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Record W7016223541

Wolf Creek Cold Regions Model Set-up, Parameterisation and Modelling Summary

2023· report· en· W7016223541 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsSnowmeltHydrographStructural basinHydrology (agriculture)StreamflowDrainage basinSnowHydrological modellingWater balance
DOInot available

Abstract

fetched live from OpenAlex

Wolf Creek Research Basin is in the Upper Yukon River Basin near Whitehorse, Yukon and is representative of headwaters in the northern Coast Mountains. It was established in 1993 to better develop northern hydrological models, and related hydrological process, ecosystem and climate science. Yukon Environment maintains Wolf Creek hydrometeorological and hydrometric stations and conducts regular snow surveys in the basin. A number of hydrological models have been tested on Wolf Creek and all have had great difficulty in simulating the cold regions hydrological processes that dominate its streamflow response to snowmelt and rainfall events. Developments in understanding hydrological processes and their interaction with terrestrial ecosystems and climate at Wolf Creek have lead to the development of the Cold Regions Hydrological Model (CRHM) by a consortium of scientists led by the University of Saskatchewan and Environment Canada. CRHM comprehensively incorporates the blowing snow, intercepted snow, sublimation, melt energetics, infiltration to frozen soils, organic terrain runoff and other cold regions hydrological phenomenon and discretizes the catchment on a hydrological response unit basis for applying water and energy balance calculations. The model is intended for prediction of ungauged basins with parameter selection from physically measurable properties of the river basin or regional transference of calibrated values. In Russia, a long tradition of cold regions hydrological research has led to the development of the Hydrograph model by the State Hydrological Institute, St. Petersburg. The Hydrograph model contains several promising innovations regarding the formation and routing of runoff, discretizes the basin using hydrological response units and addresses some (but not all) cold regions hydrological processes. Hydrograph parameter selection is made from both physically measured properties and those that are calibrated, but the calibrations can be easily regionalized. Test simulations of runoff processes using CRHM and Hydrograph for Wolf Creek Research Basin was undertaken using data archives that had been assembled and cleaned up in a related project by the University of Saskatchewan. The test simulations are a demonstration of model capabilities and a way to gain familiarity with the basin, its characteristics and data and to better compare model features. Data available included a GIS database of basin characteristics (topography and vegetation distribution) and the hydrometeorological and hydrometric observational dataset from Yukon Environment. The sub-surface hydrology presented a formidable unknown in parameterising the model. Hydrograph performed well in initial simulations of the basin hydrograph for multi-year runs. Several issues with observational data quality created substantial uncertainty in evaluating the model runs.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0130.004

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 head0.094
GPT teacher head0.219
Teacher spread0.126 · 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 designSimulation or modeling
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

Citations0
Published2023
Admission routes1
Has abstractyes

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