Compound flooding during extreme events can result in tremendous amounts of property damage and loss of life. Early warning systems and multi-hazard risk analysis can reduce these impacts. However, traditional approaches either do not involve relevant physics or are too computationally expensive to do so for large stretches of coastline. The SFINCS model (Super-Fast INundation of CoastS) is a new reduced-complexity engine recently developed by Deltares, that is capable of simulating compound flooding including a high computational efficiency balanced with good accuracy.
Release Notes
The application of SFINCS is demonstrated in Jupyter Notebooks developed in interTwin (https://github.com/interTwin-eu/DT-flood/tree/DemonstrationNotebooks).
A pilot implementation is being run on a Virtual Machine at DESY where the Notebooks are being adapted to leverage the pilot interTwin datalake.
This release offers examples of how to set up and run SFINCS and Delft-FIAT. SFINCS offers capabilities to simulate floodings using globally available data.
Users can specify a geographic area of interest and a minimal number of model-specific parameters, and SFINCS to simulate flood inundation is automatically set up using globally available data.
Globally available static and dynamic input data can be used to create deterministic flood maps based on SFINCS.
A user can specify a simulation period and the flood inundation model (SFINCS) can be run on heterogeneous computing infrastructures using Docker or Singularity containers.
A user can select scenarios to simulate, including mitigation and adaptation measures and the flood inundation model (SFINCS) and the necessary static and dynamic input data are automatically prepared to run the scenario.
Future Plans
In the next release capabilities will be created so that:
- Users can specify a geographic area of interest and a minimal number of model-specific parameters, and SFINCS to simulate flood inundation is automatically set up using locally available data.
- Users can easily run the flood inundation model (SFINCS) using locally available data.
