Vulnerability of surface water bodies to potential contamination by ammunition residues from military training ranges
Bibliographic record
Abstract
Over the last decade, a major effort has been made by Canadian Forces to understand the hydrodynamic of groundwater flow on range training areas (RTA). However, there is also a need to study surface water bodies and especially its vulnerability to potential contamination by ammunition residues. Nearly half of the surface (42%) of the studied RTA is located on bedrock prone to high rate of surface runoff. Rugged terrain is located to the north of the RTA, whereas to the south; the surface is on deltaic sediment made of sand that is favorable to high infiltration rate. Digital Elevation Models (DEMs) of topography were used in Geographic Information System (GIS) Software (ArcGis) to derive hydrologic processes. The GIS grid cells encompass basic terrain flow data that can be used to represent the flow processes at the free surface. They can also be used to derive a wide variety of information useful for the study of hydrologic processes such as topographic slope, water flow direction, contributing and drainage areas, catchments, watersheds and channel networks. The free surface flow was defined everywhere in the RTA but more specifically around targets locations, firing positions, and in impact areas. The developed methodology allows determining the hydrologic network with potential accumulation areas. The main objective is to identify areas where surficial geology and hydrological properties are favorable to rainfall-runoff and to establish if the quality of surface water may be altered by training ranges activities and subsequently if potential contaminants may migrate to receptors such as lakes and rivers. Vulnerable sectors that have high, medium or low rainfall-runoff index and surface water flow accumulation were shown on a regional map. Many other local maps were produced to define in more details surface water vulnerability in specific ranges. The possible relationship between the detection of ammunition residues in surface water bodies, the vulnerability index, the flow accumulation, the rainfall-runoff index and, the location of range training activities was investigated. Key words: hydrologic processes, surface water, ammunition residues, range training areas.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".