This data set consists of physics-based Delft3D-FLOW and SWAN hydrodynamic models input files used to study the wave-induced 3D flow over spur-and-groove (SAG) formations. SAG are a common and impressive characteristic of coral reefs. They are composed of a series of submerged shore-normal coral ridges (spurs) separated by shore-normal patches of sediment (grooves) on the fore reef of coral reef environments. Although their existence and geometrical properties are well documented, the literature concerning the hydrodynamics around them is sparse. Here, the three-dimensional flow patterns over SAG formations, and a sensitivity of those patterns to waves, currents, and SAG geometry were examined. Shore-normal shoaling waves over SAG formations were shown to drive two circulation cells: 1) a cell on the lower fore reef with offshore flow over the spur and onshore flow over the groove, except near the seabed where velocities were always onshore; and 2) a cell on the upper fore reef with offshore surface velocities and onshore bottom currents, which result in depth-averaged onshore and offshore flow over the spurs and grooves, respectively. These input files accompany the modeling conducted for the following publication: da Silva, R.F., Storlazzi, C.D., Rogers, J.S., Reyns, J., and McCall, R., 2020, Modeling three-dimensional flow over spur-and-groove morphology: Coral Reefs, https://doi.org/10.1007/s00338-020-02011-8.

This dataset consists of physics-based XBeach Non-hydrostatic hydrodynamic models input files used to study how coral reef restoration affects waves and wave-driven water levels over coral reefs, and the resulting wave-driven runup on the adjacent shoreline. Coral reefs are effective natural coastal flood barriers that protect adjacent communities. Coral degradation compromises the coastal protection value of reefs while also reducing their other ecosystem services, making them a target for restoration. Here we provide a physics-based evaluation of how coral restoration can reduce coastal flooding for various types of reefs. These input files accompany the modeling conducted for the following publication: Roelvink, F.E., Storlazzi, C.D., van Dongeren, A.R., and Pearson, S.G., 2021, Coral reef restorations can be optimized to reduce coastal flooding hazards: Frontiers in Marine Science, https://doi.org/10.3389/fmars.2021.653945.

An extensive set of physics-based XBeach Non-hydrostatic hydrodynamic model simulations (with input files here included) were used to evaluate the influence of shore-normal reef channels on flooding along fringing reef-lined coasts, specifically during extreme wave conditions when the risk for coastal flooding and the resulting impact to coastal communities is greatest. These input files accompany the modeling conducted for the following publication: Storlazzi, C.D., Rey, A.E., and van Dongeren, A.R., 2022, A numerical study of geomorphic and oceanographic controls on wave-driven runup on fringing reefs with shore-normal channels: Journal of Marine Science and Engineering, 10(6), 828, https://doi.org/10.3390/jmse10060828.

Projected wave climate trends from WAVEWATCH3 model output were used as input for nearshore wave models (for example, SWAN) for the main Hawaiian Islands to derive data and statistical measures (mean and top 5 percent values) of wave height, wave period, and wave direction for the recent past (1996-2005) and future projections (2026-2045 and 2085-2100). Three-hourly global climate model (GCM) wind speed and wind direction output from four different GCMs provided by the Coupled Model Inter-Comparison Project, phase 5 (CMIP5), were used as boundary conditions to the physics-based WAVEWATCH3 numerical wave model for the area encompassing the main Hawaiian islands. Two climate change scenarios for each of the four GCMs were run: the representative concentration pathway (RCP)-4.5 and RCP-8.5, representing a medium mitigation and a high emissions scenario, respectively. Simulation timeframes were limited to the years 2026-2045 and 2085-2100, as prescribed by the CMIP5 modeling framework. The WAVEWATCH3 modeled deep-water wave heights, wave periods, and wave directions, with current bathymetry were used as boundary conditions to drive simulations of mean and top 5 percent wave conditions at higher resolution over the insular shelves of the main Hawaiian islands using the 3rd-generation SWAN wave model. For each scenario, 12 simulations were made representing the month-averaged or top 5 percent conditions. The SWAN model is based on discrete spectral action balance equations, computing the evolution of random, short-crested waves. Physical processes such as bottom friction and depth induced breaking, and, non-linear quadruplet and triad wave-wave interactions are included. Wave propagation, growth, and decay are solved periodically throughout the model grid. The SWAN model has been shown to accurately model the propagation and breaking of waves over Pacific coral reefs.

A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on reef-lined coasts. The Bayesian estimator has high predictive skill for the XBNH model outputs that are flooding indicators, and was validated for a number of available field cases. BEWARE is a potentially powerful tool for use in early warning systems or risk assessment studies, and can be used to make projections about how wave-induced flooding on coral reef-lined coasts may change due to climate change. These data accompany the following publication: Pearson, S.G., Storlazzi, C.D., van Dongeren, A.R., Tissier, M.F.S., and Reniers, A.J.H.M., 2017, A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts: Journal of Geophysical Research—Oceans, https://doi.org/10.1002/2017JC013204.

We developed the HyCReWW metamodel to predict wave run-up under a wide range of coral reef morphometric and offshore forcing characteristics. Due to the complexity and high dimensionality of the problem, we assumed an idealized one-dimensional reef profile, characterized by seven primary parameters. XBeach Non-Hydrostatic was chosen to create the synthetic dataset and Radial Basis Functions implemented in Matlab were chosen for interpolation. Results demonstrate the applicability of the metamodel to obtain fast and accurate results of wave run-up for a large range of intrinsic coral reef morphologic and extrinsic hydrodynamic forcing parameters, offering a useful tool for risk management and early warning systems. These data accompany the following publication: Rueda, A., Cagigal, L., Pearson, S., Antolinez J.A.A., Storlazzi, C., van Dongeren, A., Camus, P., Mendez, F.J., 2019, HyCReWW: A hybrid coral reef waves and water level metamodel: Computers & Geosciences, https://doi.org/10.1016/j.cageo.2019.03.004.

Using global climate model projections of sea-surface temperature at coral reef sites, we modeled the effects of depth and exposure to semidiurnal temperature fluctuations to examine how these effects may alter the projected year of annual severe bleaching for coral reef sites globally. Here we present the first global maps of the effects these processes have on bleaching projections for three IPCC-AR5 emissions scenarios.

This part of DS 781 presents data for the map showing the predicted distribution of cup corals in the Santa Barbara Channel, California, region. The raster data file is included in "CupCorals_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the coast off southern California during a ground-truth observation cruise conducted by the U.S. Geological Survey and NOAA National Marine Fisheries Service for the California Seafloor Mapping Program. Benthic community structure was determined from 35 video towed-camera transects within California's State Waters 3-nautical-mile limit in the Santa Barbara Channel. These transects produced a total of 923 10-second observations from the Offshore of Refugio Beach map area (34.5 degrees N., 120.1 degrees W.) to the Hueneme Canyon and vicinity map area (34.1 degrees N., 119.2 degrees W.). Presence-absence data were collected for 29 benthic, structure-forming nonmobile taxa. Using this information, generalized linear models (GLMs) were developed to predict the probability of occurrence of five commonly observed taxa (cup corals, hydroids, short and tall sea pens, and brittle stars in the sediment) in five map areas within the Santa Barbara Channel (SBC). A sixth map area (Offshore of Carpinteria) was not modeled owing to insufficient data. The analysis demonstrates that the community structure for the five map areas can be divided into three statistically distinct groups: (1) the Hueneme Canyon and vicinity and the Offshore of Ventura map areas; (2) the Offshore of Santa Barbara and the Offshore of Coal Oil Point map areas; and (3) the Offshore of Refugio Beach map area. These three distinct groups are the main reason that the probability for each taxa can be so dramatically different within one predictive-distribution map area. The five most frequently observed benthic macro-invertebrate taxa were selected for these predictive-distribution grids. Presence-absence data for each selected invertebrate were fit to specific generalized linear models using geographic location, depth, and seafloor character as covariates. Data for the covariates were informed by the bathymetry, seafloor character, and other ground-truth data from the different map areas of the Santa Barbara Channel region that are part of the California State Waters Map Series DS 781. Observations based on depth were limited by the capability of the towed camera sled; as a result, no predictions were made below depths of 150 m (in other words, on the continental slope or in Hueneme Canyon). Cup corals and hydroids had high predicted probabilities of occurrence in areas of hard substrata, whereas short and tall sea pens were predicted to occur in parts of the SBC that had unconsolidated and mixed sediment. Our model predicted that brittle stars would occur throughout the entire SBC on various bottom types.

A set of physics-based XBeach Non-hydrostatic hydrodynamic model simulations (with input files here included) were used to evaluate how varying carbonate budgets, and thus coral reef accretion and degradation, affect alongshore variations in wave-driven water levels along the adjacent shoreline of Buck Island Reef National Monument (BUIS) for a number of sea-level rise scenarios, specifically during extreme wave conditions when the risk for coastal flooding and the resulting impact to coastal communities is greatest. These input files accompany the modeling conducted for the following publication: Toth, L.T., Storlazzi, C.D., Kuffner, I.B., Quataert, E., Reyns, J., McCall, R.T., Stathakopoulos, A., Hillis-Starr, Z., Holloway, N.H., Ewen, K.A., Pollock, C.G., Code, T., and Aronson, R.B., 2023, The potential for coral reef restoration to mitigate coastal flooding as sea levels rise: Nature Communications, v. 14, https://doi.org/10.1038/s41467-023-37858-2.

This data collection contains geospatial data from models predicting the spatial distributions of deep-sea corals (DSCs) and hardbottom habitats offshore of the southeastern U.S. It includes a database (.csv text file) containing records of occurrence (presence-absence) for DSCs with associated measures of sampling effort and bottom type from 20 datasets comprised of data from visual field surveys conducted with underwater vehicles. It also includes raster datasets at 100 x 100 m spatial resolution depicting the median and coefficient variation of the predicted occurrence (occupancy probability) for 24 taxa of DSCs (23 genera, 1 family) and hardbottom habitats. Additional raster datasets depict the median and coefficient of variation of the predicted genus richness for the 23 genera of DSCs. The data collection also includes raster datasets at 100 x 100 m spatial resolution depicting each of the 62 spatial environmental predictors considered for fitting the models. For more information, see Poti et al. (2022). The project to compile this model took place between 2016 and 2021, however the model input data range from 2001-2018 and the model output covers the same timeframe.