COPE: EAGER Coastal Hazard Planning in Time

The University of Washington (UW) has partnered with the town of Westport, Washington, toco-create “geo-narratives” to enhance the community’s hazard mitigation and adaptationplanning. When complete, the digital platform will include maps, scientific information, andexplanatory materials about Westport's risk from coastal hazards including tsunamis, co-seismicsubsidence, sea level rise, and increased storminess, flooding, and coastal erosion. A 3D digitalmodel of the town and its coastline, using imagery collected by RAPID Staff in 2020, forms thebasis for much of the geo-narrative visualization.The project is part of an ongoing collaborative partnership between the town and UW facultyand students to inform both local emergency preparedness and long-term investments andpolicies. Activities have ranged from updating the town’s comprehensive plan; using the modelto locate and design new tsunami vertical evacuation structures; using Minecraft and designingnew video games with local junior high school students to envision hazards impacts andmitigating strategies; and helping the students video the town from the perspective of atsunami surging inland for an evacuation practice demonstration.The RAPID-produced elements of the project are unusual in that reconnaissance was conductedin the community prior to an expected disaster, as a way of providing baseline information aboutthe environment. This information can then be manipulated for photorealistic simulations ofhazard impacts such as tsunami wave inundation, “bathtub” visualizations of coastal floodingdue to sea level rise or subsidence, and long-term erosion and sediment transport impacts tocoastlines. The setting for this project is itself unique as it is the first community in NorthAmerica to build a tsunami vertical evacuation structure (VES). The local Ocosta School Districtaccomplished this as part of an elementary school rebuild in 2016, which has provided thecommunity with a unique point of pride and students at the school with a point of reference forthinking about coastal hazards over the long term (Cascadia Subduction earthquakes andtsunamis recur only once in an interval of approximately 300-500 years; the last such eventoccurred in 1700).The 3D point cloud model and imagery have so far assisted UW undergraduate and professionalmasters students in Architecture, Landscape Architecture, and Urban Design & Planning toenvision how additional VES’s and other adaptive strategies including flood-resilient housingand recreational spaces may fit within the townscape, and thus, like the school, serve everydayfunctions as well as emergency ones. The model was unexpectedly useful for one class of theseUW students who were unable to visit the community in person due to COVID-19 travelrestrictions in Winter Quarter 2021; the studio course had to be mounted entirely online, andstudents were able to engage with the environment digitally from remote locations. In asynergistic Cascadia CoPes Hub-funded project for “Inclusive Community-based STEAMIdentity-building in Coastal Hazards Research: Pilot Activities for Cascadia TEACH with theOcosta School District, WA,” the model has also enabled local youth through an extracurriculardrone club to map out places in the community that are important to them, and to documentthem with drone-flown photography and video that they take themselves. The youth are alsoworking with the model to design a video game that depicts the interactions between hazardimpacts and possible mitigation strategies. Both these sets of activities are informing themasters theses of two graduate students in Urban Planning and Public Health. Ancillary to thisCoPes-funded data-gathering and processing, RAPID staff have helped train UW students andlocal youth to operate drones, which has been essential to the activities described above aswell as other synergistic projects. Ocosta students have visited the RAPID facility at the UWcampus, and are expected gradually to be introduced to the technology of creating point cloudmodels with drone-collected data.