Assessment of the Influence of Nonstationary Climate on Extreme Hydrology of Southwestern Canada
Notice bibliographique
Résumé
The demand for water supplies across southwestern Canada has increased substantially over the past century with growing population and economic activities. At the same time, the region’s resilience to the impacts of hydrological extremes, floods and droughts is challenged by the increasing frequency of these extreme events. In addition, increased winter temperatures over the past century have led to declines in winter snowpack and caused earlier snowmelt, leading in some years to a substantial shortage of water during late summer and fall seasons. This calls for a better understanding of the flood and drought characteristics in addition to the information on water availability for effective water management and to design infrastructure resilient to such extreme conditions. The objective of this thesis is to examine the spatial and temporal variability of available water in the naturally flowing watersheds of southwestern Canada and evaluate various regional hydroclimatic and large-scale climatic indices in representing the regional hydrology and hydrological extremes. To do so, I first examined the empirical relationships between historically observed streamflow in 24 naturally flowing watersheds across southwestern Canada and the associated watershed’s hydroclimate, represented by the watershed averaged Standardised Precipitation Evapotranspiration Index (SPEI). The hydroclimate of all the selected watersheds is assumed to be represented by the second version of the NRCAN gridded climate dataset. These empirical relationships indicate that the water availability can be represented by the watershed averaged SPEI. I then developed SPEI-based principle component regression (PCR) equations and found them to be very efficient in representing the variability in historically observed monthly and annual streamflow. These equations are simpler to build than calibrating a numerical hydrological model S. Gurrapu, 2020 P a g e | iii and can be applied over large areas and many sub-basins with minimal data requirements to estimate streamflow. I then analysed the annual peak flows in 119 naturally flowing watersheds and 8 regulated watersheds, but with naturalized streamflow datasets, across southwestern Canada to examine the impact of the Pacific Decadal Oscillation (PDO) on annual flood risk. Using Spearman’s rank correlation ρ and permutation tests on quantile-quantile plots, I found that higher magnitude floods are more likely during the negative phase of the PDO than during the positive phase. In addition, the flood frequency analysis (FFA) stratified according to PDO phase suggests that higher magnitude floods may also occur more frequently during the negative PDO phase than during the positive phase. These results question the validity of the stationarity assumption made in FFA and suggest that the knowledge of large-scale climate state should be considered prior to the design and construction of key infrastructure. The results indicate that the stationarity assumption is not tenable in the watersheds of southwestern Canada. To demonstrate the invalidity of the stationarity assumption, I evaluated the variability in drought characteristics, i.e. severity, duration and frequency as applied to the City of Calgary, as a case study. The drought characteristics are defined by the historic (100 years of observed) and prehistoric (900 years of stochastically generated from tree-ring reconstructions of annual streamflow) weekly streamflow datasets. The results indicate that the severity and duration of hydrological drought with the same frequency is substantially larger and longer in the prehistoric period than that observed over the historical period. The results also indicate that varying lengths of data used in determining characteristics of extreme events produce varying results, which indicate that the stationarity assumption could be deceptive. Overall, the results demonstrate the implications of the non-stationary climate. in the analysis of hydrological extremes.
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 distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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 tête enseignante, 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 ».