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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for f...

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Main Authors:	Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed
Format:	Article
Published:	MDPI 2018
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.um.edu.my/22087/ https://doi.org/10.3390/w10091130
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spelling	my.um.eprints.220872019-08-27T02:10:33Z http://eprints.um.edu.my/22087/ Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm Farzin, Saeed Singh, Vijay Karami, Hojat Farahani, Nazanin Ehteram, Mohammad Kisi, Ozgur Allawi, Mohammed Falah Mohd, Nuruol Syuhadaa El-Shafie, Ahmed TA Engineering (General). Civil engineering (General) Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). The major function of the IBA is to optimize the estimated value of the three-parameters associated with the Muskingum model. The IBA acts based on the chaos search tool, which mainly enhances the uniformity and erogidicty of the population. In addition, the current research, unlike the other existing models which consider flood routing, is based on dividing one reach to a few intervals to increase the accuracy of flood routing models. Three case studies with lateral flow were considered for this study, including the Wilson flood, Karahan flood, and Myanmar flood. Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. In addition, increasing the number of intervals for flood routing significantly improved the accuracy of the results. The results indicated that the Sum of Absolute Deviations (SAD) using IBA for the Karahan flood was 117, which had reduced by 83%, 88%, 94%, and 12%, compared to the PSO, GA, HS, and BA, respectively. Furthermore, the achieved results for the Myanmar flood showed that SSD for IBA relative to GA, BA, and PSO was reduced by 32%, 11%, and 42%, respectively. In conclusion, the proposed Muskingum Model integrated with IBA considering the existence of lateral flow, outperformed the existing applied simple Muskingum models in previous studies. In addition, the more the number of intervals used in the model, the better the accuracy of flood routing prediction achieved. MDPI 2018 Article PeerReviewed Farzin, Saeed and Singh, Vijay and Karami, Hojat and Farahani, Nazanin and Ehteram, Mohammad and Kisi, Ozgur and Allawi, Mohammed Falah and Mohd, Nuruol Syuhadaa and El-Shafie, Ahmed (2018) Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm. Water, 10 (9). p. 1130. ISSN 2073-4441 https://doi.org/10.3390/w10091130 doi:10.3390/w10091130
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Farzin, Saeed Singh, Vijay Karami, Hojat Farahani, Nazanin Ehteram, Mohammad Kisi, Ozgur Allawi, Mohammed Falah Mohd, Nuruol Syuhadaa El-Shafie, Ahmed Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
description	Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). The major function of the IBA is to optimize the estimated value of the three-parameters associated with the Muskingum model. The IBA acts based on the chaos search tool, which mainly enhances the uniformity and erogidicty of the population. In addition, the current research, unlike the other existing models which consider flood routing, is based on dividing one reach to a few intervals to increase the accuracy of flood routing models. Three case studies with lateral flow were considered for this study, including the Wilson flood, Karahan flood, and Myanmar flood. Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. In addition, increasing the number of intervals for flood routing significantly improved the accuracy of the results. The results indicated that the Sum of Absolute Deviations (SAD) using IBA for the Karahan flood was 117, which had reduced by 83%, 88%, 94%, and 12%, compared to the PSO, GA, HS, and BA, respectively. Furthermore, the achieved results for the Myanmar flood showed that SSD for IBA relative to GA, BA, and PSO was reduced by 32%, 11%, and 42%, respectively. In conclusion, the proposed Muskingum Model integrated with IBA considering the existence of lateral flow, outperformed the existing applied simple Muskingum models in previous studies. In addition, the more the number of intervals used in the model, the better the accuracy of flood routing prediction achieved.
format	Article
author	Farzin, Saeed Singh, Vijay Karami, Hojat Farahani, Nazanin Ehteram, Mohammad Kisi, Ozgur Allawi, Mohammed Falah Mohd, Nuruol Syuhadaa El-Shafie, Ahmed
author_facet	Farzin, Saeed Singh, Vijay Karami, Hojat Farahani, Nazanin Ehteram, Mohammad Kisi, Ozgur Allawi, Mohammed Falah Mohd, Nuruol Syuhadaa El-Shafie, Ahmed
author_sort	Farzin, Saeed
title	Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
title_short	Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
title_full	Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
title_fullStr	Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
title_full_unstemmed	Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
title_sort	flood routing in river reaches using a three-parameter muskingum model coupled with an improved bat algorithm
publisher	MDPI
publishDate	2018
url	http://eprints.um.edu.my/22087/ https://doi.org/10.3390/w10091130
_version_	1643691748626530304
score	13.211869

Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

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