Graduate Project

 

Evaluating climate change induced coastal flood impacts to San Diego Bay Naval Infrastructure - a hybrid statistical dynamical modeling approach Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_projects/8s45qg862

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  • This study utilizes probabilistic surrogate modeling techniques around San Diego Bay with an emphasis on naval infrastructure and operations to evaluate the impact of five global mean sea level rise scenarios (GMSLR). Spatially continuous total water levels (TWLs) are combined with a digital elevation model (DEM) of the region to determine the magnitude of climate change induced coastal flooding while identifying critical facilities and operations impacted by specific flooding events. Based on the locations of these critical facilities and operations, the stochastic forcing time series produced by the Time-varying Emulator for Short and Long-term Analysis of coastal flooding (TESLA-flood) and the GIS flood profile is used to predict the impact in terms of annual hours per day of lost operations for a given sea level rise scenario. Other aspects of coastal flooding and sea level rise (SLR) such as the spatial variability of TWLs, extreme water levels (EWLs), and the factors that drive these specific events were investigated to better understand the range of future conditions resulting from SLR. As the Navy develops long term planning solutions, it is important to consider the likelihood and magnitude of these events while identifying the most vulnerable areas of the installation.
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