MétaCan
Menu
Back to cohort
Record W4285014963 · doi:10.3389/frwa.2022.801134

The Impacts of Climate Change on Land Hydroclimatology of the Laurentian Great Lakes Basin

2022· article· en· W4285014963 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Water · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsEnvironment and Climate Change Canada
FundersEnvironment and Climate Change CanadaUniversity of Waterloo
KeywordsEvapotranspirationSnowpackPrecipitationEnvironmental scienceClimate changeSurface runoffDrainage basinWater resourcesClimatologyRepresentative Concentration PathwaysClimate modelStructural basinHydrology (agriculture)SnowGeographyEcologyGeologyMeteorology

Abstract

fetched live from OpenAlex

The freshwater resources of the Laurentian Great Lakes basin contribute significantly to the environment and economy of the region. With the impacts of climate change becoming more evident, sustainable management of the freshwater resources of the Laurentian Great Lakes basin is important. This study uses 36 simulations from 6 regional climate models to quantify trends and changes in land-area precipitation and temperature in two future periods (mid-century, 2035–2064 and end-century, 2065–2094) with reference to a baseline period (1951–2005) for two emission scenarios (RCP4.5 and RCP 8.5). Climatic forcings from these 36 simulations are used as input to a calibrated and validated hydrological model to assess changes in land snowpack and actual evapotranspiration, and runoff to lake. Ensemble results show wetter (7 to 15% increase in annual precipitation) and warmer (2.4–5.0°C increase in annual mean temperature) future conditions on GL land areas. Seasonal and monthly changes in precipitation and mean temperature are more sporadic, for instance although precipitation is projected to increase overall, in some scenarios, summer precipitation is expected to decrease. Projected increases in highest one-day precipitation and decreases in number of wet days indicate possible increases in extreme precipitation in future. Minimum temperature is expected to increase in a higher rate than maximum temperature. Ensemble results from the hydrological model show projected decrease in snowpack (29–58%). Similarly, actual evapotranspiration is projected to increase, especially during summer months (up to 0.4 mm/day). Annually, runoff is expected to increase (up to 48% in Superior, 40% in Michigan-Huron, 25% Erie and 28% in Ontario). Seasonal and monthly changes in runoff are more sporadic (e.g., projected decrease up to 17% in Erie subdomain in October). Such contrasting patterns of changes in land hydroclimatology of the GL basin will pose challenges to sustainable management of the water resources of the basin in future.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.151
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.198
Teacher spread0.191 · 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