Regional Estimation of Floods for Ungauged Sites Using Partial Duration Series and Scaling Approach
Bibliographic record
Abstract
One of the main obstacles in making reliable predictions of extreme events is the apparent shortness of the time series available in hydrology. There is a common advantage of both regional flood-frequency analysis and partial duration series (PDS) in which both of them allow a reduction of uncertainty by introducing more data to the site of interest. Therefore, a new regional index flood method for ungauged sites based on the PDS model is presented. The PDS model considered in this case assumes a Poisson-distributed number of threshold exceedances and generalized Pareto-distributed peak magnitudes. A new objective approach for the selection of the threshold in the context of regionalization is introduced. This approach estimates a range of reasonable thresholds (or an average annual number of events) for every site. Consequently, the regional average annual number of events can be determined as a common value for all sites in the homogeneous region. The delineation of hydrologically homogeneous regions is determined using the scaling approach. The feasibility of the proposed method was assessed using the available daily flow series from 57 watersheds in Quebec (Canada). Furthermore, the new method is compared with two existing methods for regionalization: the region of influence and canonical correlation analysis methods. Results of the numerical application indicate that the quantile estimates obtained from the new method provide the best values of the performance criteria (e.g., root-mean-square error). Hence, the new method not only eliminates subjective decisions but also greatly improves the predicted floods for ungauged sites.
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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 | 0.000 | 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".