Abstract. Southwest China is characterized by many steep mountains and deep valleys due to the uplift activity of the Tibetan Plateau. The 2008 Wenchuan Earthquake left large amounts of loose materials in this area, making it a severe disaster zone in terms of debris flow. Susceptibility is a significant factor of debris flow for evaluating its formation and impact. Therefore, it is in urgent need to analyze the susceptibility of debris flows in this area. At present, the susceptibility analysis models of the debris flow in Southwest China is mainly based on qualitative methods. Little quantitative prediction model is found in the literature. This study evaluates 70 typical debris flow gullies as statistical samples, which are distributed along the Brahmaputra River, Nujiang River, Yalong River, Dadu River, and Ming River respectively. Nine indexes are chosen to construct a factor index system and then to evaluate the susceptibility of debris flow. They are the catchment area, longitudinal grade, average gradient of the slope on both sides of the gully, catchment morphology, valley slope orientation, loose material reserves, location of the main loose material, antecedent precipitation, and rainfall intensity. Then, an empirical model based on the quantification theory type I is established for the susceptibility prediction of debris flows in Southwest China. Finally, 10 debris flow gullies on the upstream of the Dadu River are analyzed to verify the reliability of the proposed model. The results show that the accuracy of the statistical model is 90 %.
[1]
S. Han.
Sensitivity analysis for ranked data
,
2014
.
[2]
Qiang Xu,et al.
The 13 August 2010 catastrophic debris flows after the 2008 Wenchuan earthquake, China
,
2012
.
[3]
J. Moya,et al.
Rockfalls detached from a lateral moraine during spring season. 2010 and 2011 events observed at the Rebaixader debris-flow monitoring site (Central Pyrenees, Spain)
,
2012,
Landslides.
[4]
Yujing Jiang,et al.
Damage assessment of tunnels caused by the 2004 Mid Niigata Prefecture Earthquake using Hayashi’s quantification theory type II
,
2010
.
[5]
C. Gisonni.
Book Reviews
,
2008
.