How do potential evapotranspiration formulas influence hydrological projections?
Why this work is in the frame
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Bibliographic record
Abstract
This paper evaluates the sensitivity of hydrological projections to the choice of potential evapotranspiration formulas on two natural sub-catchments, in Canada and Germany. Twenty-four equations, representing a large range of options, are applied for calibration over the whole observation time series and for future conditions. The modelling chain is composed of dynamically downscaled climatic projections and a 20-member (ensemble) hydrological model, along with a snow module. The roots of the sensitivity and its propagation within the hydrological chain are evaluated to show influences on climate change impact conclusions. Results show large differences between the 24 simulated potential evapotranspiration time series. However, these discrepancies only moderately affect the calibration efficiency of hydrological models as a result of adaptation of parameters. Choice of formula influences hydrological projections and climate change conclusions for both catchments in terms of simulated and projected values, and also in the magnitude of changes during important dynamic periods such as spring and autumn high flows and summer low flows. Spread of the hydrological response is lower for the combinational formulas than for temperature-based or radiation-based equations. All the results reveal the importance of testing a large spectrum of potential evapotranspiration formulas in a decision-making context, such as water resources management.
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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 | 0.002 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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