Holistic rockfall risk assessment in high mountain areas affected by seismic activity: Application to the Uspallata valley, Central Andes, Chile

Author:

Farvacque Manon12ORCID,Eckert Nicolas2,Candia Gabriel34,Bourrier Franck2,Corona Christophe15,Toe David2

Affiliation:

1. Climate Change Impacts and Risks in the Anthropocene, Institute for Environmental Sciences University of Geneva Geneva Switzerland

2. Univ. Grenoble Alpes, INRAE, CNRS, IRD, Grenoble INP, IGE Grenoble France

3. Facultad de Ingeniería Universidad del Desarrollo Las Condes Santiago Chile

4. Research Center for Integrated Disaster Risk Management (CIGIDEN), ANID/FONDAP/15110017, Santiago, Chile

5. Université Clermont Auvergne, CNRS, GEOLAB UMR Clermont‐Ferrand France

Abstract

AbstractOver large regions exposed to natural disasters, cascading effects resulting from complex or concatenated natural processes may represent a large portion of total risk. Populated high‐mountain environments are a major concern, and methods for large‐scale quantitative risk analyses are urgently required to improve risk mitigation. This article presents a comprehensive quantitative rockfall risk assessment over a large archetypal valley of the Andean mountains, in Central Chile, which integrates a wide spectrum of elements at risk. Risk is expressed as an expected damage both in monetary terms and casualties, at different scales relevant for decision making. Notably, total rockfall risk is divided into its main drivers, which allows quantifying seismically induced rockfall risk. For this purpose, the local seismic hazard is quantified and the yield acceleration, that is, acceleration required to initiate rockfall, is determined at the regional scale. The probability of failure is thereafter derived in terms of annual frequency of rockfall initiation and integrated in the quantitative risk assessment (QRA) process. Our results show the significant role of seismic activity as the triggering mechanism of rockfalls, and highlight elements at risk that have a major contribution to the total risk. Eventually a sensitivity analysis is conducted to (i) assess the robustness of obtained risk estimates to the data and modeling choices and (ii) identify the most influential assumptions. Our approach evidences the feasibility of large‐scale QRAs in sensitive environments and opens perspectives for refining QRAs in similar territories significantly affected by cascading effects and multihazards.

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

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