曲流河流形态变化分析与预测——以阿萨姆邦巴拉克河为例

IF 1.5 Q4 WATER RESOURCES
Apurba Nath, Susmita Ghosh
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引用次数: 3

摘要

形态学研究对水资源管理、河岸开发和洪水缓解至关重要。在本研究中,利用1990-2020年印度Barak河的Landsat数据,利用曲度指数和河岸侵蚀来检测和量化地貌变化。通过对保护区形态变化的调查,分析现有保护结构对河岸迁移的影响,为制定更好的河堤修复方案提供依据。利用两个测量站的月流量数据,建立了季节自回归综合移动平均(SARIMA)模型。该地区广泛的输沙作用需要对河流流量和形态变化进行研究。开发的SARIMA模型用于预测到2025年的河流流量,并使用2006年至2015年的数据进行训练。对模型(2016-2018)的验证表明,两个测量站流量的平均绝对百分比误差分别为29.78%和23.52%。分析表明,曲度指数与河岸侵蚀成反比。SARIMA模型表明,未来的月流量可能显著高于观测序列,并同时影响河流侵蚀。这种方法适用于许多其他曲流河管理,并确定未来的形态变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meandering rivers’ morphological changes analysis and prediction – a case study of Barak river, Assam
Morphological studies are vital for water resources management, riverbank development, and flood mitigation. In this study, the sinuosity index and bank erosion were used to detect and quantify morphological changes using Landsat data (1990–2020) in the Barak river, India. The morphological changes were investigated in protected areas to analyze the effectiveness of existing protective structures on bank migration, which helps formulate better riverbank restoration plans. Using monthly discharge data from two stream gauge stations, the Seasonal Autoregressive Integrated Moving Average (SARIMA) models were developed. The extensive sediment transportation in the region necessitates studying both the river flow and morphological changes. The developed SARIMA model was used to predict river discharges up to 2025, being trained with data from 2006 to 2015. The validation of the model (2016–2018) shows that the mean absolute percentage error for discharge at two gauging stations is 29.78 and 23.52%, respectively. The analysis shows that the sinuosity index and bank erosion were inversely proportional. The SARIMA model showed that the future monthly discharge in the case study could be substantially higher than the observed series and affect river erosion simultaneously. This approach applies to many other meandering river management and identifies future morphological changes.
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来源期刊
H2Open Journal
H2Open Journal Environmental Science-Environmental Science (miscellaneous)
CiteScore
3.30
自引率
4.80%
发文量
47
审稿时长
24 weeks
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