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Quantifying the Effects of Dramatic Changes in Runoff and Sediment on the Channel Morphology of a Large, Wandering River Using Remote Sensing Images
Xie, Zhehui1,2; Huang, Heqing1,2; Yu, Guoan1,2; Zhang, Min3
2018-12-01
Source PublicationWATER
ISSN2073-4441
Volume10Issue:12Pages:26
Corresponding AuthorHuang, Heqing(huanghq@igsnrr.ac.cn)
AbstractThe Yellow River (Huanghe River), which is the second largest river in China, has experienced dramatic changes in both runoff and sediment over the last 60 years. To quantify the effects on the channel morphology of the wandering reach on the Lower Yellow River (LYR), this study extracts morphological indices from Landsat imageries taken between 1979 and 2015. Over the dynamically adjusting complex channel-floodplain system, the spatial distribution of NDVI (Normalized Difference Vegetation Index) is found helpful for identifying the wandering belt created by the frequent migrations of the pathways of the main flow, which are determined from the reflection of the sediment-laded water body in remote sensing images taken at low flows. The extracted results show clearly that the average width and area of the wandering belt over the entire study reach declined in a dramatic fashion between 1979 and 2000 and yet both varied respectively within very narrow ranges from 2000 to 2015. Although the number of bends increased significantly since the 1990s, the sinuosity of the pathways of the main flow remained almost unchanged. By combining the morphological indices extracted from the remote sensing images with field hydrological and geomorphological measurements, our regression analysis identifies that the width of the wandering belt changes at the highest degree of correspondence with the width/depth ratio of the main channel and the variations of both are related most closely to the average flow discharge and then to sediment concentration during the flood seasons. These implicate that a significant reduction of the magnitude of floods and sediment concentration is beneficial not only for making the main channel transit from a wider and shallower cross-section into a narrower and deeper profile but also for narrowing the wandering range of the LYR.
Keywordmorphological change remote sensing wandering river runoff and sediment change Lower Yellow River
DOI10.3390/w10121767
WOS KeywordPLANFORM CHANGES ; DEE MEANDERS ; BRAHMAPUTRA ; ADJUSTMENTS ; BANGLADESH ; DYNAMICS ; GEOMETRY ; EROSION ; SYSTEM ; REACH
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41330751] ; National Natural Science Foundation of China[41561144012] ; National Natural Science Foundation of China[41661144030] ; National Key R&D Program of China[2016YFC0402502]
Funding OrganizationNational Natural Science Foundation of China ; National Key R&D Program of China
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000455314300062
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/50544
Collection中国科学院地理科学与资源研究所
Corresponding AuthorHuang, Heqing
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Yellow River Water Conservancy Commiss, Inst Hydraul Res, Minist Water Resources, Key Lab Yellow River Sediment, Zhengzhou 450003, Henan, Peoples R China
Recommended Citation
GB/T 7714
Xie, Zhehui,Huang, Heqing,Yu, Guoan,et al. Quantifying the Effects of Dramatic Changes in Runoff and Sediment on the Channel Morphology of a Large, Wandering River Using Remote Sensing Images[J]. WATER,2018,10(12):26.
APA Xie, Zhehui,Huang, Heqing,Yu, Guoan,&Zhang, Min.(2018).Quantifying the Effects of Dramatic Changes in Runoff and Sediment on the Channel Morphology of a Large, Wandering River Using Remote Sensing Images.WATER,10(12),26.
MLA Xie, Zhehui,et al."Quantifying the Effects of Dramatic Changes in Runoff and Sediment on the Channel Morphology of a Large, Wandering River Using Remote Sensing Images".WATER 10.12(2018):26.
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