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Evapotranspiration prediction using system identification and genetic algorithm

Reference evapotranspiration or ETO is important to provide information in planning and management of water resource system for irrigation purposes. Hence, its accurate estimation is of vital importance to assess water availability and requirements. This study explores the use of system identificati...

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Main Authors: Ahmad, Robiah, M.Samsuri, Saiful Farhan, Zakaria, Mohd. Zakimi
Format: Article
Published: 2012
Subjects:
T Technology
Online Access:http://eprints.utm.my/id/eprint/46946/
http://dx.doi.org/10.2316/P.2012.769-053
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spelling my.utm.469462017-09-27T04:03:43Z http://eprints.utm.my/id/eprint/46946/ Evapotranspiration prediction using system identification and genetic algorithm Ahmad, Robiah M.Samsuri, Saiful Farhan Zakaria, Mohd. Zakimi T Technology Reference evapotranspiration or ETO is important to provide information in planning and management of water resource system for irrigation purposes. Hence, its accurate estimation is of vital importance to assess water availability and requirements. This study explores the use of system identification approach and modified genetic algorithm (MGA) to model the evapotranspiration process under climatic data. The method is applied in modelling hourly evapotranspiration in central and southern region of Malaysia as a function of solar radiation, temperature, humidity and wind speed. The performance of the model is compared with the traditional Penman-Monteith (PM) method. Results from the study indicate that both the data driven is comparable with that of the PM method. The MGA models are dominated by temperature and solar radiation indicating that these two inputs can represent most of the variance. The results also show that the models are parsimonious and understandable, and are well suited to modelling the dynamics of the evapotranspiration process. 2012 Article PeerReviewed Ahmad, Robiah and M.Samsuri, Saiful Farhan and Zakaria, Mohd. Zakimi (2012) Evapotranspiration prediction using system identification and genetic algorithm. Proceedings Of The Iasted International Conference On Modelling, Identification, And Control, Mic . pp. 176-183. ISSN 1025-8973 http://dx.doi.org/10.2316/P.2012.769-053
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology
spellingShingle T Technology
Ahmad, Robiah
M.Samsuri, Saiful Farhan
Zakaria, Mohd. Zakimi
Evapotranspiration prediction using system identification and genetic algorithm
description Reference evapotranspiration or ETO is important to provide information in planning and management of water resource system for irrigation purposes. Hence, its accurate estimation is of vital importance to assess water availability and requirements. This study explores the use of system identification approach and modified genetic algorithm (MGA) to model the evapotranspiration process under climatic data. The method is applied in modelling hourly evapotranspiration in central and southern region of Malaysia as a function of solar radiation, temperature, humidity and wind speed. The performance of the model is compared with the traditional Penman-Monteith (PM) method. Results from the study indicate that both the data driven is comparable with that of the PM method. The MGA models are dominated by temperature and solar radiation indicating that these two inputs can represent most of the variance. The results also show that the models are parsimonious and understandable, and are well suited to modelling the dynamics of the evapotranspiration process.
format Article
author Ahmad, Robiah
M.Samsuri, Saiful Farhan
Zakaria, Mohd. Zakimi
author_facet Ahmad, Robiah
M.Samsuri, Saiful Farhan
Zakaria, Mohd. Zakimi
author_sort Ahmad, Robiah
title Evapotranspiration prediction using system identification and genetic algorithm
title_short Evapotranspiration prediction using system identification and genetic algorithm
title_full Evapotranspiration prediction using system identification and genetic algorithm
title_fullStr Evapotranspiration prediction using system identification and genetic algorithm
title_full_unstemmed Evapotranspiration prediction using system identification and genetic algorithm
title_sort evapotranspiration prediction using system identification and genetic algorithm
publishDate 2012
url http://eprints.utm.my/id/eprint/46946/
http://dx.doi.org/10.2316/P.2012.769-053
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score 13.211869

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