Nathaniel G. Plant

Practical use of video imagery in nearshore oceanographic field studies

An approach was developed for using video imagery to quantify, in terms of both spatial and temporal dimensions, a number of naturally occurring (nearshore) physical processes. The complete method is presented, including the derivation of the geometrical relationships relating image and ground coordinates, principles to be considered when working with video imagery and the two-step strategy for calibration of the camera model. The techniques are founded on the principles of photogrammetry, account for difficulties inherent in the use of video signals, and have been adapted to allow for flexibility of use in field studies. Examples from field experiments indicate that this approach is both accurate and applicable under the conditions typically experienced when sampling in coastal regions. Several applications of the camera model are discussed, including the measurement of nearshore fluid processes, sand bar length scales, foreshore topography, and drifter motions. Although we have applied this method to the measurement of nearshore processes and morphologic features, these same techniques are transferable to studies in other geophysical settings.

Intertidal beach profile estimation using video images

Abstract In this paper, we present a technique suitable for measurement of intertidal bathymetry over a broad range of length scales (10 1 to 10 3 m) and time scales (days to decades). A series of time-averaged images of the swash zone are used to map contour lines of the beach surface. In each image, contours are identified using bands of maximum brightness associated with breaking waves at the shoreline. By mapping the location of these bands in a sequence of images collected over one tidal cycle, contour maps of the intertidal bathymetry are generated. We expect this technique to work best (smallest absolute error) under waves which are nearly reflective at the shoreline, but break enough to be observed visually. This is typical of a barred beach since the wave height at the shoreline is limited by wave breaking over the bar crest. The ability of the measurements made with this technique to resolve actual beach elevation variation depends on the ratio of the measurement error variance to the true beach elevation variance. Thus, large measurement errors may be compensated by either large tidal ranges or large temporal changes of the beach itself. In a comparison to bathymetry surveyed using a Differential Global Positioning System (DGPS) during the Duck94 experiment, in Duck, N.C., the image-based elevation estimates were well correlated with the actual bathymetry. The deviations (imagebased vs. DGPS measurements) may be partially attributed to effects scaled by wave height at the shoreline, wave-induced setup, and wave height saturation over the sand bar. In particular, setup was important during dissipative conditions. The rms deviation (vertical) between the DGPS and image-based bathymetry was reduced from 0.24 m to 0.06 m by correcting for the systematic deviations due to variations in setup and wave height saturation. Further improvement of the elevation estimates resulted from parameterizing the actual bathymetry with a simple plane beach surface, which reduced random (or unresolvable) measurement errors. This led to estimates of the beach slope that were accurate to within 10% of the actual slope and estimates of the cross-shore location of the mean sea level line accurate to about 0.50 m.

Analysis of the scale of errors in nearshore bathymetric data

Most studies of nearshore hydrodynamics, sediment transport, and morphology focus on bathymetric variability within a narrow band of spatial and temporal scales. Typically, these studies rely on bathymetry estimates derived from field observations consisting of discrete samples in space and time with varying degrees of measurement error. Sampling limitations, which result in aliasing, and measurement errors can significantly contaminate variability at resolved scales, and may lead to large errors in the representation of the scales of interest. Using a spectral analysis, interpolation errors were analyzed for three different nearshore bathymetric data sets, each of which targeted a different range of spatial scales. Bathymetric features that were unresolved or poorly resolved (e.g. beach cusps) introduced the potential for contamination in two of the data sets. This contamination was significantly reduced using an appropriate scale-controlled interpolation method, leading to more accurate representations of the actual bathymetry. An additional benefit of using scale-controlled interpolation is that interpolation errors may be estimated independently of actual observations, which allows one to design bathymetric sampling strategies that ensure that dominant scales are either resolved or largely removed. Finally, interpolation errors corresponding to a particular sample design can be used to determine which interpolated values contribute usefully to a band-limited analysis of bathymetric variability.

A behavior‐oriented dynamic model for sandbar migration and 2DH evolution

[1] A nonlinear model is developed to study the time‐dependent relationship between the alongshore variability of a sandbar, a(t), and alongshore‐averaged sandbar position, xc(t). Sediment transport equations are derived from energetics‐based formulations. A link between this continuous physical representation and a parametric form describing the migration of sandbars of constant shape is established through a simple transformation of variables. The model is driven by offshore wave conditions. The parametric equations are dynamically coupled such that changes in one term (i.e., xc) drive changes in the other (i.e., a(t)). The model is tested on 566 days of data from Palm Beach, New South Wales, Australia. Using weighted nonlinear least squares to estimate best fit model coefficients, the model explained 49% and 41% of the variance in measured xc and a(t), respectively. Comparisons against a 1‐D horizontal (1DH) version of the model showed significant improvements when the 2DH terms were included (1DH and 2DH Brier skill scores were −0.12 and 0.42, respectively). Onshore bar migration was not predicted in the 1DH model, while the 2DH model correctly predicted onshore migration in the presence of 2DH morphology and allowed the bar to remain closer to shore for a given amount of breaking, providing an important hysteresis to the system. The model is consistent with observations that active bar migration occurs under breaking waves with onshore migration occurring at timescales of days to weeks and increasing 2DH morphology, while offshore migration occurs rapidly under high waves and coincides with a reduction in 2DH morphology. Citation: Splinter, K. D., R. A. Holman, and N. G. Plant (2011), Abehavior‐orienteddynamicmodelforsandbarmigrationand2DH evolution, J. Geophys. Res., 116, C01020, doi:10.1029/2010JC006382.

Ocean Wavenumber Estimation From Wave-Resolving Time Series Imagery

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution).

Forecasting Hurricane Impact on Coastal Topography

Extreme storms can have a profound impact on coastal topography and thus on ecosystems and human-built structures within coastal regions. For instance, landfalls of several recent major hurricanes have caused significant changes to the U.S. coastline, particularly along the Gulf of Mexico. Some of these hurricanes (e.g., Ivan in 2004, Katrina and Rita in 2005, and Gustav and Ike in 2008) led to shoreline position changes of about 100 meters. Sand dunes, which protect the coast from waves and surge, eroded, losing several meters of elevation in the course of a single storm. Observations during these events raise the question of how storm-related changes affect the future vulnerability of a coast.

Inundation of a barrier island (Chandeleur Islands, Louisiana, USA) during a hurricane: Observed water‐level gradients and modeled seaward sand transport

Large geomorphic changes to barrier islands may occur during inundation, when storm surge exceeds island elevation. Inundation occurs episodically and under energetic conditions that make quantitative observations difficult. We measured water levels on both sides of a barrier island in the northern Chandeleur Islands during inundation by Hurricane Isaac. Wind patterns caused the water levels to slope from the bay side to the ocean side for much of the storm. Modeled geomorphic changes during the storm were very sensitive to the cross-island slopes imposed by water-level boundary conditions. Simulations with equal or landward sloping water levels produced the characteristic barrier island storm response of overwash deposits or displaced berms with smoother final topography. Simulations using the observed seaward sloping water levels produced cross-barrier channels and deposits of sand on the ocean side, consistent with poststorm observations. This sensitivity indicates that accurate water-level boundary conditions must be applied on both sides of a barrier to correctly represent the geomorphic response to inundation events. More broadly, the consequence of seaward transport is that it alters the relationship between storm intensity and volume of landward transport. Sand transported to the ocean side may move downdrift, or aid poststorm recovery by moving onto the beach face or closing recent breaches, but it does not contribute to island transgression or appear as an overwash deposit in the back-barrier stratigraphic record. The high vulnerability of the Chandeleur Islands allowed us to observe processes that are infrequent but may be important at other barrier islands.

Scaling coastal dune elevation changes across storm-impact regimes

Extreme storms drive change in coastal areas, including destruction of dune systems that protect coastal populations. Data from four extreme storms impacting four geomorphically diverse barrier islands are used to quantify dune elevation change. This change is compared to storm characteristics to identify variability in dune response, improve understanding of morphological interactions, and provide estimates of scaling parameters applicable for future prediction. Locations where total water levels did not exceed the dune crest experienced elevation change of less than 10%. Regions where wave-induced water levels exceeded the dune crest exhibited a positive linear relationship between the height of water over the dune and the dune elevation change. In contrast, a negative relationship was observed when surge exceeded the dune crest. Results indicate that maximum dune elevation, and therefore future vulnerability, may be more impacted from lower total water levels where waves drive sediment over the dune rather than surge-dominated flooding events.

Tidal hydrodynamics under future sea level rise and coastal morphology in the Northern Gulf of Mexico

This study examines the integrated influence of sea level rise (SLR) and future morphology on tidal hydrodynamics along the Northern Gulf of Mexico (NGOM) coast including seven embayments and three ecologically and economically significant estuaries. A large-domain hydrodynamic model was used to simulate astronomic tides for present and future conditions (circa 2050 and 2100). Future conditions were simulated by imposing four SLR scenarios to alter hydrodynamic boundary conditions and updating shoreline position and dune heights using a probabilistic model that is coupled to SLR. Under the highest SLR scenario, tidal amplitudes within the bays increased as much as 67% (10.0 cm) because of increases in the inlet cross-sectional area. Changes in harmonic constituent phases indicated that tidal propagation was faster in the future scenarios within most of the bays. Maximum tidal velocities increased in all of the bays, especially in Grand Bay where velocities doubled under the highest SLR scenario. In addition, the ratio of the maximum flood to maximum ebb velocity decreased in the future scenarios (i.e., currents became more ebb dominant) by as much as 26% and 39% in Weeks Bay and Apalachicola, respectively. In Grand Bay, the flood-ebb ratio increased (i.e., currents became more flood dominant) by 25% under the lower SLR scenarios, but decreased by 16% under the higher SLR as a result of the offshore barrier islands being overtopped, which altered the tidal prism. Results from this study can inform future storm surge and ecological assessments of SLR, and improve monitoring and management decisions within the NGOM.

A cross-validation package driving Netica with python

Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill). Cross-validation avoids overfitting, improving predictive power of Bayesian Networks.CVNetica is a Python tool for cross-validation of Bayesian Networks.Cross-validation illustrated on a data-driven and a model emulation Bayesian Network.