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Record W2170565333 · doi:10.5194/adgeo-22-41-2009

Characterizing contributions of glacier melt and groundwater during the dry season in a poorly gauged catchment of the Cordillera Blanca (Peru)

2009· article· en· W2170565333 on OpenAlexafffund
Michel Baraër, Jeffrey M. McKenzie, Bryan G. Mark, Jeffrey Bury, S. Knox

Bibliographic record

VenueAdvances in geosciences · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill UniversityOhio State University
KeywordsGroundwaterGlacierPrecipitationHydrology (agriculture)Dry seasonStructural basinDrainage basinδ18OWatershedWet seasonEnvironmental scienceGeologyWater balanceStable isotope ratioGeographyGeomorphology

Abstract

fetched live from OpenAlex

Abstract. The retreat of glaciers in the tropics will have a significant impact on water resources. In order to overcome limitations with discontinuous to nonexistent hydrologic measurements in remote mountain watersheds, a hydrochemical and isotopic mass balance model is used to identify and characterize dry season water origins at the glacier fed Querococha basin located in southern Cordillera Blanca, Peru. Dry season water samples, collected intermittently between 1998 and 2007, were analyzed for major ions and the stable isotopes of water (δ18O and δ2H). The hydrochemical and isotopic data are analysed using conservative characteristics of selected tracers and relative contributions are calculated based on pre-identified contributing sources at mixing points sampled across the basin. The results show that during the dry-season, groundwater is the largest contributor to basin outflow and that the flux of groundwater is temporally variable. The groundwater contribution significantly correlates (P-value=0.004 to 0.044) to the antecedent precipitation regime at 3 and 18–36 months. Assuming this indicates a maximum of 4 years of precipitation accumulation in groundwater reserves, the Querococha watershed outflows are potentially vulnerable to multi-year droughts and climate related changes in the precipitation regime. The results show that the use of hydrochemical and isotopic data can contribute to hydrologic studies in remote, data poor regions, and that groundwater contribution to tropical proglacial hydrologic systems is a critical component of dry season discharge.

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 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 score0.012
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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 teacher head, 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

Citations88
Published2009
Admission routes2
Has abstractyes

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