Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model
文献类型:期刊论文
作者 | Xie, Guohu6,7; Zhang, Yang5,6; Liu, Jia3,4,6; Xue, Huijie2; Ge, Jianzhong1; He, Xianqiang6; Ma, Wentao5; Chai, Fei2,7 |
刊名 | Ocean Modelling |
出版日期 | 2023-12 |
卷号 | 186 |
ISSN号 | 14635003 |
关键词 | Sediment flux Yangtze River Estuary Geostationary Ocean Color Imager (GOCI) Numerical model Morphology |
DOI | 10.1016/j.ocemod.2023.102284 |
产权排序 | 4 |
英文摘要 | Sediment flux (SF) in the estuary is vital to the coastal and estuarine environment, especially the morphodynamical and ecological processes. However, its quantitative estimation with high accuracy is difficult because it is controlled by complex mechanisms and multiple processes. This study corrects the seasonal variations of the simulated suspended sediment concentration (SSC) by using GOCI-derived surface SSC and calculates the variations of SFs at the main cross-sections in and out of the Yangtze River Estuary (YRE). The results show that in 2013, 159 Mt and 143 Mt of sediments passed through Xuliujing hydrological station in YRE and estuarine mouth section, respectively. In the inner estuary, the significant seasonal variations of sediment transport are noted that the most seaward transport happens in summer (43.8%) and the least occurs in winter (7.3%). In the outer estuary, the southward transport towards Hangzhou Bay is the most critical pathway, accounting for 109.0% of total transport at mouth section, and is prevalent in autumn and winter. With considerations of sand mining and land reclamation, obviously erosions appear in the whole estuary during both 2013 and 2015. With stronger wind conditions in 2013, severer erosion (161 Mt) happens in outer estuary than that in 2015 (86 Mt). By combining the GOCI-derived surface SSC and the numerical model results, this study can better represent high-frequency hydro- and sediment-dynamical processes to calculate the annual, seasonal, and vertical SFs with improved accuracy. Hence this method may provide a viable way to infer locally averaged morphological changes. © 2023 |
语种 | 英语 |
出版者 | Elsevier Ltd |
源URL | [http://ir.opt.ac.cn/handle/181661/96883] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
通讯作者 | Zhang, Yang |
作者单位 | 1.State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200241, China 2.State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen; 361102, China; 3.The University of Chinese Academy of Sciences, Beijing, 100049, China; 4.Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an; 710119, China; 5.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai; 519080, China; 6.State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou; 310012, China; 7.Ocean College, Zhejiang University, Zhoushan; 316021, China; |
推荐引用方式 GB/T 7714 | Xie, Guohu,Zhang, Yang,Liu, Jia,et al. Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model[J]. Ocean Modelling,2023,186. |
APA | Xie, Guohu.,Zhang, Yang.,Liu, Jia.,Xue, Huijie.,Ge, Jianzhong.,...&Chai, Fei.(2023).Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model.Ocean Modelling,186. |
MLA | Xie, Guohu,et al."Improvement of the sediment flux estimation in the Yangtze River Estuary with a GOCI data adjusted numerical model".Ocean Modelling 186(2023). |
入库方式: OAI收割
来源:西安光学精密机械研究所
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