Assessment of the impact of climate change on Fraser River low flows
Bibliographic record
Abstract
During the winter season, rivers in cold regions typically carry low discharges. Long-term forecast of river low flows is of practical importance. For example, authorities need the forecast to decide on water resources allocations and permits of the maximum allowable waste-effluent discharges from the land-based industry into a receiving river. Low river flows have important implications for river water quality and the health of aquatic life. Previously, there have been many investigations of the influence of climate change on river discharge, both low and high flows. Some studies of the Fraser River in British Columbia, Canada, dealt with the influence of climate change on flow and water temperatures. However, there is a lack of studies that consider the impact on low river flows under climate change scenarios. This study aims at improving the understanding of the impact of rising temperatures due to climate change on the low flows of the Fraser River. Specially, this study will reveal how the magnitudes of historic Fraser River low flows are related to freezing temperatures and will answer the question of to what extent low flows will change in response to projected changes in atmospheric temperature. The scope of work includes statistical analyses of the correlation between historic observations of Fraser River flows and watershed air temperatures over a time period of more than 100 years. The temperature data input is derived based on averaging values from 52 stations in the Fraser River basin. The variations in flow discharge with varying temperatures show uncertainties over the years. This study considers the cumulative freezing and thawing effects of fluctuating temperatures and divides the observed winter low flows into a lower limb and an upper limb. The correlation between discharge, Q, and temperature is established on the basis of the lower limb, yielding Q as a function of cumulative temperature, , in terms of z scores of the two variables. Global land and ocean surface temperature anomalies in the historical data are noted in several of the historic years, but their influence is removed while establishing this Q- relationship. A confidence bound relationship between flow and temperature is established for the thawing days, where the flow increases from its lowest value. The Q- relationship is further applied for forecast of future low flows, with input of temperatures from six Global Climate models (GCMs) with Representative Concentration Pathways (RCPs) 4.5 & 8.5 of the NASA Earth Exchange Global Daily Downscaled Projections (NEX GDDP) dataset. Long term forecast of river low flows is obtained. The results show an increase in the minimum flow discharge up to 48% under high emission scenarios by the end of the 21st century. Under low emission scenarios, the minimum flow discharge can increase by 11%. The methods developed in this study can be applied to other cold region rivers. This is useful for addressing the issue of climate change impacts on river low flows, making necessary adjustments to the hydraulic design of water resources infrastructures, and planning the protection of aquatic life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".