A Model Selection Procedure for Stream Re-Aeration Coefficient Modelling
David Omole
Modern Applied Science, 2015, vol. 9, issue 9, 138
Abstract:
Model selection is finding wide applications in a lot of modelling and environmental problems. However, applications of model selection to re-aeration coefficient studies are still limited. The current study explores the use of model selection in re-aeration coefficient studies by combining several suggestions from numerous authors on the interpretation of data regarding re-aeration coefficient modelling. The model selection procedure applied in this research made use of Akaike information criteria, measures of agreement such as percent bias (PBIAS), Nash-Sutcliffe Efficiency (NSE) and RMSE observation Standard deviation Ratio (RSR) and gragh analysis in selecting the best performing model. An algorithm prescribing a generic model selection procedure was also provided. Out of ten candidates models used in this study, the O’Connor and Dobbins (1958) model emerged as the top performing model in its application to data collected from River Atuwara in Nigeria. The suggested process could save software and model developers lots of time and resources, which would otherwise be spent in investigating and developing new models. The procedure is also ideal in selecting a model in situations where there is no overwhelming support for any particular model by observed data. Â
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://ccsenet.org/journal/index.php/mas/article/download/45538/28290 (application/pdf)
https://ccsenet.org/journal/index.php/mas/article/view/45538 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ibn:masjnl:v:9:y:2015:i:9:p:138
Access Statistics for this article
More articles in Modern Applied Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().