Using stable water isotopes to partition source water contribution and assess spatio-temporal source water dynamics of wetlands ecosystems in the eastern Canadian Rocky Mountains
Notice bibliographique
Résumé
Subalpine and montane regions of the Canadian Rocky Mountains are expected to experience continued changes in hydrometeorological processes due to anthropogenically-tied climate warming. These regions are important in regulating the global water balance since they contribute a significant amount to annual surface runoff. The major river networks sustained by these catchments provide water to a large portion of people in western Canada and parts of the United States. In such environments, wetlands are important elements of mountain hydrologic systems because of their ability to regulate flow by contributing water to downstream sources. However, these ecosystems are potentially sensitive to changing hydrometeorological conditions and it is not clear how climate trends will affect source water composition. Therefore, an understanding of the contribution of subalpine and montane wetlands to downstream water bodies, and their controlling climatic factors, across space and time remains a major gap in mountain hydrological research. \nThis thesis addresses these research gaps by using stable water isotope (δ2H and δ18O) techniques to partition source waters from a subalpine wetland to downstream water bodies and assess evaporative fluxes in wetland surface waters across spatial and temporal scales. Since different source waters have distinguishable isotopic signatures, they can be used in combination with knowledge of climate patterns and landscape characteristics to trace spatiotemporal water movement over catchment and regional scales. Source waters (e.g. rain, snow, groundwater, stream, and surface waters) were sampled and analyzed during the 2018, 2019, and 2020 growing seasons, then combined with historic data from 2012, to determine the relative contribution of wetland source waters to downstream water bodies and determine the influence of evaporative fluxes on wetland surface waters. \n\tOverall, the composition of downstream surface waters followed seasonal patterns and indicated periods of heavy source water mixing. There was strong seasonal dependence on snow meltwater, rainfall, and presumably, glacial meltwater during the pre-, peak, and post- growing seasons, respectively. Snowmelt inputs during the pre- growing season recharged groundwater stores and promoted downstream flow. Transitioning to the peak- growing season, the Burstall Valley relied heavily on rainfall to sustain saturation levels and generate runoff. Finally, inputs from glacial meltwater trigged rapid streamflow during the post- growing season resulting in a greater proportion of downstream surface waters originating from the Burstall Streams. There was minimal evaporation from Burstall Wetland throughout the growing season as seasonal source waters replaced waters stored within the landscape. However, this was not the case at extensive sites. Instead, evaporation fluxes followed a strong spatiotemporal gradient with stronger d-excess signals at lower elevations during the late summer, indicating greater surface water storage capacity. These results indicate that under certain climate conditions (e.g. drought, warmer temperatures), subalpine and montane wetlands may experience increased water loss or dry out during the late summer months if snowmelt continues to occur earlier in the year prolonging the growing season.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 ».