• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

河流动力学 - 利用陆地卫星遥感数据和 GIS 对孟加拉国 1973-2019 年期间的雅鲁藏布江(布拉马普特拉河)进行的地理空间分析。

River dynamics - a geospatial analysis of Jamuna (Brahmaputra) River in Bangladesh during 1973-2019 using Landsat satellite remote sensing data and GIS.

机构信息

Dept. of Geography and Environmental Studies, University of Rajshahi, Rajshahi, 6205, Bangladesh.

出版信息

Environ Monit Assess. 2022 Nov 10;195(1):96. doi: 10.1007/s10661-022-10638-z.

DOI:10.1007/s10661-022-10638-z
PMID:36355262
Abstract

The present study is designed to illuminate the dynamics of the Jamuna River in Bangladesh for 46 years, from 1973 to 2019. About 240 km of the Jamuna River course was assessed using remote sensing and GIS. Landsat remote sensing imageries were processed, and bank lines were extracted and analysed using GIS. The main objective of the study was to understand the pattern of bed movement of the Jamuna River. The river dynamics were assessed based on bank erosion, accretion, bank line shifts, channel width, and river course and confluence shift. Area vulnerable to erosion was assessed using historical erosion rate and trend analysis. The result revealed that the river area increased by about 48% over 46 years. The total eroded area was about 1038 km, with 35.40% more erosion on the left bank than on the right. Due to higher erosion than deposition, the river widened. The average width of the river increased by about 56.40% during the period. The average rate of shifting was higher on the left bank than on the right, indicating the eastward movement of the river. Impact analysis showed that overall, a total of 822 km and 390 km of croplands and settlements were eroded during the period 1973-2019. The width of the confluence at the Padma River junction decreased by about 28%. The straight shift of the confluence was 9.27 km towards the southeast. The vulnerable area assessment anticipated that there would be more erosion on the left bank than on the right, and that Kurigram, Tangail and Jamalpur are the districts most susceptible to future left bank erosion. And, the lower reach of the right bank of the Padma River is at high vulnerable to erosion at the confluence. The methods and analysis adopted in this study can be applied to any other braided river to monitor the dynamics of the river and to formulate an action plan to protect the river from erosion.

摘要

本研究旨在阐明 1973 年至 2019 年期间,孟加拉国杰纳布河 46 年来的动态变化。利用遥感和 GIS 技术对杰纳布河约 240 公里的河道进行了评估。对 Landsat 遥感图像进行了处理,并利用 GIS 提取和分析了河岸线。该研究的主要目的是了解杰纳布河河床移动的模式。根据河岸侵蚀、淤积、河岸线移动、河道宽度以及河道和汇流点的移动来评估河流的动态变化。利用历史侵蚀速率和趋势分析评估了易受侵蚀的区域。研究结果表明,46 年来,该河流面积增加了约 48%。总侵蚀面积约为 1038 公里,左岸侵蚀面积比右岸多 35.40%。由于侵蚀大于淤积,河流变宽。在此期间,河流的平均宽度增加了约 56.40%。左岸的平均移动速率高于右岸,表明河流向东移动。影响分析表明,1973 年至 2019 年期间,共有 822 公里和 390 公里的耕地和居民区受到侵蚀。在帕德玛河汇流处,河道的宽度减少了约 28%。汇流点的直线移动方向向东南方向移动了 9.27 公里。易受侵蚀区的评估预计,左岸的侵蚀将超过右岸,而库尔纳、坦盖尔和杰马勒布尔是最容易受到未来左岸侵蚀影响的地区。并且,帕德玛河右岸下游在汇流处易受侵蚀。本研究采用的方法和分析可以应用于任何其他辫状河流,以监测河流的动态变化,并制定保护河流免受侵蚀的行动计划。

相似文献

1
River dynamics - a geospatial analysis of Jamuna (Brahmaputra) River in Bangladesh during 1973-2019 using Landsat satellite remote sensing data and GIS.河流动力学 - 利用陆地卫星遥感数据和 GIS 对孟加拉国 1973-2019 年期间的雅鲁藏布江(布拉马普特拉河)进行的地理空间分析。
Environ Monit Assess. 2022 Nov 10;195(1):96. doi: 10.1007/s10661-022-10638-z.
2
Morphology and land use change analysis of lower Padma River floodplain of Bangladesh.孟加拉国下帕德玛河洪泛平原的形态和土地利用变化分析。
Environ Monit Assess. 2023 Jun 26;195(7):886. doi: 10.1007/s10661-023-11461-w.
3
Mapping tidal channel dynamics in the Sundarbans, Bangladesh, between 1974 and 2017, and implications for the sustainability of the Sundarbans mangrove forest.绘制孟加拉国孙德尔本斯地区 1974 年至 2017 年之间的潮汐河道动态图,以及对孙德尔本斯红树林可持续性的影响。
Environ Monit Assess. 2018 Sep 11;190(10):582. doi: 10.1007/s10661-018-6944-4.
4
Quantification of river bank erosion by RTK GPS monitoring: case studies along the Ningxia-Inner Mongolia reaches of the Yellow River, China.利用 RTK GPS 监测量化河岸侵蚀:以中国黄河宁蒙河段为例。
Environ Monit Assess. 2019 Feb 8;191(3):140. doi: 10.1007/s10661-019-7269-7.
5
Study on shoreline migration and island dynamics over the last five decades in the Muriganga River using multi-temporal satellite images.利用多时相卫星影像研究默里甘加河近五十年的岸线迁移和岛屿动态。
Environ Monit Assess. 2024 Jan 24;196(2):199. doi: 10.1007/s10661-024-12370-2.
6
Soil erosion vulnerability and soil loss estimation for Siran River watershed, Pakistan: an integrated GIS and remote sensing approach.巴基斯坦锡兰河流域土壤侵蚀脆弱性和土壤流失评估:一种综合 GIS 和遥感方法。
Environ Monit Assess. 2023 Dec 30;196(1):104. doi: 10.1007/s10661-023-12262-x.
7
Coastal environmental monitoring using remotely sensed data and GIS techniques in the Modern Yellow River delta, China.利用遥感数据和 GIS 技术在中国现代黄河三角洲进行沿海环境监测。
Environ Monit Assess. 2011 Aug;179(1-4):15-29. doi: 10.1007/s10661-010-1716-9. Epub 2010 Sep 24.
8
Spatio-temporal variation in land use/land cover pattern and channel migration in Majuli River Island, India.印度马久利岛土地利用/土地覆盖格局的时空变化与河道迁移。
Environ Monit Assess. 2021 Nov 16;193(12):811. doi: 10.1007/s10661-021-09614-w.
9
Detailed assessment of spatial and temporal variations in river channel changes and meander evolution as a preliminary work for effective floodplain management. The example of Sajó River, Hungary.详细评估河道变化和河曲演变的时空变化,作为有效管理洪泛区的初步工作。以匈牙利绍约河为例。
J Environ Manage. 2019 Oct 15;248:109277. doi: 10.1016/j.jenvman.2019.109277. Epub 2019 Jul 23.
10
Monitoring and predicting spatio-temporal dynamics of river bankline movements: a case study for land use risk management in the lower Ganga River, India.监测和预测河岸线移动的时空动态:以印度恒河下游土地利用风险管理为例
Environ Sci Pollut Res Int. 2025 Apr;32(16):10279-10298. doi: 10.1007/s11356-024-34723-7. Epub 2024 Aug 29.

引用本文的文献

1
Evaluation of the surface water quality using global water quality index (WQI) models: perspective of river water pollution.使用全球水质指数(WQI)模型评估地表水水质:河流水污染视角
Sci Rep. 2023 Nov 22;13(1):20454. doi: 10.1038/s41598-023-47137-1.