Assessment of the Influence of Nonstationary Climate on Extreme Hydrology of Southwestern Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".