Flow patterns and bed changes due to traditional river training structures “Seigyu”

2020 ◽  
pp. 936-944
Author(s):  
S.A. Kantoush ◽  
M.M. Al Mamari ◽  
Y. Takemon ◽  
M. Saber ◽  
O. Habiba ◽  
...  
Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2588 ◽  
Author(s):  
Maarten van der Wal

The planform of the Brahmaputra-Jamuna River followed its natural path in Bangladesh until the construction of bank protection works started to save Sirajganj from bank erosion since the 1930s. Several so-called hardpoints such as groynes and revetments were constructed in the period 1980–2015 and the Jamuna Multipurpose Bridge was opened in 1998. The Brahmaputra Right Embankment and other projects had saved the western flood plain from inundation during monsoon floods. These river training works experienced severe damage by geotechnical failures, mostly flow slides. A flow slide is an underwater slope failure because of liquefaction or a breaching process in the subsoil or a combination of both. The design of most of these training works did not consider the risk of damage by flow slides. All descriptions of the observed damages show that scour phenomena in the channel close to a river training work are a cause of flow slides, besides pore water outflow. The research question was: how can the design of river training works be improved to reduce the risk of damage by flow slides? The main part of the investigation was focussed on reducing local scour holes near river training works. The most promising results are river training works with gentle bank slopes, permeable groynes, bed protections in dredged trenches with gentle side slopes, and methods to increase locally the bearing capacity of the subsoil. It is recommended to increase the knowledge of the failure mechanisms in the Brahmaputra-Jamuna River by improved monitoring in the field, the setup of a database with descriptions of all observed flow slides and the circumstances in which they occur. In addition to these recommendations, a field test facility is proposed to verify the knowledge of the failure mechanisms in that river. These activities will optimise the design of new river training structures with a very low risk of damages by flow slides and geotechnical instabilities and they will contribute to an improvement of the current design guidelines for river training structures.


1992 ◽  
Vol 19 (6) ◽  
pp. 1049-1061 ◽  
Author(s):  
P. F. Doyle

The durability of several common bank protection methods used as less expensive or environmentally acceptable alternatives to toe-trenched angular rock riprap has been documented during the 1980s at seven typical bank erosion sites in British Columbia. Since the sites were uncontrolled examples of actual river training works in operation, natural events hindered a precise comparison of each scheme with toe-trenched angular rock riprap protection. However, of the four alternatives investigated – gravel dykes, tree revetments, riprap with toe apron, and semi-round riprap – all but semi-round riprap performed less than satisfactorily over the years of observation. Documentation of performance is sufficient to conclude that on steep gravel-bed rivers, gravel dykes do not endure; tree revetments require constant maintenance and will not endure large floods, unless extremely well-constructed; toe aprons are not as reliable as toe trenches for the same volume of rock; and well-placed, large semi-round rock performs well under moderately severe attack. Key words: erosion, bank protection, channel stability, river training structures, gravel-bed.


Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1680 ◽  
Author(s):  
Xianglong Wei ◽  
Yongjun Lu ◽  
Zhili Wang ◽  
Xingnian Liu ◽  
Siping Mo

Little research has been done on the application of machine learning approaches to evaluating the damage level of river training structures on the Yangtze River. In this paper, two machine learning approaches to evaluating the damage level of spur dikes with tooth-shaped structures are proposed: a supervised support vector machine (SVM) model and an unsupervised model combining a Kohonen neural network with an SVM model (KNN-SVM). It was found that the supervised SVM model predicted the damage level of the validation samples with high accuracy, and the unsupervised data-mining KNN-SVM model agreed well with the empirical evaluation result. It is shown that both machine learning approaches could become effective tools to evaluate the damage level of spur dikes and other river training structures.


2020 ◽  
pp. 79-96
Author(s):  
Davor Kvočka

River training structures, such as dikes and chevrons, are commonly used for improving riparian navigation conditions. These structures are usually submerged under most flows and are aligned at variable angles to the main river flow direction. In this study, two different approaches for two-dimensional hydraulic modelling of submerged dikes and chevrons in MIKE 21 Flow Model FM have been analysed: (i) by representing the geometry of the structures explicitly in the bathymetry of the river channel (i.e. bathymetry approach), and (ii) by utilising the “dike” sub-grid module, where the flow past a structure is calculated by employing an empirical discharge relationship (i.e. dike module approach). The model results have been compared to theoretical and empirical studies, as well as to field observations and measurements. The obtained results indicate that the bathymetry approach is the more appropriate method for simulating predominantly submerged river training structures. However, these types of models should be used only for general assessment of potential river engineering solutions. For more detailed analysis of solution options, more complex models are recommended, e.g. three-dimensional hydrodynamic models.


1990 ◽  
Vol 22 (5) ◽  
pp. 167-172 ◽  
Author(s):  
F. László ◽  
Zs Homonnay ◽  
M. Zimonyi

The impacts of river training and gravel dredging on the quality of bank filtered waters are considered along the Danube sections upstream and downstream of Budapest, where important sources of drinking water are situated. Case studies are presented to show that training structures and dredging operations affect the hydraulic conditions in the river that are conducive to silting in areas with reduced flow velocities. Adverse hydrochemical changes occur in the silted filter layer, especially the dissolution of iron and manganese,and higher concentrations of ammonium-ion are observable. Dredging tends to disrupt the biologically active filter layer, while the ensuing bed degradation causes changes in the inflow ratio, increasing the proportion of polluted groundwater from the background areas in the wells.


2020 ◽  
Vol 56 (4) ◽  
Author(s):  
Lu Wang ◽  
Bruce W. Melville ◽  
Asaad Y. Shamseldin ◽  
Ruihua Nie

Sign in / Sign up

Export Citation Format

Share Document