Modelling integrated extreme hydrology
Bibliographic record
Abstract
The present research is concerned with some numerical developments and practical application of a physically based numerical model FreshWaterSheds that incorporates a finite element solution to the steady/transient problems of the joint ground/surface fresh/salt water flows in inland and coastal regulated watersheds.The proposed model considers surface and groundwater interactions to be 2-D horizontally distributed and depth-averaged through a diffusive wave approach.Infiltration rates, overland flows and evapotranspiration processes are considered by diffuse discharge from surface water, unsaturated subsoil and groundwater table.New improvements also allow for the management of surface water flow control through the capacity of diversion on flooding zones of catchment areas, as well as on river beds, spillways and outflow operations of floodgates in weirs and dams of reservoirs.Practical application regards the flooding hazard of Aznalcóllar toxic spillages.This flooding disaster was caused by the sequential ruptures of the dikes of two mining residual reservoirs of a pyrite mine, releasing about 10•10 6 m 3 of contaminated wastewater and mining sludge onto the Guadiamar River.The numerical model was adapted to the wastewater and sludge properties of both sudden spillages, as well as to the river bed, the flooded zones and the underneath alluvial aquifer.The model simulation and calibration were made during the date of this hydrological hazard to the likely discharges and dual hydrograph produced by the sudden twofold failure of both reservoirs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".