Dr. Aránguiz-Muñoz, Rafael

Tsunamis are devastating natural hazards that can reach runups of 30 m in coastal areas. One of the most important mitigation measures to save human lives is evacuation, which requires identification of both the inundation area and safe zones. Currently, a ground elevation of 30 m is used to determine safe zones in Chile. However, it has also been used for urban planning, for which the actual tsunami hazard may be overestimated. This research aims to propose a criterion based on probabilistic analysis to determine the tsunami inundation limit, considering both the runup and inundation distance from the shoreline. To this end, a synthetic database of runup and inundation distance from the shoreline was analyzed. First, stochastic earthquake sources were used to simulate tsunami events up to an inundation level in 10 coastal cities. Second, maximum runup and inundation distance were calculated for each tsunami scenario along transect lines perpendicular to the coastline. Finally, three exceedance probabilities of runup – 0.5%, 1%, and 2% in 50 years – were calculated to estimate the runup and inundation distances for each city. The results showed that geomorphology has an important role in runup and inundation distance. In addition, this research introduced new criteria for inundation limit identification, which are more flexible and accurate than the current 30-m ground elevation criterion used for tsunami risk assessment and urban planning. The application of this proposed method would allow local authorities to improve the locations of both critical infrastructure and safe zones.

Tsunami inundation maps are crucial for understanding the impact of tsunamis and planning mitigation measures. Our research focuses on creating a database of stochastic tsunami scenarios along the Chilean subduction zone and probabilistic inundation maps for 11 coastal cities. We divided the Chile-Perú subduction zone into four seismic segments based on historical seismicity. Stochastic rupture scenarios, ranging from 8.0 to 9.6 magnitudes, were generated using the Karhunen-Loeve expansion. The Stochastic Reduced Order Model (SROM) helped select representative tsunami scenarios for each segment and magnitude bin. We then used the NEOWAVE model to simulate these scenarios to an inundation level, creating probabilistic tsunami maps for various return periods. Our findings reveal that local geography significantly influences tsunami inundation, with some areas facing high inundation risks while others experience minimal impacts. As a result, a uniform planning and design criterion across the entire country is not advisable; site-specific studies are necessary. These probabilistic scenarios can provide tailored solutions for different Chilean coastal cities, enhancing their resilience. Additionally, this research marks the first comprehensive probabilistic tsunami hazard analysis for the Chilean coast, considering multiple seismic sources, marking a crucial step toward full tsunami risk assessment for coastal communities.

The September 28 2018 Palu tsunami surprised the scientific community, as neither the earthquake magnitude nor its strike-slip mechanism were deemed capable of producing the wave heights that were observed. However, recent research has shown that the earthquake generated several landslides inside Palu bay. The authors conducted a post-disaster field survey of the area affected to collect spatial data on tsunami inundation heights, nearshore and bay bathymetry, and carried out eyewitness interviews to collect testimonies of the event. In addition, numerical simulations of the tsunami generation and propagation mechanisms were carried out and validated with the inferred time series. Seven small submarine landslides were identified along the western shore of the bay, and one large one was reported on the eastern shore of Palu City. Most of these landslides occurred at river mouths and reclamation areas, where soft submarine sediments had accumulated. The numerical simulations support a scenario in which the tsunami waves that arrived at Palu city 4–10 min after the earthquake were caused by the co-seismic seafloor deformation, possibly coupled with secondary waves generated from several submarine landslides. These findings suggest that more comprehensive methodologies and tools need to be used when assessing probabilistic tsunami hazards in narrow bays.