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Upscaling Fill-and-Spill Hydrologic Processes

2023· dissertation· en· W7072066516 sur OpenAlex

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Notice bibliographique

RevueUWSpace (University of Waterloo) · 2023
Typedissertation
Langueen
DomaineComputer Science
ThématiqueQR Code Applications and Technologies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWetlandSurface runoffSnowmeltProbabilistic logicHydrology (agriculture)Hydrological modellingStructural basinStatistical modelBoreal
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Low-gradient landscapes found in parts of the Taiga Plains and the North American Prairies can be dominated by many depressional wetlands with variable storage capacity. Runoff from these regions is influenced by the local storage capacity of individual wetlands and water exchange between the wetlands. Fill-and-spill conceptual models have been proposed to consider the connectivity-controlled process in wetland dominated catchments. Although fill-and-spill phenomenon has been locally observed, few studies examine the response of a landscape to thousands of cascading wetlands, as is seen in a number of Canadian landscapes. Being able to characterize, understand, and parameterize this response in hydrological models may enable successful simulation of the contribution area and runoff response in wetland-dominated regions. Current probabilistic fill-and-spill models consider individual features rather than the cumulative connections between adjacent wetlands in a cascade. The lack of understanding of the regional effects of wetland distributional characteristics on landscape hydrology, combined with insufficiently resolved elevation data, particularly in flat terrains, are two concerns that signify the need for an improved probabilistic runoff model. We propose an upscaled wetland fill-and-spill (UWFS) algorithm to investigate the response of large-scale wetland systems in low gradient areas to rainfall or snowmelt events. The research addressed in this thesis consists of the following:
\n
\n1. An explicit probabilistic-analytic model is developed and tested for cascades of wetlands, providing an upscaling approach to understand and characterize system responses. To do this, first, a probabilistic analytic model is developed based on the
\nfill-and-spill conceptualization, which considers each wetland in the basin as a member of an ensemble. The mathematical solution requires information about the initial deficit distribution and distribution of wetland local contributing areas which may be
\nestimated via a combination of spatial analysis and field observation. Then, by using the derived distribution approach, the response of a landscape with a single wetland cascade is upscaled to the response of a landscape with thousands of wetlands.
\nThis event model is extended to evaluate the continuous response of a heterogeneous wetland complex to rainfall and snowmelt events by evolving the deficit distribution based on evaporation and precipitation.
\n2. A Monte Carlo based approach is proposed here that samples from initial deficit and concentrating factor distributions and finds the generated runoff from water balance equation applied to wetland cascade networks. This model along with the analytical model enables us to explore the impacts of network depth, branching, and gatekeeping on fill-and-spill runoff responses from complex wetland networks. The accuracy of the probabilistic analytical solution is also assessed by comparing the results with those from the Monte Carlo approach.
\n3. The proposed probabilistic analytical runoff model has been implemented into an existing two-dimensional semi-distributed hydrologic model, Raven, to test the ability of the upscaling method in lumped runoff simulation of wetland-dominated basins
\ninfluenced by fill-and-spill hydrology. The model has been tested at 10 subbasins inside the Qu’Appelle River Basin in Prairie and the simulation results has been compared to an existing Prairie model named HYdrological model for Prairie Region
\n(HYPR).
\n4. The proposed UWFS algorithm has been applied to a discontinuous permafrost region, Scotty Creek basin in the Northwest Territories, to simulate runoff generation from secondary runoff areas (the wetlands not directly connected to the fen network).
\nThe streamflow responses to different landcover transitions and meteorological forcings from different climate change scenarios are applied to quantify the effects of lateral permafrost thaw on the hydrological response of the study basin.
\n
\nThe UWFS algorithm is applied to improve our understanding of the effects of distribution characteristics, network branching, wetland deficit conditions, and cascade depth upon the contributing area and effective runoff from heterogeneous wetland-dominated basins. We can use the proposed model to understand potential long-term hydrological impacts of climate change located in regions where climate warming changes the role of wetlands from storage features to water conveyors.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,345
Score d'incertitude au seuil0,707

Scores Codex et Gemma par catégorie

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

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 Opus0,013
Tête enseignante GPT0,206
Écart entre enseignants0,193 · 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