The Hunga Tonga–Hunga Ha’apai (HTHH) volcanic eruption in January 2022 generated catastrophic tsunami and contends for the largest natural explosion in more than a century. The main island, Tongatapu, suffered waves up to 17 m, and Tofua Island suffered waves up to 45 m, comfortably placing HTHH in the “megatsunami” league. We present a tsunami simulation of the Tongan Archipelago calibrated by field observations, drone, and satellite data. Our simulation emphasizes how the complex shallow bathymetry of the area acted as a low-velocity wave trap, capturing tsunami for more than 1 hour. Despite its size and long duration, few lives were lost. Simulation suggests that HTHH’s location relative to urban centers saved Tonga from a worse outcome. Whereas 2022 seems to have been a lucky escape, other oceanic volcanoes have the capacity to spawn future tsunami at HTHH scale. Our simulation amplifies the state of understanding of volcanic explosion tsunami and provides a framework for assessment of future hazards.

Palaseanu-Lovejoy, M.; Danielson, J.; Thatcher, C.; Foxgrover, A.; Barnard, P.; Brock, J., and Young, A., 2016. Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in Southern California. In: Brock, J.C.; Gesch, D.B.; Parrish, C.E.; Rogers, J.N., and Wright, C.W. (eds.), Advances in Topobathymetric Mapping, Models, and Applications. Journal of Coastal Research, Special Issue, No. 76, pp. 162–173. Coconut Creek (Florida), ISSN 0749-0208. Seacliff erosion is a serious hazard with implications for coastal management and is often estimated using successive hand-digitized cliff tops or bases (toe) to assess cliff retreat. Even if efforts are made to standardize manual digitizing and eliminate subjectivity, the delineation of cliffs is time-consuming and depends on the analyst's interpretation. An automatic procedure is proposed to extract cliff edges from high-resolution lidar-derived bare-earth digital elevation models, generalized coastal shoreline vectors, and approxim...

We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain. The algorithm automatically and sequentially delineates and smooths shoreline vectors, generates orthogonal transects and elevation profiles with a minimum spacing equal to the DEM resolution, and extracts the position and elevation of the cliff top and toe. Outputs include the non-smoothed raster and smoothed vector coastlines, normals to the coastline (as vector shape files), xyz profiles (as comma-separated-value, CSV, files), and the cliff top and toe (as point shape files). The algorithm also automatically assesses the quality of the profile and omits low-quality profiles (i.e. extraction of cliff top and toe is not possible). The performance of the proposed algorithm is compared with an existing method, which was not specifically designed for very irregular coastlines, and to manually digitized boundaries by numerous professionals. Also, we assess the reproducibility of the results using different DEM resolutions (5, 10 and 50 m), different user-defined parameter sets related to the degree of coastline smoothing, and the threshold used to identify the cliff top and toe. The model output sensitivity is found to be smaller than the manually digitized uncertainty. The code and a manual are publicly available on a GitHub repository.

The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models. CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.