Local groundwater management for British Columbia: linking data to protection practices
Bibliographic record
Abstract
Groundwater management decisions are continuously made under conditions of incomplete data and information. The hidden nature of groundwater resources makes detection of contamination and depletion of supply difficult to anticipate. However, neglecting to monitor groundwater resources can lead to consequences which are difficult or impossible to rectify. Changing trends in the governance of water resources in Canada indicate that greater responsibility for groundwater management is being shifted to local levels of government. This however requires information and expertise traditionally maintained at senior levels of government. The purpose of this thesis is to develop an analytical framework for use by local governments in B.C. planning for sustained, multipurpose groundwater use and quality protection. Analysis for this framework focusses on threeareas of concern for local governments facing increasing responsibility for groundwater management: data requirements, land use management and groundwater protection practices. Of the various approaches surveyed, georeferenced analysis is suggested to be one of the more flexible and useful analytical tools for use in groundwater management. The framework suggested consists of four components: 1) a list of parameters required for land use management for the purpose of groundwater protection, 2) an analysis of groundwater protection measures and required data, 3) a prioritized list of data collection activities based on the ease of collection of information, the time required to collect a critical mass of data and the relative importance to present groundwater concerns in B.C. and 4) a procedure for integrating land use classification with groundwater data collection and protection measures. Hatzic Valley, situated in the Lower Fraser Basin is used to illustrate the suggested framework and to investigate the extent of existing data for an area which has not previously been intensely studied. Available data for the area, while limited, is found to be sufficient for initial delineation of land areas which should be protected to reduce the likelihood of groundwater contamination in the area. However, groundwater quality data, used as a primary indicator of change in groundwater resources, is largely lacking. Groundwater management is an iterative process within which communication of uncertainty and consultation with the public allow for effective and flexible groundwater protection planning. Community involvement in data collection is a cost effective alternative to expenditures on groundwater remediation or developing alternative sources of water should contamination occur. Uncertainty in all aspects of groundwater management can be reduced by clearer expression of where and what the limitations are in the available data. Decision makers should address issues of community development and values to most efficiently resolve community and groundwater resource use conflict.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".