Testing Tsunami Inundation Maps for Evacuation Planning in Italy

Abstract

Inundation maps are a fundamental tool for coastal risk management and in particular for designing evacuation maps and evacuation planning. These in turn are a necessary component of the tsunami warning systems’ last-mile. In Italy inundation maps are informed by a probabilistic tsunami hazard model. Based on a given level of acceptable risk, Italian authorities in charge for this task recommended to consider, as design hazard intensity, the average return period of 2500 years and the 84th percentile of the hazard model uncertainty. An available, regional-scale tsunami hazard model was used that covers the entire Italian coastline. Safety factors based on analysis of run-up variability and an empirical coastal dissipation law on a digital terrain model (DTM) were applied to convert the regional hazard into the design run-up and the corresponding evacuation maps with a GIS-based approach. Since the regional hazard cannot fully capture the local-scale variability, this simplified and conservative approach is considered a viable and feasible practice to inform local coastal risk management in the absence of high-resolution hazard models. The present work is a first attempt to quantify the uncertainty stemming from such procedure. We compare the GIS-based inundation maps informed by a regional model with those obtained from a local high-resolution hazard model. Two locations on the coast of eastern Sicily were considered, and the local hazard was addressed with the same seismic model as the regional one, but using a higher-resolution DTM and massive numerical inundation calculations with the GPU-based Tsunami-HySEA nonlinear shallow water code. This study shows that the GIS-based inundation maps used for planning deal conservatively with potential hazard underestimation at the local scale, stemming from typically unmodeled uncertainties in the numerical source and tsunami evolution models. The GIS-based maps used for planning fall within the estimated “error-bar” due to such uncertainties. The analysis also demonstrates the need to develop local assessments to serve very specific risk mitigation actions to reduce the uncertainty. More in general, the presented case-studies highlight the importance to explore ways of dealing with uncertainty hidden within the high-resolution numerical inundation models, e.g., related to the crude parameterization of the bottom friction, or the inaccuracy of the DTM.

Tsunami risk management for crustal earthquakes and non-seismic sources in Italy

“…MIH then represents the maximum inundation height averaged along the~20 km long stretch of coast represented by each POI. It follows that the locally maximum MIH and run-up values can be (up to 3-4 times) larger than those indicated by the hazard model, for example, due to tsunami energy focusing by topographic features [53,62,63,139].…”

“…Non-linear shallow water models are most frequently used for this purpose (e.g., the review [64]); Boussinesq model applications are used as well, despite that they are more prone to instabilities (see discussion in [220]). Despite the relatively high accuracy of these modelling techniques, large uncertainty still exists (e.g., [54,63,69,92,127,221]), and the potential impact of uncertainty in initial/boundary conditions or of different modelling techniques still have to be fully understood.…”

“…The full procedure describing the conversion between MIH to maximum run-up and inundation areas is described in detail in [62,63]. Nevertheless, we provide here a short description of this procedure for the sake of completeness.…”

“…For TWSs, it is required to timely produce a forecast of the tsunami intensity at different sites due to an event (for example, an earthquake) that has just occurred, or it is forecasted to occur in the relatively near future (for example, for a volcanic eruption or a subaerial landslide) based on the information registered by a monitoring system. The forecast is then generally used to define alert levels associated with specific short-term risk reduction measures, like population evacuation [55,[60][61][62][63]. On the other hand, PTHA is a forecast of the potential future activity and it quantifies the probability of exceeding different tsunami intensities due to whatever possible tsunami in a target location within a relatively long time windows (e.g., 50 years).…”

“…To efficiently contribute to forecast procedures like TWS and PTHA, all the advancements in modelling techniques should also be accompanied by a synergic parallel effort dedicated to the management of existing uncertainty, both in forecasting the occurrence of the source process and in quantifying the potential consequent tsunami, in order to increase precision without loosing in accuracy. Also this field is indeed a field of intense research activity [11,31,54,63,[90][91][92], and it is particularly challenging when extending to the large variety of atypical tsunami sources (e.g. [11,17,32,54]).…”