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Record W2755348950 · doi:10.1002/hyp.11356

Using hydrochemical, stable isotope, and river water recharge data to identify groundwater flow paths in a deeply buried karst system

2017· article· en· W2755348950 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.

Bibliographic record

VenueHydrological Processes · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsUniversity of Waterloo
FundersBeijing Municipal Science and Technology CommissionNational Science Foundation
KeywordsGroundwater rechargeGroundwaterAquiferKarstHydrology (agriculture)Surface waterGeologyGroundwater flowDepression-focused rechargeSpring (device)Environmental science

Abstract

fetched live from OpenAlex

Abstract The deeply buried river‐connected Xishan karst aquifer (XKA) in western Beijing, China, has been suffering from diminishing recharge for several decades, which in turn leads to the disappearing of spring water outflows and continuously lowering of groundwater level in the area. Thus, it is important to correctly recognize the groundwater recharge and flow paths for the sustainable development of the XKA. To investigate these issues, the hydrochemical and isotopic compositions are analysed for both surface water and groundwater samples collected over an area of about 280 km 2 . Results show that (a) the river water is characterized by high Na contents; (b) the δ 2 H and δ 18 O values in the river water are distinctively higher than those of groundwater samples, after experiencing the long‐time evaporative enrichment in the upstream reservoir; (c) the Sr concentrations and 87 Sr/ 86 Sr ratios of groundwater clearly indicated the interaction between water and carbonate minerals but excluded the water–silicate interaction; and (d) the groundwater samples in the direct recharge area of the XKA have the lowest Na concentrations and the δ 2 H and δ 18 O values. Based on the large differences in the Na contents and 18 O values of groundwater and surface water, a simple two‐component mixing model is developed for the study area and the fractions of the river water are estimated for groundwater samples. We find that the distribution pattern of the river water fractions in the XKA clearly shows a change of directions in the preferential flow path of the groundwater from its source zone to the discharge area. Overall, our results suggest that the recharged surface water can be a useful evidence for delineating the groundwater flow path in river‐connected karst aquifer. This study improves our understanding of the heterogeneity in karst groundwater systems.

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)0.001
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 score0.592
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.101
GPT teacher head0.300
Teacher spread0.199 · 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