Yuchuan Bai , Yanjie Sun , Xiaolong Song , Haijue Xu
{"title":"An improved method for sand wave morphology discrimination in rivers by combining a flow resistance law and support vector machines","authors":"Yuchuan Bai , Yanjie Sun , Xiaolong Song , Haijue Xu","doi":"10.1016/j.ijsrc.2023.10.003","DOIUrl":null,"url":null,"abstract":"<div><p>A parameterized expression for sand wave morphology in rivers is established using a flow resistance law while accounting for sediment incipient velocity. A distinct relation is drawn between the proposed characteristic parameters and the sand wave morphology based on flume data. Support vector machines (SVMs) are then used to separate the boundaries of the sand wave morphology due to the high classification accuracy of SVMs. The boundary line data from each sand wave morphology is extracted and fitted to establish a discriminant standard, which is then successfully validated using experimental and quantifiable data. Also, based on the foregoing methodoly, it is further discovered that the short-term significant fluctuation of sand wave morphology is closely correlated with significant channel changes in rivers with a high width-depth ratio, using Yellow River Estuary as an example.</p></div>","PeriodicalId":50290,"journal":{"name":"International Journal of Sediment Research","volume":"39 1","pages":"Pages 144-152"},"PeriodicalIF":3.5000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1001627923000744/pdfft?md5=69a5480f06eac8441b5df60a68a9e3a2&pid=1-s2.0-S1001627923000744-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sediment Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1001627923000744","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
A parameterized expression for sand wave morphology in rivers is established using a flow resistance law while accounting for sediment incipient velocity. A distinct relation is drawn between the proposed characteristic parameters and the sand wave morphology based on flume data. Support vector machines (SVMs) are then used to separate the boundaries of the sand wave morphology due to the high classification accuracy of SVMs. The boundary line data from each sand wave morphology is extracted and fitted to establish a discriminant standard, which is then successfully validated using experimental and quantifiable data. Also, based on the foregoing methodoly, it is further discovered that the short-term significant fluctuation of sand wave morphology is closely correlated with significant channel changes in rivers with a high width-depth ratio, using Yellow River Estuary as an example.
期刊介绍:
International Journal of Sediment Research, the Official Journal of The International Research and Training Center on Erosion and Sedimentation and The World Association for Sedimentation and Erosion Research, publishes scientific and technical papers on all aspects of erosion and sedimentation interpreted in its widest sense.
The subject matter is to include not only the mechanics of sediment transport and fluvial processes, but also what is related to geography, geomorphology, soil erosion, watershed management, sedimentology, environmental and ecological impacts of sedimentation, social and economical effects of sedimentation and its assessment, etc. Special attention is paid to engineering problems related to sedimentation and erosion.