Key points are not available for this paper at this time.
ABSTRACT: Rockfall magnitude-cumulative frequency (MCF) distributions are useful for hazard analysis in slope asset management, including evaluating risk and the potential need for mitigation measures. MCF distributions can be produced from rockfall inventories; recently, remote sensing methods such as terrestrial lidar scanning (TLS) or structure from motion (SfM) photogrammetry have become popular tools for the generation of such inventories. However, it is not feasible to monitor every cut slope in mountainous regions such as Colorado, and for slopes that are monitored, it can take multiple years to develop an inventory that provides a reliable MCF distribution. This study evaluates the performance of an alternative rapid MCF curve estimation method relative to MCF curves generated from TLS- and SfM-based rockfall inventories. The estimation method involves a field or desktop inspection, wherein the inspector assesses the annual rockfall frequency and proportions of different rockfall volumes on the slope. The resulting frequencies are then averaged with literature values for the corresponding rockmass type to adjust the generic literature MCF curve to reflect credible rockfall from the slope. This method was applied to six cut slopes in Colorado that have at least two years of remote sensing-based rockfall inventories. We find that for many (but not all) of the slopes, the method provides a reasonable approximation of the MCF curve obtained using remote sensing data, and we discuss potential reasons for observed discrepancies. 1. INTRODUCTION Monitoring rockfall along transportation corridors is imperative for understanding rockfall frequency and estimating risk associated with cut slopes (Hungr et al., 1999). A risk value communicates both the hazard of the slope and the potential consequences to roadway users. Rockfall hazard is represented by rockfall magnitude-cumulative frequency (MCF) distributions, which describes how often a certain rockfall volume or larger will occur. Thus, the MCF curve can be used as a key input for estimating cut slope risk.
Werley et al. (Sun,) studied this question.