High-resolution mapping of river hydrokinetic energy resources in Canada using remote sensing.

Saved in:
Bibliographic Details
Title: High-resolution mapping of river hydrokinetic energy resources in Canada using remote sensing.
Authors: Kirby, Katelyn1,2 (AUTHOR) kkirb087@uottawa.ca, Ferguson, Sean2 (AUTHOR), Rennie, Colin D.1 (AUTHOR), Cousineau, Julien2 (AUTHOR), Burcher, Richard2 (AUTHOR), Nistor, Ioan1 (AUTHOR)
Source: Renewable Energy: An International Journal. Jan2026:Part B, Vol. 256, pN.PAG-N.PAG. 1p.
Subject Terms: *Renewable energy sources, *Electric power production, *Streamflow, *Sustainability, Databases, Remote sensing
Geographic Terms: Canada
Abstract: Many remote and northern communities rely on imported diesel for electricity, facing high costs, logistical challenges, and environmental risks. River hydrokinetic energy (HKE), which generates electricity from flowing water without dams unlike conventional hydropower, offers a lower-impact, locally available renewable alternative. However, identifying promising HKE sites typically requires extensive and costly field data collection, creating a barrier for development. To address this gap, the authors present the first national, high-resolution database of river HKE across Canada, covering all river segments with flows exceeding 100 m3/s. The database includes cross-sectional measurements and estimates of flow, depth, width, velocity, and power at up to 100-m intervals, allowing communities and developers to identify areas with strong local energy potential before committing to field investigations. Validation against field and modelled data confirmed good agreement, supporting its reliability for preliminary site screening and policy planning. By capturing energy-enhancing river features such as lateral constrictions and steep gradients, this dataset provides a valuable tool for accelerating the transition from diesel-based electricity to renewable HKE, particularly in remote and rural communities. [ABSTRACT FROM AUTHOR]
Copyright of Renewable Energy: An International Journal is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: GreenFILE
Description
Abstract:Many remote and northern communities rely on imported diesel for electricity, facing high costs, logistical challenges, and environmental risks. River hydrokinetic energy (HKE), which generates electricity from flowing water without dams unlike conventional hydropower, offers a lower-impact, locally available renewable alternative. However, identifying promising HKE sites typically requires extensive and costly field data collection, creating a barrier for development. To address this gap, the authors present the first national, high-resolution database of river HKE across Canada, covering all river segments with flows exceeding 100 m3/s. The database includes cross-sectional measurements and estimates of flow, depth, width, velocity, and power at up to 100-m intervals, allowing communities and developers to identify areas with strong local energy potential before committing to field investigations. Validation against field and modelled data confirmed good agreement, supporting its reliability for preliminary site screening and policy planning. By capturing energy-enhancing river features such as lateral constrictions and steep gradients, this dataset provides a valuable tool for accelerating the transition from diesel-based electricity to renewable HKE, particularly in remote and rural communities. [ABSTRACT FROM AUTHOR]
ISSN:09601481
DOI:10.1016/j.renene.2025.123970