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Record W2160309473 · doi:10.5194/hess-15-267-2011

Modelling hourly rates of evaporation from small lakes

2011· article· en· W2160309473 on OpenAlexaffabout
R. J. Granger, N. Hedstrom

Bibliographic record

VenueHydrology and earth system sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsEnvironmental scienceEvaporationWind speedAtmospheric sciencesHumidityEddy covarianceHydrology (agriculture)Potential evaporationAtmospheric instabilityMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract. The paper presents the results of a field study of open water evaporation carried out on three small lakes in Western and Northern Canada. In this case small lakes are defined as those for which the temperature above the water surface is governed by the upwind land surface conditions; that is, a continuous boundary layer exists over the lake, and large-scale atmospheric effects such as entrainment do not come into play. Lake evaporation was measured directly using eddy covariance equipment; profiles of wind speed, air temperature and humidity were also obtained over the water surfaces. Observations were made as well over the upwind land surface. The major factors controlling open water evaporation were examined. The study showed that for time periods shorter than daily, the open water evaporation bears no relationship to the net radiation; the wind speed is the most significant factor governing the evaporation rates, followed by the land-water temperature contrast and the land-water vapour pressure contrast. The effect of the stability on the wind field was demonstrated; relationships were developed relating the land-water wind speed contrast to the land-water temperature contrast. The open water period can be separated into two distinct evaporative regimes: the warming period in the Spring, when the land is warmer than the water, the turbulent fluxes over water are suppressed; and the cooling period, when the water is warmer than the land, the turbulent fluxes over water are enhanced. Relationships were developed between the hourly rates of lake evaporation and the following significant variables and parameters (wind speed, land-lake temperature and humidity contrasts, and the downwind distance from shore). The result is a relatively simple versatile model for estimating the hourly lake evaporation rates. The model was tested using two independent data sets. Results show that the modelled evaporation follows the observed values very well; the model follows the diurnal trends and responds to changes in environmental 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)0.000
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 score0.612
Threshold uncertainty score0.309

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 head0.037
GPT teacher head0.196
Teacher spread0.160 · 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

Citations106
Published2011
Admission routes2
Has abstractyes

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