A numerical study was conducted to characterize the probability and intensity of storm surge hazards in Canada’s western Arctic. The utility of the European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) dataset to force numerical simulations of storm surges was explored. Fifty historical storm surge events that were captured on a tide gauge near Tuktoyaktuk, Northwest Territories, were simulated using a two-dimensional (depth-averaged) hydrodynamic model accounting for the influence of sea ice on air-sea momentum transfer. The extent of sea ice and the duration of the ice season has been reducing in the Arctic region, which may contribute to increasing risk from storm surge-driven hazards. Comparisons between winter storm events under present-day ice concentrations and future open-water scenarios revealed that the decline in ice cover has potential to result in storm surges that are up to three times higher. The numerical model was also used to hindcast a significant surge event that was not recorded by the tide gauge, but for which driftwood lines along the coast provided insights to the high-water marks. Compared to measurements at proximate meteorological stations, the ERA5 reanalysis dataset provided reasonable estimates of atmospheric pressure but did not accurately capture peak wind speeds during storm surge events. By adjusting the wind drag coefficients to compensate, reasonably accurate predictions of storm surges were attained for most of the simulated events. The extreme value probability distributions (i.e., return periods and values) of the storm surges were significantly altered when events absent from the tide gauge record were included in the frequency analysis, demonstrating the value of non-conventional data sources, such as driftwood line surveys, in supporting coastal hazard assessments in remote regions.

A numerical hydrodynamic model was used to simulate the generation and evolution of storm surges in Atlantic Canada in response to synoptic‐scale surface wind and atmospheric pressure fields. The modelling was conducted as part of a broader initiative to support community‐scale inundation modelling and coastal flood risk assessment for communities located in the Acadian Peninsula region of New Brunswick. The 44 largest storm surge events on record at a tide gauge proximate to the region of interest were simulated using the numerical model. Initially, a comparison between simulated storm surges and peak non‐tidal residuals from tide gauge records showed relatively poor agreement, producing an R² value of 0.403. Model skill was improved by incorporating the influence of sea ice cover on air‐sea momentum transfer in the hydrodynamic model, and improved correlation with measured residuals was obtained by adding estimates of wave set‐up to the predicted storm surges, ultimately resulting in an R² value of 0.803. The results of the simulations provided a basis for identifying distinct regional factors affecting storm surges and water level residuals and demonstrated conditions where wave set‐up and sea ice cover play an important role in contributing to extreme high water levels.

Despite the growing range and availability of resources to support coastal flood hazard model development, there is often a scarcity of data to support critical assessment of the performance of community-scale coastal inundation models. Even where long-term tide gauge measurements are available in close proximity to the study area, the records provide little insight into the spatial distribution and limits of overland flooding, or the influence of topographic features and structures on flooding pathways. We present methods to support the assessment of model performance using field observations in lieu of, or supplementary to, conventional water-level records. A high-resolution, numerical coastal flood hazard model was developed to simulate storm surge-driven flooding in the Acadian Peninsula region of New Brunswick, Canada. Owing to the remoteness of the study area from tide gauge stations, model performance was assessed based on a comparison with field measurements of deposited wrack and debris, as well as photographic and video evidence of coastal flooding, for two significant storm surge events in recent history. Our research findings illustrate the value of observational and qualitative data for characterizing coastal flood hazards, lending gravity to the importance of non-conventional data sources, particularly in data-scarce regions.

This paper presents the result of a multiyear study consisting of field measurements and numerical modeling of a highly dynamic tidal inlet located on the west side of the Gulf of Saint Lawrence near Le Goulet, New Brunswick, Canada. Due to a lack of human intervention in the past few decades, natural processes have taken hold of this tidal inlet and large volumes of sediment have been deposited within the inlet. The Shippagan Gully inlet transects the Acadian Peninsula and is therefore subject to tidal forcing from both ends. An appreciable phase lag present in the two open ocean boundaries results in ebb flows through Shippagan Gully, which regularly exceed 2 m/s, to be twice as strong as the flood flows. This flow imbalance along with a long history of human intervention has created a complex and highly dynamic tidal inlet. The purpose of the study was to develop a numerical model of the hydrodynamic and morphological processes that occur at Shippagan Gully and to use the model to assess alternative engineering measures that could be implemented to promote a safe and navigable channel through the inlet.