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.

scholarly journals Use of Radarsat-2 and Landsat TM Images for Spatial Parameterization of Manning’s Roughness Coefficient in Hydraulic Modeling

2015 ◽  
Vol 7 (1) ◽  
pp. 836-864 ◽  
Author(s):  
Joseph Mtamba ◽  
Rogier van der Velde ◽  
Preksedis Ndomba ◽  
Vekerdy Zoltán ◽  
Felix Mtalo
Keyword(s):  
Hydraulic Modeling ◽  
Landsat Tm ◽  
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 Impact of initial conditions on the prediction of the spread of thermal pollution in rivers

2018 ◽  
Vol 40 ◽  
pp. 05048
Author(s):  
Monika B. Kalinowska ◽  
Pawel M. Rowiński ◽  
Artur Magnuszewski
Keyword(s):  
Open Channel ◽  
Flow Model ◽  
River Flow ◽  
Initial Conditions ◽  
Two Dimensional ◽  
River Temperature ◽  
Heated Water ◽  
Different Temperatures ◽  
Rivmix Model ◽  
Water Depths

The influence of initial conditions on the prediction of the increase of river temperature below the point of release of heated water for a designed power plant has been analysed in this study. The results for different assumed values of river flow and different temperatures of the discharged heated water have been presented. The results have been analysed taking into account existing legal frames. The two-dimensional inhouse RivMix model has been used to simulate the temperature distribution whereas the two-dimensional depth-averaged turbulent open channel flow model CCHE2D has been used to simulate the velocity fields and the water depths for the selected flows of the river.

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

Decentralisation of the Emscher sewerage system - expansion of the Emscher mouth treatment plant

1996 ◽  
Vol 33 (12) ◽  
pp. 19-28
Author(s):  
Burkhard Teichgräber ◽  
Ulrich Hermanns
Keyword(s):  
Waste Water ◽  
Treatment Plant ◽  
Nitrogen And Phosphorus ◽  
Pilot Studies ◽  
The North ◽  
The North Sea ◽  
Water Courses ◽  
The Subject ◽  
Aeration Volume ◽  
Bodies Of Water

Since the beginning of the 20th Century, the Emscher and its tributaries have been operated as open waste water courses (Emscher System). Between 1966 and 1977, the Emscher Mouth Treatment Plant was constructed for the biological treatment of domestic and industrial discharge from the 774 square kilometre Emscher catchment area. The plant was designed for 5 million population equivalents. Since the beginning of the Nineties, the Waste Water Management Regulations require, apart from the elimination of carbon, also the elimination of nitrogen and phosphorus, in order to reduce, as far as possible, the load on natural, flowing bodies of water and to protect the North Sea. While the COD values are observed with a narrow margin, the nitrogen values make it necessary to expand the aeration volume of the Emscher Mouth Treatment Plant by 50% to 216,000 m3. For this purpose, comprehensive studies, as well as pilot studies on the subject of filtration, have been carried out. Construction of the new aeration tanks was begun in spring 1993. The expansion will be completed at the end of 1996. Investments totalling 102 million DM are required.

scholarly journals Applying micro-genetic algorithm in the one-dimensional unsteady hydraulic model for parameter optimization

2013 ◽  
Vol 16 (4) ◽  
pp. 772-783 ◽  
Author(s):  
Tsun-Hua Yang ◽  
Yu-Chi Wang ◽  
Shun-Chung Tsung ◽  
Wen-Dar Guo
Keyword(s):  
Evaluation Criteria ◽  
Hydraulic Modeling ◽  
Hydraulic Model ◽  
Roughness Coefficient ◽  
Limited Information ◽  
Good Tool ◽  
Physical Conditions ◽  
The One ◽  
Flow Quantity ◽  
River Meandering

Selection of an appropriate value for Manning's roughness coefficient could significantly impact the accuracy of a hydraulic model. However, it is highly variable and depends on flow circumstances, such as water stage and flow quantity; a stream's geomorphology, such as the fluvial process and river meandering; and physical conditions, such as the channel surface roughness and irregularities. Nevertheless, choosing proper roughness coefficients is not easy, especially with limited information and time in a practical application. Even it is done for a specific event it may not apply to another event due to its time- and site-dependency. This study proposes a Visual Basic (VB)-based system, which integrates the HEC-RAS modeling tool and the μGA to efficiently search for Manning's roughness coefficients. The matching coefficients will thereafter improve the accuracy of hydraulic modeling. Two events in the Yilan River Basin were applied to test the feasibility of the system and four evaluation criteria were used to evaluate the system performance. The results showed that μGA efficiently converged and the hydraulic model showed good agreement in comparison with the measured data. The system can be used as a good tool for finding onsite Manning's roughness coefficients in hydraulic modeling when detailed information is not available.

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 Conceptual Basics of Standardization of Ecological and Free Flow for Rivers in Kazakhstan

2020 ◽  
pp. 52-73
Keyword(s):  
River Flow ◽  
Water Bodies ◽  
Free Flow ◽  
Ecological Safety ◽  
Transboundary Water ◽  
Methods Of Determination ◽  
Flow Parameters ◽  
Ecological Flow ◽  
Water Courses

The article presents methodical proposals concerning replacement of the approved norms for calculation of sanitary releases from reservoirs for ecological flow, proposals for the methods of determination of the ecological flow parameters that could be accepted for Kazakhstan for the river flow regulating. We tried to use the developed methodical principles based on ecological safety for determination of scientifically proved quantitative dependencies and norms of the flow permissible withdrawal for the main rivers of Kazakhstan. Within the framework of the performed studies Kazakhstan as the Chairperson of the Convention on Transboundary Water Courses and Water Bodies of the UN EEC intends to present the methods for determination of ecological flow and permissible river flow withdrawal for discussion.

scholarly journals Using Optimisation Meta-Heuristics for the Roughness Estimation Problem in River Flow Analysis

2021 ◽  
Vol 11 (22) ◽  
pp. 10575
Author(s):  
Antonio Agresta ◽  
Marco Baioletti ◽  
Chiara Biscarini ◽  
Fabio Caraffini ◽  
Alfredo Milani ◽  
...  
Keyword(s):  
Cross Sections ◽  
Computational Models ◽  
River Flow ◽  
Heuristic Algorithms ◽  
Flow Analysis ◽  
Differential Evolution Algorithm ◽  
Optimal Estimation ◽  
Evolution Strategy ◽  
Computational Time ◽  
Roughness Coefficient

Climate change threats make it difficult to perform reliable and quick predictions on floods forecasting. This gives rise to the need of having advanced methods, e.g., computational intelligence tools, to improve upon the results from flooding events simulations and, in turn, design best practices for riverbed maintenance. In this context, being able to accurately estimate the roughness coefficient, also known as Manning’s n coefficient, plays an important role when computational models are employed. In this piece of research, we propose an optimal approach for the estimation of ‘n’. First, an objective function is designed for measuring the quality of ‘candidate’ Manning’s coefficients relative to specif cross-sections of a river. Second, such function is optimised to return coefficients having the highest quality as possible. Five well-known meta-heuristic algorithms are employed to achieve this goal, these being a classic Evolution Strategy, a Differential Evolution algorithm, the popular Covariance Matrix Adaptation Evolution Strategy, a classic Particle Swarm Optimisation and a Bayesian Optimisation framework. We report results on two real-world case studies based on the Italian rivers ‘Paglia’ and ‘Aniene’. A comparative analysis between the employed optimisation algorithms is performed and discussed both empirically and statistically. From the hydrodynamic point of view, the experimental results are satisfactory and produced within significantly less computational time in comparison to classic methods. This shows the suitability of the proposed approach for optimal estimation of the roughness coefficient and, in turn, for designing optimised hydrological models.

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