Scaling and regionalization of flood flows in British Columbia, Canada
Bibliographic record
Abstract
Abstract A regionalization of flood data in British Columbia reveals a common scaling with drainage area over the range 0·5×102<Ad<104 km2. This scaling is not a function of flood return period, which implies that simple scaling—consistent with a snowmelt‐dominated flow regime—applies to the province. The observed scale relation takes the form $Q \propto A_{d}^{0{\cdot}75}$ , similar to values reported in previous studies. The scaling relation identified was used to define the regional pattern of hydroclimatic variability for flood flows in British Columbia after discounting the effect of drainage area. The pattern was determined by kriging a scale‐independent runoff factor k for the mean annual flood, 5 year flood and 20 year flood. The analysis permits quantification of uncertainty of the estimates, which can be used in conjunction with the mapped k‐fields to calculate a mean and range for floods with the identified return period for ungauged basins. Owing to the sparsity of data, the precision is relatively poor. The standard error is generally less than 75% of the estimate in the southern half of the province, whereas in the northern half it is often between 75 and 100%. Examination of the relative increase in flood magnitude with increasing return period reveals spatially consistent but statistically insignificant differences. Flood magnitude tends to increase more rapidly in the western regions, where rain events may contribute to flood generation. The relative increase in flood magnitude with return period is consistently lower in the eastern mountain ranges, where snowmelt dominates the flood flow regime. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".