Using a fully nonlinear Boussinesq wave model on the near shore area of Branford, Norwalk, and New Haven to determine the total water elevation on the shores.

The goal of the research was to numerically resolve sea dynamics (such as currents, waves, sea surface displacement) at the Connecticut coastline. The estuarine circulation of the LIS mediates key biogeochemical cycles (cycles in which chemical elements and simple substances are transferred between living systems and the environment) in the region upon which local environments depend. Understanding local changes in the wave field and circulation dynamics in the LIS goes beyond purely scientific endeavors, with future implications that effect coastal communities and the†natural environments. Currently, there is particular attention being placed into evaluating the risk of flooding at coastal areas as the upcoming and present challenges of climate change at a regional scale become apparent with changes in sea level and storm frequency and intensity. This work will help coastal communities better understand the effect of waves at the coastline ñ where people live, work, and play.

Flood hazard planning requires the accurate estimation of total water elevation due to predicted tide, surge, and wave runup to design flood protection structures and improve coastal risk planning for severe storms. The beach topography and nearshore hydrodynamic conditions impact the conclusive flood inundation mapping in complex environments. The conventional approaches of flood modeling are limited due to either i) simple static estimates, ii) the application of a coupled circulation and phase-averaged wave models in coarse resolution, iii) failing to calibrate and validate with in-situ data, or iv) not considering sea-level rise projections in mapping the flood extent. We used a high-resolution wave model (FUNWAVE-TVD) capable of resolving processes like wave refraction and diffraction on the nearshore area to determine total water elevation on the shores.

Understanding the risk posed by extreme storm events and accurate assessment of the flood risk is crucial for the successful management of the coastal communities using increasing resiliency. There are only a few available tide gauge, buoy, and storm sensor data in the Long Island Sound to project the extreme sea level statistics using the observed records available to determine the level of risk along the Connecticut coastline accurately. In this work, we reproduced the highest 44 storms between 1950-2018 using a coupled circulation and wave model. The modeled events are fit to a probability distribution to statistically estimate the annual exceedance probabilities and return periods for expected storms. In addition to evaluating historical risks, we also added a sea-level height offset of 0.5 m for 2050 estimates in order to examine the effect of rising sea-levels on the analysis. We find that sea-level rise reduces the return period of a 10-year storm to two years. We advise periodically updating this work as improved sea-level rise projections become available.

This paper examines case studies of compound flood hazards affecting critical infrastructure in coastal Connecticut.† Seven coastal river reaches were studied where eight power grid substations lie in proximity to riverbanks and are prone to flooding caused by coastal storms (such as hurricanes) that combine heavy precipitation and high surge.

Long records of wave parameters are central to the estimation of coastal flooding risk and the causes of coastal erosion. This paper leverages the predictive power of wave height history and correlations with wind speed and direction to build statistical models for time series of wave heights to develop a method to fill data-gaps and extend the record length of coastal wave observations.

This paper summarizes the statistics of observations of wind and surface gravity waves in Long Island Sound. Researchers examine the relationship between significant wave height and wind speed and direction and show that the significant wave height and dominant period in western Long Island Sound have an asymmetric response to the wind direction.