Surface water volume changes in the McKenzie Delta using satellite images and radar altimetry
Bibliographic record
Abstract
The Mackenzie Delta, located in the North West of Canada, is the second largest delta in the Arctic Ocean. The delta is frozen from October to May and the ice break-up, which occurs at the end of May or in the beginning of June, provokes an increase of the river’s flows. This phenomenon is reponsible for the flooding of extensive areas along the delta every year. In our study, the flood extent and the water stored in the surface reservoir were determined from 2000 to 2015 by combining multisatellite. Inundated areas were extracted from MODIS images at a 500 m resolution and water levels from rivers were derived from radar altimetry data from ERS-2, ENVISAT and SARAL missions. These informations were combined to compute weekly maps of of water levels from June to September. The flooded area reached its highest extent at the end of June or at the begining of July with an area of 2000 km² in yearly average, representing 20% of the delta’s total surface. Water heights were compared to in situ data made available by Natural Resources Canada. High correlations were found between the two data sources. Maps of water height exhibit high water heights during June/July which can reach 10 meters ahead of the delta and lowest level in August or September. Variations of surface water volume are around 1 km3 annually during the whole study period, with a maximum of 2.25 km3 observed in 2006. High correlation (>0.7) was found between water stored in the floodplains of the McKenzie Delta and the volume that was transferred to the ocean through the discharge. Comparisons were also perfromed between these two quantities and the geochemical activity measured using water color from MODIS in coastal areas.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".