AustralieFrV1, Main, Exploration, bibRecord, 003F28

The error in agricultural systems model prediction depends on the variable being predicted : Agricultural Systems Modelling and Software - Part I

Identifieur interne : 003F28 ( Main/Exploration ); précédent : 003F27; suivant : 003F29

The error in agricultural systems model prediction depends on the variable being predicted : Agricultural Systems Modelling and Software - Part I

Auteurs : Daniel Wallach [France] ; Peter J. Thorburn [Australie]

Source :

Environmental modelling & software [ 1364-8152 ] ; 2014.

RBID : Pascal:15-0019899

Descripteurs français

Pascal (Inist)
- Erreur, Système agraire, Modèle, Variable, Gaz effet serre, Irrigation, Protoxyde d'azote, Incertitude, Zea mays.
Wicri :
- topic : Irrigation.

English descriptors

KwdEn :
- Agricultural system, Error, Greenhouse gas, Irrigation, Models, Nitrogen protoxide, Uncertainty, Variable, Zea mays.

Abstract

Models are generally evaluated based on the squared error of model predictions compared with individual data. However, if major interest is in some quantity averaged over time or space it would be more pertinent to evaluate how well the model predicts this average quantity. We show that the model squared error for predictions averaged over space or time will always be smaller than average squared prediction error and how to estimate the difference between the two, using commonly available data. We illustrate with two case studies concerning irrigation management, (where major interest is in yield averaged over years) and nitrous oxide emissions (where major interest is in emissions averaged over a growing season). Squared error of the average was estimated to be only 57% and 10% of the average squared error for the irrigation and nitrous oxide emissions studies, respectively, in the limit of averaging over long times.

Affiliations:

Links toward previous steps (curation, corpus...)

to stream PascalFrancis, to step Corpus: 000103
to stream PascalFrancis, to step Curation: 005D50
to stream PascalFrancis, to step Checkpoint: 000057
to stream Main, to step Merge: 003F81
to stream Main, to step Curation: 003F28

Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Agricultural system</term>
<term>Error</term>
<term>Greenhouse gas</term>
<term>Irrigation</term>
<term>Models</term>
<term>Nitrogen protoxide</term>
<term>Uncertainty</term>
<term>Variable</term>
<term>Zea mays</term>
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<keywords scheme="Pascal" xml:lang="fr"><term>Erreur</term>
<term>Système agraire</term>
<term>Modèle</term>
<term>Variable</term>
<term>Gaz effet serre</term>
<term>Irrigation</term>
<term>Protoxyde d'azote</term>
<term>Incertitude</term>
<term>Zea mays</term>
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<front><div type="abstract" xml:lang="en">Models are generally evaluated based on the squared error of model predictions compared with individual data. However, if major interest is in some quantity averaged over time or space it would be more pertinent to evaluate how well the model predicts this average quantity. We show that the model squared error for predictions averaged over space or time will always be smaller than average squared prediction error and how to estimate the difference between the two, using commonly available data. We illustrate with two case studies concerning irrigation management, (where major interest is in yield averaged over years) and nitrous oxide emissions (where major interest is in emissions averaged over a growing season). Squared error of the average was estimated to be only 57% and 10% of the average squared error for the irrigation and nitrous oxide emissions studies, respectively, in the limit of averaging over long times.</div>
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<country name="Australie"><noRegion><name sortKey="Thorburn, Peter J" sort="Thorburn, Peter J" uniqKey="Thorburn P" first="Peter J." last="Thorburn">Peter J. Thorburn</name>
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The error in agricultural systems model prediction depends on the variable being predicted : Agricultural Systems Modelling and Software - Part I

The error in agricultural systems model prediction depends on the variable being predicted : Agricultural Systems Modelling and Software - Part I

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri