William C. O'Reilly

Equilibrium shoreline response: Observations and modeling

[1] Shoreline location and incident wave energy, observed for almost 5 years at Torrey Pines beach, show seasonal fluctuations characteristic of southern California beaches. The shoreline location, defined as the cross-shore position of the mean sea level contour, retreats by almost 40 m in response to energetic winter waves and gradually recovers during low-energy summer waves. Hourly estimates of incident wave energy and weekly to monthly surveys of the shoreline location are used to develop and calibrate an equilibrium-type shoreline change model. By hypothesis, the shoreline change rate depends on both the wave energy and the wave energy disequilibrium with the shoreline location. Using calibrated values of four model free parameters, observed and modeled shoreline location are well correlated at Torrey Pines and two additional survey sites. Model free parameters can be estimated with as little as 2 years of monthly observations or with about 5 years of ideally timed, biannual observations. Wave energy time series used to calibrate and test the model must resolve individual storms, and model performance is substantially degraded by using weekly to monthly averaged wave energy. Variations of free parameter values between sites may be associated with variations in sand grain size, sediment availability, and other factors. The model successfully reproduces shoreline location for time periods not used in tuning and can be used to predict beach response to past or hypothetical future wave climates. However, the model will fail when neglected geologic factors are important (e.g., underlying bedrock limits erosion or sand availability limits accretion).

Field evidence of beach profile evolution toward equilibrium

An equilibrium framework is used to describe the evolution of the cross-shore profile of five beaches (medium grain size sand) in southern California. Elevations were observed quarterly on cross-shore transects extending from the back beach to 8 m depth, for 3–10 years. Transects spaced 100 m in the alongshore direction are alongshore averaged into nineteen 700–900 m long sections. Consistent with previous observations, changes about the time average profile in many sections are captured by the first mode empirical orthogonal function (EOF). The first EOF poorly describes sections with hard substrate (less than roughly 80% sandy bottom) and also fails near the head of a submarine canyon and adjacent to an inlet. At the 12 well-described sections, the time-varying amplitude of the first EOF, the beach state A, describes the well-known seasonal sand exchange between the shoreline and offshore (roughly between 4 and 7 m depth). We show that the beach state change rate dA/dt depends on the disequilibrium between the present state A and wave conditions, consistent with the equilibrium concepts of Wright and Short (1984) and Wright et al. (1985). Empirically determined, optimal model coefficients using the framework of Yates et al. (2009a, 2011) vary between sections, but a single set of globally optimized values performs almost as well. The model implements equilibrium concepts using ad hoc assumptions and empirical parameter values. The similarity with observed profile change at five southern California beaches supports the underlying model equilibrium hypotheses, but for unknown reasons the model fails at Duck, NC.

Model predictions of nearshore processes near complex bathymetry

Waves undergo significant transformation over complex bathymetry, and the resulting nearshore wave conditions can be sensitive to small changes in the offshore wave forcing. A potential consequence of this transformation sensitivity is large uncertainties in modeled nearshore waves owing to the amplification of the error in the deep water spectra used as initial conditions. In preparation for the upcoming Nearshore Canyon Wave Experiment in La Jolla, CA, a boundary condition sensitivity analysis was performed over the regions submarine canyon bathymetry using the SWAN wave model. The sensitivity analysis included varying the offshore spectrum discretization (frequency and directional bandwidths), the peak period and direction of the spectra, and the frequency and directional spreads. In each case, the magnitude of the spectral variations was governed by expected uncertainties when initializing a nearshore model with a) typical buoy data for the area, and b) global WAM model hindcasts or forecasts. In addition, data from the Torrey Pines Outer Buoy (located 12 km offshore) from the first week of November 2001 were used to initialize the model, and the maximum change seen in the domain over the course of the week were compared to those derived from the sensitivity analysis. The nearshore locations that showed the largest change in wave height over time were also the areas most sensitive to boundary condition errors, and correspond to areas of wave focusing. Errors in the estimation of the peak offshore wave direction were found to have the greatest impact on the accuracy of the nearshore wave predictions. The coarse directional resolution (15 degrees) of deep water spectra provided by the present generation of operational global models is shown to be a significant source of error when handcasting or forecasting nearshore waves over complex bathymetry.

A framework for sea level rise vulnerability assessment for southwest U.S. military installations

We describe an analysis framework to determine military installation vulnerabilities under increases in local mean sea level as projected over the next century. The effort is in response to an increasing recognition of potential climate change ramifications for national security and recommendations that DoD conduct assessments of the impact on U.S. military installations of climate change. Results of the effort described here focus on development of a conceptual framework for sea level rise vulnerability assessment at coastal military installations in the southwest U.S. We introduce the vulnerability assessment in the context of a risk assessment paradigm that incorporates sources in the form of future sea level conditions, pathways of impact including inundation, flooding, erosion and intrusion, and a range of military installation specific receptors such as critical infrastructure and training areas. A unique aspect of the methodology is the capability to develop wave climate projections from GCM outputs and transform these to future wave conditions at specific coastal sites. Future sea level scenarios are considered in the context of installation sensitivity curves which reveal response thresholds specific to each installation, pathway and receptor. In the end, our goal is to provide a military-relevant framework for assessment of accelerated SLR vulnerability, and develop the best scientifically-based scenarios of waves, tides and storms and their implications for DoD installations in the southwestern U.S.