## 5 Discussion and Conclusions
Therefore, the frequency of other volumes being exceeded depends on how many blocks are surveyed and the volumes of the largest blocks. The DFN generated volume-cumulative relative frequencies differed significantly from observations when all volumes generated were considered. However, their similarity increased significantly when the DFN generated volumes were truncated at the highest measured volume. This finding can be interpreted as the DFN generated volumes overestimating the volume of the least frequent blocks, and that for the largest blocks, fragmentation in the absence of weak planes or non-persistent discontinuities have asignificant effect. However, it is also possible that this discrepancy is caused by observation bias, where the likelihood of larger blocks predicted by the DFN is so small (very small frequency), that these events were simply not observed during the discrete observation periods. As an example, the large rockfall event in 2013 at Site S042 supports the potential for large fragmented blocks as identified by the DFN prediction. There is also a potential for undocumented rock fall events that may have occurred prior to the establishment of AT's GRMP in 1999. These may also increase the number of actual large block volumes. The volume-cumulative relative frequencies derived from persistent DFN's are very similar to observations when block volumes are truncated to the largest observed volumes, however some overprediction occurs in both case studies. At the Tornado Mountain site, the findings indicate, for example, that 90% of blocks are smaller than approximately 3 m\({}^{3}\) and 1.5 m\({}^{3}\) for the DFN prediction and observations, respectively; however, both the DFN predictions and the observations indicate that 95% of blocks are smaller than approximately 3.3 m\({}^{3}\). At Site S042, 90% of blocks are smaller than approximately 0.24 m\({}^{3}\) and 0.14 m\({}^{3}\) for the DFN prediction and observations, respectively; however, both the DFN predictions and the observations indicate that 99% of blocks are smaller than approximately 0.35 m\({}^{3}\). It is possible that these overpredictions are a result of neglecting breakage of blocks not associated with weak planes or non-persistent discontinuities, such as breakage of intact rock bridges at impact, abrasion during rolling and in situ effects of weathering (e.g., freeze-thaw effects). In the absence of fragmented rockfall databases or observations, application of the method requires truncating the maximum DFN predicted volumes based on judgment about their likelihood according to measurements and observations at the rockfall source, any observed fragmented blocks associated with sources in the vicinity, previous experience, and design life of proposed mitigation measures (e.g., are we designing for rockfalls with a return period of 1 in every 100, 1000, or 10,000 years?). Further investigation into the method could aim at confirming the trend in DFN overpredictions with other case studies in similar rock materials, such that observation bias is reduced, and develop statistical volume correction factors that could account for block fragmentation not associated with weak planes or non-persistent discontinuities. Furthermore, the method needs to be tested at rockfall sources with different lithological units to evaluate its applicability. Conceptualization, R.M. ; Data curation, C.G. and R.S. ; Formal analysis, R.M. ; Investigation, R.M. ; Methodology, R.M. ; Validation, C.G. and R.S. ; Writing--original draft, R.M. and C.G. ; Writing--review and editing, R.S. All authors have read and agreed to the published version of the manuscript. This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Klohn Crippen Berger Ltd. through a Collaborative Research and Development Grant (CRD) (CRDPJ543429-19).