Estimation and prediction of riverbank erosion and accretion rate using DSAS, BEHI, and REBVI models: evidence from the lower Ganga River in India

Md Hasanuzzaman (), Biswajit Bera (), Aznarul Islam () and Pravat Kumar Shit ()
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Md Hasanuzzaman: Raja N. L. Khan Women’s College (Autonomous)
Biswajit Bera: Sidho Kanho Birsha University
Aznarul Islam: Aliah University, 17 Gorachand Road
Pravat Kumar Shit: Raja N. L. Khan Women’s College (Autonomous)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 118, issue 2, No 13, 1163-1190

Abstract: Abstract The process of riverbank erosion 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 calculate past, present, and future riverbank erosion and accretion (EA) rates using an automated digital shoreline analysis system (DSAS) model of the lower part of the Ganga River in India. Moreover, this study evaluated the EA with bank erosion hazard index (BEHI) and river embankment breaching vulnerability index (REBVI). In this study, satellite images (1973, 1987, 1997, 2007, and 2020) were used for EA rates calculation and field survey data (bank materials, geotechnical parameters, embankment structure, hydraulic pressure, etc.) were used for BEHI and REBVI scores calculation. From 1973 to 2020, the average bank EA rate was found to be 0.119 km/year and 0.046 km/year at the left bank and 0.052 km/year and 0.066 at the right bank. During this period, six villages/mouza (smallest administrative unit of India for revenue collection) were very highly vulnerable due to very high left bank erosion. The long-term prediction (2020–2045) estimates that the average EA rate will be 0.164 km/year and 0.021 km/year at the left bank and 0.031 km/year and 0.045 km/year at the right bank. From this period, 21 villages were highly vulnerable due to very high left bank erosion. Moreover, BEHI and REBVI scores were very high in these villages. RMSE, Student’s t-test, and R2 statistical techniques were used for DSAS model validation. Therefore, RMSE (from 0.103 to 0.247), Student’s t-test, and $$R^{2}$$ R 2 (0.82 for the left bank and 0.79 for the right bank) values justified the acceptance of the model. This study may help decision makers as the spatial guidelines to understand future trends of riverbank EA rates for land-use planning and management strategies to protect riverbanks.

Keywords: Erosion–accretion; DSAS model; BEHI; REBVI; Alluvial channel; Remote sensing (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06044-4

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