Journal
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
Volume 76, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ijdrr.2022.103009
Keywords
Susceptibility mapping; Mass movements; Alpine infrastructure; Logistic regression; Informative value
Funding
- Austrian Research Promotion Agency (FFG) through the project MontEO [873667]
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The alpine infrastructure of trails and huts is crucial for summer tourism, but is prone to damage from mass movements caused by extreme rainfall events. This study utilized susceptibility mapping techniques to assess the mass movement susceptibility of alpine hut and trail infrastructure in Austria. Two statistical methods, logistic regression and informative value, were employed and compared, with both methods showing high prediction rates. Field validation demonstrated the reliability of the informative value method. Alpine associations recognize the potential of susceptibility mapping for strategic management of alpine infrastructure.
The alpine infrastructure of trails and huts enables access to the Alps and is an essential element of summer tourism. Mass movements, whose frequency and magnitude are expected to increase due to extreme rainfall events associated with climate change, frequently affect this infrastructure. Alpine associations need to adopt new ways within their management and maintenance to cope with the expected effects. An option is the use of susceptibility maps to assess the impact of mass movements on the alpine infrastructure network at a regional scale. Thus, this study aimed to assess the mass movement susceptibility of alpine hut and trail infrastructure in a popular hiking area in the Salzkammergut region in Austria. Two statistical susceptibility mapping approaches (logistic regression and informative value) were applied, assessed for their accuracy, and compared. The susceptibility of the alpine infrastructure to mass movements was calculated for trails and huts. Field validation was performed in a mass movement hotspot within the study area. The resulting mass movement susceptibility maps show similar patterns for areas with low and high susceptibility for both methods but are influenced by the completeness of the mass movement inventory and the quality of the conditioning factors. Both methods presented a prediction rate above 68%, with a higher rate for the logistic regression method. The informative value, however, presented more reliable results during the field validation. Discussions with Alpine associations show the potential of susceptibility mapping to aid strategic alpine infrastructure management by providing an overview of susceptible alpine trails and huts.
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