Investigating the impact of considering hazard preconditions in scenario-based risk estimation

Scenarios are commonly used in alpine hazard risk management. They can serve different purposes such as design of structures and mitigation measures, risk analysis for the prioritization of measures and the allocation of resources, and in preparing for the unexpected. In scenario-based quantitative risk analysis, few scenarios are used to obtain an estimate of risk, i.e., the annual expected losses, by approximating the loss exceedance curve. The scenarios are frequently selected from a range of plausible hazard intensities, such as discharges for hydrologic hazards or volumes for gravitational hazards and evaluated in terms of their expected consequences.

In the absence of long event records and lack of comprehensive data collection (e.g., from measurement stations or field investigations), as is often the case in alpine catchments, it can be difficult to assign occurrence probabilities to the specified hazard intensities. The recurrence of the scenarios (and thereby the expected consequences) is frequently equated with the recurrence of meteorological trigger conditions, thereby neglecting the effects of necessary preconditions for hazards to occur. In turn, to consider preconditions as additional parameters in evaluating the recurrence of expected consequences, it is required to adapt the development of the loss exceedance curve. For that purpose, we derive the unconditional probability distribution of the expected consequences from the distributions of damages conditional on the preconditions.

Using the example of an alpine catchment, we illustrate how considering preconditions invalidate the assumption of equating the recurrence frequency of the triggering conditions with the recurrence frequency of the consequences. We investigate the impact of considering different preconditions on the risk estimates by modelling the physical response of the natural environment to these trigger conditions. The information about frequency and magnitude of hazard scenarios is combined with the probability of different preconditions to derive scenarios that are representative of consequences with given recurrence frequency, hence better reflect the overall risk.