Browsing by Subject "ADCIRC"
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Item Data assimilation for parameter estimation in coastal ocean hydrodynamics modeling(2013-12) Mayo, Talea Lashea; Dawson, Clinton N.Coastal ocean models are used for a vast array of applications. These applications include modeling tidal and coastal flows, waves, and extreme events, such as tsunamis and hurricane storm surges. Tidal and coastal flows are the primary application of this work as they play a critical role in many practical research areas such as contaminant transport, navigation through intracoastal waterways, development of coastal structures (e.g. bridges, docks, and breakwaters), commercial fishing, and planning and execution of military operations in marine environments, in addition to recreational aquatic activities. Coastal ocean models are used to determine tidal amplitudes, time intervals between low and high tide, and the extent of the ebb and flow of tidal waters, often at specific locations of interest. However, modeling tidal flows can be quite complex, as factors such as the configuration of the coastline, water depth, ocean floor topography, and hydrographic and meteorological impacts can have significant effects and must all be considered. Water levels and currents in the coastal ocean can be modeled by solv- ing the shallow water equations. The shallow water equations contain many parameters, and the accurate estimation of both tides and storm surge is dependent on the accuracy of their specification. Of particular importance are the parameters used to define the bottom stress in the domain of interest [50]. These parameters are often heterogeneous across the seabed of the domain. Their values cannot be measured directly and relevant data can be expensive and difficult to obtain. The parameter values must often be inferred and the estimates are often inaccurate, or contain a high degree of uncertainty [28]. In addition, as is the case with many numerical models, coastal ocean models have various other sources of uncertainty, including the approximate physics, numerical discretization, and uncertain boundary and initial conditions. Quantifying and reducing these uncertainties is critical to providing more reliable and robust storm surge predictions. It is also important to reduce the resulting error in the forecast of the model state as much as possible. The accuracy of coastal ocean models can be improved using data assimilation methods. In general, statistical data assimilation methods are used to estimate the state of a model given both the original model output and observed data. A major advantage of statistical data assimilation methods is that they can often be implemented non-intrusively, making them relatively straightforward to implement. They also provide estimates of the uncertainty in the predicted model state. Unfortunately, with the exception of the estimation of initial conditions, they do not contribute to the information contained in the model. The model error that results from uncertain parameters is reduced, but information about the parameters in particular remains unknown. Thus, the other commonly used approach to reducing model error is parameter estimation. Historically, model parameters such as the bottom stress terms have been estimated using variational methods. Variational methods formulate a cost functional that penalizes the difference between the modeled and observed state, and then minimize this functional over the unknown parameters. Though variational methods are an effective approach to solving inverse problems, they can be computationally intensive and difficult to code as they generally require the development of an adjoint model. They also are not formulated to estimate parameters in real time, e.g. as a hurricane approaches landfall. The goal of this research is to estimate parameters defining the bottom stress terms using statistical data assimilation methods. In this work, we use a novel approach to estimate the bottom stress terms in the shallow water equations, which we solve numerically using the Advanced Circulation (ADCIRC) model. In this model, a modified form of the 2-D shallow water equations is discretized in space by a continuous Galerkin finite element method, and in time by finite differencing. We use the Manning’s n formulation to represent the bottom stress terms in the model, and estimate various fields of Manning’s n coefficients by assimilating synthetic water elevation data using a square root Kalman filter. We estimate three types of fields defined on both an idealized inlet and a more realistic spatial domain. For the first field, a Manning’s n coefficient is given a constant value over the entire domain. For the second, we let the Manning’s n coefficient take two distinct values, letting one define the bottom stress in the deeper water of the domain and the other define the bottom stress in the shallower region. And finally, because bottom stress terms are generally spatially varying parameters, we consider the third field as a realization of a stochastic process. We represent a realization of the process using a Karhunen-Lo`ve expansion, and then seek to estimate the coefficients of the expansion. We perform several observation system simulation experiments, and find that we are able to accurately estimate the bottom stress terms in most of our test cases. Additionally, we are able to improve forecasts of the model state in every instance. The results of this study show that statistical data assimilation is a promising approach to parameter estimation.Item Integration of Different Wave Forcing Formulations with Nearshore Circulation Models(2012-02-14) Sharma, AbhishekWave-induced circulation in general coastal environments is simulated by coupling two widely-used finite-element models, namely, a refraction-diffraction-reflection model based on the elliptic mild-slope equation, and a two-dimensional (depth-averaged) shelf-scale circulation model. Such models yield wave-induced current-fields and set-up/down. This involves exploration of some numerical and practical issues, for example, the selection of appropriate boundary condition and grid resolution, numerical errors owing to higher-order derivatives, etc. Computations of the wave forcing from the elliptic wave model, and the wave-induced quantities from the circulation model, are validated with theoretical and published results. The coupled system is then used to simulate the wave-induced circulation in the domains where structures (e.g. breakwater, jetty, etc.) and bathymetric features (e.g. shoal, etc.) are present. In practice, usually an approximate form of the wave-induced forcing is used. This has certain limitations in some application, which have been poorly studied so far. Therefore, here we consider two alternative approaches. The performance of these wave forcing formulations is examined in the regions where the effects of wave reflection, diffraction and focusing are significant. It is observed that the ?generalized approach? provides satisfactory results in most situations, provided a grid resolution of L/10 or more is achievable for the wave model domain. The widely-used simplified approach may produce a chaotic pattern of set-up/down and current field in the regions where the wave field is not purely progressive. The third approach ignores the effect of wave diffraction and reflection, and primarily simulates the effect of energy dissipation. Differences up to 25 percent are observed between the modeled current fields obtained with the generalized and the simplified approach. The results suggest that the generalized approach can be used with little practical difficulty and greater reliability.Item Storm surge analysis using numerical and statistical techniques and comparison with NWS model SLOSH(Texas A&M University, 2005-11-01) Aggarwal, ManishThis thesis presents a technique for storm surge forecasting. Storm surge is the water that is pushed toward the shore by the force of the winds swirling around the storm. This advancing surge combines with the normal tides to create the hurricane storm tide, which can increase the mean water level by almost 20 feet. Numerical modeling is an important tool used for storm surge forecast. Numerical model ADCIRC (Advanced Circulation model; Luettich et al, 1992) is used in this thesis for simulating hurricanes. A statistical technique, EST (Empirical Statistical Technique) is used to generate life cycle storm surge values from the simulated hurricanes. These two models have been applied to Freeport, TX. The thesis also compares the results with the model SLOSH (Sea, Lake, and Overland Surges from Hurricanes), which is currently used for evacuation and planning. The present approach of classifying hurricanes according to their maximum sustained winds is analyzed. This approach is not found to applicable in all the cases and more research needs to be done. An alternate approach is suggested for hurricane storm surge estimation.