Rainfall-flow Modeling Using a Global Conceptual Model: Case of the Beni Bahdel Watershed (Northwest of Algeria)
Bibliographic record
Abstract
Rainfall-flow modeling remains necessary, even essential, to understand the dynamics of a watershed and to solve problems related to the disruption of hydrological regimes. It has been proven effective by providing solutions to many water-related problems, such as sizing and management of structures, and flood forecasting. Global hydrological models can simulate the transformation of rainfall data into flows on natural basins for many practical applications in the field of water resource management. Our study aims to evaluate the reliability of one of these models, that of Rural Engineering 'GR' at three time steps: annual (GR1A), monthly (GR2M), and daily (GR4J), which will be applied to the Beni Bahdel watershed with an area of 1040 km², one of the sub-basins of Northwestern Algeria. The input parameters are precipitation and potential evapotranspiration (PET), and the output parameters are flows. The results obtained, both in calibration and validations, are encouraging, where the evaluation criteria taken into consideration, namely the Nash criterion and the correlation coefficient, exceeded 70% and 0.80 respectively. The study could be a decision-making tool for the simulation of flows, and be very useful for future hydraulic developments in the study area.
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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 | 0.001 | 0.001 |
| 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".