Intersections of wildfire, water and land: using groundwater science to reduce risks to water supplies
Bibliographic record
Abstract
For over three weeks, fire suppression teams sought to control the 2018 Parry Sound 33 Wildfire (covering 11,362 hectares in northeastern Ontario). Following the fire, the wide spread concern has been the impact of the Parry Sound 33 Wildfire upon the Key Harbour First Nation's and Henvey Inlet First Nation's water security. This in turn has sparked groundwater geochemistry questions. Our research seeks to understand one question: how can the post-Parry Sound 33 fire water quality research provide guidance for future ground water research in Southern Ontario and across Canada? Informed by research from i) post fire mobilization of contaminants into surface water resources; ii) short term impacts of fire events on karst; and iii) community based fire management, this project has several objectives: a) Provide gap analysis of the post-fire groundwater for drinking water quality research; b) Detail how Canadian universities and research institutions take a strategic view of post-fire water quality research to support land use planning and public health and safety initiatives; c) Document actionable information products created to communicate to communities how to manage post fire water quality. This paper presents preliminary results of our research, noting: Contamination of high quality potable water in groundwater can occur through natural events such as wildfires because wildfires modify the surface environment by combusting vegetation and changing soil properties; Most prior research on post-fire water quality research has focused on surface water to determine fire-prone forested water source areas; The emerging field of post fire contamination of water sources is receiving considerable attention, evidenced by the 2018 NSERC funded Water Institute/University of Waterloo project. But there is little research being done to understand the vulnerabilities of groundwater aquifers to post fire debris, sediment and chemical constituents (indicators that could be included in future assessments). This paper is intended to inform discussions on the preparation of suitable post fire water management plans in order to maintain drinking water quality in a cost-effective manner.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".