Uncertainty sources in flood projections over contrasting hydrometeorological regimes
Why this work is in the frame
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Bibliographic record
Abstract
This study evaluates the uncertainty of four components of the hydroclimatic modelling chain on flood projections over 96 basins covering contrasting hydrometeorological regimes located in Canada and Mexico. Two ensembles of climate simulations are considered, a large ensemble of 22 global climate model simulations and a smaller ensemble of three high-resolution regional climate model simulations. The other components are two post-processing techniques, three lumped hydrological models and six probability distributions. These four sources are assessed through a method of variance decomposition applied to six flood indicators over a reference period and two future periods: 1976–2005, 2041–2070 and 2070–2099. Systematic differences are observed between basins with contrasting flood-generating processes. Snow-dominated basins consistently show larger variance contributions from hydrological models, while rain-dominated basins show climate simulations as their dominant source. These results underline the need to consider the variability of each component’s uncertainty contribution and its link to hydroclimatic conditions and dominant processes.
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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 | 0.003 | 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 | 0.003 | 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) | 0.010 | 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 it