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Record W1597050087 · doi:10.1002/wrcr.20332

Transient, spatially varied groundwater recharge modeling

2013· article· en· W1597050087 on OpenAlexafffundabout
Kibreab Assefa, Allan D. Woodbury

Bibliographic record

VenueWater Resources Research · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Manitoba
FundersCanadian Water Network
KeywordsGroundwater rechargeWatershedHydrology (agriculture)Environmental scienceGroundwaterSpatial variabilityGroundwater modelSoil scienceGeologyGeotechnical engineeringAquiferComputer science

Abstract

fetched live from OpenAlex

The objective of this work is to integrate field data and modeling tools in producing temporally and spatially varying groundwater recharge in a pilot watershed in North Okanagan, Canada. The recharge modeling is undertaken by using the Richards equation based finite element code (HYDRUS‐1D), ArcGIS™, ROSETTA, in situ observations of soil temperature and soil moisture, and a long‐term gridded climate data. The public version of HYDUS‐1D and another version with detailed freezing and thawing module are first used to simulate soil temperature, snow pack, and soil moisture over a one year experimental period. Statistical analysis of the results show both versions of HYDRUS‐1D reproduce observed variables to the same degree. After evaluating model performance using field data and ROSETTA derived soil hydraulic parameters, the HYDRUS‐1D code is coupled with ArcGIS™ to produce spatially and temporally varying recharge maps throughout the Deep Creek watershed. Temporal and spatial analysis of 25 years daily recharge results at various representative points across the study watershed reveal significant temporal and spatial variations; average recharge estimated at 77.8 ± 50.8 mm/year. Previous studies in the Okanagan Basin used Hydrologic Evaluation of Landfill Performance without any attempt of model performance evaluation, notwithstanding its inherent limitations. Thus, climate change impact results from this previous study and similar others, such as Jyrkama and Sykes (2007), need to be interpreted with caution.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.014

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 head0.055
GPT teacher head0.286
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2013
Admission routes3
Has abstractyes

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