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Flood prediction for Klang river using Maskingum and ANN models

Link to publisher’s homepage at https://www.myiem.org.my/

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Main Authors: Jer Lang, Hong, Kee An, Hong
Other Authors: jerlang.hong@taylors.edu.my
Format: Article
Language:English
Published: The Institution of Engineers, Malaysia (IEM) 2019
Subjects:
ANN Muskingum
Calibration
Flood Routing NAE
RMSE
Validation
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/62198
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spelling my.unimap-621982019-10-08T03:58:08Z Flood prediction for Klang river using Maskingum and ANN models Jer Lang, Hong Kee An, Hong jerlang.hong@taylors.edu.my keeanhong@yahoo.co.uk ANN Muskingum Calibration Flood Routing NAE RMSE Validation Link to publisher’s homepage at https://www.myiem.org.my/ Temporal and spatial variations of a flood hydrograph moving through a river reach can be simulated using flood routing tools such as hydrodynamic, hydrological and the ANN (Artificial Neural Networks) models. The ANN models have emerged as viable tools in flood routing and are widely adopted for this purpose. The aim of this study is to make an objective comparison of these two flood routing models to evaluate their individual performance. Four flood events recorded for Klang river at Kuala Lumpur in the period October 1973 to December 1974 for stations at Leboh Pasar and Sulaiman Bridge which are 950m apart were used for this study. The statistical performance of the models is assessed using criteria such as peak flow, root mean square error, mean absolute error and Nash –sutcliffe coefficient. Results from calibration runs for the 02/05/1974 flood event show that the MAE, RMSE and NAE for ANN and Muskingum models are 0.75,1.24,0.9917 and 1.1,1.3, 0.992 respectively. The performance of the two models was verified using three other different events. Results of simulation runs for the 10/12/1974 event gave 2.72, 3.24, 0.96 and 2.1,3.1,0.963 MAE, RMSE and NAE values for ANN and Muskingum. Graphical inspections and statistical tests show that the ANN and Muskingum methods performed equally well in flood prediction for this study, using the flood events of Klang river. 2019-10-08T03:58:08Z 2019-10-08T03:58:08Z 2018-12 Article The Journal of the Institution of Engineers, Malaysia, Vol. 79(2), Disember 2018, pages 9-14. 0126-513x http://dspace.unimap.edu.my:80/xmlui/handle/123456789/62198 https://www.myiem.org.my/ en The Institution of Engineers, Malaysia (IEM)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic ANN Muskingum
Calibration
Flood Routing NAE
RMSE
Validation
spellingShingle ANN Muskingum
Calibration
Flood Routing NAE
RMSE
Validation
Jer Lang, Hong
Kee An, Hong
Flood prediction for Klang river using Maskingum and ANN models
description Link to publisher’s homepage at https://www.myiem.org.my/
author2 jerlang.hong@taylors.edu.my
author_facet jerlang.hong@taylors.edu.my
Jer Lang, Hong
Kee An, Hong
format Article
author Jer Lang, Hong
Kee An, Hong
author_sort Jer Lang, Hong
title Flood prediction for Klang river using Maskingum and ANN models
title_short Flood prediction for Klang river using Maskingum and ANN models
title_full Flood prediction for Klang river using Maskingum and ANN models
title_fullStr Flood prediction for Klang river using Maskingum and ANN models
title_full_unstemmed Flood prediction for Klang river using Maskingum and ANN models
title_sort flood prediction for klang river using maskingum and ann models
publisher The Institution of Engineers, Malaysia (IEM)
publishDate 2019
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/62198
_version_ 1651868653849673728
score 13.222552

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