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Delineating and Quantifying Ground Water Discharge Zones Using Streambed Temperatures

2004· article· en· W2165202893 on OpenAlexaff
Brewster Conant

Bibliographic record

VenueGround Water · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPiezometerGroundwater rechargeHydrology (agriculture)Flux (metallurgy)GroundwaterSurface waterEnvironmental scienceGroundwater dischargeDischargeHyporheic zoneGeologyAquiferGeotechnical engineeringMaterials scienceEnvironmental engineering

Abstract

fetched live from OpenAlex

Streambed temperature mapping, hydraulic testing using minipiezometers, and geochemical analyses of interstitial water of the streambed were used to delineate the pattern of ground water discharge in a sandy streambed and to develop a flux-based conceptual model for ground water/surface water interactions. A new and simple empirical method was used to relate fluxes obtained from minipiezometer data to streambed temperatures. The relationship allowed flux to be calculated at locations where only streambed temperature measurements were made. Slug testing and potentiomanometer measurements at 34 piezometers indicated ground water discharge ranged from 0.03 to 446 L/m2/day (and possibly as high as 7060 L/m2/day) along a 60 m long by 11 to 14 m wide reach of river. Complex but similar plan-view patterns of flux were calculated for both summer and winter using hundreds of streambed temperatures measured on a 1 by 2 m grid. The reach was dominated by ground water discharge and 5% to 7% of the area accounted for approximately 20% to 24% of the total discharge. < 12% of the total area consisted of recharge zones or no-discharge zones. A conceptual model for ground water/surface water interactions consisting of five different behaviors was developed based on the magnitude and direction of flux across the surface of the streambed. The behaviors include short-circuit discharge (e.g., high-flow springs), high discharge (e.g., preferential flowpaths), low to moderate discharge, no discharge (e.g., horizontal hyporheic or ground water flow), and recharge. Geological variations at depth played a key role in determining which type of flow behavior occurred in the streambed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations432
Published2004
Admission routes1
Has abstractyes

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