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Record W6891619102 · doi:10.4224/40003267

Numerical simulation of storm surges in the Beaufort Sea and coastal flood hazards in the Hamlet of Tuktoyaktuk, Northwest Territories

2024· report· en· W6891619102 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2024
Typereport
Languageen
Field
Topic
Canadian institutionsNational Research Council CanadaInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsStorm surgeFlood mythHazard analysisHazardNatural hazardStormCoastal hazardsArcticFlooding (psychology)

Abstract

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The work described in this report was completed as part of the Coastal Flood Mitigation Canada project, which received funding from Defence Research and Development Canada's Centre for Security Science through the Canadian Safety and Security Program. The project included three coastal flood hazard and risk assessment case studies, one for each of Canada's Atlantic, Arctic, and Pacific coasts. These case studies were designed to explore and demonstrate good practices to inform the development of new guidelines for coastal flood hazard assessment in Canada. As part of the Arctic case study, a coastal flood hazard assessment was performed for the Hamlet of Tuktoyaktuk, Northwest Territories. The primary objective of the coastal flood hazard assessment was to develop estimates of storm surge-driven flood hazards in Tuktoyaktuk for a range of events with defined return periods or annual exceedance probabilies (AEPs), which provided key inputs to a risk assessment by Natural Resources Canada (NRCan). Several community and partner engagement workshops were conducted during the project to obtain community input on the project scope, identify community flood risk management priorities, communicate progress and findings to the community, and to obtain community input to the risk assessment by NRCan. Two numerical hydrodynamic models were developed to support the coastal hazard assessment: a regional-scale storm surge model with a domain corresponding to approximately the maximum extent of open water (i.e., minimum ice extent) in the Beaufort Sea; and a higher-resolution, community-scale, overland flood hazard model with a domain covering areas within Kugmallit Bay and the Hamlet of Tuktoyaktuk. Model elevations were based on a digital elevation model created using bathymetric data from the General Bathymetric Chart of the Oceans, multibeam surveys, and topographic data from NRCan’s High-Resolution Digital Elevation Model. The two-dimensional (2D) numerical models were forced with surface pressures and winds from the ERA5 global atmospheric reanalysis dataset (hereafter referred to as ERA5). Surface pressure data from the ERA5 reanalysis dataset was in close agreement with measured atmospheric pressures at weather stations near Tuktoyaktuk. The overall variability, mean and trends in ERA5 surface wind speeds were also consistent with observations but peak surface wind speeds were consistently underestimated by ERA5. With some adjustment of wind speeds to better match observed storm peak values, the ERA5 dataset provided useful input to the storm surge modelling. Fifty historical storm surge events captured by a tide gauge at Tuktoyaktuk between 1979 and 2019 were simulated at the regional and community scale to support model calibration and validation. The effects of sea ice on storm surges were also assessed by implementing a model parametrization that adjusted the momentum imparted by the wind to the sea surface depending on the ice concentration. Ice concentrations provided by the Canadian Ice Service were prescribed as input to the model, and it was found that if sea ice had not been present to attenuate storm surges, some historical winter storm events might have produced peak storm surges three times greater than what was observed. Examination of the tide gauge records in the Beaufort Sea revealed a lack of continuous, long-term records of water levels. Two of the most significant storm surge events in recent history were not captured by the tide gauge at Tuktoyaktuk. However, evidence of peak water levels produced by these two events was available from field surveys of driftwood line deposits conducted by Harper et al. (1988). The highest water level recorded by the Tuktoyaktuk tide gauge was +2.23 m above local Chart Datum (m CD) on October 4th, 1963. However, based on driftwood observations by Harper et al. (1988), storm surge events occurring on September 1st, 1944, and September 14th, 1970 (not captured by the gauge) produced peak water levels equal to +2.95 m CD. The inclusion (or exclusion) of these two events from extreme value statistical analyses significantly impacted estimates of return periods (or AEPs) and return levels associated with storm surge-driven extreme water levels. Accounting for tide gauge records alone, a return level of 2.1 m was estimated for the 100-year return period storm surge event (equivalent to 1% AEP). Incorporating the September 1st, 1944 and September 14th, 1970 events into the analysis increased the 1% AEP storm surge to 2.92 m. Tidal variation in the Tuktoyaktuk region is small, with the difference between the highest astronomical tide (HAT) and lowest astronomical tide (LAT) being 0.62 m and a mean higher high water (MHHW) level of +0.497 m CD. Flood extents, water depths, depth-velocity products, and momentum fluxes were mapped for storm surge events with return periods of 2, 5, 10, 20, 50 and 100 years (coinciding with 50%, 20%, 10%, 5%, 2%, and 1% AEPs) superimposed on a static MHHW tidal elevation. The effects of three sea-level rise scenarios on the expected flood hazard were examined, coinciding with global sea-level rises of 0.5 m, 1.0 m, and 2.0 m, which translated to local (relative) sea-level rises of 0.54 m, 1.05 m, and 2.15 m, respectively. These scenarios may be interpreted in different ways depending on emissions scenarios, and confidence limits for future sea-level projections. However, the first two scenarios align with the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) projections for the Representative Concentration Pathway (RCP) 8.5 median at 2080, and the RCP 8.5 upper 95th percentile at 2100. A 2.0-m global sea-level rise represents a low probability, high-end scenario for the year 2100, or sea-level rise at some time beyond 2100, depending on the climate scenario. Under present-day sea-level conditions, Tuktoyaktuk is exposed to wide-scale storm surge-driven flooding with potentially destructive momentum fluxes for return periods of 50 years and longer (AEPs ≤ 2%). As sea levels continue to rise, Tuktoyaktuk faces increasingly frequent exposure to storm surge-driven flood hazards, and more severe hazards.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.827

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.305
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes3
Has abstractyes

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