Evaluating Risk of Waterborne Debris
Abstract
The problem of surface and subsurface waterborne debris is of increasing concern on a global scale. Recent surges in the number and intensity of worldwide tsunami and storm events, as well as growing populations and continuous land development have exacerbated the predicament. These events have resulted in both man-made and natural debris entering outflows to coastal waterways and eventually oceans. Depending on the type and concentration of debris that is introduced into a flow field, it has the potential to increase the risk of damage to aquatic infrastructure and ecosystems. Decreased performance and failure of critical infrastructure as well as diminished health of wildlife due waterborne debris are potential consequences that have already been observed. The behavior of debris is highly dependent on the type of debris and characteristics of the waterway flow field, which makes debris transport and trajectory a complex phenomenon to model.
The need to better understand and characterize the subsets of debris behavior and interactions that lead to these negative outcomes is the focus of this research. A probabilistic model is developed to quantitatively investigate the nature of the risks associated with waterborne debris and capture the inherent uncertainties in modeling its behavior. A fault tree framework is used to establish the relationships between sub-events that lead to the disruptive behavior of waterborne debris. Specific focus is given to illustrative examples for the entanglement of whales in derelict fishing gear for the US Atlantic and Pacific coastlines and impact loading from large waterborne debris on fixed structures in a channel. The risk of entanglement is characterized by the type of fishing gear, including its usage rates and loss rates, the region of study, and the seasonal migration of whales. The risk of impact loading is characterized by the rate of occurrence of debris-generating events, debris characteristics, channel dimensions, flow conditions, and the position and dimensions of the structure. Several methods of visualization reveal the sensitivity of the model to parameter definitions. The developed comprehensive model provides an adaptable risk-based framework for assembling available data to be interpreted into meaningful assessments for a wide range of applications.
Citation
Brown, Anita Helene (2021). Evaluating Risk of Waterborne Debris. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /193088.
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