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\begin{document}

\title{High Spatiotemporal Resolution River Networks Mapping on Catchment Scale
Using Satellite Remote Sensing Imagery and DEM Data}



\author[1]{Peng Li}%
\author[1]{Yun Zhang}%
\author[2]{Cunren Liang}%
\author[1]{Houjie Wang}%
\author[3]{Zhenhong Li}%
\affil[1]{Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Ocean University of China}%
\affil[2]{Peking University}%
\affil[3]{Chang'an Universituy}%


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  \date{May 22, 2024}


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\begin{abstract}
Characterizing and understanding the changes in the flow regimes of
rivers have been challenging. Existing global river network datasets are
not updated and can only identify rivers wider than 30 m. We propose a
novel automated method to map river networks on a monthly basin scale
for the first time at 10-m resolution using Sentinel-1 {Synthetic
Aperture Radar}, Sentinel-2 multispectral images, and the AW3D30 Digital
Surface Model. This method achieved an overall accuracy of 95.8\%. The
total length of the Yellow River network produced is 40,280 km,
approximately 3.2 times that of the Global River Widths from Landsat
(GRWL) database, more effectively covering small and medium rivers. The
monthly river geometry revealed a positive correlation between river
network area and precipitation. This study is expected to provide a
cost-effective alternative to accurately mapping global river networks
and advance our understanding of the changes and drivers of river
systems.%
\end{abstract}%



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