Assimilation of flood extent maps into a shallow water model

  • Fabian from Luxembourg Institute of Science and Technology (LIST)
  • From Luxembourg
  • Responsive
  • Innovative Products and Technologies

Summary of the technology

LIST’s software enables the effective assimilation of flood inundation probabilistic maps derived from Earth observation data into a shallow water model. It is based on a particle filter with sequential importance sampling, a technique that allows estimating the individual posterior probabilities of an ensemble of shallow water model simulations given an observed flood inundation extent (detailed descriptions of the filter are provided in Hostache et al., WRR, 2018 and di Mauro et al., HESS, 2021).

Luxembourg Institute of Science and Technology (LIST)

Details of the Technology Offer

Background:Predictions of shallow water models and Earth observation-derived flood extent maps suffer from inherent and potentially large uncertainties (e.g. due to erroneous input data, model parameters and model simplifications). Our technology enables an optimal combination of these two sources of information, thereby reducing model uncertainties in terms of simulations of flood extent, water depth, and river discharge.


  • fully automated and easy to implement
  • Can be adapted to a large variety of shallow water models and satellite Earth observation data sets
  • Very low computational cost
  • No need to update the model states and therefore no need to re-run the model each time an observation becomes available
  • The procedure can be applied “online” and “offline”; the ‘offline’ application uses as input a stack of pre-computed model maps


  • The optimal combination of a stack of simulated flood extent maps and an observed flood extent improves the accuracy and reliability of flood extent and water depth maps (application areas: emergency mapping, flood risk assessment)
  • Improvement of flood prediction and forecasting via the sequential and systematic assimilation of flood extent into a hydrodynamic model (applications area: flood forecasting)
  • Estimation in near real time of the return period of an unfolding flood event using a stack of precomputed flood extent maps and an observed flood extent map (application area: parametric modelling for insurance/reinsurance companies).


The priority is to increase the TRL of the solution via RDI projects targeting the development and evaluation of the method, and the increase of its level of automation.

Additional funding is needed to develop a ready-to-use software solution and/or an operational service enabling the application of the filter for different scenarios (e.g. flood forecasting, emergency mapping, risk modelling), different shallow water models and multi-source remote sensing data.

Desired business relationship

Technology development

Other : Licensing

Related Keywords

  • Data Processing / Data Interchange, Middleware
  • Measurements and Standards
  • Measurement Tools
  • Protecting Man and Environment
  • Safety
  • Environment
  • Water Management
  • Flood Management
  • Social and Economics concerns
  • Sustainability

About Luxembourg Institute of Science and Technology (LIST)

The Luxembourg Institute of Science and Technology (LIST) is a mission-driven Research and Technology Organisation (RTO) active in the fields of materials, environment and IT.
LIST develops competitive and market-oriented product/service prototypes for public and private stakeholders, and works across the entire innovation chain: fundamental/applied research, incubation, transfer of technologies.
By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

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Luxembourg Institute of Science and Technology (LIST)

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