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Medientyp:
E-Book;
Hochschulschrift
Titel:
Accounting for environmental change and uncertainties in landslide susceptibility modeling
:
case study of the eastern Alpine forelands in Austria
Anmerkungen:
Kumulative Dissertation, enthält Zeitschriftenaufsätze
Tag der Verteidigung: 29.05.2024
Zusammenfassungen in deutscher und englischer Sprache
Beschreibung:
Landslides are a major natural hazard in the eastern Alpine forelands of Austria. However, the relative role of intense rainfall, soil moisture, and land use/land cover (LULC) changes explaining landslide occurrences is still not fully understood. Additionally, uncertainties about their occurrence in a changing environment are substantial. In this dissertation, I developed a model design that allows to assess landslide susceptibility, focusing on rainfall-triggered landslides of the slide type with possible transitions to complex slide flows. Beginning with a retrospective view spanning a period of nearly 200 years, I examined the effects of historical LULC changes on models of present-day landslide susceptibility by introducing a novel indicator of historical land use intensity. I subsequently addressed susceptibility modeling of landslides triggered by extreme rainfall events in June 2009 and September 2014 in the Styrian Basin. By taking a prospective view on the 2009 event, I investigated storylines of pre-industrial and future landslide susceptibility and the uncertainty cascade of the integrated modeling framework of landslide and climate models. The results showed that hydrometeorological and LULC variables were of high relative importance in explaining landslides and significantly improved model performance when added. Furthermore, I discovered a generally lower landslide susceptibility for the pre-industrial climate, while for the future climate (2071–2100) a potential increase of 35 % in highly susceptible areas may be compensated for by much drier soils. However, the estimated uncertainties in the storylines were generally high — especially for the landslide model. In the future, the availability of event-based landslide inventories and high-resolution soil and precipitation data will help to improve the assessment of landslide susceptibility.