High‐resolution spatiotemporal analysis of hydrologic connectivity in the historical floodplain of straightened lowland agricultural streams
Bibliographic record
Abstract
Abstract In agricultural watersheds, human interventions such as channel straightening have disrupted the hydrologic connectivity between headwater streams and their riparian environment and have thus undermined the ecological services provided by these small streams. Knowledge of the hydrologic connectivity between these streams and their immediate environment (shallow riparian groundwater in the historical floodplain and on adjacent hillslopes) in human‐impacted settings is critical for understanding and restoring these hydrological systems but remains largely incomplete. The objective of this research is to investigate the hydrogeomorphological conditions controlling hydrologic connectivity in the historical floodplain of straightened lowland streams. Detailed measurements on the spatiotemporal variability of groundwater‐surface water interactions between straightened reaches, historical floodplain including abandoned meanders, and the adjacent hillslopes were obtained using a dense network of piezometers at two sites in the St. Lawrence Lowlands (Quebec, Canada). Results show that the complex mechanisms controlling hydrologic connectivity in naturally meandering lowland rivers also operate in highly disturbed straightened reaches, despite backfilling and agricultural practices. The pre‐straightening hydrogeomorphological configuration of the floodplain partly explains the complex patterns of piezometric fluctuations observed at the sites. The apex of the abandoned meanders stands out as a focal area of hydrologic connectivity as water levels indicate pressure transfer that may reflect flows from the stream, the hillslopes, and the surrounding historical floodplain. These unique field observations suggest that abandoned meanders should be promoted as key elements of restoration strategies in lowland agricultural straightened headwater streams.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".