Modeling the Dynamics of Carbon Dioxide Emission and Ecosystem Exchange Using a Modified SWAT Hydrologic Model in Cold Wetlands
Bibliographic record
Abstract
The restoration and protection of wetlands are crucial in reducing greenhouse gas emissions. In this research, the SWAT model was modified to investigate and estimate the groundwater table, net ecosystem exchange (NEE), and soil respiration impact on carbon dioxide (CO2) emission in the cold regions in Alberta. There is a lack of a process-based model that accounts explicitly for the CO2 emission and ecosystem exchange resulting from interactions between hydrological and biogeochemical processes. The SWAT model is modified to make unique contributions to wetlands by estimating CO2 emissions, soil temperature, and soil respiration that account for the dynamics of water tables and the relationship between subsurface and surface water storage. The modified model results predicted daily NEE with a very good model fit resulting in an R2 (Coefficient of determination), NSE (Nash-Sutcliffe Efficiency), PBIAS (percent bias), and RMSE (root mean square error) of 0.88, 0.72, 2.5, and 0.45 in the calibration period and 0.82, 0.67, −1.8, and 0.56 for the validation period, respectively. The prediction result indicated that the modified model performed well in predicting soil temperature, the groundwater table, and ecosystem respiration in the calibration and validation periods. In general, this study concluded that the modified model has the capability of representing the effects of water table dynamics on CO2 emissions and NEE in cold wetlands.
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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".