Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-4995-2021
https://doi.org/10.5194/hess-25-4995-2021
Research article
 | 
16 Sep 2021
Research article |  | 16 Sep 2021

Sequential data assimilation for real-time probabilistic flood inundation mapping

Keighobad Jafarzadegan, Peyman Abbaszadeh, and Hamid Moradkhani

Viewed

Total article views: 3,360 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,314 988 58 3,360 48 42
  • HTML: 2,314
  • PDF: 988
  • XML: 58
  • Total: 3,360
  • BibTeX: 48
  • EndNote: 42
Views and downloads (calculated since 18 May 2021)
Cumulative views and downloads (calculated since 18 May 2021)

Viewed (geographical distribution)

Total article views: 3,360 (including HTML, PDF, and XML) Thereof 3,136 with geography defined and 224 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
In this study, daily observations are assimilated into a hydrodynamic model to update the performance of modeling and improve the flood inundation mapping skill. Results demonstrate that integrating data assimilation with a hydrodynamic model improves the performance of flood simulation and provides more reliable inundation maps. A flowchart provides the overall steps for applying this framework in practice and forecasting probabilistic flood maps before the onset of upcoming floods.