River bank erosion risk potential estimation through mechanical and erodibility analysis of soil: A study on left bank of Ganga river near Malda district in West Bengal, India

2020 ◽  
Vol 66 (4) ◽  
pp. 331-346
Author(s):  
Samrat Majumdar ◽  
◽  
Sujit Mondal ◽  
Keyword(s):  
Bank Erosion ◽  
Mechanical Analysis ◽  
Ganga River ◽  
Sieve Analysis ◽  
Left Bank ◽  
River Bank ◽  
Erosion Risk ◽  
River Bank Erosion ◽  
North East ◽  
Basic Parameters

River bank erosion is a hazardous and common phenomenon in diara region near Malda district of North East India during monsoon and post-monsoon periods of every year. One of the significant causes behind the erosion is the textural composition and its arrangement along the river bank. The left bank of Ganga River is texturally very weak along diara region of Malda district. In the present study, the nature of riverbank soil textural composition has been measured by basis parameters analysis and mechanical analysis of soil and its erodibility level. Sieve analysis has been done on all collected soil samples and determines soil basic parameters. The nature of the soil has been derived through the mechanical analysis of particles after Folk and Worst method. Besides that, the degree of soil erodibility has been analyzed through the Bouyoucos Erodibility Index and ROM scale after Roslan and Mazidah. The results show that the erodibility levels become high to the moderate condition along the middle to lower extension of left bank line and relatively low along with upper extension according to ROM scale. Nature of soil along the left bank is dominantly sandy which also indicates the vulnerable condition of bank sites. Basic parameters of soil and its mechanical analysis also reveals that unstable condition exists along with the whole extension of the riverbank line but instability condition is increasing from upper to lower segment of bank line. So the risk of riverbank failure can be measured by determining the textural composition of the soil.

Bank Material Characteristics and its Impact on River Bank Erosion, West Tripura District, Tripura, North-East India

2018 ◽  
Vol 115 (8) ◽  
pp. 1571 ◽  
Author(s):  
Moujuri Bhowmik ◽  
Nibedita Das (Pan) ◽  
Champakali Das ◽  
Istak Ahmed ◽  
Jatan Debnath
Keyword(s):  
Bank Erosion ◽  
River Bank ◽  
North East India ◽  
River Bank Erosion ◽  
North East ◽  
Material Characteristics

scholarly journals Estimation and Prediction of Riverbank Erosion Susceptibility and Shifting Rate Using DSAS, BEHI, and REBVI Models: Evidence from the Lower Ganga River in India

2021 ◽  
Author(s):  
Md. Hasanuzzaman ◽  
Biswajit Bera ◽  
Aznarul Islam ◽  
Pravat Kumar Shit
Keyword(s):  
Land Use Planning ◽  
Anthropogenic Activities ◽  
Hazard Index ◽  
Bank Erosion ◽  
Ganga River ◽  
Hydraulic Pressure ◽  
Left Bank ◽  
River Bank ◽  
Riverbank Erosion ◽  
The Right

Abstract The process of riverbank erosion (RE) is often accelerated by natural events and anthropogenic activities leading to the transformation of this natural process to natural hazard. The present study aims to estimate bank erosion rate and prediction of the lower Ganga River in India using digital shoreline analysis system (DSAS) model. The prediction of RE susceptibility mapping has been generated using three ensemble models such as DSAS, bank erosion hazard index (BEHI), and river embankment breaching vulnerability index (REBVI). For the study satellite images and field data (bank materials, geotechnical parameters, embankment structure, hydraulic pressure etc.) have been used to recognize the river bank position and BEHI and REBVI scores. During 1973-2020, the average bank erosion and accretion rate was found 0.059 km/y and 0.022 km/y at the left bank while 0.026 km/y and 0.046 at the right bank respectively. The prediction results illustrated that the very high vulnerable condition of 06 villages and 21 villages for high vulnerable due to left bank erosion. BEHI and REBVI scores have been the significant performance of understanding and identification of RE vulnerable areas. The long-term (2020-2045) average erosion and deposition rate was predicted at 0.135 km/y and 0.024 km/y at the left bank and 0.043 km/y and 0.045 km/y at the right bank respectively. The prediction accuracy and validation of models were measures by statistical techniques such as student’s t-test, RMSE, and R2 values. This study would be help planners and decision makers the spatial guidelines to understanding future trends of bank erosion and shifting rate for land-use planning and management strategies to protect riverbank.

scholarly journals Assessing the instability of Dong Nai River in Bien Hoa District using Bank Erosion Hazard Index (BEHI) and Remote Sensing and GIS

2019 ◽  
Vol 2 ◽  
pp. 1-5
Author(s):  
Pham Thi Huong Lan ◽  
Le Minh Nguyet ◽  
Le Thi Viet Hoa
Keyword(s):  
Hazard Index ◽  
Bank Erosion ◽  
Strong Relationship ◽  
Quantitative Prediction ◽  
Rooting Depth ◽  
Left Bank ◽  
River Bank ◽  
Surface Protection ◽  
Erosion Hazard ◽  
River Bank Erosion

<p><strong>Abstract.</strong> In this study, a method for developing a quantitative prediction of river bank erosion in Bien Hoa district in Dong Nai River is presented. The river bank erosion hazard index (BEHI) was estimated to assess the stability of the river bank erosion in consultation with bank height, bank slope, rooting depth, rooting density and surface protection. The estimated BEHI of Dong Nai River in Bien Hoa district are high which indicates the riverbank instability. The estimated BEHI along the left bank is about 25&amp;ndash;30. The satellite data of LANSAT TM 5, LANDSAT ETM 7 for the year 1995, 2005 and 2015 were used to assess the nature of shifting of the river bank and to estimate the land loss from river bank. All the derived images were transported on GIS environment to extract the course of the river. 13 sites were considered along the Dong Nai River in Bien Hoa District to estimate the leftward shifting of the bank line and to assess the shifting distance of the river bank line. There is a strong relationship between bank instability BEHI, shifting distance of the bank line and eroded bank area in this study.</p>

Modelling river bank erosion using a 2D depth-averaged numerical model of flow and non-cohesive, non-uniform sediment transport

2016 ◽  
Vol 93 ◽  
pp. 75-88 ◽  
Author(s):  
Kamal El Kadi Abderrezzak ◽  
Andrés Die Moran ◽  
Pablo Tassi ◽  
Riadh Ata ◽  
Jean-Michel Hervouet
Keyword(s):  
Sediment Transport ◽  
Numerical Model ◽  
Bank Erosion ◽  
River Bank ◽  
River Bank Erosion

A review on share of river bank erosion to the total sediment load with increasing catchment size

2021 ◽  
Author(s):  
Ghulam Abbas ◽  
Seifeddine Jomaa ◽  
Michael Rode
Keyword(s):  
Sediment Load ◽  
Bank Erosion ◽  
Surface Erosion ◽  
Sediment Sources ◽  
Catchment Scale ◽  
River Bank ◽  
River Bank Erosion ◽  
Wide Range ◽  
Catchment Size ◽  
Total Sediment

&lt;p&gt;Information on the share of river bank erosion to the total sediment load at catchment scale by using the fingerprinting approach is important to address our knowledge of erosion processes to better target soil erosion control measures. In particular, river bank erosion is affected by many factors such as spatial and temporal variables and is difficult to quantify the relationship of the share of bank erosion to catchment size and upland erosion rate without extensive fieldwork and data analysis. Potential tracers including geochemical, fallout radionuclides, bulk and compound-specific stable isotopes, and magnetic properties have been used, often in combination with sediment source apportionment. In this worldwide review, the global dataset for percent share of river bank and surface erosion using fingerprinting approach was collected to establish the significance of catchment size and other physical controls on river bank erosion. Google Scholar and Web of Science were used to review research articles that included river bank/subsurface as one of the sediment sources in the study areas. This database showed that the UK (n = 84), USA (n = 14) and Brazil (n = 10) had the highest number of catchments, followed by Iran (n = 4), Southern Zambia (n = 1), Australia (n = 1), Spain (n = 1), Mongolia (n = 1) and Burkina Faso (n = 1) ranging in size from 0.31 to 15000 km&lt;sup&gt;2&lt;/sup&gt;, predominately agriculture. Based on published studies, there is a clear shift of sediment sources from surface erosion to river bank erosion with increasing catchment size. The results show the wide range of relative contributions of surface and river bank sources to the catchment sediment yield around the globe. There are a number of catchments with river bank contribution exceeding 25% and surface contribution exceeding 90% of total sediment loss. This diversity highlights the many factors that influence river bank erosion. In addition to the wide range, sediment source contribution in the range 1-25% from river bank is generally representative around the World. We recommend that long term monitoring of sediment load and surface and river bank sources at nested sites within a catchment are indispensable. Furthermore, limited information on the share of sources often makes it difficult to target mitigation measures reducing sediment loads at the catchment scale.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;Sediment load, catchment size, fingerprinting approach, river bank share&lt;/p&gt;

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