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Record W2765794824 · doi:10.2166/wcc.2017.033

Decrease of the water recharge and identification of water recharge zones in the Alto Atoyac sub-basin, Oaxaca, as a result of climate change

2017· article· en· W2765794824 on OpenAlexaff
Edwin Antonio Ojeda Olivares, Salvador Isidro Belmonte Jiménez, Tim K. Takaro, José Oscar Campos Enríquez, María Ladrón de Guevara Torres

Bibliographic record

VenueJournal of Water and Climate Change · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGroundwater rechargeImpervious surfaceEnvironmental sciencePrecipitationClimate changeHydrology (agriculture)Structural basinGroundwaterClimatologyGeologyGeographyAquiferMeteorologyEcologyGeomorphologyOceanography

Abstract

fetched live from OpenAlex

Abstract This study analyzes effects of climate change (CCh) and of the increase of impervious surfaces on the groundwater recharge in the Alto Atoyac sub-basin (Oaxaca, southern Mexico). Water recharge was modeled based on HELP 3.95D; temperature and precipitation were derived, for a near (2015–2039) and a far distant future scenario, from GFDL-CM3 global circulation model (GCM), which describes the climate of Mexico under the RCP8.5 scenario. Potential recharge loss zones for the period of 1979–2013 were estimated through a remote sensing analysis. The actual estimated mean annual recharge of 169 million cubic metres could be reduced by 17.97% and 65.09% according to the analyzed CCh scenarios, and the loss of 135 km2 of permeable soil would represent additionally 2.65 × 106 m3 of non-infiltrated water. This study indicates three sites, with high recharge potential, and it can be used to propose local adaptations to guarantee the availability of the water resource in the studied sub-basin.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.037
GPT teacher head0.251
Teacher spread0.214 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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