Preprints
https://doi.org/10.5194/hess-2021-125
https://doi.org/10.5194/hess-2021-125

  08 Apr 2021

08 Apr 2021

Review status: this preprint is currently under review for the journal HESS.

Simultaneous assimilation of water levels from river gauges and satellite flood maps for near-real time flood mapping

Antonio Annis1,2, Fernando Nardi1,3, and Fabio Castelli2 Antonio Annis et al.
  • 1WARREDOC, University for Foreigners of Perugia, Perugia Italy
  • 2DICEA, University of Florence, Florence, Italy
  • 3Institute of Water and Environment, Florida International University, Miami, USA

Abstract. Hydro-meteo hazard Early Warning Systems (EWSs) are operating in many regions of the world to mitigate nuisance effects of floods. EWSs performances are majorly impacted by the computational burden and complexity affecting flood prediction tools, especially for ungauged catchments that lack adequate river flow gauging stations. Earth Observation (EO) systems may surrogate to the lack of fluvial monitoring systems supporting the setting up of affordable EWSs. But, EO data, constrained by spatial and temporal resolution limitations, are not sufficient alone, especially at medium-small scales. Multiple sources of distributed flood observations need to be used for managing uncertainties of flood models, but this is not a trivial task for EWSs. In this work, a near real-time flood modelling approach is developed and tested for the simultaneous assimilation of both water level observations and EO-derived flood extents. An integrated physically-based flood wave generation and propagation modelling approach, that implements a Ensemble Kalman Filter, a parsimonious geomorphic rainfall-runoff algorithm (WFIUH) and a Quasi-2D hydraulic algorithm, is proposed. A data assimilation scheme is tested that retrieves distributed observed water depths from satellite images to update 2D hydraulic modelling state variables. Performances of the proposed approach are tested on a flood event for the Tiber river basin in central Italy. The selected case study shows varying performances depending if local and distributed observations are separately or simultaneously assimilated. Results suggest that the injection of multiple data sources into a flexible data assimilation framework, constitute an effective and viable advancement for flood mitigation tackling EWSs data scarcity, uncertainty and numerical stability issues.

Antonio Annis et al.

Status: open (until 01 Aug 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-125', Anonymous Referee #1, 26 May 2021 reply
  • RC2: 'Comment on hess-2021-125', Maurizio Mazzoleni, 22 Jul 2021 reply

Antonio Annis et al.

Antonio Annis et al.

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Short summary
In this work, we proposed a multi-source Data Assimilation framework for near-real time flood mapping. We used a Quasi-2D hydraulic model updating model states by injecting both stage gauge observations and satellite derived flood extents. Results showed improvements in terms of water level prediction as respect to the non-assimilated flood model. The work is aimed to exploit the availability of diverse sets of distributed flood observations for improving flood alerting and emergency management.