Hazard zonation of large-scale landslides along Sichuan—Tibet Railway based on contributing weights model

Abstract

Sichuan—Tibet Railway is the national important infrastructure construction projects, and ensuring the smooth construction and the safe post operation of the railway is very important. The large-scale landslides with extensive development and serious damage along the railway have become the key control nodes of the railway and even the whole line, which is related to the success of the project construction. This paper takes large landslides along the railway (including giant landslides) as the main research object. Based on the field investigation and remote sensing interpretation of the large-scale landslides, the contributing weights model is used to assess the large-scale landslides hazard along the railway area in the ArcGIS platform and the Natural Breaks method is used to partition and statistically analyze the hazard assessment results. The results show that there are 147 large and extra-large landslides along the Sichuan—Tibet Railway, including 106 large landslides and 41 large landslides, mainly distributed in the zone of Baiyu to Jiangda, Changdu to Basu, Lang County to Jiacha. The areas along the railway in the three-level (high, moderate and low) dangerous areas are 35918.5 km2, 95484.3 km2 and 12039.7 km2 respectively, and the distribution density of large-scale landslides in the high hazard area is 0.00199/km−2, which is approximately two times of the moderate and the low hazard area. The high hazard area is mainly concentrated in the zone of Bangda to Basu, Guxiang to Layue, and Baiyu to Jiangda. It can be seen that the hazard scale of the large landslide along the Sichuan-Tibet Railway calculated by the contributing weights model is consistent with the landslide distribution density of the field survey. Relevant research results can provide scientific reference and basis for the construction of Sichuan—Tibet Railway project.

Keywords

• large-scale landslide
• hazard zonation
• contributing weights model
• sichuan—tibet railway