Determination of manning's roughness coefficient for dhaleshwari river using hec-ras

2018 ◽  
Vol 7 (2) ◽  
pp. 17
Author(s):  
Tasmiah Ahsan ◽  
M. A. Matin
Keyword(s):  
Roughness Coefficient ◽  
Manning’S Roughness Coefficient

scholarly journals A New Method for Determination of Joint Roughness Coefficient of Rock Joints

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Shigui Du ◽  
Huicai Gao ◽  
Yunjin Hu ◽  
Man Huang ◽  
Hua Zhao
Keyword(s):  
Scale Effect ◽  
Fractal Model ◽  
Rock Joints ◽  
Effective Length ◽  
Roughness Coefficient ◽  
Joint Roughness Coefficient ◽  
Joint Roughness ◽  
Exposed Rock ◽  
Study Results

The joint roughness coefficient (JRC) of rock joints has the characteristic of scale effect. JRC measured on small-size exposed rock joints should be evaluated by JRC scale effect in order to obtain the JRC of actual-scale rock joints, since field rock joints are hardly fully exposed or well saved. Based on the validity analysis of JRC scale effect, concepts of rate of JRC scale effect and effective length of JRC scale effect were proposed. Then, a graphic method for determination of the effective length of JRC scale effect was established. Study results show that the JRC of actual-scale rock joints can be obtained through a fractal model of JRC scale effect according to the statistically measured results of the JRC of small-size partial exposed rock joints and by the selection of fractal dimension of JRC scale effect and the determination of effective length of JRC scale effect.

scholarly journals Field and Laboratory-based Approach for the Determination of Friction Angle of Geological Discontinuities of Malaysian Granites

2011 ◽  
Vol 28 (2) ◽  
pp. 151 ◽  
Author(s):  
R. A Ghani ◽  
T. L Goh ◽  
A. M Hariri ◽  
Y. N Baizura
Keyword(s):  
Friction Angle ◽  
Roughness Coefficient ◽  
Average Value ◽  
Peak Friction Angle ◽  
Maximum Value ◽  
Wide Range ◽  
Discontinuity Surfaces ◽  
Geological Discontinuities ◽  
Range Of Values

The basic friction angle, Φb for artificially sawn discontinuity planes for fresh granite, as determined by tilt testing, has an average value of 30º. For the natural rough discontinuity surfaces, a wide range of values have been determined for the peak friction angle, Φpeak ranging from 47º to a maximum value of 80º, depending on the joint roughness coefficient (JRC). The average values of the friction angles for the different degrees of roughness were as follows: JRC 2–4 = 58°; JRC 6–8 = 60°; JRC 8–10 = 47°; JRC 12–14 = 60°; JRC 14–16 = 71° ; JRC 18–20 = 80°.

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.

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