Abstract

Extreme storms commonly trigger landslides in regions of humid, warm tropical climate causing loss of life and economic devastation. The tropical mountainous areas of Guerrero in southwest Mexico are frequently hit by extreme hurricanes and cyclones and thus prone to landslides. On 16 September 2013, a huge landslide resulted in 71 fatalities and destroyed a large part of La Pintada Village. We applied remote sensing techniques using the LIDAR DEM and high-resolution images of the La Pintada area, a post-landslide field survey, geotechnical laboratory tests of colluvium material from the landslide, and a slope stability analysis. We also interviewed eyewitnesses accounts of the event. Our results suggest that the 2013 La Pintada landslide was a complex and two-stage event. An intense four-day-long rainfall event related to the landfall of Hurricane Manuel resulted in the oversaturation of soil, which was the main factor that caused the landslide. The effect of rainfall was amplified by the lack of high and dense vegetation on the 250-m-high slope. The lack of vegetation and slope-under-cutting likely contributed to the decreased slope stability. We suggest that increased intensity of extreme storms has contributed to increased landslides in this area. Furthermore, in tropical climate areas, where significant population lives in mostly developing countries, the combination of these phenomena makes them highly vulnerable to extreme storms and landslide hazards.

Details

Title
La Pintada landslide—A complex double-staged extreme event, Guerrero, Mexico
Author
Ramírez-Herrera, María Teresa 1 ; Gaidzik, Krzysztof 1 

 Laboratorio Universitario de Geofísica Ambiental & Instituto de Geografía, Universidad Nacional Autónoma de México, Ciudad Universitaria, Coyoacán, 04510 Ciudad de México, México 
Publication year
2017
Publication date
Dec 2017
Publisher
Taylor & Francis Ltd.
e-ISSN
23312041
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1994426660
Copyright
© 2017 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.