Volume estimation and stage division of the Mahu landslide in Sichuan Province, China

Yulong Cui (), Jianhui Deng and Chong Xu
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Yulong Cui: Anhui University of Science and Technology
Jianhui Deng: Sichuan University
Chong Xu: Earthquake Administration China

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 2, No 19, 955 pages

Abstract: Abstract The Mahu lake, the third deepest lake in China, is located on the west bank of the Jinsha River in Leibo county, Sichuan Province. It is a dammed lake created by an old landslide on the ancient Huanglang river, a tributary on the west bank of the Jinsha River. Previous studies (Wang and Lu in J Mt Res S1:44–47, 2000) suggested that this landslide was caused by an earthquake approximately 372 ka (Middle Pleistocene), during which a few hundreds of million cubic meters of debris were deposited between 1177 and 900 m a.s.l. (above sea level), covering an area of around 15 km2. Our further investigations, including geodetic survey, borehole drilling, and field reconnaissance, combining with five chronological data, have made some new discoveries at this site. First, the toe of the landslide extends from 900 m a.s.l. down to 320 m a.s.l., i.e., the local bed elevation of the contemporary Jinsha River. Second, the area of the landslide deposits is 17.3 km2 with a volume of 2.38 km3, much larger than the previous estimation. Thus, it should be one of the largest known landslides in China. And the lower elevation of the landslide’s toe also rules out the possibility that it is a hanging valley on the ancient Huanglang river. Our work suggests that this landslide was created by five events according to the overlapping characteristics of the deposits and five chronological data, which are old than 52,600 years, old than 16,000 years, old than 15,500 years, 5800 years, and old than 4200 years, respectively.

Keywords: Mahu lake; Large landslide; Volume estimation; Stage division (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3334-8

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