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Record W2991230551 · doi:10.1038/s41598-019-53981-x

Streamflow variations across the Andes (18°–55°S) during the instrumental era

2019· article· en· W2991230551 on OpenAlexaff
Mariano Masiokas, Leandro Cara, Ricardo Villalba, Pierre Pitte, Brian H. Luckman, Ezequiel Toum, Duncan A. Christie, C. Quesne, Steven A. Mauget

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsWestern University
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasComisión Nacional de Investigación Científica y TecnológicaUniversidad Nacional de San JuanConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsStreamflowClimatologySurface runoffGeographyEl Niño Southern OscillationMultivariate statisticsPhysical geographySpatial ecologyClimatic variabilityClimate changeEnvironmental scienceGeologyOceanographyEcologyDrainage basinCartography

Abstract

fetched live from OpenAlex

The rivers originating in the southern Andes (18°-55°S) support numerous ecosystems and a large number of human populations and socio-economic activities in the adjacent lowlands of Chile, Argentina and Bolivia. Here we show that ca. 75% of the total variance in the streamflow records from this extensive region can be explained by only eight spatially coherent patterns of variability. Five (three) of these Andean patterns exhibit extreme dry (wet) conditions in recent years, with strong interannual variations in northern Chile; long-term drying trends between 31° and 41°S; a transitional pattern in the central Patagonian Andes; and increasing trends in northwestern Argentina and southern Bolivia, the Fueguian Andes, and the eastern portion of the South Patagonian Icefield. Multivariate regression analyses show that large-scale indices of ENSO variability can predict 20% to 45% of annual runoff variability between 28° and 46°S. The influence of Antarctic and North Pacific indices becomes more relevant south of 43°S and in northwestern Argentina and southern Bolivia, respectively, but their overall skill as predictors of Andean streamflows is weak. The analyses provide relevant new information to improve understanding of the spatial coherence, the main temporal features, and the ocean-atmospheric forcings of surface runoff across the southern Andes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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.

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

Citations48
Published2019
Admission routes1
Has abstractyes

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