Quantifying Estuarine Hydrometeorological Coastal Hazards Using a Combined Field Observation and Modeling Approach

Abstract

Coastal development and its associated site management have rapidly expanded to estuarine environments while continuing to increase worldwide. With the growth of coastal management projects, field observations are required to understand how anthropogenic construction, coastal defense, environmental restoration, and conservation areas will react to the typical, extreme, and long-term conditions at the proposed sites. To address these unknowns, we present a multi-faceted coastal risk assessment of a unique, recently nourished estuarine beach near the mouth of the Delaware Bay Estuary by merging rapid-response remote sensing platforms, hydrodynamic models, and publically available monitoring datasets. Specifically, hydrometeorological events from 2015 to 2019 were the focus of peak-over-threshold statistics, event type definition, and clustered event interval determination. The 95th percentile thresholds were determined to be the following: 0.84 m for the significant wave height, 13.5 m/s for the 10-m elevation wind speed, and 0.4 m for the total water level residuals. Tropical and extra-tropical cyclones, light gales, or cold and stationary fronts proved to be the meteorological causes of the sediment mobility, inducing the hydrodynamics at the site. Using these event types and exceedance instances, clustered meteorological events were defined as having an interval greater than twelve hours but less than five days to be considered clustered. Clustered events were observed to cause greater volumetric change than individual events, and are currently underrepresented in coastal risk planning and response in the region. Coastal monitoring field measurements should consider clustered events when conducting post-hazardous or erosional event response surveys. This work highlights the importance of clustered hydrometeorological events causing estuarine coastal risk, and how to quantify these effects through combined field observations and modeling approaches.