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Modeling River Discharge Using Automated River Width Measurements Derived from Sentinel-1 Time Series

  • Against the background of a worldwide decrease in the number of gauging stations,the estimation of river discharge using spaceborne data is crucial for hydrological research, rivermonitoring, and water resource management. Based on the at-many-stations hydraulic geometry(AMHG) concept, a novel approach is introduced for estimating river discharge using Sentinel-1time series within an automated workflow. By using a novel decile thresholding method, no a prioriknowledge of the AMHG function or proxy is used, as proposed in previous literature. With arelative root mean square error (RRMSE) of 19.5% for the whole period and a RRMSE of 15.8%considering only dry seasons, our method is a significant improvement relative to the optimizedAMHG method, achieving 38.5% and 34.5%, respectively. As the novel approach is embedded intoan automated workflow, it enables a global application for river discharge estimation using solelyremote sensing data. Starting with the mapping of river reaches, which have large differences inriver width overthe year, continuous river width time series are created using high-resolution andweather-independent SAR imaging. It is applied on a 28 km long section of the Mekong River nearVientiane, Laos, for the period from 2015 to 2018.

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Metadaten
Author:David Mengen, Marco Ottinger, Patrick Leinenkugel, Lars Ribbe
URN:urn:nbn:de:hbz:832-epub4-16210
DOI:https://doi.org/10.3390/rs12193236
ISSN:2072-4292
Parent Title (English):Remote Sensing
Year of Completion:2020
Publisher:MDPI
Document Type:Article
Language:English
Date of first Publication:2020/10/05
Date of Publication (online):2021/02/23
Tag:AMHG; Decile thresholding; Discharge modeling; Mekong River; River width; SAR; Sentinel-1; Time series
Volume:12
Issue:19
Page Number:24
Institutes:Fakultät für Raumentwicklung und Infrastruktursysteme (F12) / Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen
Dewey Decimal Classification:500 Naturwissenschaften und Mathematik / 550 Geowissenschaften
Open Access:Open Access
DeepGreen:DeepGreen
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International