Shallow landslide susceptibility map at a regional scale (Asturias, NW Spain). A heuristic-driven approach

The study area (Asturias), located in NW Spain, is a mountainous region extending over 10,000 km2, where shallow landslides triggered after heavy rainfall episodes are very frequent and pose a major threat and hazard to infrastructure and human populations, causing significant economic losses and da...

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Detalles Bibliográficos
Autores: Menéndez Duarte, Rosa Ana|||0000-0002-3261-239X, Marquínez García, Jorge Luis|||0000-0003-0624-712X, Vázquez Tarrío, Daniel|||0000-0002-5658-4426, Fernández Rodríguez, Francisco José|||0000-0001-9405-1981
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad de Oviedo (UNIOVI)
Repositorio:RUO. Repositorio Institucional de la Universidad de Oviedo
Idioma:inglés
OAI Identifier:oai:digibuo.uniovi.es:10651/73933
Acceso en línea:https://hdl.handle.net/10651/73933
https://dx.doi.org/10.1080/17445647.2024.2375094
Access Level:acceso abierto
Palabra clave:Rainfall-induced landslides
susceptibility map
heuristic models
geological/ geomorphological mapping
Descripción
Sumario:The study area (Asturias), located in NW Spain, is a mountainous region extending over 10,000 km2, where shallow landslides triggered after heavy rainfall episodes are very frequent and pose a major threat and hazard to infrastructure and human populations, causing significant economic losses and damage every year. In this regard, Shallow Landslide Susceptibility Mapping (SLSM) represents a very powerful tool for managers and agencies dealing with landslide hazards and land planning. Here we produced an SLSM for Asturias based on basic geological/geomorphological maps and a heuristic approach. The regional-scale model built here has a cell resolution of 50 m and combines bedrock geology, and surface deposits mapped at a1:25k scale together with a digital slope model. The resulting map was compared with two local inventories of landslides, giving a goodness of fit of 80 and 77.5%. To better understand the results, the erroneous data have been reviewed individually and the causes of error were analysed. Our study highlights the value of high-quality geological and, especially, geomorphological mapping for landslide susceptibility assessments .