Measuring solids concentrations in urban stormwater and snowmelt: a new operational procedure
Bibliographic record
Abstract
A comparative study of five methods measuring suspended sediment or solid concentrations in water-sediment mixtures indicated that, depending on the method used, broadly varying results can be obtained. For water-sediment mixtures containing sand size particles, the standard TSS method produced negatively biased results, accounting for 0 to 90% of the present solids; the negative bias directly depended on the magnitude of the sand fraction in the water-sediment mixture. The main reason for the differences between the TSS and the rest of the methods laid in the handling of samples; in the former methods, whole samples were analysed, whereas the TSS analysis was performed on sub-samples withdrawn from the water sample, the withdrawal process tending to exclude large particles. The methods using whole water-solid samples, rather than aliquots withdrawn from such samples, produced accurate estimates of solid concentrations, with a fairly good precision. Two whole-sample methods were studied in detail, a slightly modified standard SSC-B method and the newly proposed operational procedure referred to as the Multiple Filter Procedure (MFP), using three filters arranged in a series with decreasing pore sizes (25, 1.6 and 0.45 µm). Both methods assessed accurately concentrations of solids in a broad range of concentrations (200-8000 mg L(-1)) and particle sizes (0.063-4.0 mm). The newly introduced MFP was in good agreement with the SSC procedure, the differences between the two procedures not exceeding the standard bias defined for the SSC-B method. The precision of both SSC and MFP was generally better than ±10%. Consequently, these methods should be used when the total mass of transported solids is of interest.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".