Thermal transport modelling in a fully integrated surface/subsurface framework
Bibliographic record
Abstract
Abstract Thermal stream loadings from both natural and anthropogenic sources have significant relevance with respect to ecosystem health and water resources management, particularly in the context of future climate change. In recent years, there has been an increase in field‐based research directed towards characterizing thermal energy transport exchange processes that occur at the surface water/groundwater interface of streams. In spite of this effort, relatively little work has been performed to simulate these exchanges and elucidate their roles in mediating surface water temperatures and to simultaneously take into account all the pertinent hydrological, meteorological and surface/variably‐saturated subsurface processes. To address this issue, HydroGeoSphere, a fully‐integrated surface/subsurface flow and transport model, was enhanced to include fully integrated thermal energy transport. HydroGeoSphere can simulate water flow, evapotranspiration, and advective‐dispersive heat and solute transport over the 2D land surface and water flow and heat and solute transport in the 3D subsurface under variably saturated conditions. In this work, the new thermal capabilities of HydroGeoSphere are tested and verified by comparing HydroGeoSphere simulation results to those from a previous subsurface thermal groundwater injection study and also by simulating an example of atmospheric thermal energy exchange. High‐resolution 3D numerical simulations of a well‐characterized reach of the Pine River in Ontario, Canada are also presented to demonstrate thermal energy transport in an atmosphere–groundwater–surface water system. The HydroGeoSphere simulation successfully matched the spatial variations in the thermal patterns observed in the riverbed, the surface water and the groundwater. The computational framework can be used to provide quantitative guidance towards establishing the conditions needed to maintain a healthy ecosystem. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".