Application of a fully‐integrated surface‐subsurface flow model at the watershed‐scale: A case study
Bibliographic record
Abstract
Results are presented in which a physically‐based, three‐dimensional model that fully integrates surface and variably‐saturated subsurface flow processes is applied to the 75 km 2 Laurel Creek Watershed within the Grand River basin in Southern Ontario, Canada. The primary objective of this study is to gauge the model's ability to reproduce surface and subsurface hydrodynamic processes at the watershed scale. Our objective was first accomplished by calibrating the steady‐state subsurface portion of the system to 50 observation wells where hydraulic head data were available, while simultaneously matching the stream baseflow discharge. The level of agreement between the observed and computed subsurface hydraulic head values, baseflow discharge and the spatial pattern of the surface drainage network indicates that the model captures the essence of the surface‐subsurface hydraulic characteristics of the watershed. The calibrated model is then subjected to two time series of input rainfall data and the calculated discharge hydrographs are compared to the observed rainfall‐runoff responses. The calculated and observed rainfall‐runoff responses were shown to agree moderately well for both rainfall data series that were utilized. Additionally, the spatial and temporal responses of the watershed with respect to the overland flow areas contributing to streamflow and the surface‐subsurface exchange fluxes across the land surface during rainfall inundation and subsequent drainage phases demonstrate the dynamic nature of the interaction occurring between the surface and subsurface hydrologic regimes. Overall, it is concluded that it is feasible to apply a fully‐integrated, surface/variably‐saturated subsurface flow model at the watershed scale and possibly larger scales.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".