Seied Hosein Afzali

Dr. Seied Hosein Afzali

Department of Civil Engineering, School of Engineering, Shiraz University, Zand Blvd., Shiraz, Iran
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Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 September 2023 in Water Resources Management
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Journal Article
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RPReza Piraei
Reza Piraei
Seied Hosein AfzaliSeied Hosein Afzali
Seied Hosein Afzali
Majid NiazkarMajid Niazkar
Majid Niazkar

1 August 2018 in Food and Chemical Toxicology
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Journal Article
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MSMarjan Salari
Marjan Salari
ESEsmaeel Salami Shahid
Esmaeel Salami Shahid
Seied Hosein AfzaliSeied Hosein Afzali
Seied Hosein Afzali
MEMajid Ehteshami
Majid Ehteshami
Gea Oliveri ContiGea Oliveri Conti
Gea Oliveri Conti
SSSolmaz Nikbakht Sheibani
Solmaz Nikbakht Sheibani

1 April 2015 in Journal of Hydrologic Engineering
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Journal Article
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Majid NiazkarMajid Niazkar
Majid Niazkar
Seied Hosein AfzaliSeied Hosein Afzali
Seied Hosein Afzali


18 January 2017 in Computer Applications in Engineering Education
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Majid NiazkarMajid Niazkar
Majid Niazkar
Seied Hosein AfzaliSeied Hosein Afzali
Seied Hosein Afzali

1 November 2017 in KSCE Journal of Civil Engineering
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Journal Article
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Majid NiazkarMajid Niazkar
Majid Niazkar
Seied Hosein AfzaliSeied Hosein Afzali
Seied Hosein Afzali
The Muskingum model has been widely utilized for flood routing by water resources engineers for decades. Since the relation between channel storage and weighted summation of inflow and outflow seems to be nonlinear, a constant exponent parameter is used to account for this nonlinearity. On the other hand, the nonlinear Muskingum models with constant parameters cannot address variation of Muskingum parameters during flood period. In this paper, fourteen new Muskingum models with variable parameters are proposed. In these models, the routing period is divided into two or three sub-periods and the proposed versions of the Muskingum models can possess parameters with different values in these sub-periods. This capability enhances the Muskingum flood routing approach to better capture the reach characteristics and subsequently improve the routing results. The flood routing results for the selected data set demonstrate that three variable-parameter model reduces the SSQ value more than 89% comparing with the best three constant-parameter Muskingum model in the literature. Additionally, it was concluded that considering x-parameter as a variable parameter during a flood period affects the parameter estimation more than imposing the K- and m-parameters to be variable.