干旱区生态环境知识资源中心(Arid): Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data

Arid

DOI	10.1016/j.jag.2024.103933
	Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data
	Wang, Weiwei; Lin, Xingwen; Johnson, Brian Alan; Shi, Jingchao; Kumar, Pankaj; Tan, Mou Leong; Gao, Guang; Min, Xuemin; Hu, Guanghui; Zhang, Fei
通讯作者	Zhang, F
来源期刊	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN	1569-8432
EISSN	1872-826X
出版年	2024
卷号	130
英文摘要	Dynamic monitoring of reservoir water storage in arid areas is important for water resources assessment, hydroelectric power generation and agricultural irrigation. However, existing reservoir water calculation methods often rely on in -situ measurements, which limits their application in data scarce regionals and for regional scale analyses. Hence, we propose a novel method to estimate the water storage of channel -type reservoirs in arid areas with unknown underwater topography, with the Bosten Lake watershed serving as a case study site. The method first divides reservoirs into three types based on their upstream and downstream topography: V-shape, Ushape, and flat -shape reservoirs. For the V-shape and U -shape reservoirs, the underwater topography was produced by fitting a linear fit and a polynomial based on the observed elevation above the water surface, respectively. Meanwhile, extrapolation or splining techniques were used to derive the underwater topography for the flat -shape reservoir. The proposed methods are able to measure the underwater topography of the Bosten Lake watershed accurately, with the coefficient of determination (R 2 ) values of 0.83, 0.75 and 0.61 for the Vshape, U -shape, and flat -shape reservoirs, respectively. In addition, the fit of the in -situ water depths of unmanned ships was matched to the simulated water depths for the Xiaoshankou and Bayi reservoirs, yielding R 2 values of 0.91 and 0.83 as well as root mean square error (RMSE) of 1.27 m and 1.18 m, respectively. Our approach may be applied in other areas where river underwater topography data is lacking or sparse, and provide important basis for rational water resources management in these areas.
英文关键词	Remote sensing Channel -Type Reservoirs Underwater topography Water storage estimate
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001247061000001
WOS关键词	KAIDU RIVER-BASIN ; INDEX NDWI ; LAKES ; VOLUME ; AREAS
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404194
推荐引用方式 GB/T 7714	Wang, Weiwei,Lin, Xingwen,Johnson, Brian Alan,et al. Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data[J],2024,130.
APA	Wang, Weiwei.,Lin, Xingwen.,Johnson, Brian Alan.,Shi, Jingchao.,Kumar, Pankaj.,...&Zhang, Fei.(2024).Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,130.
MLA	Wang, Weiwei,et al."Remote sensing estimation of water storage in the channel-type reservoirs under unknown underwater topographic data".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 130(2024).