干旱区生态环境知识资源中心(Arid): Spatiotemporal variability of global river extent and the natural driving factors revealed by decades of Landsat observations, GRACE gravimetry observations, and land surface model simulations

Arid

DOI	10.1016/j.rse.2021.112725
	Spatiotemporal variability of global river extent and the natural driving factors revealed by decades of Landsat observations, GRACE gravimetry observations, and land surface model simulations
	Gao, Shang; Li, Zhi; Chen, Mengye; Lin, Peirong; Hong, Zhen; Allen, Daniel; Neeson, Thomas; Hong, Yang
通讯作者	Li, Z ; Hong, Y (corresponding author), Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA.
来源期刊	REMOTE SENSING OF ENVIRONMENT
ISSN	0034-4257
EISSN	1879-0704
出版年	2021
卷号	267
英文摘要	Rivers are among the most dynamic components in Earth's terrestrial water cycle and provide critical ecosystem services. Yet, the spatiotemporal variability of river surface extents remains largely unquantified at the global scale. Satellite remote sensing provides a promising alternative to in-situ observations, which can enable a more comprehensive survey and systematic analysis of global rivers at fine spatial resolutions. The study examines the spatiotemporal variability of river surface extent globally and its natural driving factors, by combining the use of Landsat-based Global Surface Water (GSW) and Global River Widths from Landsat (GRWL) databases. In addition to examining the long-term mean river surface extent in various climate zones, we perform statistical analyses to correlate monthly times series of fractional river extent with the terrestrial water storage (TWS) components obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite observation and the Global Land Data Assimilation System (GLDAS) model simulations. Results show that the spatiotemporal variability of water presence in rivers can be explained well via differentiating climate zones. The analysis also shows that 52.7% of the global maximum river extent is covered by water less than half of time. Changes of fractional river extent are found to be highly correlated with groundwater storage in low- and mid-latitudes, whereas snow melting dominates the river dynamics in high latitudes. By examining the extremes of fractional river extent, we found that the abrupt changes of fractional river extent are well linked to precipitation anomalies in the equatorial, arid, and warm temperate areas. This study offers an innovative perspective to study spatiotemporal dynamics of rivers by combining optical remote sensing (Landsat), gravimetry observations (GRACE), and land surface simulations; and it highlights the significant role of low-flow-generating processes (snow melting, infiltration, and recharge-discharge) in controlling river dynamics in certain regions, which warrants future investigation.
英文关键词	Landsat Global river GRWL GSW GRACE GLDAS Correlation analysis Coincidence analysis
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000708550700002
WOS关键词	MAJOR FLOODS ; WATER ; RESOLUTION ; WIDTH ; DECOMPOSITION ; DISCHARGES ; EMISSIONS ; IMAGERY ; BASIN
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	北京大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/364502
作者单位	[Gao, Shang; Li, Zhi; Chen, Mengye; Hong, Zhen; Hong, Yang] Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA; [Lin, Peirong] Peking Univ, Sch Earth & Space Sci, Inst Remote Sensing & GIS, Beijing, Peoples R China; [Allen, Daniel] Univ Oklahoma, Dept Biol, Norman, OK 73019 USA; [Neeson, Thomas] Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA
推荐引用方式 GB/T 7714	Gao, Shang,Li, Zhi,Chen, Mengye,et al. Spatiotemporal variability of global river extent and the natural driving factors revealed by decades of Landsat observations, GRACE gravimetry observations, and land surface model simulations[J]. 北京大学,2021,267.
APA	Gao, Shang.,Li, Zhi.,Chen, Mengye.,Lin, Peirong.,Hong, Zhen.,...&Hong, Yang.(2021).Spatiotemporal variability of global river extent and the natural driving factors revealed by decades of Landsat observations, GRACE gravimetry observations, and land surface model simulations.REMOTE SENSING OF ENVIRONMENT,267.
MLA	Gao, Shang,et al."Spatiotemporal variability of global river extent and the natural driving factors revealed by decades of Landsat observations, GRACE gravimetry observations, and land surface model simulations".REMOTE SENSING OF ENVIRONMENT 267(2021).