Effect of Drawdown on Ammonium and Iron Concentrations in a Coastal Mountain Reservoir
Bibliographic record
Abstract
Abstract Part way through a year-long water quality field survey, the Capilano Reservoir, located in the Greater Vancouver Water District, was drawn down to accommodate earthquake reinforcement work on the Cleveland Dam. This paper reports observations of the effect of drawdown on water quality in the reservoir, in the context of the original study. The drawdown exposed a large zone of deltaic material through which the Capilano River eroded a path up to 2.5 m deep. The deltaic material contained substantial amounts of nitrogen and iron (TKN, 4,470 mg kg-1; total iron, 21,800 mg kg-1). During drawdown, turbidity in the reservoir increased up to 25 times as compared to prior conditions. Ammonium (NH4+-N) and dissolved and particulate iron concentrations in the drawdown zone were up to two orders of magnitude higher than concentrations upstream. Both NH4+-N and dissolved iron were observed to travel the length of the reservoir. Persistence of NH4+-N in the highly oxygenated conditions may be explained by the presence of factors that inhibit nitrification. Persistence of NH4+-N and particularly dissolved iron may be due to adsorption and com-plexation reactions. Seasonally high concentrations of iron and ammonium at the water intake corresponded to the timing of complaints of taste, odour, turbid water, and staining in the distribution system. Observations made during this extreme drawdown suggest that transport of N and Fe from exposed deltaic sediments may play a role in the periodic increases in ammonium and iron observed in the Capilano Reservoir. Further understanding of the impacts associated with changing reservoir elevation should lead to the development of appropriate management strategies to maintain the high quality of GVWD water.
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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 | 0.006 | 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) | 0.002 | 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".