Integrated modeling of groundwater–surface water interactions in a tile‐drained agricultural field: The importance of directly measured flow route contributions
Bibliographic record
Abstract
Understanding the dynamics of groundwater–surface water interaction is needed to evaluate and simulate water and solute transport in catchments. However, direct measurements of the contributions of different flow routes from specific surfaces within a catchment toward the surface water are rarely available. For this study, we physically separated the tile drain discharge toward a 43.5 m ditch transect from the groundwater–plus–overland flow routes. Direct groundwater flow and ephemeral overland flow were jointly captured in three sheet pile in‐stream reservoirs, while the effluent from three tile drain outlets was collected in vessels. Our flux measurements showed that, in response to a rainfall event, the tile drain contribution to the total ditch discharge decreased from 80% to 28%. We used these flow route measurements to calibrate a field‐scale integrated water transport model. The HydroGeoSphere code was used because it simultaneously solves the flow regimes in the variably saturated domain, the tile drain domain, and the surface flow domain. This simultaneous solution is needed for a correct representation of the mutual interactions between groundwater flow, tile drain flow, and ditch water flow. Our model produced a flow distribution between the flow paths which deviated only 2% from the measured flow distribution. A sensitivity analysis showed that model parameters related to tile drain entrance resistance and to the resistance to water flow through the surface water system controlled the water flow route distribution but with little effect on groundwater levels. This indicates that a model calibration based on groundwater levels alone does not necessarily produce a correct representation of the flow route contributions.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".