Effects of climate variability on hydrological processes in a Canadian Rockies headwaters catchment
Bibliographic record
Abstract
The variability of climate in mountain headwaters has an important impact on downstream water users and extreme events such as drought and flooding. Climate strongly influences hydrological processes in mountain basins, with subsequent control on streamflow generation. By studying the variability of climate and its impact on the variability of hydrological processes, the changing interaction between climate and hydrology over time can be better understood. A meteorological and streamflow data set, from 1962 to 2013, from Marmot Creek in the Kananaskis region of the Canadian Rocky Mountains was used to calculate the key hydrological processes over a period of climate variability and change. Through the use of hydrological process modelling with the Cold Regions Hydrological Modelling platform, changes to water balance components such as precipitation, evaporation, sublimation, storage, runoff, and the processes behind these changes were investigated. Observed variability among simulated hydrological processes over time was documented. Trends in hydrological processes, climate and streamflow events and their relationships to teleconnections such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) not only documented and diagnosed historical change, but provided an indication of potential future changes to these processes and the way they will interact with a future climate. Results showed an increase trend in basin temperature and precipitation, resulting in a deeper snow pack and higher runoff volumes at higher elevations. Despite these increases, streamflow generation from the basin was unaffected due to compensation by the water budget components. Increased precipitation inputs, especially at higher elevations, were counterbalanced by losses to sublimation and evapotranspiration, especially at lower elevations, resulting in a highly resilient and consistent streamflow regime throughout the study period. Correlation analysis between the PDO and ENSO and modelled annual hydrometeorological variables and water balance component values on both hydrological year (Oct-Sep) and winter (Oct-Mar) periods revealed limited significant correlations. The Mann-Whitney U (WU) test on PDO regime shift years revealed a significant correlation with evapotranspiration in the Forest Clearing Blocks. However, the PDO and ENSO showed no consistent basin-wide impact on any hydrological process or on basin scale runoff. This research increases the knowledge of mountain basin streamflow generation’s resiliency to climate change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".