A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations

The river stage–discharge relationship has an important impact on modeling, planning, and management of river basins and water resources. In this study, the capability of the Gaussian Process Regressions (GPR) kernel-based approach was assessed in predicting the daily river stage–discharge (RSD) rel...

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Autores principales:	Kiyoumars Roushangar, Masoumeh Chamani, Roghayeh Ghasempour, Hazi Mohammad Azamathulla, Farhad Alizadeh
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	eemd gpr pre-processing river stage-discharge wt Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/041be1ee94714725a9bef2be425a3e42
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spelling	oai:doaj.org-article:041be1ee94714725a9bef2be425a3e422021-11-06T10:08:40ZA comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations1606-97491607-079810.2166/ws.2021.073https://doaj.org/article/041be1ee94714725a9bef2be425a3e422021-09-01T00:00:00Zhttp://ws.iwaponline.com/content/21/6/3080https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798The river stage–discharge relationship has an important impact on modeling, planning, and management of river basins and water resources. In this study, the capability of the Gaussian Process Regressions (GPR) kernel-based approach was assessed in predicting the daily river stage–discharge (RSD) relationship. Three successive hydrometric stations of the Housatonic River were considered, and based on the flow characteristics during the period of 2002–2006 several models were developed and tested via GPR. To enhance the applied model efficiency, two pre-processing techniques, namely Wavelet Transform (WT) and Ensemble Empirical Mode Decomposition (EEMD), were used. Also, two states of the RSD modeling were investigated. In state 1, each station's own data was used and in state 2, the upstream stations’ datasets were used as input to model the RSD downstream of the river. The single and integrated model results showed that the integrated WT- and EEMD-GPR models resulted in more accurate outcomes. Data processing enhanced the models' capability between 25% and 40%. The results showed that the RSD modeling in state 1 led to better results; however, when the station's own data were not available the integrated methods could be applied successfully for the RSD modeling using the previous stations’ data. HIGHLIGHTS The advantages of two WT and EEMD pre-processing techniques and kernel-based model were merged for RSD modeling.; Two states of modeling based on station's own data or previous stations’ data were investigated.; Integrated hybrid techniques outperformed the single GPR method.;Kiyoumars RoushangarMasoumeh ChamaniRoghayeh GhasempourHazi Mohammad AzamathullaFarhad AlizadehIWA Publishingarticleeemdgprpre-processingriver stage-dischargewtWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 6, Pp 3080-3098 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	eemd gpr pre-processing river stage-discharge wt Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	eemd gpr pre-processing river stage-discharge wt Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Kiyoumars Roushangar Masoumeh Chamani Roghayeh Ghasempour Hazi Mohammad Azamathulla Farhad Alizadeh A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
description	The river stage–discharge relationship has an important impact on modeling, planning, and management of river basins and water resources. In this study, the capability of the Gaussian Process Regressions (GPR) kernel-based approach was assessed in predicting the daily river stage–discharge (RSD) relationship. Three successive hydrometric stations of the Housatonic River were considered, and based on the flow characteristics during the period of 2002–2006 several models were developed and tested via GPR. To enhance the applied model efficiency, two pre-processing techniques, namely Wavelet Transform (WT) and Ensemble Empirical Mode Decomposition (EEMD), were used. Also, two states of the RSD modeling were investigated. In state 1, each station's own data was used and in state 2, the upstream stations’ datasets were used as input to model the RSD downstream of the river. The single and integrated model results showed that the integrated WT- and EEMD-GPR models resulted in more accurate outcomes. Data processing enhanced the models' capability between 25% and 40%. The results showed that the RSD modeling in state 1 led to better results; however, when the station's own data were not available the integrated methods could be applied successfully for the RSD modeling using the previous stations’ data. HIGHLIGHTS The advantages of two WT and EEMD pre-processing techniques and kernel-based model were merged for RSD modeling.; Two states of modeling based on station's own data or previous stations’ data were investigated.; Integrated hybrid techniques outperformed the single GPR method.;
format	article
author	Kiyoumars Roushangar Masoumeh Chamani Roghayeh Ghasempour Hazi Mohammad Azamathulla Farhad Alizadeh
author_facet	Kiyoumars Roushangar Masoumeh Chamani Roghayeh Ghasempour Hazi Mohammad Azamathulla Farhad Alizadeh
author_sort	Kiyoumars Roushangar
title	A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
title_short	A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
title_full	A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
title_fullStr	A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
title_full_unstemmed	A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations
title_sort	comparative study of wavelet and empirical mode decomposition-based gpr models for river discharge relationship modeling at consecutive hydrometric stations
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/041be1ee94714725a9bef2be425a3e42
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A comparative study of wavelet and empirical mode decomposition-based GPR models for river discharge relationship modeling at consecutive hydrometric stations

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