Abstract
Abstract. Rockfalls are major and essentially unpredictable sources of danger, particularly along transportation routes (roads and railways). Thus, assessment of their probabilities of occurrence is a major challenge for risk management. From a qualitative perspective, experience has shown that rockfalls occur mainly during periods of rain, snowmelt, or freeze–thaw. Nevertheless, from a quantitative perspective, these generally assumed correlations between rockfalls and their possible meteorological triggering events are often difficult to identify because (i) rockfalls are too rare for the use of classical statistical analysis techniques and (ii) all intensities of triggering factors do not have the same probability. In this study, we propose a new approach to investigate the correlation of rockfalls with rain, freezing periods, and strong temperature variations. This approach is tested on three French rockfall databases, the first of which exhibited a high frequency of rockfalls (approximately 950 events over 11 yr), whereas the other two databases were more common (approximately 140 events over 11 yr). These databases were for (1) the national highway RN1 on La-Réunion Island, (2) a railway in the Bourgogne region, and (3) a railway in the Auvergne region. Whereas a basic correlation analysis is only able to highlight an already obvious correlation in the case of the "rich" database, the newly suggested method appears to detect correlations in the "poor" databases. This new approach, easy to use, leads to identify the conditional probability of rockfall, according to the selected meteorological factor. It will help to optimize risk management in the considered areas with respect to their meteorological conditions.