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Record W1993593764 · doi:10.2134/jeq2004.4760

Changes in Ground Water Quality in an Irrigated Area of Southern Alberta

2004· article· en· W1993593764 on OpenAlexaffabout
S. J. Rodvang, D. M. Mikalson, M. Cathryn Ryan

Bibliographic record

VenueJournal of Environmental Quality · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of CalgaryAgriculture Food and Rural Development
Fundersnot available
KeywordsEnvironmental scienceGroundwaterWater qualityHydrology (agriculture)GeologyBiologyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Few studies have documented spatial and temporal variations in ground water quality in areas with high densities of animal farming operations (AFOs), or the long-term effects on surface-water quality. Changes in ground water quality were characterized in an irrigated area with a high density of AFOs in southern Alberta, Canada to evaluate the effect on ground water quality of manure application to fields. Fifty-five piezometers in the oxidized zone were sampled once or twice annually from 1995 to 2001, and temporal changes were analyzed using mixed model analysis. Average NO3- -N increased significantly from 12.5 to 17.4 mg L(-1) and average Cl- increased significantly from 19.4 to 34.4 mg L(-1) in piezometers installed in an unconfined sand aquifer at locations receiving fertilizer and manure. Compared with these manured locations, nitrate and chloride concentrations were significantly lower in shallow aquifer water in areas of pasture or native range, and concentrations did not change significantly with time. Nitrate and chloride concentrations in shallow ground water in fine-textured manured locations did not change significantly. Ground water below about 6 m in till and fine lacustrine sediments contains 18O signatures indicative of recharge under preirrigation or glacially influenced conditions, suggesting this ground water has a low vulnerability to agricultural contamination. Evaluations suggest that shallow ground water discharge will cause NO3- -N and Cl- in the Oldman River to increase by factors of at least 4.3 and 1.3, respectively, with more significant effects in smaller streams and under low-flow conditions.

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 categoriesInsufficient 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 score0.033
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.242
Teacher spread0.216 · 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

Citations57
Published2004
Admission routes2
Has abstractyes

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