Quantifying the riverbank erosion and accretion rate using DSAS model study from the lower Ganga River, India

Md Hasanuzzaman , Aznarul Islam , Biswajit Bera , Pravat Kumar Shit
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Abstract

Assessing the erosion and accretion (EA) rate of the lower Ganga River in India is crucial for scientific planning and implementing development activities in river basin management. The current study utilized the digital shoreline analysis system (DSAS model) to measure the erosion and accretion rate from 1972 to 2022. The objective was to quantify the spatiotemporal variation of erosion vulnerability and project future trends at the village level to support different developmental programs. Satellite images and field survey data were employed to analyze the EA rates. The results indicated a significantly higher average erosion rate of 0.0583 ​km/year on the left banks compared to the right bank in the study area. The net shoreline movement (NSM) analysis demonstrated that erosion on the left bank occurred at an average distance of approximately 2.91 ​km, which was twice as high as the erosion on the right bank. Furthermore, the findings suggested a consistent trend of increasing erosion rates that are projected to continue until 2042. It is noteworthy that the study identified a majority of highly erosional villages (92.86% of the villages) located on the left bank of the river, particularly upstream from the Farakka barrage. The DSAS model underwent validation using RMSE, T-test, ROC, and R2 techniques, confirming its acceptance with satisfactory results. In summary, this research introduces a new technique and framework for accurately measuring EA rates and making future predictions for management projects.
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利用 DSAS 模型对印度恒河下游河岸侵蚀和增生率进行量化研究
评估印度恒河下游的侵蚀和淤积(EA)速率对流域管理的科学规划和实施发展活动至关重要。本研究利用数字海岸线分析系统(DSAS模型)测量了1972 - 2022年的侵蚀和增生速率。目的是量化侵蚀脆弱性的时空变化,并在村庄层面预测未来趋势,以支持不同的发展计划。采用卫星影像和野外调查资料对EA率进行分析。结果表明,研究区左岸的平均侵蚀速率为0.0583 km/年,显著高于右岸。净岸线运动(NSM)分析表明,左岸的侵蚀发生在平均约2.91 km的距离上,是右岸的2倍。此外,研究结果表明,预计到2042年,侵蚀率将持续上升。值得注意的是,该研究确定了大多数高度侵蚀的村庄(92.86%的村庄)位于河的左岸,特别是在法拉卡拦河坝上游。采用RMSE、t检验、ROC和R2技术对DSAS模型进行了验证,结果令人满意。总之,这项研究引入了一种新的技术和框架,用于准确地测量EA率,并为管理项目做出未来的预测。
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