Individual risk
In a comparison of risk regulation in the UK and the Netherlands, Ale (2005) noted that following the Sizewell B Enquiry the Health & Safety Executive (HSE) (Anon. 1992) described a tolerable risk level as one that is allowed to continue to exist somewhere in society. The highest tolerated risk at that time in the UK was that to miners and the individual risk to those workers was estimated to be of the order of 1E-03 (10− 3) per year. From that it was derived that members of the general public could be exposed to an individual risk of 1E-04 (10− 4) per year in the wider interests of society.
This compares to the computed Personal Individual Risk (PIR) of fatality for a single trip (per year) which is speed dependent (Table 1) and varies from
2.045E-09 (40 mile/h), 1.742E-09 (50 mile/h) to 1.583E-09 (60 mile/h) at the A83 Rest and be Thankful, and
1.328E-10 (40 mile/h), 1.147E-10 (50 mile/h) to 1.061E-10 (60 mile/h) at A85 Glen Ogle.
Those who make multiple trips are exposed to a greater level of risk.
Estimates of the annual probability of fatality for those most at risk have been made for commuters and logistics truck drivers and the highest probability is around 2E-06 fatalities per year or once every 520,000 years, while the lowest probability corresponds to around 5E-08 or around 1 in 20 million years (Table 2).
The values of PIR are considerably lower than those that Lee and Jones (2014) suggest that the UK Health and Safety Executive currently use to define the upper (1E-04 or 10− 04) and lower (1E-06 or 10− 06) bounds of As Low As Reasonably Practicable for individual risk and may be described as Broadly Acceptable or tolerable; the exception is the risk for the logistics truck driver which falls just within the ALARP zone. These risks are noticeably lower than those described by Ale (2005).
The results for the two parts of this risk assessment (debris flow hitting vehicle and vehicle hitting debris flow) show, unsurprisingly and as noted above, that the resulting risk is vehicle speed dependent, albeit to a relatively small degree. It is important to apply these results in context. The larger overall risk of a debris flow hitting a vehicle (Scenario A) has a decreasing risk for higher speeds, while the overall lower risk of a vehicle hitting a debris flow (Scenario B) has an increased risk with increasing speed (Fig. 17).
Overall the risk of a fatality (Scenario A plus B) from a debris flow shows a small decrease with vehicle speed. It is important that increased speed is not seen, in any way, as an effective remedial measure, or tactic, for drivers to reduce the overall risk that they face on the road. It is important to recognise that increased speed also increases the (considerably higher) risk of a road traffic accident and reduces the control that a driver may have over the vehicle in the event of encountering a debris flow. Recommendations to drivers should focus on the balance of speed to driving conditions as such recommendations would in any other scenario.
Societal risk
The societal risk from debris flow at the A85 Glen Ogle is dealt with in terms of the classic, and widely used, F-N diagram. There are two approaches to generating the data to be plotted on this diagram as described by Wong et al. (2004) and by Lee and Jones (2014); neither is considered to be more correct than the other. In this study a speed of 50 mile/h has been taken as an estimate of the average speed of traffic at the two sites. The approach of Lee and Jones (2014), while not presented here, produces values of N that include some that are less than unity, the lowest value on the x-axis, which do not plot on the F-N diagram that has its lower bound value at unity (see Wong and Winter 2018; Winter 2018). The approach of Wong et al. (2004) produces results that are more suited to being plotted on the F-N diagram and a clearer picture emerges (Figs. 12 and 13).
Figure 12 shows that prior to the application of mitigation measures the risk levels for one and two fatalities (N = 1 and 2) plot just into the Unacceptable zone, while the risks for higher numbers of fatalities plot in the ALARP zone. The application of reductions to the risk levels in response to the mitigation measure implemented at the A83 Rest and be Thankful (Fig. 16) brings the value for N = 2 into the ALARP zone and that for N = 1 only fractionally into the Unacceptable zone. The initial intrusion of the data into the Unacceptable zone is considered to be within the limits of error of the study and thus the overall risk levels can be considered to be within the ALARP zone after mitigation. This indicates the value and effectiveness of the mitigation measures implemented.
For the A85 Glen Ogle site the diagram (Fig. 13) shows that the risk levels plot broadly in the ALARP zone for lower numbers of fatalities and in the Broadly Acceptable risk zone for higher numbers of fatalities.
The Lee and Jones (2014) methodology is particularly helpful in that it allows the ready calculation of a figure for the Potential Loss of Life (PLL). This is the annual probability of a fatality being caused by debris flow. At the A83 Rest and be Thankful, for an average traffic speed of 50 mile/h, this is 4.083E-03, corresponding to one fatality every 245 years or approximately four fatalities per millennium. At the A85 Glen Ogle and, for the same average traffic speed, the PLL is 2.616E-04, which corresponds to one fatality every 3822 years (Table 3).
Climate change
Climate change will have an impact on the frequency and magnitude of such events and the potential impact of increased rainfall on landslide and flood events has been widely discussed (e.g. Barnett et al., 2006a, b; Duan et al. 2015, 2016, 2019).
In broad terms the available climate change forecasts suggest that in the winter months when rainfall is expected to increase, landslide hazard frequency and/or magnitude may increase in Scotland in the future, whereas in the summer months the frequency may decrease, but with a possibility of increasing magnitude (Winter and Shearer 2014a, 2014b).
Increased hazard frequency, or P(Event), is relatively straight forward to deal with and Eq. (2) suggests that doubling, for example, the frequency of event occurrence would double the risk. This would increase the risk to logistics truck drivers using the A83 from 1.922E-06 to 3.844E-06 (at the speed limit for heavy goods vehicles of 40 mile/h and from 1.248E-07 to 2.496E-07 for those using the A85, still well within the highest tolerated individual risk to workers of 1E-03 (10− 3) per year, as reported by Ale (2005).
Increases in hazard magnitude would have an influence on P(Damage|Hit), while P(Hit|Event) seems unlikely to change to such a significant degree. This increase in P(Damage|Hit) seem likely to be greater in Scenario A than in Scenario B. Taking a lead from fragility curves for road infrastructure (Winter et al. 2014b), it seems reasonable to suggest that a doubling in the magnitude may lead to a doubling of the risk and a broadly similar outcome as for a doubling of the event frequency. While a doubling of the event frequency would still leave the societal risk at the A85 within the ALARP zone for smaller numbers of fatalities and in the Broadly Acceptable zone for higher numbers of fatalities, the picture at the A83 is rather different and the societal risk would return to the lower reaches of the Unacceptable zone on the F-N diagram for low numbers of fatalities (N = 1 or 2).
Of course, an assumption of the doubling of either frequency or magnitude is rather speculative and it must be remembered that frequency and magnitude are not completely decoupled; an increase in magnitude may leave less loose previously mobilised material to be entrained and may lead to a decrease in the frequency, similarly an increase in the frequency may well mean that the channels are relatively clear of such material and it may be less likely that a larger magnitude event will develop. In addition, such increases must be offset against the substantial additional landslide risk reduction measures that have been implemented at the Rest and be Thankful since October 2014 when the data for this study was collected.
It is, of course, not sufficient to consider only the effect of climate change on the hazard and the effects of demographic change, including travel patterns, also must be considered and may be either coupled and/or decoupled to the effects of climate change. Typically, such changes are found to be at least as important as the changes to the hazard (Winter and Shearer 2013; Milne et al., 2016; Winter et al. 2017).
Landslide frequency and inventory
Perhaps the most challenging aspect of this work was the evaluation of landslide frequency. This was a direct result of the relative paucity of data relating to past landslides, even for the Rest and be Thankful site the recorded record covers a period of less than two decades while at Glen Ogle the relative infrequency of events provided the challenge.
Wong and Winter (2018) recommended that a more complete and systematic database of the landslide history of the A83 Rest and be Thankful and other sites around Scotland site should be implemented and this is being taken forward for the strategic road network.
Limitations
In addition to the limitations set-out in the foregoing sections, including but not limited to the landslide inventory, it is important to note that the QRA technique is neither a neutral, nor is it an entirely objective, process such that the results could be value-laden and biased (Lee and Jones 2014). Suzanne Lacasse describes QRA as “… the systematic application of engineering judgement” in her, as yet unpublished, 2015 Rankine Lecture. The QRA methodology was developed based on a review of the application of QRA in landslide studies in different parts of the world and the site-specific information available. Particular care was taken to avoid systematic unidirectional bias and to balance the application of conservatism in areas where there were significant uncertainties with a less conservative approach in other area. The uncertainties were tested using a process of challenge and counter-challenge by the members of the team and with internal reviewers in order to ensure that a balance was applied to the different factors assessed in the risk analysis, including the testing of alternative judgement options to those proposed. Such tests were also conducted with colleagues with relevant expertise including inter alia vehicle impacts and those with extensive knowledge and experience of the road network, and the routes and sections under consideration.