Browsing by Author "Urrutia, A."

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    Impact of earthquake magnitude on the estimation of tsunami evacuation casualties
    (2018) Castro, S.; Poulos, A.; Urrutia, A.; Herrera, J. C.; Cienfuegos, R.; Llera Martin, Juan Carlos de la
    The importance of evacuation plans has been widely proven in recent tsunami events. Several evacuation models have been proposed to develop these plans and estimate city evacuation times. Typically, single extreme earthquake scenarios are used in these estimations; however, the impact of earthquake damage on the evacuation routes is usually neglected in these models. This article deals with the evaluation of the effect of three different earthquake magnitudes and the following tsunamis. Several spectral accelerations were sampled for each magnitude to estimate city damage, and from there the reduced capacity of evacuation routes due to earthquake debris. An agent-based evacuation model was used to assess the evacuation times for the city of Iquique, located in north Chile. Results show significant variability for different magnitude scenarios, thus leading to an observed increment on evacuation times up to 40% and an increase in the number of casualties due to the evacuation delay caused by earthquake debris spread on the evacuation routes
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    Sea surface network optimization for tsunami forecasting in the near field: application to the 2015 Illapel earthquake
    (OUP, 2019) Navarrete, P.; Cienfuegos Carrasco, Rodrigo Alberto; Satake, K.; Wang, Y.; Urrutia, A.; Benavente, R.; Catalan, P. A.; Crempien de la Carrera, Jorge; Mulia, I.
    We propose a method for defining the optimal locations of a network of tsunameters in view of near real-time tsunami forecasting using sea surface data assimilation in the near and middle fields, just outside of the source region. The method requires first the application of the empirical orthogonal function analysis to identify the potential initial locations, followed by an optimization heuristic that minimizes a cost-benefit function to narrow down the number of stations. We apply the method to a synthetic case of the 2015 M w 8.4 Illapel Chile earthquake and show that it is possible to obtain an accurate tsunami forecast for wave heights at near coastal points, not too close to the source, from assimilating data from three tsunameters during 14 min, but with a minimum average time lag of nearly 5 min between simulated and forecasted waveforms. Additional tests show that the time lag is reduced for tsunami sources that are located just outside of the area covered by the tsunameter network. The latter suggests that sea surface data assimilation from a sparse network of stations could be a strong complement for the fastest tsunami early warning systems based on pre-modelled seismic scenarios.