Assessing the influence of calibration methodology and model structure on glacio-hydrological simulations in the Cheakamus River Basin, British Columbia, Canada
Bibliographic record
Abstract
As glaciers across the world continue to recede, there is a concern that their loss as a fresh water reservoir within mountainous basins will have a negative impact on stream temperatures and downstream water resources. Currently, there are relatively few glacio-hydrological models (GHMs) appropriate to study such phenomena and studies that have used GHMs generally acknowledge the high uncertainty associated with their simulations. Calibration techniques present a particular issue in GHMs as available glacier observations are limited and errors in the glacierized portion of a basin can be compensated by errors in the non-glacierized portion. Using as a study site the Cheakamus Basin in British Columbia, Canada, we 1) present a new, fully-coupled GHM, 2) analyze the effects different calibration techniques have on the model’s summer streamflow projections, and 3) compare the fully-coupled GHM results to projections using a one-way GHM. The calibration techniques studied vary in terms of glacier representation (dynamic/static), and glacier constraint (mass balance/thinning rates/thinning rates and area change). We find projected future climate forcings are sufficiently strong in the Cheakamus Basin so as to generally make the sign and significance of changes to the basin’s hydrology insensitive to the calibration and projection procedures studied. However, the variation among these procedures produces significant changes in the projected magnitude of future hydrological changes and therefore should be carefully considered in studies where precision beyond the sign and significance of change is required. Based on analysis of the variation within each procedure’s set of model outputs, we conclude 1) the two-way GHM has benefits over the one-way model, 2) calibration using dynamic glaciers and a thinning rate constraint is preferable for the new GHM, and 3) there is a need for additional studies on the uncertainties associated with the calibration of glacio-hydrological models.
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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 | 0.001 | 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".