Modelling potential impacts of coalbed methane development on stream water quality in an American watershed
Bibliographic record
Abstract
Abstract Coalbed methane (CBM) development raises serious environmental concerns and concerted efforts have been made to collect chemistry, salinity, and sodicity data on CBM produced water. A model is sorely needed to make use of this data to quantify potential changes in stream water quality resulting from directly and/or indirectly receiving CBM produced water, on which little information is available in the literature. However, the application of existing hydrodynamic and water quality models such as CE‐QUAL‐W2 is not straightforward because the number of outfalls is usually large and the channels poorly defined for intermittent streams in semiarid areas such as the Powder River watershed, located in the states of Wyoming and Montana. Hence, the objectives of this study were to: (1) develop a CBM produced water routing (CBMPRO) model, and (2) apply the new CBMPRO model, along with a CE‐QUAL‐W2 model, to examine potential changes in stream water quality due to CBM development in the Powder River watershed. The CBMPRO model was developed and used to chart the CBM discharge and the transport of its associated constituents (e.g. total dissolved solids and alkalinity) from an outfall to its inclusive subwatershed outlet. In turn, the outputs from the CBMPRO model were applied as inputs into the CE‐QUAL‐W2 model to predict changes in the water quantity and quality along the Powder River mainstem. The results indicate that discharges from CBM developments adversely affect the stream water quality. Compared with the baseline conditions, the developments would increase the stream flows as well as make the stream water warmer and more saline. In addition, the impacts were predicted to undergo seasonal and spatial variations and to become smaller with time, as expected. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".