Effects of Paleo Climate Boundary Conditions on Regional Groundwater Flow in Discretely Fractured Crystalline Rock
Bibliographic record
Abstract
A detailed groundwater flow analysis for a 100 sq. km. portion of a larger regional 5734 sq. km. watershed situated on the Canadian Shield has been conducted to illustrate aspects of regional and sub-regional groundwater flow evolution due to glaciation and deglaciation events over a period of 120,000 years. Field investigations at the Underground Research Lab (URL) of the Whiteshell Research Area (WRA) near Lac du Bonnet, Manitoba, show evidence of anomalously high piezometric heads, likely resulting from surface loading from the Laurentide Ice Sheet, and high total dissolved solids (TDS) concentrations of 50 to 100 g/L in the deeper sparsely fractured rock (SFR). Consequently, long-term climate change is an important factor which can influence the safety and performance of a hypothetical used nuclear fuel repository, particularly the occurrence of peri-glacial and glacial conditions that would alter a repository’s mechanical, thermal, and hydraulic boundary conditions over a period of tens to hundreds of thousands of years. A 121,000 year continental scale paleo climate simulation is used as the basis for assigning boundary conditions and permeability reduction due to the presence of permafrost to the sub-regional scale model. Ice thicknesses of over 3,000 m and permafrost depths of more than 400 m are encountered during the course of the simulation. The discrete-fracture dual continuum finite element model FRAC3DVS was used to investigate the importance of glaciation events on flow and particle migration. Orthogonal fracture faces (between adjacent finite element blocks) were used to best represent the irregular discrete-fracture network. Crystalline rock between these structural discontinuities was assigned properties characteristic of the URL representing either SFR or moderately fractured rock (MFR). The transmissivity and porosity of the complex planar fracture zones was represented using random permeability, thickness and porosity fields that were scaled to various permeability depth models which were conditioned using data from the URL. The permeability and porosity distributions of MFR were developed in an independent inverse modeling study of tracer experiments in the MFR at the URL. Interconnectivity of permeable fracture features is an important pathway for the relatively rapid migration of average water particles and subsequent reduction in residence times.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".