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Enregistrement W6944339146 · doi:10.17605/osf.io/tscyx

Linking Mountain Glacier Retreat and Hydrological Changes in Southwestern Yukon

2019· other· en· W6944339146 sur OpenAlexaboutno aff

Notice bibliographique

RevueOpen Science Framework · 2019
Typeother
Langueen
DomaineEarth and Planetary Sciences
ThématiqueCryospheric studies and observations
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGlacierThematic MapperTidewater glacier cycleGlacier mass balanceMoraineSatellite imageryWatershedSnow

Résumé

récupéré en direct d'OpenAlex

The project is linked to a paper by Chesnokova et al. (2020) “Linking Mountain Glacier Retreat and Hydrological Changes in Southwestern Yukon” and contains: 1. Glacier inventory data for three years for each study watershed (glacier_outlines.zip; files) are named based on the inventory year and the ID number from the discharge station at the watershed outlet provided by from Water Survey of Canada (Environment and Natural Resources, 2016; https://wateroffice.ec.gc.ca/). Glacier cover changes for each watershed were obtained by delineating glacier outlines for different years using freely available Landsat satellite images (Landsat Thematic Mapper 5, 7 and 8). Only August-September images with minimal snow and cloud cover were used for the inventory. Based on the temporal range of best available images suitable for the delineation, we choose years 1989, 1998 (1999 for White River watershed) and 2017, resulting in a time window of 28 years for the quantification of glacier cover changes. Initial glacier delineation was performed using the Global Land Ice Measurements from Space (GLIMS) (Kargel et al., 2014; available at https://www.glims.org/RGI/) shapefiles as a base. They were first modified in a way that each individual glacier was represented by an individual polygon instead of being merged with others. Delineating each individual glacier was required because glacier areas were used for glacier volume estimation in the SWBM. Glacier outlines were then modified according to the changes observed on satellite images for 1989, 1998 and 2017. Individual glacier area was subsequently calculated for the three years using ArcGIS®. 2. Simple water balance model (SWBM) (SWBM.zip; includes 8 models - one per study watershed) are named based on the ID numbers from the discharge station at the watershed outlet provided by from Water Survey of Canada (Environment and Natural Resources, 2016; https://wateroffice.ec.gc.ca/ ) (the modelling procedure, equations as well as model parameters can be found in the manuscript). SWBM was adapted from the model used by Baraer et al., (2012) to support the interpretation of trends in measured discharge in the Cordillera Blanca, Peru. As in the original version, based on water budget, the model generates synthetic hydrographs using the watershed area, the initial glacierized surface and the annual ice loss rate as an input. SWBM allows studying the direct impact of glaciers retreat on discharge thereby eliminating the uncertainties stemming from modeling the response of the glacier to changes in climatic forcing. In the present case, components of the energy balance, as well as physical characteristics of glacierized parts of the watersheds (glacier elevation range, slope orientation, ice flow etc.) that influence meltwater production, are integrated into an ice loss rate parameter. Moreover, most of the model parameters are taken from the literature, so if losses to evapotranspiration and deep infiltration can be estimated, the SWBM can even be used for ungauged watersheds. Modifications included rationalization of internal parameters, improvement of the watershed glaciers volume and glacier annual retreat calculation methods, and integration of extra processes such as the seasonality in groundwater and evapotranspiration fluxes. 3. Simple water balance model (SWBM) outputs that were used to create Figure 4 of the manuscript (SWBM_outputs.xlsx). For each studied watershed (column A) SWBM provides a peak water (PW) phase for the year 2017 (Phase, columns C & D) as well as a number of scenarios that assigned it (Number, column X;16 scenarios are summarized in Table 2 of the manuscript). The PW discharge relative to the original discharge, Qpeak/Q0, and the relative final discharge, Qend/Q0, is given annually (columns F & G) and for ablation period (columns H and I) for each scenario that predicted phases P1, P2 and P3. SWBM also calculates the potential of glaciers to further increase the watershed outflows in case of retreat acceleration, ∫Q+, (column J), estimated peak water year for scenario that did not lead to phase 3 or 4 (column K), and the precipitation increase rate Preq [mm/year] that would be required to reverse a negative trend in yearly discharge (or a positive trend in the coefficient of variation) arising from the PW analysis (column L).

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,400
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,031
Tête enseignante GPT0,274
Écart entre enseignants0,243 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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