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Record W3087051421 · doi:10.5194/egusphere-egu2020-859

Hydrological response to warm and dry extremes in glacierized catchments: when and how are glaciers compensating?

2020· article· en· W3087051421 on OpenAlexaboutno aff
Marit Van Tiel, Anne F. Van Loon, Jan Seibert, Kerstin Stahl

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsStreamflowGlacierMeltwaterEvapotranspirationPrecipitationEnvironmental scienceClimate changeDrainage basinClimatologySnowHydrology (agriculture)Physical geographyGeologyGeographyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Extreme warm and dry summer conditions often cause low-flow situations due to the precipitation deficit and increased evapotranspiration. In glacierized catchments, however, the same extreme weather conditions can lead to a very different hydrological response, namely increased streamflow because of increased glacier melt. In larger combined rainfed and glacierfed catchments, meltwater from glaciers can, thus, buffer the adverse hydrological effects of warm and dry spells. The question is how much glacier cover in a catchment is needed to counterbalance the hydrological processes that cause a decline in streamflow. Moreover, due to climate change, glaciers have been retreating, which affects the hydrological response and the buffering effect of glaciers. In this study, we analysed long-term streamflow records of around 60 glacierized catchments in Switzerland, Austria, Norway and Canada with varying glacier coverage. In addition, a few catchments were modelled to analyse some extreme events in more detail and perform sensitivity tests. Warm and dry spells were selected based on weather data for the catchments and the corresponding hydrological responses were investigated. The events were analysed taking into account catchment characteristics, such as glacier cover and elevation information, and antecedent conditions, such as snowfall in winter and precipitation amounts in the period before the warm and dry event. Results show that during extreme warm and dry spells small glacier cover fractions (< 10%) can already alleviate the otherwise emerging streamflow drought. Moreover, we see a clustering of warm and dry periods in recent years and a decreasing trend of summer streamflow in many catchments. Antecedent conditions appear to shape the individual summer streamflow responses. Overall, understanding the hydrological responses to warm and dry spells is essential due to projected increases in weather extremes. Especially in glacierized catchments, our results imply that with changing glacier cover due to global warming, changes in the buffering capacity of glacierized catchments during warm and dry periods can be expected.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.037
GPT teacher head0.221
Teacher spread0.184 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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