A national rockfall dataset as a tool for analysing the spatial and temporal rockfall occurrence in Germany

Abstract

This study presents an evaluation of a comprehensive dataset with information on about 700 recorded rockfall events in Germany for the first time. The focus is on the analysis of monthly distributions of three rockfall clusters in German low mountain ranges and of three elevation classes to provide an overview of the characteristic seasonal occurrence of rockfalls in Germany. Each rockfall distribution is correlated with records of meteorological station clusters which are representative for the long‐term climate conditions of the particular rockfall cluster and elevation class, respectively. The stored parameters in the dataset (year of occurrence, rock volumes, slope angles, affected objects) are evaluated to complete the extensive and differentiated overview of rockfalls in Germany. The analyses of the distributions of the three rockfall clusters show a distinct event concentration in the winter months. Differences are apparent between the monthly distributions of the elevation classes in which clear peaks are partially visible. Freeze–thaw cycles are considered to be the major trigger of winter rockfalls in Germany. Overall, the presented results may serve as a basis for further studies in the German low mountain ranges. © 2020 John Wiley & Sons, Ltd.

A New Methodology for Mapping Past Rockfall Events: From Mobile Crowdsourcing to Rockfall Simulation Validation

“…What we have shown is just a glimpse of what can be done with the collected rockfall data. The other possible applications could for example studying of rockfall triggering mechanisms and temporal occurrence [32,34,[64][65][66][67][68], magnitude-frequency of the events [7,8,15,17,20], lithological characteristics [32,[69][70][71], studying the protection effect of forest against rockfalls [72][73][74][75], rockfall distribution at different elevations [32,64], influence of climate change on rockfall activity [64,67,76] etc.…”

“…[15,33]. Often the data on smaller rockfall events are missing especially those that did not cause any damage [15,34]. Databases are, therefore, incomplete, not harmonised, and include various uncertainties about their reliability.…”

Quantification of meteorological conditions for rockfall triggers in Central Europe

“…The present study uses historical rockfall data which are extracted from the landslide database of Germany (cf. Damm and Klose, 2015;Rupp and Damm, 2020). Scientific publications, governmental reports, police reports, civil protection reports, newspapers, field data collections as well as GIS and web analyses were the vital information sources for the landslide database which currently contains about 6000 mass movement events of different types.…”

“…It is important to keep in mind that, despite the name of the analysis, a statistical relationship is no prove for a cause and effect relationship. As rockfall occurrence in Germany exhibits a seasonal cycle with a maximum in January (Rupp and Damm, 2020) it is easy to establish a statistically significant but physically incoherent relationship to any unrelated variable with a similar seasonal cycle. To account for this problem, we only analysed variables for which a physical relationship to rockfall events has already been established in previous studies for other sites.…”

“…In this context, the question arises whether a statistical model focused on meteorological parameters can accurately predict rockfall occurrence. A first investigation conducted on a monthly basis by Rupp and Damm (2020) already suggests that a relationship between rockfall events, temperature and precipitation is likely to exist in the selected study areas. The present analysis focuses on the quantification of these effects.…”