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Record W1505436295 · doi:10.1002/hyp.9848

Geometric calculation of view factors for stream surface radiation modelling in the presence of riparian forest

2013· article· en· W1505436295 on OpenAlexaff
R. D. Moore, Jason A. Leach, J. M. Knudson

Bibliographic record

VenueHydrological Processes · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRiparian zoneEnvironmental scienceRiparian forestSurface (topology)Hydrology (agriculture)STREAMSPhysical geographyGeologyGeographyMathematicsGeometryComputer scienceEcologyGeotechnical engineeringHabitatBiology

Abstract

fetched live from OpenAlex

Many efforts to model stream temperature by using an energy budget approach have not accounted for view factors in modelling stream surface radiative exchanges, used informal approaches for computing them, or relied on calibration, which is not applicable for prediction at unmonitored sites or for predicting the effects of changes in riparian vegetation. In this paper, equations are derived for calculating view factors on the basis of geometric considerations for streams with and without riparian forest. The solutions can accommodate vegetation overhanging the stream surface. Example calculations illustrate the substantial variability of view factors across the stream width, which has implications for the estimation of view factors from point-scale radiation measurements over the stream surface, and the important influence of overhanging vegetation on view factors for narrow streams. View factors computed from the geometric model agreed well with view factors computed from hemispherical photography for streams ranging from 1 to almost 50 m wide, indicating that the model appears to be reasonably robust to deviations from the simplified geometry assumed by the model. In addition to their use in modelling stream surface energy exchanges, the solutions could also be adapted for application to energy balance and microclimate modelling in linear forest openings, such as seismic lines used in oil and gas exploration. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.201

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.033
GPT teacher head0.245
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations15
Published2013
Admission routes1
Has abstractyes

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