River system classifications and cumulative watershed perspectives to inform sustainable river basin management at global and regional scales
Notice bibliographique
Résumé
At present, humans appropriate more than half of the Earth's renewable and accessible water. This high demand for water resources comes at a cost: it puts an estimated 65% of global river discharge under moderate to high threat from anthropogenic drivers of stress. One way to alleviate some of this pressure is to develop and apply sustainable management practices to human activities that affect river systems. To develop best managements practices in this context require methods, data and scientific information that are specific to river systems. Given the interconnectedness of rivers over large spatial extents, sustainable management strategies need to be designed for basin, regional, or even global scales. Sustainable management is multifaceted and often requires drawing information from various disciplines. To advance the sustainable management of large river systems, we need information and data related to different research themes, and we need specific methods that reflect the connected and cumulative nature of river systems. In this thesis, I explore novel data and methods to advance three particular research themes that are closely related to sustainable river management, namely the natural flow regime paradigm, the representation of aquatic biodiversity through proxies, and the concept of hydrologic ecosystem services. I develop one global and three large-scale studies, each representing different contributions, including new data and methods, to the three themes. As an overarching approach to provide and analyze new baseline information, I first develop a multidisciplinary approach to river classification and use it to design a novel river reach typology at the global scale. I then explore this framework for river classifications at two regional scales, where I evaluate river classes (1) as a potential contribution to natural and environmental flow assessments in Canada, and (2) as proxies for fish assemblages in the Greater Mekong Region. Finally, in Canada, I quantify capacity for, demand for, and pressure from freshwater provision and regulation based on hydrological connectivity, and I design a composite indicator of risk to the provision of this hydrologic ecosystem service. The resulting river reach classifications at the global scale, in Canada, and in the Greater Mekong Region provide typologies that can facilitate freshwater conservation efforts and environmental assessments. They also provide a new avenue to support the integration of environmental flow requirements and fish assemblages in large-scale river management. The novel hydrological method to quantify freshwater ecosystem services can be used to design new, large-scale assessments of ecosystem services around the world that account for the connected and cumulative nature of river systems. This quantification also presents a first-time high-resolution mapping of the risk to freshwater provision and regulation in Canada. My conclusions discuss overarching findings from the thesis, including the importance of innovative statistical approaches,…
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,002 | 0,008 |
| Communication savante | 0,008 | 0,017 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».