Land use impacts on ground and surface water quality in the Bertrand Creek watershed (Township of Langley, B.C.)
Bibliographic record
Abstract
Bertrand Creek is a small transboundary watershed with mixed land use that provides a good case study to compare the impacts of urban and agricultural activities on water resources. Located in southeastern Langley, it encompasses the city of Aldergrove and an agricultural area that extends from south of Aldergrove to the Canada - US international border. The main goal of this study was to determine land use impacts on water quality. Water samples were analyzed for nutrients and dissolved elements and results were linked to land use through a GIS. Streambed sediments were analyzed for trace metals and bioavailability of metals was measured along Bertrand Creek using the diffusive gradients in thin films (DGT) technique. Land use didn't seem to be correlated to groundwater quality but results indicated that nitrate contamination in the Abbotsford aquifer is a concern. Well depth appeared to have a significant influence in the quality of groundwater and only wells <15 m deep exceeded the drinking water quality guidelines for NO₃ - N. Surface water analysis indicated high concentrations of nitrate and phosphorus, especially on Howes Creek. Correlation with land use data showed that high concentrations of manganese in surface water and concentrations of copper, lead and zinc in sediments were positively correlated to the extent of impervious surfaces. Nitrate - N concentrations were influenced by agricultural activities particularly during the wet season. It is therefore important that stormwater and agricultural best management practices be exercised, including the increase of riparian buffer areas, improved manure management and storage techniques and the construction of stormwater detention ponds, particularly at sites that receive direct runoff from heavily used roads. Despite the importance of the streams in this watershed to aquatic life there appears to be a significant lack of water quality studies and monitoring. The results of the present study warrant further research in the watershed to ensure a healthy habitat for aquatic life and to protect drinking water sources in rural areas.
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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 | 0.001 | 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 | 0.001 |
| 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".