| Summary |
Compound Coastal Water Events (CCWE) are a type of multi-hazard climate event characterized by three different types of flooding: Tidal, Fluvial, and Pluvial. To differentiate between these types, tidal is caused by extreme tide conditions, fluvial is caused by rivers or streams overflowing their banks, and pluvial is caused by extreme precipitation. Through an in-depth analysis of the current literature, it does not appear that research has been taken to analyze the relationship between all these drivers. Eastern North Carolina is a suitable location to research CCWE given its climatologic and research setting. Estuary environments are particularly at risk of compound flooding due to the exposure posed by the geography of river systems meeting the open ocean. Eastern North Carolina is known for having the second largest estuary systems in the United States. Tropical cyclones are often a cause of all three of these CCWE drivers occurring at the same time and location. North Carolina, on average, has a hurricane landfall every 5 to 7 years, and is often impacted by hurricane remnants that make landfall in another state. When stakeholders prepare for these events the current hazard assessment tools are univariate or bivariate. Examples being floodplain maps primarily considering fluvial flooding and tidal inundation maps predominantly considering tidal flooding. Furthermore, there is little integration of precipitation which represents the pluvial aspects and is actively requested by stakeholders. A more effective approach would be to consider all three components. This study seeks to further understand the relationship between drivers of CCWE that occur in Eastern North Carolina. Analyses of three different locations were conducted to determine if there is a regionality of these relationships. The proposed methodology includes two processes. The first is a trivariate copula-based approach using the proxies of precipitation, stream discharge and tidal gauge data for CCWE drivers. The second process is to compare data sourced from a focus group with practitioners who respond and prepare for CCWE. Through utilization of copula models, simulated CCWE were created to create return periods from an initially limited data set. Trivariate "AND"--Based return periods are studied specifically as they quantify the chance that all drivers occur and meet or exceed a certain measurement. All three case studies have statistically similar distributions of trivariate return periods of CCWE though the southern location has a greater amount of lower return period values. Lower return period values indicate a higher probability of occurrence further denoting a higher risk environment. In interpreting the qualitative data sourced from a focus group consisting of decision makers within Eastern North Carolina, further information about CCWE was revealed building upon the statistical analysis. In the investigation of survey results and transcribed discussions, the decision makers perceptions of the CCWE drivers coincided with the research motivations and copula simulated results, emphasizing the importance of precipitation as a important driver of CCWE. Participants noted how they see the compounding nature of these events within their constituency and they view that they are at a high level of risk to these events. Combining the physical and social science data provided a better understanding of CCWE from a risk perspective and a decision-making context. Future work could delve into further temporal and spatial scales considering more study locations as well as the seasonality of events. CCWE are a phenomena that is extremely relevant to vulnerable coastal communities and further understanding of it will be able to benefit those who reside in these regions. |
