The Spatial Extent of Hydrological and Landscape Changes across the Mountains and Prairies of the Saskatchewan and Mackenzie Basins
Notice bibliographique
Résumé
Abstract. East of the Continental Divide, the cold interior of Western Canada has one of the world's most extreme and variable climates and is experiencing rapid environmental change. In the large Saskatchewan and Mackenzie River basins, the warming climate is changing the landscape, vegetation, cryosphere, and water. This study of a large number (395) of gauged basins in these large river basins provides the basis for a large-scale analysis of observed hydrological and landscape changes. In this region, the existing data sets are complex; observed streamflow records are available for differing series of years and streamflow measurements consist of both continuous and seasonal records. This diversity has been compensated for using novel analytical approaches: [1] a Streamflow Regime classification using dynamic time-warping that covers only the common period of the calendar year amongst all stations, and which is restricted to a time window of seasonal observations, [2] a classification of seasonal Streamflow Regime change using k-means clustering of the year divided into five-day bins. An assessment of landscape and hydrological storage change for each gauged basin was conducted using Landsat 5 TM imagery of Normalized Difference Vegetation, Water, and Snow Indices (NDVI, NDWI, and NDSI) for 1985 to 2010. Therefore, this analysis is for a different time period than the streamflow regime and trend patterns. Twelve Streamflow Regime Types were identified using dynamic time-warping to overcome the problem of timing differences producing flow clusters due to latitude or elevation, rather than from the shape of the hydrograph resulting from differing processes. The success of this approach suggests that there is sufficient information in the time window to adequately resolve regions; Streamflow Regime Types exhibit a strong connection to location; the spatial distribution follows ecoregions and shows a strong distinction between mountains and plains. Clustering of seasonal trends resulted in six Trend Patterns. The Trend Patterns also have a strong and distinct spatial organization. The Trend Patterns include one with decreasing streamflow, four with different seasonal increasing streamflows, and one without any apparent trend structure. Trends in the mean, minimum, and maximum of three satellite indices were determined; the spatial patterns of NDWI and NDSI were similar to each other, but NDVI patterns were generally dissimilar. Streamflow Regime Types, the Trend Patterns, and satellite indices showed spatial coherence. The overlap between hydrological and landscape change was not perfectly coherent, suggesting that landscape changes may have a different domain from the existing hydrological regimes and from the observed trend patterns. Three particular areas of change are identified: [i] north of 60° where streamflow and greenness are increasing while wetness and snowcover are decreasing, [ii] in the western Boreal Plains where streamflows and greenness are decreasing but wetness and snowcover are not changing, and [iii] across the Prairies where there are three patterns of increasing streamflow and an increase in the wetness index, the largest changes occur in the eastern portion of the Canadian Prairies, with only few increases in greenness and snow indices. The results demonstrate the spatial extent of these changes.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».