Abstract
Snow avalanches are recurring natural hazards that affect the population and transport infrastructure in alpine regions during the winter months such as in the most recent avalanche winters of 2018 and 2019, where large damages were caused by avalanches throughout the Alps. Decision makers need detailed information on the spatial distribution of the hazard and risk in order to prioritize and apply appropriate adaptation strategies and mitigation measures to minimize impacts. Here, we present a novel risk assessment approach for assessing the spatial distribution of avalanche risk by combining large-scale hazard mapping with a state-of-the-art risk assessment tool, where risk is understood as the product of hazard, exposure, and vulnerability. Hazard disposition is modeled using the large-scale hazard indication mapping method RAMMS::LSHIM, and risks are assessed using the probabilistic Python-based risk assessment platform CLIMADA, developed at ETH Zürich. The avalanche hazard mapping for scenarios with a 30, 100, and 300 year return period is based on a high-resolution terrain model, 3-day snow depth increase, automatically determined potential release areas, and protection forest information. Avalanche hazard for 40,000 single snow avalanches is assessed in avalanche intensity measured as pressure. Exposure is represented with a detailed building layer indicating the spatial distribution of monetary assets. Vulnerability of the buildings is defined by damage functions based on the software EconoMe, which is in operational use in Switzerland. The outputs of the hazard, exposure, and vulnerability analyses are combined to quantify the risk in spatially explicit risk maps. The risk considers the probability and intensity of snow avalanche occurrence as well as the concentration of vulnerable, exposed buildings. Uncertainty and sensitivity analyses were performed to capture inherent variability in the input parameters. This new risk assessment approach allows for the quantification of avalanche risk on large scales and results in maps that show the spatial distribution of risk at specific locations. Large-scale risk maps can assist decision makers in identifying areas where hazard mitigation and/or adaption is needed to address current and future avalanche risk.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.