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Record W2953712204 · doi:10.1002/hyp.13546

Modelling the effects of permafrost loss on discharge from a wetland‐dominated, discontinuous permafrost basin

2019· article· en· W2953712204 on OpenAlexafffundabout
Lindsay E. Stone, Xing Fang, Kristine M. Haynes, Manuel Helbig, John W. Pomeroy, Oliver Sonnentag, William L. Quinton

Bibliographic record

VenueHydrological Processes · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcMaster UniversityCenter for Northern StudiesUniversité de MontréalUniversity of SaskatchewanWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostWetlandPeatHydrology (agriculture)Environmental scienceSurface runoffWater balancePlateau (mathematics)Structural basinDrainageEvapotranspirationDrainage basinLand coverBogGeologyLand useGeomorphologyEcologyGeography

Abstract

fetched live from OpenAlex

Abstract Permafrost degradation in the peat‐rich southern fringe of the discontinuous permafrost zone is catalysing substantial changes to land cover with expansion of permafrost‐free wetlands (bogs and fens) and shrinkage of forest‐dominated permafrost peat plateaux. Predicting discharge from headwater basins in this region depends upon understanding and numerically representing the interactions between storage and discharge within and between the major land cover types and how these interactions are changing. To better understand the implications of advanced permafrost thaw‐induced land cover change on wetland discharge, with all landscape features capable of contributing to drainage networks, the hydrological behaviour of a channel fen sub‐basin in the headwaters of Scotty Creek, Northwest Territories, Canada, dominated by peat plateau–bog complexes, was modelled using the Cold Regions Hydrological Modelling platform for the period of 2009 to 2015. The model construction was based on field water balance observations, and performance was deemed adequate when evaluated against measured water balance components. A sensitivity analysis was conducted to assess the impact of progressive permafrost loss on discharge from the sub‐basin, in which all units of the sub‐basin have the potential to contribute to the drainage network, by incrementally reducing the ratio of wetland to plateau in the modelled sub‐basin. Simulated reductions in permafrost extent decreased total annual discharge from the channel fen by 2.5% for every 10% decrease in permafrost area due to increased surface storage capacity, reduced run‐off efficiency, and increased landscape evapotranspiration. Runoff ratios for the fen hydrological response unit dropped from 0.54 to 0.48 after the simulated 50% permafrost area loss with a substantial reduction of 0.47 to 0.31 during the snowmelt season. The reduction in peat plateau area resulted in decreased seasonal variability in discharge due to changes in the flow path routing, with amplified low flows associated with small increases in subsurface discharge, and decreased peak discharge with large reductions in surface run‐off.

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 score0.218
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.217
Teacher spread0.199 · 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

Citations23
Published2019
Admission routes3
Has abstractyes

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