Calibratie van modellen ten behoeve van regionalisatie studies. Twee methoden voor het schatten van verdelingsfuncties van modelparameters, op basis van Monte-Carlo sampling

2.50
Hdl Handle:
http://hdl.handle.net/10029/256691
Title:
Calibratie van modellen ten behoeve van regionalisatie studies. Twee methoden voor het schatten van verdelingsfuncties van modelparameters, op basis van Monte-Carlo sampling
Authors:
Heuberger PSC; Sanders R; Janssen PHM
Other Titles:
Model calibration for regionalisation studies. Two methods to estimate distribution functions of model parameters, based on Monte-Carlo sampling
Abstract:
Abstract niet beschikbaar

In this report two techniques for regional calibration of mathematical models are discussed. Regional calibration is concerned with rescaling the model from a local (site) level to a regional level. This is typically done by assigning probability distributions to the unknown parameters, which reflect their (regional) spatial variability in an adequate way. Due to insufficient availability of data on the local level, the calibration of the parameters is performed on the regional level by matching the (simulated) distribution of the model outputs with the distribution of the measurement data. The discussed techniques, Bin Filling (BF) and Weighted Frequency Matching, are based on Monte Carlo sampling and simulation in combination with a reweighing of the sampled values to accomplish an optimal match between the distributions of the model results and the measurement data. The characteristic features of the presented techniques are discussed and their utility is indicated. In addition some guidelines are presented for an appropriate use of the methods which have been implemented aas software for general use.
Issue Date:
30-Sep-1992
URI:
http://hdl.handle.net/10029/256691
Additional Links:
http://www.rivm.nl/bibliotheek/rapporten/723001008.html
Type:
Onderzoeksrapport
Language:
nl
Sponsors:
Stuurgroep Verzuring (in het kader van het Additioneel Programma Verzuring 3-de fase)
Appears in Collections:
RIVM official reports

Full metadata record

DC FieldValue Language
dc.contributor.authorHeuberger PSC-
dc.contributor.authorSanders R-
dc.contributor.authorJanssen PHM-
dc.date.accessioned2012-12-12T14:28:42Z-
dc.date.available2012-12-12T14:28:42Z-
dc.date.issued1992-09-30-
dc.identifier723001008-
dc.identifier.urihttp://hdl.handle.net/10029/256691-
dc.description.abstractAbstract niet beschikbaarnl
dc.description.abstractIn this report two techniques for regional calibration of mathematical models are discussed. Regional calibration is concerned with rescaling the model from a local (site) level to a regional level. This is typically done by assigning probability distributions to the unknown parameters, which reflect their (regional) spatial variability in an adequate way. Due to insufficient availability of data on the local level, the calibration of the parameters is performed on the regional level by matching the (simulated) distribution of the model outputs with the distribution of the measurement data. The discussed techniques, Bin Filling (BF) and Weighted Frequency Matching, are based on Monte Carlo sampling and simulation in combination with a reweighing of the sampled values to accomplish an optimal match between the distributions of the model results and the measurement data. The characteristic features of the presented techniques are discussed and their utility is indicated. In addition some guidelines are presented for an appropriate use of the methods which have been implemented aas software for general use.en
dc.description.sponsorshipStuurgroep Verzuring (in het kader van het Additioneel Programma Verzuring 3-de fase)-
dc.format.extent35 p-
dc.language.isonl-
dc.relation.ispartofRIVM Rapport 723001008-
dc.relation.urlhttp://www.rivm.nl/bibliotheek/rapporten/723001008.html-
dc.subject20nl
dc.subject92-3nl
dc.subjectwiskundige modellennl
dc.subjectmodelcalibratienl
dc.subjectsysteemidentificatie; regionale calibratienl
dc.subjectkansverdelingennl
dc.subjectbin fillingnl
dc.subjectweighted frequency matchingnl
dc.subjectmonte-carlo samplingnl
dc.titleCalibratie van modellen ten behoeve van regionalisatie studies. Twee methoden voor het schatten van verdelingsfuncties van modelparameters, op basis van Monte-Carlo samplingnl
dc.title.alternativeModel calibration for regionalisation studies. Two methods to estimate distribution functions of model parameters, based on Monte-Carlo samplingen
dc.typeOnderzoeksrapport-
dc.date.updated2012-12-12T14:28:43Z-
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