Repositorio
Institucional

Lizama, Elizabet

Morales, Bastian

Somos-Valenzuela, Marcelo

Chen, Ningsheng

Liu, Mei

Understanding Landslide Susceptibility in Northern Chilean Patagonia: A Basin-Scale Study Using Machine Learning and Field Data

MDPI

REMOTE SENSING

The interaction of geological processes and climate changes has resulted in growing landslide activity that has impacted communities and ecosystems in northern Chilean Patagonia. On 17 December 2017, a catastrophic flood of 7 x 10(6) m(3) almost destroyed Villa Santa Lucia and approximately 3 km of the southern highway (Route 7), the only land route in Chilean Patagonia that connects this vast region from north to south, exposing the vulnerability of the population and critical infrastructure to these natural hazards. The 2017 flood produced a paradigm shift on the analysis scale to understand the danger to which communities and their infrastructure are exposed. Thus, in this study, we sought to evaluate the susceptibility of landslides in the Yelcho and Rio Frio basins, whose intersection represents the origin of this great flood. For this, we used two approaches, (1) geospatial data in combination with machine learning methods using different training configurations and (2) a qualitative analysis of the landscape considering the geological and geomorphological conditions through fieldwork. For statistical modeling, we used an inventory of landslides that occurred between 2008 and 2017 and a total of 17 predictive variables, which are geoenvironmental, climatological and environmental triggers derived from volcanic and seismic activity. Our results indicate that soil moisture significantly impacted spatial susceptibility, followed by lithology, drainage density and seismic activity. Additionally, we observed that the inclusion of climatic predictors and environmental triggers increased the average performance score of the models by up to 3-5%. Based on our results, we believe that the wide distribution of volcanic-sedimentary rocks hydrothermally altered with zeolites in the western mountains of the Yelcho and Rio Frio basin are highly susceptible to generating large-scale landslides. Therefore, the town of Villa Santa Lucia and the Carretera Austral (Route 7) are susceptible to new landslides coming mainly from the western slope. This requires the timely implementation of measures to mitigate the impact on the population and critical infrastructure.

2022

artículo original

This research study was funded by the Chilean National Agency of Research and Development (ANID in Spanish) through the Program of International Cooperation (PCI in Spanish), grant number PII-180008.

Este estudio de investigación fue financiado por la Agencia Nacional de Investigación y Desarrollo (ANID) de Chile a través del Programa de Cooperación Internacional (PCI), número de subvención PII-180008.

10.3390/rs14040907

PDF

landslides

natural hazards

northern Patagonia

Villa Santa Lucia

landslide susceptibility

machine learning

EARTHQUAKE

CLIMATE

CLASSIFICATION

TECTONICS

INSIGHTS

MODEL

ANDES

AREA

Vulcanología

deslizamientos

peligros naturales

patagonia norte

Villa Santa Lucía

susceptibilidad a deslizamientos

aprendizaje automático

TERREMOTO

CLIMA

CLASIFICACIÓN

TECTONICA

INSIGHTS

MODELO

ANDES

AREA

Geociencias

Geología

Oceanografía, Hidrología y Recursos del Agua

Versión publicada

CC BY 4.0

artículo original

ANID-PCI PII-180008

ANID PCI PII-180008

acceso abierto

acceso abierto

WOS:000773551000001