The Spatial Extent of Hydrological and Landscape Changes across the Mountains andPrairies of Canada in the Mackenzie and Nelson River Basins Based on Data from aWarm Season Time Window
Bibliographic record
Abstract
Abstract. The cold interior of Western Canada, east of the Continental Divide, has one of the world's most extreme and variable climates and is experiencing rapid environmental change. In the large Mackenzie and Nelson River basins, the warming climate is changing the landscape, vegetation, cryosphere, and hydrology. This is a study of a large number (395) of natural (unmanaged) gauged basins where streamflow may be continuous or temporary, and observed streamflow records had been collected either year-round or during only the warm season. Each station may have records for a different series of years between 1910 and 2012. Instead of a common period of years and a small number of stations, as in many trend studies, an annual warm season time window where observations were available across all stations is used to classify [1] streamflow regime using dynamic time-warping, and [2] seasonal trend patterns with k-means clustering. The trends in seasonal streamflow patterns were compared to changes in satellite Normalized Difference Vegetation, Water, and Snow Indices (NDVI, NDWI, and NDSI) for each gauged basin using Landsat 5 TM imagery between 1985 and 2010. Twelve streamflow regime types were identified using dynamic time-warping which overcomes timing differences in streamflow generation due to latitude or elevation. These streamflow regime types exhibit a strong connection to location; the spatial distribution follows ecozones and shows a strong distinction between mountains and plains in the study area. Clustering of seasonal trends using the annual common time window resulted in six trend patterns that also have a strong and distinct spatial organization. The trend patterns include one with decreasing streamflow, four with different patterns of increasing streamflow, and one with stations without trend structure. Trends in the mean, minimum, and maximum of three satellite indices were determined; the spatial patterns of trends in NDWI and NDSI were similar to each other, but different from NDVI trends. Streamflow regime types, the trend patterns, and satellite indices trends each showed spatially coherent patterns reflecting the influence of sources in the Canadian Rockies and other range in the west and poorly defined drainage basins due to post-glacial topography in the east and north. The overlap between hydrological and satellite index trends were not consistent across the study area. Three particular areas of change were identified: [i] in the mountains or lake-dominated, cold taiga-covered subarctic, north of 60° N, streamflow and greenness were increasing while wetness and snowcover were decreasing, [ii] in the forested Boreal Plains, particularly in the mountain west, streamflows and greenness were decreasing but wetness and snowcover were not changing, and [iii] in the semi-arid to sub-humid agricultural Prairies three patterns of increasing streamflow and an increase in the wetness index were observed. The largest changes in streamflow occurred in the eastern Canadian Prairies, where there were only a few increases in greenness and snow indices.
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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 | 0.000 | 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 | 0.001 |
| 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".