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Enregistrement W7133286747

Science Response : risk to fish from VLH turbine installations

2024· other· en· W7133286747 sur OpenAlexaboutno aff
Fisheries and Oceans Canada, Pêches et Océans Canada

Notice bibliographique

RevueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTurbineHydroelectricityFlushingFish <Actinopterygii>Entrainment (biomusicology)Hydro powerDownstream (manufacturing)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

One of the most significant concerns with hydroelectric power production is injury and mortality of fish passing through turbines during intentional or unintentional downstream passage (Algera et al. 2020). There are several mechanisms by which fish can become injured or killed as a result of passage (entrainment) through turbines as summarized by Čada (2001), including rapid and extreme pressure changes, cavitation, sheer stress, collision, turbulence, and grinding. As a result, developers have been working for decades to create ‘fish friendly’ turbines that incorporate features to make them less hazardous to entrained fish (Fraser et al. 2007, Foust et al. 2011, Romero-Gomez et al. 2022, Watson et al. 2022). To determine whether a turbine is indeed ‘fish friendly’, not only does mortality rate need to be quantified, but sublethal effects must also be considered (Ferguson et al. 2006). Many current hydro entrainment mortality monitoring plans typically involve periodically walking downstream of the turbine to observe and record dead fish; this level of monitoring likely does not yield reliable information as to the risk to fish. Increasingly, other methods of monitoring entrainment mortality are being employed, including fish flushing trials and modelling to estimate the death of fish from entrainment, but to date there are no standard or consistent methods considered as ‘best practices’. Several novel turbine technologies (Quaranta et al. 2022) are being proposed at new and existing infrastructure (weirs, non-power dams), which still need to be assessed for their ‘fish friendliness’ (Cooke et al. 2011) and Canadian application (NRCan 2018). Low head (< 15 m) dams are being explored as viable hydropower options, which could add between 5-10 GW of power (Tung et al. 2007, or about 10% of Canada’s 82.3 GW of installed capacity, IHA 2022) to Canada’s total energy generation capacity. The Very Low Head (VLH) turbine, developed by MJ2 Technologies, is a unique, cost-effective class of turbines designed to address a head of 1.4-4.5 m, discharge of 10-30 m3/s and up to 500 kW of capacity (Fraser et al. 2007, Quaranta et al. 2022). The standard configuration consists of 8 Kaplan-style adjustable runner blades and 18 fixed guide veins, with a diameter of 0.6-5.6 m. The VLH turbine design incorporates several features designed to minimize impact to fish including: • using a large runner diameter (which allows for low velocity and negates the need for a draft tube), • minimizing velocity and pressure gradients, • minimizing the tip gap and the number of blades, and • ensuring the shape of the Kaplan style runner blades is blunt (Fraser et al. 2007). A VLH turbine that was installed in 2015 at Wasdell Falls on the Severn River, ON, provided a unique site for the first study of this new technology in Canada. The VLH installation on the Severn River was supported by NRCan as a demonstration site to represent a clean and reliable low-impact source of electricity. VLH technology allows for significant cost savings related to civil works due to its modularity concept, making the development of VLH hydro resources economically feasible, yet it is important that testing was conducted in Canada to determine if this technology can indeed be considered ‘fish friendly’ for Canadian taxa and systems. Using acoustic telemetry, live fish passage, and sensors designed to record the conditions experienced by fish as they pass through turbines, this research aimed to provide a direct quantification of the risk of entrainment, injury, and immediate or delayed mortality to fish resulting from the VLH turbine installation at Wasdell Falls. Since the Wadell Falls installation was at the site of an existing dam, this research was designed to specifically quantify the increased risk to fish from the installation of the turbine at an existing barrier, not to assess the full impacts of the presence of the dam itself. The risk of entrainment to resident fish upstream of the VLH was estimated by measuring the rate of entrainment of tagged fish via acoustic telemetry. Live fish, representative of the local fish community, were flushed through a VLH turbine to estimate expected injury and mortality rates for resident fish that pass through the VLH turbines. Together, the likelihood of entrainment and risk of injury or mortality from turbine passage can be used to provide an estimate of the overall risk to the fish upstream of the VLH. In addition to live fish passage, electronic sensors were passed through the VLH turbine to provide quantitative information on the physical conditions experienced by fish during passage, some of which may not have presented as obvious injuries during the live fish trials. The results presented in this Science Response Report are intended to provide direct quantification of risk from VLH turbines to Fisheries and Oceans Canada (DFO)’s Fish and Fish Habitat Protection Program (FFHPP). Specifically, the objectives are as follows: 1. To determine the overall risk to the resident fish community from the VLH turbine installation at Wasdell Falls; 2. To determine the level and type of monitoring required at future installations; and, 3. Identify uncertainties and knowledge gaps, and if necessary, recommend additional information, research, monitoring, data collection, etc. that is required to further assess the potential impacts of VLH turbine installations on Canadian fish communities. This Science Response Report results from the regional peer review of December 5-6, 2023, for the Risk to Fish from Very Low Head Turbine Installations.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,995
Score d'incertitude au seuil0,105

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,001
Science ouverte0,0010,003
Intégrité de la recherche0,0050,003
Charge utile insuffisante (le modèle a refusé de juger)0,0320,007

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,243
Écart entre enseignants0,235 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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