Forecasting model for the change in stage of reservoir water level

Reservoir is one of major structural approaches for flood mitigation. During floods, early reservoir water release is one of the actions taken by the reservoir operator to accommodate incoming heavy rainfall. Late water release might give negative effect to the reservoir structure and cause flood at...

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Main Author:	Nur Athirah, Ashaary
Format:	Thesis
Language:	eng eng
Published:	2016
Subjects:	QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/6033/1/s814388_01.pdf https://etd.uum.edu.my/6033/2/s814388_02.pdf
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id	my-uum-etd.6033
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Wan Ishak, Wan Hussain Ku Mahamud, Ku Rohana
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Nur Athirah, Ashaary Forecasting model for the change in stage of reservoir water level
description	Reservoir is one of major structural approaches for flood mitigation. During floods, early reservoir water release is one of the actions taken by the reservoir operator to accommodate incoming heavy rainfall. Late water release might give negative effect to the reservoir structure and cause flood at downstream area. However, current rainfall may not directly influence the change of reservoir water level. The delay may occur as the streamflow that carries the water might take some time to reach the reservoir. This study is aimed to develop a forecasting model for the change in stage of reservoir water level. The model considers the changes of reservoir water level and its stage as the input and the future change in stage of reservoir water level as the output. In this study, the Timah Tasoh reservoir operational data was obtained from the Perlis Department of Irrigation and Drainage (DID). The reservoir water level was categorised into stages based on DID manual. A modified sliding window algorithm has been deployed to segment the data into temporal patterns. Based on the patterns, three models were developed: the reservoir water level model, the change of reservoir water level and stage of reservoir water level model, and the combination of the change of reservoir water level and stage of reservoir water level model. All models were simulated using neural network and their performances were compared using on mean square error (MSE) and percentage of correctness. The result shows that the change of reservoir water level and stage of reservoir water model produces the lowest MSE and the highest percentage of correctness when compared to the other two models. The findings also show that a delay of two previous days has affected the change in stage of reservoir water level. The model can be applied to support early reservoir water release decision making. Thus, reduce the impact of flood at the downstream area.
format	Thesis
qualification_name	other
qualification_level	Master's degree
author	Nur Athirah, Ashaary
author_facet	Nur Athirah, Ashaary
author_sort	Nur Athirah, Ashaary
title	Forecasting model for the change in stage of reservoir water level
title_short	Forecasting model for the change in stage of reservoir water level
title_full	Forecasting model for the change in stage of reservoir water level
title_fullStr	Forecasting model for the change in stage of reservoir water level
title_full_unstemmed	Forecasting model for the change in stage of reservoir water level
title_sort	forecasting model for the change in stage of reservoir water level
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2016
url	https://etd.uum.edu.my/6033/1/s814388_01.pdf https://etd.uum.edu.my/6033/2/s814388_02.pdf
_version_	1747828011050205184
spelling	my-uum-etd.60332021-04-19T03:10:05Z Forecasting model for the change in stage of reservoir water level 2016 Nur Athirah, Ashaary Wan Ishak, Wan Hussain Ku Mahamud, Ku Rohana Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA71-90 Instruments and machines Reservoir is one of major structural approaches for flood mitigation. During floods, early reservoir water release is one of the actions taken by the reservoir operator to accommodate incoming heavy rainfall. Late water release might give negative effect to the reservoir structure and cause flood at downstream area. However, current rainfall may not directly influence the change of reservoir water level. The delay may occur as the streamflow that carries the water might take some time to reach the reservoir. This study is aimed to develop a forecasting model for the change in stage of reservoir water level. The model considers the changes of reservoir water level and its stage as the input and the future change in stage of reservoir water level as the output. In this study, the Timah Tasoh reservoir operational data was obtained from the Perlis Department of Irrigation and Drainage (DID). The reservoir water level was categorised into stages based on DID manual. A modified sliding window algorithm has been deployed to segment the data into temporal patterns. Based on the patterns, three models were developed: the reservoir water level model, the change of reservoir water level and stage of reservoir water level model, and the combination of the change of reservoir water level and stage of reservoir water level model. All models were simulated using neural network and their performances were compared using on mean square error (MSE) and percentage of correctness. The result shows that the change of reservoir water level and stage of reservoir water model produces the lowest MSE and the highest percentage of correctness when compared to the other two models. The findings also show that a delay of two previous days has affected the change in stage of reservoir water level. The model can be applied to support early reservoir water release decision making. Thus, reduce the impact of flood at the downstream area. 2016 Thesis https://etd.uum.edu.my/6033/ https://etd.uum.edu.my/6033/1/s814388_01.pdf text eng public https://etd.uum.edu.my/6033/2/s814388_02.pdf text eng public other masters Universiti Utara Malaysia Abdul Mokhtar, S., Wan Ishak, W. H., & Md Norwawi, N. (2014). Modelling of Reservoir Water Release Decision Using Neural Network and Temporal Pattern of Reservoir Water Level. International Conference on Intelligent Systems, Modelling and Simulation, 127–130. http://doi.org/10.1109/ISMS.2014.27 Adnan, R., Ruslan, F. A., Samad, A. 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