@article{MengenOttingerLeinenkugeletal.2020,
  author    = {David Mengen and Marco Ottinger and Patrick Leinenkugel and Lars Ribbe},
  title     = {Modeling River Discharge Using Automated River Width Measurements Derived from Sentinel-1 Time Series},
  series   = {Remote Sensing},
  volume    = {12},
  number    = {19},
  publisher = {MDPI},
  issn      = {2072-4292},
  doi       = {10.3390/rs12193236},
  url       = {https://nbn-resolving.org/urn:nbn:de:hbz:832-epub4-16210},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}