A fully integrated groundwater-surface-water model for southern Ontario: proof-of-concept and data release
Bibliographic record
Abstract
A prototype groundwater-surface-water model for the southern Ontario Phanerozoic Basin Region has been developed with HydroGeoSphere (HGS), which provides a 3-dimensional, physics-based simulation of fully integrated groundwater - surface-water flow. To-date, the model has been tested for its ability to reproduce average monthly surface water flow rates and groundwater levels, and its sensitivity to spatial and temporal resolution. The utility of the model has been demonstrated through an assessment of groundwater extraction influences on regional groundwater levels, in order to showcase how it could be used to address water resources and hydrologic questions. The full model domain encompasses 109,565 km2, with approximately 79,000 km2 being land area and the remainder being surface water area within the Great Lakes. To facilitate the assessment of sensitivity to spatial resolution, low- and high-resolution versions of the model have been constructed, with surface water features resolved down to Strahler order 4 and Strahler order 3, respectively. The hydrostratigraphy in the model is constructed using recently released three-dimensional Paleozoic and Quaternary geological models, along with mapping that depicts depth to the base of high-sulphur content groundwater. In total, the respective low- and high-resolution models consist of 21 and 16 layers, and 874,398 and 2,127,760 3-dimensional finite element mesh nodes. Both models incorporate spatially distributed soil and landcover, and spatially and temporally distributed evapotranspiration. To assess model performance, 321 wells from the Provincial Groundwater Water Monitoring Network (PGMN) and 29 hydrometric stations from the Water Survey of Canada (WSC) were incorporated as validation targets. Simulation results show that both the low- and high-resolution versions of the model were able to capture the magnitude and seasonal variation in both groundwater levels and surface water flow rates. Given that the model was subjected to minimal calibration, this is a meaningful validation of its performance. Differences in performance between the low- and high-resolution versions were minimal for both the surface water flow rates and groundwater level results. However, with its higher spatial resolution and greater density of surface water features, the high-resolution version can be expected to provide a better representation of localized hydrologic processes. Conversely, with its faster run time, the low-resolution version will better facilitate large ensemble simulations, such as those associated with uncertainty or climate change analyses. Results demonstrate the feasibility and utility of a regional scale, fully-integrated hydrologic model for investigating important aspects of water resources. The model could evolve into a multi-objective groundwater/surface-water simulation tool for southern Ontario, wherein seasonal water balances and general trends in groundwater and surface water availability under climate change and anthropogenic influences within the Great Lakes Region can be quantitatively assessed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".