Assessing the effects of land cover change in runoff processes with RHESSys: a case study in the Waterford River Watershed, Newfoundland and Labrador, Canada
Bibliographic record
Abstract
Evaluating the current state of hydrologic processes in urban and semi-urban areas is an essential part of ensuring the sustainable management of water and preventing emergencies of extreme events. This study evaluated the effects of land use and land cover (LULC) change on runoff processes in the Waterford River Watershed (WRW), located in the eastern part of the province of Newfoundland and Labrador (NL), Canada. The Regional Hydro – Ecological Simulation System (RHESSys), a GIS-based hydro-ecological model, was used in a new urbanistic approach to simulate the effects of increasing impervious land as well as reducing urban green areas. The increase in hypothetical peak flows had a direct relationship with the reduction of pervious areas in the watershed. The most sizeable flow increases were observed in the periods of April to May and October to December. This study emphasizes the importance of using a prominent network of green and pervious structures or water retention areas when allocation for residential and commercial land increase.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".