A tidal resource assessment dataset for the Quatsino Sound region, British Columbia, was developed, including temporal maximum, mean, and minimum velocity magnitudes, standard deviations, and power density. The dataset was generated using a high-resolution 2D depth-averaged hydrodynamic model based on the Telemac-Mascaret solver, with Natural Neighbor interpolation applied for raster creation. This newly published dataset is the first in a series of regional tidal energy maps for Canada. Developed by CanmetENERGY Ottawa in collaboration with partners, these maps aim to support effective project planning and development by providing comprehensive tidal resource data across the country.
Disclaimer:
Potential errors in the model results may arise from inherent limitations in the topo-bathymetric data accuracy, assumptions in boundary conditions, approximations within the numerical methods, and the input data used in the numerical modeling. These factors introduce uncertainties that can affect the overall model outcomes. The model is subject to the following conditions:
• Topo-bathymetric data: Obtained from electronic navigational charts and the Canadian Hydrographic Service’s (CHS) NONNA-10 Bathymetric Data packages, consolidating CHS-managed digital bathymetric sources with a maximum resolution of 10 m.
• Tidal and current harmonic components: Used as boundary conditions from the TPXO9 global tidal model.
• Model calibration and validation: Performed using data from Acoustic Doppler Current Profilers (ADCP), surface elevations recorded at CHS tidal stations, and Lagrangian drifter measurements.
• Interpolation method: Dataset outputs were generated with Natural Neighbor interpolation, which assumes smoothly varying data and may not capture sharp local gradients or features.
• Modeled estimates: All values for velocity magnitudes, velocity standard deviations, and power density are modeled estimates and not direct field measurements.
This dataset is intended for preliminary assessment of tidal projects only. It should not be the sole basis for making critical decisions or investments. We strongly recommend further validation and in-depth analysis. Users are responsible for conducting their own due diligence and additional research to verify the data's accuracy and relevance for specific applications.
By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.