MétaCan
Menu
← Back to cohort
Record W4243348841 · doi:10.5194/hess-2020-613

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

2021· preprint· en· W4243348841 on OpenAlexaffabout
Paul H. Whitfield, Philip Kraaijenbrink, Kevin Shook, John W. Pomeroy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of SaskatchewanSimon Fraser UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsStreamflowClimatologyClimate changePhysical geographyStructural basinNormalized Difference Vegetation IndexEnvironmental scienceNorth Atlantic oscillationVegetation (pathology)SnowDrainage basinGeographyGeologyMeteorologyOceanographyCartography

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.238
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicHydrology and Watershed Management Studies→French-language works237,207→