scholarly journals NUMERICAL SIMULATION OF MANNING'S ROUGHNESS COEFFICIENT OF COMPOUND RIVER CHANNEL

2008 ◽  
Vol 52 ◽  
pp. 769-774
Author(s):  
Masahiro TAMAI ◽  
Satoshi TEDUKA
Keyword(s):  
Numerical Simulation ◽  
River Channel ◽  
Roughness Coefficient ◽  
Manning’S Roughness Coefficient

scholarly journals Calibration method for Manning's roughness coefficient for a river flume model

2020 ◽  
Vol 20 (8) ◽  
pp. 3597-3603
Author(s):  
Yujian Li ◽  
Yixin Geng ◽  
Liang Mao
Keyword(s):  
Numerical Simulation ◽  
Error Analysis ◽  
Water Surface ◽  
Calibration Method ◽  
Empirical Method ◽  
Tarim River ◽  
Roughness Coefficient ◽  
Flume Experiments ◽  
N Value ◽  
Manning’S Roughness Coefficient

Abstract This paper takes the Tarim River as an example to study the selection of Manning's roughness coefficient (n) in numerical simulation and presents a new method for calibrating Manning's roughness coefficient of a flume model. The measured topographic data and hydraulic data obtained from the flume experiments are taken as the initial boundary conditions in flow simulation, and n value for a flume model of the Qiman reach of Tarim River is calibrated by using a CCHE2D model. The consistency between the simulated water surface and the measured water surface with different n value is compared by using the error analysis method. Manning's n value for a flume model which meets the minimum error requirements is determined. The relative error between n value obtained by the empirical method and n value obtained by the numerical simulation method is analyzed. The result shows that the calibration method of n value for a flume model by using the CCHE2D model and error analysis presented in this paper is feasible and reliable.

scholarly journals Automated calibration of a two-dimensional overland flow model by estimating Manning's roughness coefficient using genetic algorithm

2017 ◽  
Vol 20 (2) ◽  
pp. 440-456
Author(s):  
J. Drisya ◽  
D. Sathish Kumar
Keyword(s):  
Genetic Algorithm ◽  
Flow Model ◽  
Overland Flow ◽  
Fitness Function ◽  
Roughness Coefficient ◽  
Model Parameters ◽  
Automatic Data ◽  
Automated Calibration ◽  
Manning’S Roughness Coefficient ◽  
Overland Flow Model

Abstract Calibration is an important phase in the hydrological modelling process. In this study, an automated calibration framework is developed for estimating Manning's roughness coefficient. The calibration process is formulated as an optimization problem and solved using a genetic algorithm (GA). A heuristic search procedure using GA is developed by including runoff simulation process and evaluating the fitness function by comparing the experimental results. The model is calibrated and validated using datasets of Watershed Experimentation System. A loosely coupled architecture is followed with an interface program to enable automatic data transfer between overland flow model and GA. Single objective GA optimization with minimizing percentage bias, root mean square error and maximizing Nash–Sutcliffe efficiency is integrated with the model scheme. Trade-offs are observed between the different objectives and no single set of the parameter is able to optimize all objectives simultaneously. Hence, multi-objective GA using pooled and balanced aggregated function statistic are used along with the model. The results indicate that the solutions on the Pareto-front are equally good with respect to one objective, but may not be suitable regarding other objectives. The present technique can be applied to calibrate the hydrological model parameters.

Numerical Simulation of Petroleum Spreading in a Complex River Channel

2021 ◽  
Author(s):  
Dongliang Yu ◽  
Ji Wang ◽  
Quan Cao ◽  
Xinglong Zhang ◽  
Xueguang Liu
Keyword(s):  
Numerical Simulation ◽  
River Channel

scholarly journals Manning’s roughness coefficient for the Doce River

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Emmanuel Kennedy da Costa Teixeira ◽  
Márcia Maria Lara Pinto Coelho ◽  
Eber José de Andrade Pinto ◽  
Jéssica Guimarães Diniz ◽  
Aloysio Portugal Maia Saliba
Keyword(s):  
River Flow ◽  
Hydraulic Modeling ◽  
Roughness Coefficient ◽  
Local Approach ◽  
Water Courses ◽  
Time Variations ◽  
The Subject ◽  
Manning’S Roughness Coefficient ◽  
Doce River ◽  
Water Depths

ABSTRACT The Manning’s roughness coefficient is used for various hydraulic modeling. However, the decision on what value to adopt is a complex task, especially when dealing with natural water courses due to the various factors that affect this coefficient. For this reason, most of the studies carried out on the subject adopt a local approach, such as this proposal for the Doce River. Due to the regional importance of this river in Brazil, the objective of this article was to estimate the roughness coefficient of Manning along the river, in order to aid in hydraulic simulations, as well as to discuss the uncertainties and variations associated with this value. For this purpose, information on flow rates and water depths were collected at river flow stations along the river. With this information, the coefficients were calculated using the Manning equation, using the software Canal, and their space-time variations were observed. In addition, it was observed that the uncertainties in flow and depth measurements affect the value of the Manning coefficient in the case studied.

Research on the Numerical Simulation of Silting in Floodplain and Scouting in Main Channel of Over-Bank Flooding in the Lower Yellow River

2011 ◽  
Vol 255-260 ◽  
pp. 3692-3696
Author(s):  
Xiao Lei Zhang ◽  
Dong Po Sun ◽  
Feng Ran Zhang
Keyword(s):  
Numerical Simulation ◽  
Mathematical Model ◽  
Yellow River ◽  
Main Channel ◽  
River Channel ◽  
Lower Yellow River ◽  
The Lower Yellow River ◽  
Water And Sediment ◽  
Simulation Results ◽  
Set Up

The 2-D water and sediment mathematical model which reflects silting in floodplain and scouting in main channel of over-bank flooding in the Lower Yellow River has been set up in this paper. Through carrying on 2-D water and sediment numerical simulation of the “96.8” typical flood, the author studied influence of over-bank flooding on flood travel and transverse exchange. The primary simulation results show that, adopting the over-bank flooding for silting in floodplain and scouting in main channel effectively guaranteed and expanded transverse exchange between floodplain and main channel and maintained the river channel vigor. This can relieve “secondary suspended river” states in the Low Yellow River to a certain extent; at the same time, the different magnitudes of over-bank floods have different effect of silting in floodplain and scouting in main channel.

Manning's roughness coefficient for ecological subsurface channel with modules

2019 ◽  
Vol 18 (3) ◽  
pp. 349-361 ◽  
Author(s):  
Reza Mohammadpour ◽  
Muhammad Kashfy Zainalfikry ◽  
Nor Azazi Zakaria ◽  
Aminuddin Ab. Ghani ◽  
Ngai Weng Chan
Keyword(s):  
Roughness Coefficient ◽  
Manning’S Roughness Coefficient

Manning’s N Value of Bridge-in-Backpack

2014 ◽  
Vol 638-640 ◽  
pp. 965-968
Author(s):  
Jing Ma ◽  
Ling Qiang Yang
Keyword(s):  
Water Flow ◽  
Roughness Coefficient ◽  
N Value ◽  
New Type ◽  
Manning’S Roughness Coefficient ◽  
Manning’S N ◽  
Manning's N

Bridge-in-a-Backpack is a new type bridge. this study will investigate the interaction of flow under the bridge with the tubes and decking, and recommend Manning’s roughness coefficient for water flow under the composite backbridge system.

scholarly journals The Numerical Simulation of Shallow Water: Estimation of the Roughness Coefficient on the Flood Stage

2013 ◽  
Vol 5 ◽  
pp. 787016 ◽  
Author(s):  
Sergey S. Khrapov ◽  
Andrey V. Pisarev ◽  
Ivan A. Kobelev ◽  
Artur G. Zhumaliev ◽  
Ekaterina O. Agafonnikova ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Shallow Water ◽  
Roughness Coefficient
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