Remote sensing of hydrologic recharge in the Peace‐Athabasca Delta, Canada
Bibliographic record
Abstract
Northern wetlands like Canada's Peace‐Athabasca Delta (PAD) have global environmental significance, yet fundamental processes of hydrologic recharge critical to their functionality remain poorly understood. We use in situ water level and MODIS satellite data to examine how main‐stem river level fluctuations drive inundation across the delta. Temporal covariance between the two datasets allows inference of hydrologic connectivity processes, not just inundation extent. A strong contrast is found between hydrologic connectivity properties in a high‐water (2007) vs. low‐water year (2006). Results suggest that existing theoretical models of floodplain recharge fail to capture observed patterns of inundation in the PAD. Instead, we find a dichotomy between the distributary channel network, which responds to summer high‐water events, and floodplain lakes and wetlands, which do not. The latter occurs even where hydrologic connections do exist between the two. Results have strong management implications for the impact of proposed up‐river water diversion on PAD hydrology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".