the relationship between the snowmelt threshold and the slope gradient.


Snowmelt-induced landslide Set pair analysis Analytical hierarchy process Effective snowmelt model Risk assessment 



This research is supported by the National Key R&D Program of China (2017YFC1501301), the National Natural Science Foundation of China (41572278), and the National Science-Technology Support Projects (2008BAC47B04). We would like to thank the colleagues in our laboratory for their constructive comments and assistance.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Faculty of EngineeringChina University of GeosciencesWuhanChina

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