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Record W7077312394

Numerical Modeling of Channelization Impacts on Hydrodynamic and Floods:Case of Okanagan River

2025· other· fr· W7077312394 on OpenAlexaboutno aff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2025
Typeother
Languagefr
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsNumerical modelingHydrology (agriculture)Numerical modelsWestern europe
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: «La linéarisation des rivières est une pratique courante d’aménagement des cours d’eau qui consiste à retirer artificiellement les courbes naturelles d’une rivière, ce qui entraîne une diminution de sa sinuosité. Bien que ces activités anthropiques aient offert certains avantages, une inquiétude croissante émerge quant aux impacts potentiellement négatifs sur l’hydrodynamique, la géomorphologie et l’environnement des systèmes fluviaux. Cependant, notre compréhension du lien entre le redressement des rivières et ces conséquences, ainsi que la quantification précise de ces impacts, reste limitée. Cela souligne la nécessité de recherches approfondies sur les effets du redressement des rivières. Cette recherche étudie et quantifie numériquement l’impact du redressement des rivières sur l’hydrodynamique des flux et les conditions d’inondation. Elle repose sur un modèle hydrodynamique bidimensionnel (2D) à profondeur moyenne appliqué à divers scénarios de flux avec et sans linéarisation de la rivière. L’étude de cas concerne le cours d’eau redressé de la zone Oliver de la rivière Okanagan en Colombie-Britannique, qui a été soumise à des inondations fréquentes ces dernières années. La méthodologie utilisée dans cette recherche met l’accent sur les conséquences directes des inondations dans les sections redressées, afin de répondre à la question de la causalité entre les récents événements d’inondation extrême et la linéarisation de la rivière. L’aspect hydrodynamique de la recherche implique la simulation des caractéristiques du flux, notamment les changements de l’étendue des plaines inondables et les risques d’inondation. En quantifiant les réponses du comportement de la rivière à la linéarisation, les résultats confirment les impacts négatifs de la linéarisation à long terme sur les aspects hydrodynamiques, les modèles de flux et l’étendue des plaines inondables. Le modèle pré-linéarisation a montré une plus grande stabilité, avec moins de variations prononcées de la vitesse et des niveaux d’eau comparativement au modèle post-linéarisation sous les mêmes conditions hydrologiques, pour les sections en amont et en aval du cours d’eau de la zone Oliver. Bien que l’efficacité de la linéarisation des rivières pour le contrôle des inondations ait été confirmée par un avantage temporaire et localisé au milieu du cours d’eau redressé près de la zone urbaine. Cette analyse souligne les défis hydrodynamiques et de risque d’inondation posés par la linéarisation des rivières, mettant en évidence l’importance d’une évaluation minutieuse des processus d’ingénierie fluviale.» ABSTRACT: «Channelization is a common river engineering practice that involves artificially removing the natural meandering bends of a river, resulting in a decrease in sinuosity. Although these anthropogenic activities have offered certain benefits, there is a growing concern about the potential negative impacts on hydrodynamics, geomorphology, and the environment of river systems. However, our understanding of the connection between river straightening and these consequences, as well as the precise quantification of these impacts. This underscores the need for comprehensive research on the impacts of river straightening. This research numerically studies and quantifies the impact of river straightening on the flow hydrodynamics and flooding condition. It is based on a two-dimensional (2D) depth-average hydrodynamic model applied to flow various scenarios with and without river channelization. The case study is the channelized Oliver stream of the Okanagan River in British Columbia which has been subject to frequent floods recent years. The methodology applied in this research emphasizes direct flood consequences in straightened sections and further downstream to answer the question of causality between recent extreme flood events and river channelization. The Hydrodynamic aspect of the research involves the simulation of flow characteristics including changes in floodplain, flood extent, and flood risk. By quantifying the responses of river behavior to channelized river, the results confirme the negative impacts of channelization on long-term to hydrodynamic aspects, flow patterns and floodplain extends. The pre-channelization model demonstrated greater stability, with less pronounced variations in velocity and water levels compared to the post-channelization model under the same hydrological conditions, for both upstream and dowstream locations of the Oliver stream. While, a temporary and localized benefit of channelization was clear in the middle of the stream near urban area for water levels confirming the effectiveness of channelization for flood control. This analysis underscores the hydrodynamic and flood risk challenges posed by channelization, emphasizing the importance of careful evaluation in river engineering processes.»

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 score0.899
Threshold uncertainty score0.200

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 communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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