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

Md Hasanuzzaman , Aznarul Islam , Biswajit Bera , Pravat Kumar Shit
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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. 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Quantifying the riverbank erosion and accretion rate using DSAS model study from the lower Ganga River, India
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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