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Record W4408252015 · doi:10.1016/j.envadv.2025.100627

Catchment-scale assessment of groundwater discharge using ecological, thermal, and hydrochemical surveillance data in the Halton Region, Ontario

2025· article· en· W4408252015 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

VenueEnvironmental Advances · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsToronto and Region Conservation AuthorityQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaQueen's UniversityCanada Foundation for Innovation
KeywordsGroundwaterEnvironmental scienceDrainage basinScale (ratio)Hydrology (agriculture)Groundwater dischargeEcologyWater resource managementGeographyAquiferGeologyCartographyGroundwater flowBiology

Abstract

fetched live from OpenAlex

• Aggregation of >21,000 interpolated groundwater and stream monitoring data • Ecological parameters reflective of larger-scale groundwater discharge patterns • Temperature but not hydrochemical gradients reflect groundwater discharge dynamics • Surface water surveillance data can guide groundwater discharge monitoring efforts Groundwater-surface water exchange is spatiotemporally variable and costly to assess at high-resolution across large areas. This study explores the application of readily available surface water monitoring data to identify potential groundwater discharge locations in 15 catchments within Conservation Halton's jurisdiction within the Halton Region, Ontario, Canada. We first compared two interpolated groundwater discharge models and subsequently contrasted these against stream ecology data (macrophyte and fish taxa) and surface- and groundwater quality measurements that were aggregated to derive temperature and hydrochemical (alkalinity, chloride) gradients across the hyporheic zone. Both groundwater models agreed in their prediction of discharge locations for only 52% of monitoring sites, corroborating the need for further reconnaissance of potential discharge areas. Fish temperature preferences and ecological temperature classifications aligned reasonably with the groundwater discharge models (<55% of sites) and air-to-stream temperature differences agreed better with groundwater discharge predicted by modeling (p<0.04, R 2 >0.40) than stream-to-groundwater gradients (p<0.1, R 2 <0.25). Instead, hydrochemical signatures of both chloride and alkalinity in the streams were more ambiguous and displayed poor correlation with groundwater discharge maps and other monitoring parameters. Finally, we amalgamated the various investigated parameters into a classification scheme to determine the likelihood of groundwater discharge at the monitoring locations . This work exemplifies how combining commonly available monitoring information may be used to provide additional insight into groundwater discharge dynamics and stream health across larger and diverse catchment types where lack of in-situ monitoring or unverified numerical models complicate a clear understanding of groundwater discharge patterns.

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 score0.011
Threshold uncertainty score0.401

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 studies0.0000.001
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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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