Agricultural intensification and urban expansion affect the seasonal flow regime in southern Ontario watersheds
Bibliographic record
Abstract
Abstract The mosaic of urban, agricultural and natural covers that typifies most developed landscapes makes it challenging to identify the primary causes of stream flow perturbation in mixed landcover watersheds. This is especially true in southern Ontario, Canada, where approximately 1/3 of the Canadian population lives in urban areas surrounded by agriculture. Whilst previous studies have examined the impacts of urban or agricultural landcover on stream flow separately, they are rarely considered together. Furthermore, major expansions in tile‐drained (TD) cropland in Ontario over the past several decades could affect the flow regime; however, this has never been examined. This study assessed the effect of landcover on flow regime at 19 proximal watersheds that varied in agriculture (0%–87%), natural (2%–97%) and urban landcover (2%–96%) using the Richards–Baker index (RBI), the coefficient of variation (CV) and a Baseflow index (BFI). Urbanized watersheds were consistently the most flashy (highest RBI and CV), regardless of season, whereas agricultural watersheds had moderately flashy conditions that varied between the growing (GS) and non‐growing seasons (NGS). Natural watersheds were the least flashy and had the highest BFI. Watersheds dominated by TD cropland were flashier during the NGS compared with un‐tiled agricultural watersheds. Furthermore, TD‐streams were warmer in the NGS and cooler in the GS, such that the former could affect ice breakup. A 50‐year analysis at three watersheds showed statistically significant increases in flashiness and decreases in BFI at an urbanizing watershed. In contrast, watersheds that remained agricultural or natural underwent small but significant declines in flashiness and increases in baseflow, potentially due to increases in precipitation and forest maturation. Our results suggest that continued expansions of urban and TD cropland may increase NGS flashiness. In contrast, enhanced soil moisture storage provided by TD could decrease the potential for flooding in the GS in southern Ontario.
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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".