Identification and characterization of contributing areas, runoff processes and water quality in an agricultural Prairie watershed
Bibliographic record
Abstract
Determining contributing areas, streamflow sources, flow pathways, and nutrient dynamics in typical agricultural Prairie watersheds in the presence of numerous anthropogenic disturbances is not straightforward. The three main objectives of this study were: (1) delineating contributing areas and the influence of temporal and spatial control factors, (2) identifying hydrological processes using direct and indirect methods, (3) assessing spatiotemporal patterns of water quality through the surface drainage network using hydrochemical connectivity principles. This study was conducted in the 589 km2 Elm Creek watershed (ECW) in Manitoba, Canada. Sixteen soil moisture maps and ten soil moisture thresholds were selected to produce indicator maps showing active and inactive areas. Contributing areas were then delineated as active areas physically connected to the watershed outlet, as opposed to isolated active areas. Also, streamflow sources and flow pathways were assessed for six successive rainfall events using hyetograph-hydrograph, isotopic hydrograph separation (IHS), concentration-discharge hysteresis, and spatiotemporal hydrometric analyses. Electrical conductivity (EC) and soluble reactive phosphorus (SRP) concentrations were measured for surface water samples collected from ten targeted drain channel locations on 15 occasions throughout spring and summer 2014. The spatiotemporal variability of EC and SRP was examined through the drainage channels. Additionally, hydrochemical connectivity was assessed among nine upstream-downstream pairs through the drainage network. Results show that climate, topography, and soil characteristics influence contributing areas for an effective range of soil moisture thresholds between 0.25 to 0.35 m3/m3. Different types of overland flow (infiltration-excess and saturation-excess overland flow) were observed in the ECW for six rainfall events. Isotope-based hydrograph separation results hinted at new water contributions, whereas hydrometric data did not reveal significant overland flow response, suggesting that new water travels via shallow subsurface flow. Soil moisture data analyses revealed the presence of shallow preferential flow at a limited number of sites. Local hydrochemical connectivity for a few upstream-downstream pairs was observed through the surface drainage network. This study demonstrated that important knowledge insights could be made about contributing areas, hydrological processes, and nutrient dynamics when various control factors are studied through the different lenses of connectivity, flow sources, and flow pathways.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".