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Enregistrement W7014615412

From processes to predictions in hydrological modelling of glacierized basins

2022· dissertation· en· W7014615412 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Langueen
DomaineEarth and Planetary Sciences
ThématiqueCryospheric studies and observations
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésStreamflowGlacierClimate changeSnowDrainage basinHydrological modellingWater resourcesFlood forecasting
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Glacierized mountain headwaters act as water towers, providing critical water resources to downstream environments when other sources are unavailable. These headwaters are currently witnessing a shift in their coupled hydrological and glaciological systems. This shift is reducing glacier volume, extent and elevation range, in addition to changing the snow dynamics across both glacierized and non-glacierized areas. These interconnected changes occur simultaneously, driven by complex physical feedbacks, and they impact streamflow generation processes. To properly characterize this transition period and predict future hydrological behaviour in these glacierized basins, physically based glacio-hydrological models representing the full range of both glacier and basin hydrological processes are needed. However, obtaining the data to apply such modelling approaches is complicated by the scarce data availability in mountain regions. New approaches to collect the required data and parametrize these complex processes need to be developed in parallel with increased process representations in glacio-hydrological models. This thesis aims to assess the impact of future climate and glacier change on glacierized basin hydrological processes and streamflow generation. Its specific objectives are to (1) develop and apply innovative approaches to characterize hydro-glaciological processes in glacierized basins, (2) diagnose hydrological and glaciological processes resulting in streamflow generation and variability and (3) assess the coupled impacts of climate and landscape change on the hydrological processes and streamflow generation in a glacierized basin. Field-based investigations of streamflow measurement uncertainty, sub-debris melt and surface energy balance were conducted and used to guide new and revised algorithms for the Cold Region Hydrological Modelling (CRHM) platform. Using CRHM with the newly added process representations for katabatic wind turbulent transfer, hourly energy balance and sub-debris melt, a physically based glacio-hydrological model was developed and tested in the Peyto Glacier Research Basin, a 53% glacierized headwater basin (as of 2013) located in the Canadian Rockies. This glacio-hydrological model was used to investigate the recent past and current (1990-2020) hydrology of the basin using in-situ weather observations. Over the 32 years, strong inter-annual variability in the meteorological forcings caused highly variable streamflow in this cold alpine basin. Snowmelt always provided the largest fraction of annual streamflow (44 to 89%), with lower snowmelt contributions occurring in high streamflow years. Ice melt provided between 10 to 45% of total streamflow, with a higher contribution associated with high flow years. Both rainfall-runoff and firn melt contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43˚C warmer than low streamflow years, and high streamflow years had lower winter snow accumulation, earlier snowmelt and higher summer rain than years with low streamflow. The glacier hydrology of current (2000-2015) and future periods (2085-2100) was compared, using bias-corrected, dynamically downscaled, convection-permitting high-resolution atmospheric model outputs. The simulations show that the end-of-century increase in precipitation, mainly expressed as an increase in rainfall at the expense of snowfall, will nearly compensate for the decreased ice melt associated with almost complete deglaciation, resulting in a decrease of 7% in annual streamflow. However, the timing of streamflow will advance substantially, with the timing of peak flow shifting from July to June, and August streamflow dropping by 68%. To examine the sensitivity of future hydrology to possible future post-glacial landscapes, the end-of-century simulations were run under a range of boundary conditions and were most sensitive to initial ice volume and surface water storage. This research provides better modelling techniques to represent the complex systems of headwater glacierized basins, as well as robust estimates of future glacier contributions to streamflow in reference basins of the Canadian Rockies and should be useful for water availability studies and water management mitigation strategies.

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)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,016
Tête enseignante GPT0,169
Écart entre enseignants0,154 · 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'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

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
Publié2022
Routes d'admission1
Résumé présentoui

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