Abstract
A rockfall dataset for Germany is analysed with the objective of identifying the meteorological and hydrological (pre-) conditions that change the probability for such events in Central Europe. The factors investigated in the analysis are precipitation amount and intensity, freeze-thawing cycles as well as sub-surface moisture. As there is no suitable observational dataset for all relevant sub-surface moisture types (e.g. water in rock pores and cleft water) available, simulated soil moisture and parameterised pore water are tested as substitutes. The potential triggering factors were analysed both for the day of the event as well as for the days leading up to the event. It is found that the most important factor influencing rockfall probability in the research area is precipitation amount at the day of the event but the water content of the ground on that day and freeze-thawing cycles in the days prior to the event also influence the hazard probability. Comparing results with simulated soil moisture and parameterised pore water revealed that precipitation minus potential evaporation evaluated for a weekly period performs well as a proxy for the relevant sub-surface moisture types. A logistic regression model was built, which considers individual potential triggering factors as well as their interactions. Using this model the effects of meteorological conditions on rockfall probability in the Central European low mountain ranges can be quantified. The model suggests that precipitation is most efficient, when the moisture content of the ground is high. An increase of daily precipitation from its local 50th percentile to its 90th percentile approximately doubles the probability for a rockfall event under median sub-surface moisture conditions. When the moisture content of the ground is at its 95th percentile the same increase in precipitation leads to a four-fold increase in rockfall probability. The occurrence of a freeze-thaw cycle in the preceding days can further increase the rockfall hazard. The most critical combination can be expected in the winter season after a freeze-thaw transition which is followed by a day with high precipitation amounts and takes place in a region preconditioned by a high level of sub-surface moisture.
Highlights
Landslides are geomorphological hazards associated with damage and fatalities to people and their connected structures (Froude and Petley, 2018)
The performance of the statistical models listed in Tab.1 can be compared with the help of the cross validated logarithmic skill score (LSScv) with a higher skill score denoting a better performance of the model
Models 6–8 reveal that considering soil moisture in addition to the local percentile of daily precipitation improves the statistical model with the best result obtained by using 225 both variables individually as well as their interaction term
Summary
Landslides are geomorphological hazards associated with damage and fatalities to people and their connected structures (Froude and Petley, 2018). As effects of climate change become more and more visible, the scientific community tries 25 to understand and predict the consequences for landslides (e.g., Gariano and Guzzetti, 2016; Macciotta et al, 2017; Haque et al, 2019; Bajni et al, 2021). Specific weather conditions must meet specific ground conditions for landslides to occur. Meteorological parameters and thresholds are spatially heterogeneous and results from previous studies on this issue site-specific. The term “landslides” encompasses multiple mass wasting processes on slopes (e.g., mud flow and rockfall) that each depend on different preconditions and trigger mechanisms (Varnes, 1978; Hungr et al, 2014). 30 It is sensible to study these different types of processes separately The term “landslides” encompasses multiple mass wasting processes on slopes (e.g., mud flow and rockfall) that each depend on different preconditions and trigger mechanisms (Varnes, 1978; Hungr et al, 2014). 30 It is sensible to study these different types of processes separately
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