scholarly journals Estimation of Manning’s Roughness Coefficient Through Calibration Using HEC-RAS Model: A Case Study of Rohri Canal, Pakistan

2021 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Shan-e-hyder Soomro ◽  
Caihong Hu ◽  
Muhammad Munir Babar ◽  
Mairaj Hyder Alias Aamir
Keyword(s):  
Roughness Coefficient ◽  
Manning’S Roughness Coefficient

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.

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.

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 Effect of aquatic vegetation on Manning´s roughness coefficient value – Case study at the Šúrsky channel

2020 ◽  
Vol 21 (1) ◽  
pp. 123-129
Author(s):  
Radoslav Schügerl ◽  
Yvetta Velísková ◽  
Valentín Sočuvka ◽  
Renáta Dulovičová
Keyword(s):  
Aquatic Vegetation ◽  
Roughness Coefficient

Scale effect on the anisotropy characteristics of rock joint roughness

2021 ◽  
pp. qjegh2020-066
Author(s):  
Shi-Gui Du ◽  
Kai-Qian Du ◽  
Rui Yong ◽  
Jun Ye ◽  
Zhan-You Luo
Keyword(s):  
Scale Effect ◽  
Rock Joint ◽  
Rock Joints ◽  
Roughness Coefficient ◽  
Scale Dependency ◽  
Joint Roughness Coefficient ◽  
Local Anisotropy ◽  
Joint Roughness ◽  
Threshold Length

Accurate assessment of anisotropy and scale effect of rock joint roughness is essential for evaluating the mechanical behaviour of rock joints. However, in previous studies, how to quantify roughness anisotropy of rock joints remains largely unsolved, and the research about scale effect on roughness anisotropy is not conclusive. A statistical analysis on joint roughness coefficient of different sized profiles was implemented to investigate the scale-dependency of joint roughness. The scale effect on the roughness anisotropy were investigated based on class ratio transform approach. The roughness anisotropy was characterized by local anisotropy and global anisotropy. The global anisotropy tends to be almost constant when the sample size exceeds the stationarity threshold length of 70 cm. The result shows that the global anisotropy is scale-dependent. However, the scale effect on local anisotropy is less apparent. The case study indicates that the class ratio transform approach implies its superiority in roughness anisotropy investigation.

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