Numerical models can represent the coastal environment and its response to the combined effects of tides, river flows, and winds. It is especially challenging for numerical models to represent the response of estuaries to storms, due to the complex interactions of fresh and saline waters, and thus relatively few studies have used models to represent both storm- and density-driven circulation in estuaries. These few studies have shown that salinities and temperatures of estuaries can change significantly during storms and may require weeks to recover, depending on the amount of freshwater discharge. However, these studies have been limited in number and geographic coverage, relied on coupling to other models for baroclinic inputs, did not have the estuarine mixing and stratification as a focus, or were missing physics. Much is still uncertain about how estuarine circulation evolves during a storm event. How quickly do the horizontal salinities respond to the storm? How does the salinity transport vary through an estuary? How do freshwater discharges due to rainfall affect the mixing? Another uncertainty is the salinity response after the storm. How quickly does a system recover? Do the freshwater discharges interrupt the recovery? In this thesis, it is hypothesized that, for a large and shallow estuarine system with minimal connections to the open ocean, the storm forcing will cause large brackish and freshwater intrusions and recoveries that vary through the system.
To investigate this hypothesis, we developed a three-dimensional model of storm- and density-driven circulation in the Albemarle-Pamlico Estuarine System (APES) in North Carolina. Irene (2011) was used as the basis for storm event simulations to examine the evolution of the horizontal salinity distribution. Included in this model were hurricane-strength winds and pressures, tides, river discharges, and density circulation. Using this model, it was determined that during Irene, APES experienced movements of brackish water into the estuaries and saline water into the sounds. These movements were heavily dependent on the winds. After the stormsimulation, the large river discharges produced intrusions of fresher water into major areas of the sound, and after two weeks, the system was not fully regulated.
From this research, we have developed a better understanding of the horizontal salinity distribution of APES as well as how the system reacts to a single storm event. This research allows for future studies to consider different types of storms along with refinement of the river forcings, to understand better the full range of estuarine responses.
In this dissertation, first a morphodynamic model is used to explore the effects of Isabel (2003) on the NC Outer Banks, with the focus on a large domain that covers 30 km of the barrier island from Rodanthe to Avon. It is hypothesized that the model can be coarsened and expanded to a large domain while preserving accuracy. Model predictions for dune erosion and overwash are in good agreement with post-storm observations. Sensitivity studies show that the model accuracy is less sensitive to the alongshore resolution of the mesh. Then, the topographic elevation changes are upscaled to a region-scale flooding model to allow overwash and inundation behind the dunes. The loose coupling of these process-based models improves the flooding predictions in region-scale model significantly.
Then, a more complex case of beaching and its impacts on larger-scale circulations are explored. Isabel (2003) breached the barrier island near the town of Hatteras and formed three channels connecting the ocean to the sound. Two-way coupling of high-resolution numerical models for coastal erosion and flooding is implemented to study the temporal and spatial evolution of the breach and its contribution to the hydrodynamics in the sound. It is hypothesized that the channels were formed due to the combined effects of ocean-side dune erosion and lagoon-side elevated water levels. The model shows that the flow from the sound to the ocean has an important role in deepening the breached channels. The morphodynamic model can predict the initiation and approximate location of the breach. However, it failed to accurately capture the channels’ depths. Several flooding scenarios are considered to implement the ground surface changes in the flooding model. The evolving breach can affect the timing and extent of flow into the lagoon. The model results show that the breach has region-scale effects on flooding that extend about 10 km into the lagoon.
Finally, the erosion of nourished beaches subjected to multiple storms is investigated. Beach nourishment provides a buffer during extreme events in the short-termbut has a finite lifespan as the beach responds to subsequent storms. Numerical models are widely used to predict the beach morphodynamics, however, they are computationally expensive. In this research, a surrogate model is developed by coupling deterministic and probabilistic models to improve the computational efficiency and to include the randomness of possible future scenarios. A large data set of storm data and beach profiles is used to create a library of thousands of hypothetical scenarios to train the surrogate model. It is hypothesized that adding the beach profile variability in the analysis can improve the model in the sense that it can be applied to any beach state. The results show that predicted erosion volume by the surrogate model is very close to the numerical model predictions. The model produced the results in a few seconds which shows a significant improvement in computational time compared to numerical models.
One of the most unpredictable and deadly parts of a coastal storm is the storm surge, which can cause devastating flooding of coastal regions, and can result in loss of property and life. Storm surge is a result of winds pushing water from the nearshore ocean to rise above regular tide levels. Storm surge can have a short duration; elevated water levels are limited to when the storm winds are strongest at the coast, typically for a few hours as the storm makes landfall. This short duration is a challenge for predictions of when storm surge will start, how long it will persist, and which regions will be flooded.
This research will explore the arrival of storm effects for Florence, which made landfall along the North Carolina coast during September 2018. It is an ideal storm for this research as its track was shore-normal, and thus its coastal effects increased as it approached landfall. This will allow for investigating the most optimal switch by focusing on a single switch between a lower-resolution mesh to a higher-resolution mesh. The switches will be initiated by several triggers, including wind speeds and water levels at the coast and inland locations, and with several lead times, including near and several days before landfall. Model performance will be quantified via comparisons to observations of storm effects in the region, as well as to a single, high-resolution simulation for the full storm. It will be shown that switching from a coarse resolution mesh to a fine resolution mesh will lead to an increase in efficiency gains across all switching simulations with the most optimal switch time resulting in the most accurate predictions of water levels as compared to our full high-resolution simulation.
This research describes a method to improve the accuracy and efficiency of coastal flooding predictions. First, an existing model is used to explore the effect of storm forward speed and timing on tides and storm surge during Hurricane Matthew (2016). It is hypothesized that the spatial variability of Matthew’s effects on total water levels is due to the surge interacting nonlinearly with tides. If the storm occurred a few hours earlier or later, then the largest surges would have been shifted to other regions of the U.S. southeast coast. A change in forward speed of the storm also should alter its associated flooding due to differences in the duration over which the storm impacts the coastal waters. If the storm had moved faster, then the peak water levels would have increased along the coast, but the overall volume of inundation would have decreased. Then this research explores ways to increase the model’s accuracy and efficiency. To better represent Matthew’s effects, a mesh with detailed coverage of the coastal regions from Florida to North Carolina was developed by combining regional meshes originally developed for floodplain mapping. Compared to predictions using the earlier model, the new mesh allows for simulations of inundation that better match to observations especially inland.
Then, to best utilize this new mesh, a multi-resolution approach is implemented to use meshes of varying resolution when and where it is required. It is hypothesized that by `switching’ from coarse- to fine-resolution meshes, with the resolution in the fine mesh concentrated only at specific coastal regions influenced by the storm at that point in time, both accuracy and computational gains can be achieved. As the storm approaches the coastline and the landfall location becomes more certain, the simulation will switch to a fine-resolution mesh that describes the coastal features in that region. Application of the approach during Hurricanes Matthew and Florence revealed the predictions to improve in both accuracy and efficiency, as compared to that from single simulations on coarse- and fine-resolution meshes, respectively.
During major storm events such as hurricanes, emergency managers rely on fast and accurate forecasting models to make important decisions concerning public safety. These models can be computationally costly and cannot quickly make predictions at the highest geospatial resolution. However, model output can be post-processed to mimic high-resolution results with minimal additional computational cost. This research proposes methods for improvement in the accuracy of downscaling (enhancing the resolution of) a real-time storm surge forecasting model. Such improvements to downscaling methods include 1) expansion in its spatial applicability, 2) adding physics using water surface slopes, and 3) adding physics using friction losses across the ground surface.
The downscaling process is also improved by adding physics using the slopes method and the head loss method. The slopes method incorporates the slopes of the water levels produced by ADCIRC, rather than only the value of the water level. By interpolating ADCIRC output water elevation points into a smooth surface, slopes of this surface can be used to influence the elevations of downscaled water levels. The head loss method adds friction loss due to variations in the ground surface based on land cover types and friction associated with each type. As water travels over any surface, head loss, or a loss in energy, occurs at different rates depending on the surface roughness. This rudimentary hydrologic principle is applied to increase the accuracy of the downscaling process at minimal cost. The downscaling methods are applied for results from an ADCIRC simulation used in real-time forecasting, and then compared with results from an ADCIRC simulation with 10 times more resolution in Carteret County, NC. The static method tends to over-estimate the flood extents, and the slopes method is similar. However, the head loss method generates a downscaled flooding extent that is a close match to the predictions from the higher-resolution, full-physics model.
The study begins with an application of a state-of-the-art storm surge model to examine the effects of meteorological forecast errors on coastal flooding predictions along the North Carolina (NC) coastline. As Hurricane Arthur (2014) moved over Pamlico Sound, it increased the total water levels to 2.5 m above sea level; this water pushed first into the river estuaries and against the inner banks, and then moved eastward to threaten the sound-side of the barrier islands. It is hypothesized that a combination of storm track and intensity errors caused errors in the forecast winds and water levels along the NC coast during Arthur. Model results reveal that, as the forecast storm track and intensity errors increase, the errors in forecast wind speeds also increase, but the errors in forecast water levels remain relatively the same, signifying the non-linear response of the coastal ocean to wind effects. By separating the forecast errors in storm track and storm strength, this study quantifies their effects on the coastal ocean, which provides useful guidance for designing relevant forecast ensembles.
In addition to flooding impacts, storms can also cause dramatic changes in estuarine salinities, which can negatively impact estuarine ecosystems. Baroclinic models are useful tools for predicting estuarine salinity response under changing environmental conditions. In the present work, the features of wind- and plume-driven circulation in the vicinity of Choctawhatchee Bay (CB) and Destin Inlet, Florida, are analyzed with a recently-enhanced, three-dimensional, baroclinic model. Satellite imagery showed a visible brackish surface plume at Destin during low tide. The goal of the present study is to quantify variability in the plume signature due to changes in tidal and wind forcing. Modeled tides, salinities and plume signature are validated against in-situ observations and satellite imagery and then applied to analyze plume response in two scenarios. In the first case, model plume behavior is analyzed on successive days of near-constant tidal amplitudes and changing wind directions due to passing cold fronts. In the second case, plume response is investigated during consecutive days of neap-spring variability in the tides and near-constant wind speeds. Model results reveal a larger plume during spring tides and periods of weak wind forcing. Oshore winds enhance the north-south expansion of the plume, whereas onshore winds restrict the plume to the coastline.
Finally, the validated model is applied to identify salinity and transport characteristics within CB. Based on past studies, it is hypothesized that CB is a stratified system with limited flushing and zones of distinct salinity gradients. These hypotheses are tested by analyzing bay salinities from the validated model during a period of low river flows. Model surface salinities indicate brackish conditions (20 psu) throughout the bay except for near the river mouth. Stratification (10 to 15 psu) within the bay is unaffected by the passage of cold fronts and neap-spring tidal variability. The residence time within the Choctawhatchee Bay, an important indicator of estuarine health, is computed via particle tracking and is equal to roughly 40 days.
Coastal Louisiana and Mississippi are especially prone to large hurricanes due to their geographic location in the north-central Gulf of Mexico. Several recent hurricanes have devastated the region, creating complicated environments of waves and storm surge. Katrina (2005) and Gustav (2008) made landfall in southeastern Louisiana, and their counter-clockwise winds pushed surge onto the Louisiana-Mississippi continental shelf, into the low-lying wetlands surrounding the Mississippi River, and over and through the levee system that protects metropolitan New Orleans. Rita (2005) and Ike (2008) passed farther to the west, moved across the Texas-Louisiana continental shelf, and created surge that flooded large portions of southwestern Louisiana.