Remote Sensing-Based Modeling of the Bathymetry and Water Storage for Channel-Type Reservoirs Worldwide

doi:10.1029/2020WR027147

	Remote Sensing-Based Modeling of the Bathymetry and Water Storage for Channel-Type Reservoirs Worldwide
	Liu, Kai 1; Song, Chunqiao 1; Wang, Jida 2; Ke, Linghong 3,4; Zhu, Yunqiang 5; Zhu, Jingying 1,6; Ma, Ronghua 1; Luo, Zhu 1
刊名	WATER RESOURCES RESEARCH
	2020-11-01
卷号	56 期号:11 页码:19
关键词	reservoir bathymetry water storage DEM satellite imagery
ISSN号	0043-1397
DOI	10.1029/2020WR027147
通讯作者	Song, Chunqiao(cqsong@niglas.ac.cn)
英文摘要	Estimations of reservoir bathymetry and storage are of great significance due to their substantial impacts on hydrological processes and water resource management. However, existing approaches for reservoir bathymetry construction often rely on field measurements, which restricts their application at regional and global scales. This study proposes a novel Approach for Determining the BAthymetry and water storage of channel-type Reservoirs, hereafter referred to as ADBAR, for which only open-access digital elevation model (DEM) and satellite images are required. The basic idea of ADBAR is to utilize the geomorphological similarity and topographical continuity of the reservoir inundation area with its lateral valleys and upstream/downstream regions to predict underwater bathymetry. Forty-eight reservoirs with different topographic and geometric characteristics were selected for method validation. The selected reservoirs were all impounded after the year 2000, so the modeled reservoir bathymetry can be validated by the "reference" reservoir storage calculated using the exposed topography in SRTM DEM and the mapped water extents from spectral images. The difference between the estimated and reference storages is about 13% on average. Furthermore, the modeled results in two selected basins with dense reservoir distributions, the Upper Yellow River Basin in China and the Tocantins River Basin in Brazil, are comparable with the documented effective storage capacities. The validations for both individual reservoirs and the two large basins demonstrate that ADBAR is a robust tool for estimating reservoir bathymetries and storage capacities and thus facilitates the modeling of reservoir impacts on water budgets at large and global scales.
资助项目	National Key Research and Development Program of China[2018YFD0900804] ; National Key Research and Development Program of China[2019YFA0607101] ; National Key Research and Development Program of China[2018YFD1100101] ; Thousand Young Talents Program in China[Y7QR011001] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100102] ; National Natural Science Foundation of China[41971403] ; National Natural Science Foundation of China[41801321]
WOS关键词	SURFACE-WATER ; LAKE VOLUME ; QUALITY ; LEVEL ; DEPTH ; CHINA ; AREA
WOS研究方向	Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
语种	英语
出版者	AMER GEOPHYSICAL UNION
WOS记录号	WOS:000595832300004
资助机构	National Key Research and Development Program of China ; Thousand Young Talents Program in China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/156447]
专题	中国科学院地理科学与资源研究所
通讯作者	Song, Chunqiao
作者单位	1.Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Watershed Geog Sci, Nanjing, Peoples R China 2.Kansas State Univ, Dept Geog & Geospatial Sci, Manhattan, KS 66506 USA 3.Hohai Univ, Coll Hydrol & Water Resources, Nanjing, Peoples R China 4.Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Kai,Song, Chunqiao,Wang, Jida,et al. Remote Sensing-Based Modeling of the Bathymetry and Water Storage for Channel-Type Reservoirs Worldwide[J]. WATER RESOURCES RESEARCH,2020,56(11):19.
APA	Liu, Kai.,Song, Chunqiao.,Wang, Jida.,Ke, Linghong.,Zhu, Yunqiang.,...&Luo, Zhu.(2020).Remote Sensing-Based Modeling of the Bathymetry and Water Storage for Channel-Type Reservoirs Worldwide.WATER RESOURCES RESEARCH,56(11),19.
MLA	Liu, Kai,et al."Remote Sensing-Based Modeling of the Bathymetry and Water Storage for Channel-Type Reservoirs Worldwide".WATER RESOURCES RESEARCH 56.11(2020):19.