## 4 Discussion  
Sites A and B are located in a generally similar geologic setting, while Site C is located in distinctly different terrain. Despite the different settings, Figure 22 shows that, when normalized by area, all sites have similar magnitude-frequency relationships. Still, there is some variation observed between the sites. Perhaps most notably, Site C had significantly more events detected and a higher total volume of debris released during the observation period (\(\sim\)3 times higher debris volume when normalized by surface area). We attribute this to the marginal stability of Slope C, which was over-steepened during highway construction and today exhibits a very high rate of slope activity, evidenced by the need for frequent debris removal to maintain the catchment at the toe of the slope. In addition to generating a large volume of debris, Site C also produced a much wider range of rockfall fragment sizes, especially for larger volumes. We believe this is related to large slope height of the rock slope (\(\sim\)125 m), which allows large rock blocks to \"daylight\" and eventually fall from the slope. Sites A and B, in contrast, experienced fewer large volume failure events during the time period than expected based on the power law relationship. This may be a consequence of both the relatively short observation period (\(\sim\)1 year) and the relatively small slope heights (\(<\)10 m), which could impose kinematic constraints on large blocks within the rockmass. In either case, consideration of volume is important because rockfall runout distances generally increase with the mass of the debris being released [62]. Finally, it is worth noting that although the three sites exhibit generally similar normalized magnitude-frequency characteristics, from a practical perspective, Site C poses a much greater hazard to the highway simply because of its large rock face. Comparison and detection of very small failures (\(<\)0.01 m\({}^{3}\)) remains a challenging task unless modeled at very high resolutions (e.g., 0.025 cm). For example, Figure 22 shows weaker inverse power law relationships when considering failures with volumes between 0.001 and 0.01 m\({}^{3}\) for a 0.05 m model. At Sites A and B, these smaller events were not detected resulting in significant differences in  
Figure 22: Comparison of magnitude-frequency relationships (2013 to 2014, 0.05 cm holes filled models) and power law regressions for each site, normalized to an equivalent 1000 m\({}^{2}\) area based on events \(>\)0.001 m\({}^{3}\) (**a**) with and (**b**) without hole filling and events \(>\)0.01 m\({}^{3}\) (**c**) with and (**d**) without hole filling. power law regression fits. At Site C, in contrast, there is actually a slight improvement to the fit when considering these smaller events. This difficulty in detecting these small events occurs because:  
1. Each scan is individually linked to GPS coordinates which have an accuracy of a few centimeters in ideal conditions,
2. Obtaining sufficient resolution and complete coverage across the entire cliff face to model such features is difficult, especially for tall or complex cliffs. While operators can control the desired angular resolution, there is always a tradeoff between the amount of coverage achievable and the desired level of detail (e.g., resolution). TLS systems do not capture resolution uniformly across the cliff surface due to the fact that it samples on angular increments, resulting in denser spacing close to the scanner and sparser further from the scanner. This wide distribution of sampling presents challenges when attempting to model the surface systematically for analysis. 3. There are noise present in each scan, which can be on the order of a few cm at oblique angles (e.g., [63]), or from small vegetation on the cliff surface that is difficult to remove, and
4. Holes will occur at different locations in the surveys at each epoch because it is very difficult to reoccupy the same positions when performing surveys of this scope.