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Mangroves and other natural coastal defenses have the potential to augment or replace traditional engineered coastal structures in preventing adverse events such as wave overtopping. Natural, or “green” systems may reduce maintenance costs, reduce sediment erosion, and increase biodiversity compared to traditional “gray” infrastructure built from stone and concrete. To effectively inform the design of hybrid green-gray infrastructure, experimental results must be reliable, but testing at 1:1 scale is time-consuming, expensive, and available at only a few facilities worldwide. This study addresses a knowledge gap in defining the nature of the interactions between green and gray coastal defenses with a focus on overtopping and scaling experimental results. This study will compare data from mangrove-related experiments conducted at scales including 1:2 and 1:8 as part of a collaborative effort between Oregon State University (OSU) and the United States Naval Academy (USNA). The study aims to analyze this data and contribute to the joint compilation of a methodology for designing prototype-scale tests from small-scale experiments to identify the relative importance of friction and scaling effects between prototype and small-scale experiments. Testing conducted at USNA as part of this study included a 1:8 scale, 0.61m-wide (2ft.) flume that replicates the conditions of 1:2 scale experiments at Oregon State University. The experimental setup includes a model Rhizophora mangrove forest placed in front of a seawall, behind which overtopping is measured as volume per unit length either computed from overtopped water weight or directly measured by overtopped volume. Mangroves are modeled as central trunks with stilt roots, as this study focuses on the effects of the root structures on overtopping. Waves generated for the 1:8 experiments include regular waves with heights between 5cm and 10cm and periods between 1 and 2 seconds, scaled according to Froude similitude. Implications of scaled-up measurements of overtopping are also discussed. 

This paper presents the use of tsunami evacuation drills within a coastal community in the Cascadia Subduction Zone (CSZ) to better understand evacuation behaviors and thus to improve tsunami evacuation preparedness and resilience. Evacuees’ spatial trajectory data were collected by Global Navigation Satellite System (GNSS) embedded in mobile devices. Based on the empirical trajectory data, probability functions were employed to model people’s walking speed during the evacuation drills. An Evacuation Hiking Function (EHF) was established to depict the speed–slope relationship and to inform evacuation modeling and planning. The regression analysis showed that evacuees’ speed was significantly negatively associated with slope, time spent during evacuation, rough terrain surface, walking at night, and distance to destination. We also demonstrated the impacts of milling time on mortality rate based on participants’ empirical evacuation behaviors and a state-of-the-art CSZ tsunami inundation model. Post-drill surveys revealed the importance of the drill as an educational and assessment tool. The results of this study can be used for public education, evacuation plan assessment, and evacuation simulation models. The drill procedures, designs, and the use of technology in data collection provide evidence-driven solutions to tsunami preparedness and inspire the use of drills in other types of natural disasters such as wildfires, hurricanes, volcanoes, and flooding. 

Inundation from storms like Hurricanes Katrina and Sandy, and the 2011 East Japan tsunami, have caused catastrophic damage to coastal communities. Prediction of surge, wave, and tsunami flow transformation over the built and natural environment is essential in determining survival and failure of near-coast structures. However, unlike earthquake and wind hazards, overland flow event loading and damage often vary strongly at a parcel scale in built-up coastal regions due to the influence of nearby structures and vegetation on hydrodynamic transformation. Additionally, overland flow hydrodynamics and loading are presently treated using a variety of simplified methods (e.g. bare earth method) which introduce significant uncertainty and/or bias. This study describes an extensive series of large-scale experiments to create a comprehensive dataset of detailed hydrodynamics and forces on an array of coastal structures (representing buildings of a community on a barrier island) subject to the variability of storm waves, surge, and tsunami, incorporating the effect of overland flow, 3D flow alteration due to near-structure shielding, vegetation, waterborne debris, and building damage.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/EDLiEK6b64E 

Abstract This study couples FN‐curves with Agent‐based Modeling and Simulation (ABMS) to assess risk for tsunamis with various recurrence intervals . By considering both expected number of casualties and the likelihood of tsunami events, multiple series of simulations and in‐depth analyses determine (1) how vertical evacuation structure (VES) placement impacts mortality rate; (2) what the best evacuation strategies VES locations are; and (3) where evacuees are likely to be caught by tsunami waves. The results from utilizing FN‐curves to conduct disaggregative analyses based on six tsunami scenarios indicate that choosing one tsunami scenario or averaging the risk of different scenarios may not fully articulate VES impacts due to the “levee effect,” which potentially leads to false positives. Findings show that placing VESs close to shorelines saves nearby at‐risk populations, but also results in two risk increasing phenomena: “exposure to risk” (i.e., evacuees being attracted to high risk roads by a VES when evacuating) and “blind zones” (i.e., locations near a VES where evacuees increase their risk by evacuating to that VES). When limited to one VES, placement near a population's centroid results in the lowest mortality rate. More than one VES may lower mortality rate further if VESs are spreading out according to community's topography. In addition to the analysis of tsunamis, the approach of coupling FN‐curves with ABMS can be used by local authorities and engineers to determine tailored hard‐adaptive measures and evacuation strategies, which helps to avoid maladaptive actions in different hazardous events.