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题名

Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets

作者
通讯作者Jiang,Liguang
发表日期
2023-03-01
DOI
发表期刊
ISSN
0048-9697
EISSN
1879-1026
卷号862
摘要
The flow regime change of rivers, especially transboundary rivers, affected by reservoir regulations is evident worldwide and has received much attention. Investigating dam-induced flow regime alterations is essential for understanding potential adverse downstream effects and facilitating dialogue around coordinated water use in transboundary basins, such as the Lancang River Basin (LRB). This study explored the value of combining several types of satellite Earth observation (EO) datasets that monitor different water balance components to constrain the parameter space of lumped conceptual hydrological models. Thus, we aimed to reconstruct the natural flow regimes upstream and downstream of the cascade reservoirs. Specifically, reservoir water storage changes were first estimated using satellite imagery and altimetry datasets. Then, storage changes were combined with hydrological model simulations of reservoir inflow to estimate the regulated flow regime downstream. Our results showed that integrated hydrological modeling combined with EO datasets exhibited better overall performance. Continuous warming and drying of the LRB resulted in a decrease in discharge of approximately 47 %. By comparing the simulated natural and regulated flow regimes, we revealed the pivotal role of the Xiaowan and Nuozhadu reservoirs in regulating natural flows. The wet season shortens (approximately 45 days), the flood peak flattens, and the low flow in the dry season has primarily increases. The two reservoirs attenuated 50 % of the flood peaks in the wet seasons and mitigated droughts by releasing up to 100 % of the natural flows in the dry seasons at the China–Laos border. Overall, these results enhance the understanding of upper reservoir operation, and the approaches can be applied to studies of dammed basins under climate change scenarios when knowledge of the upstream area is limited.
关键词
相关链接[Scopus记录]
收录类别
SCI ; EI
语种
英语
学校署名
通讯
资助项目
Strategic Priority Research Program of the Chinese Academy of Sciences[XDA2006020202] ; National Natural Science Foundation of China[42201037] ; EOForChina project - Ministry of Foreign Affairs of Denmark[18-M01-DTU] ; Chinese Academy of Sciences[E2S20001Y5] ; China Postdoctoral Science Foundation[2022M713122]
WOS研究方向
Environmental Sciences & Ecology
WOS类目
Environmental Sciences
WOS记录号
WOS:000928164100005
出版者
EI入藏号
20225013247141
EI主题词
Climate change ; Climate models ; Drought ; Earth (planet) ; Earth system models ; Flood control ; Floods ; Observatories ; Rivers ; Satellite imagery
EI分类号
Reservoirs:441.2 ; Flood Control:442.1 ; Meteorology:443 ; Atmospheric Properties:443.1 ; Precipitation:443.3 ; Water Resources:444 ; Satellites:655.2 ; Maintenance:913.5 ; Accidents and Accident Prevention:914.1 ; Mathematics:921
ESI学科分类
ENVIRONMENT/ECOLOGY
Scopus记录号
2-s2.0-85143833963
来源库
Scopus
引用统计
被引频次[WOS]:12
成果类型期刊论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/442657
专题工学院_环境科学与工程学院
作者单位
1.Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing,100101,China
2.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.DHI-GRAS,Hørsholm,2970,Denmark
4.Department of Environmental Engineering,Technical University of Denmark,Kgs. Lyngby,2800,Denmark
通讯作者单位环境科学与工程学院
推荐引用方式
GB/T 7714
Zhang,Xingxing,Jiang,Liguang,Liu,Zhaofei,et al. Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2023,862.
APA
Zhang,Xingxing.,Jiang,Liguang.,Liu,Zhaofei.,Kittel,Cecile M.M..,Yao,Zhijun.,...&Bauer-Gottwein,Peter.(2023).Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets.SCIENCE OF THE TOTAL ENVIRONMENT,862.
MLA
Zhang,Xingxing,et al."Flow regime changes in the Lancang River, revealed by integrated modeling with multiple Earth observation datasets".SCIENCE OF THE TOTAL ENVIRONMENT 862(2023).
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