Understanding Water Use Conflicts to Advance Collaborative Planning: Lessons Learned from Lake Diefenbaker, Canada
Bibliographic record
Abstract
Conflicts around the multi-purpose water uses of Lake Diefenbaker (LD) in Saskatchewan, Canada need to be addressed to meet rapidly expanding water demands in the arid Canadian prairie region. This study explores these conflicts to advance collaborative planning as a means for improving the current water governance and management of this lake. Qualitative methodology that employed a wide participatory approach was used to collect focus group data from 92 individuals, who formed a community of water users. Results indicate that the community of water users is unified in wanting to maintain water quality and quantity, preserving the lake’s aesthetics, and reducing water source vulnerability. Results also show these users are faced with water resource conflicts resulting from lack of coherence of regulatory instruments in the current governance regime, and acceptable management procedures of both consumptive and contemporary water uses that are interlinked in seven areas of: irrigation, industrial, and recreational water uses; reservoir water level for flood control and hydroelectricity production; wastewater and lagoon management; fish farm operations; and regional water development projects. As a means of advancing collaborative planning, improvements in water allocation and regulatory instruments could be made to dissipate consumptive use conflicts and fill the under-regulation void that exists for contemporary water uses. Additionally, a comprehensive LD water use master plan, as a shared vision to improve participation in governance, could be developed to direct the water uses that have emerged over time. This study suggests that these three areas are practical starting conditions that would enable successful collaborative planning for the seven areas of water uses. Focusing on these three areas would ensure the current and future needs of the community of water users are met, while avoiding reactive ways of solving water problems in the LD region, especially as the water crisis in the Canadian Prairie region where LD is located is expected to intensify.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".