The four layers show the flash flood impact levels forecasted for the upcoming five days, summarised at the catchment level. This forecasted impact level is estimated by intersecting a flash flood hazard forecast with static exposure data on a risk matrix. Both the flash flood hazard and the exposure data are split into three categories to create the risk matrix (Fig. 1).
The low, medium, and high values for flash flood hazard on the y-axis of the impact matrix indicate where there is a 5%-50%, 50%-80%, and >80% probability of exceeding the 2-year return period threshold. This flash flood hazard is estimated by comparing blended forecasts of precipitation (from the OPERA radar mosaic and ECMWF NWP forecasts) accumulated on the river network, with the reference values derived from climatology. This climatology is from:
- 8-year gauge-adjusted OPERA data
- A dataset of 20-year reforecasts obtained with ECMWF Integrated Forecasting System (IFS)
The exposure data accounts for population and critical infrastructure in the form of health, education, transport, and energy generation facilities. Data for each of these five categories was harmonised and combined with equal weighting to create a combined exposure layer. The categories for low, medium, and high exposure are 1.0-1.3, 1.3-1.6 and 1.6-2.0 respectively and form the x-axis of the impact matrix. These categories were chosen based on the statistical distribution of exposure values across the EFAS domain, and consequently mean 81.0% the exposure values are classified as low exposure, 8.0% as medium exposure and 1.2% as high exposure. This reflects the reality that most grid points in Europe have a low population density and with few exposed critical infrastructures.
Figure 1. The flash flood impact level forecast for a leadtime of 0-6h near Strasbourg, on the 31st August 2022 at 00 UTC
This combination of flash flood hazard level with exposure gives impact levels for the river network cells. To create the catchment level summary, firstly for each of the 4 lead time aggregation windows (0-6h, 7-24h, 25-48h, 49-120h), the maximum impact level forecasted throughout the window is calculated. Next, the catchments are shaded according to the 90th percentile of the impact level of all cells forecasted within each catchment. Use of the 90th percentile of impact (instead of the maximum) is to avoid communicating potentially misleadingly high forecast information to users based on single cell values.
By clicking on specific catchments, users are able to see a pop-out window showing where in the impact matrix the catchment lies (Fig. 1). There is also some additional information on the number of people, education, health and energy generation facilities forecasted to be affected.
These catchment summary layers can be very useful for identifying the general areas and time periods where flash flood impacts are possible. It is recommended that these layers should be consulted first before looking at the animated TAMIR - impact forecasts layer which can be difficult to visualise when zoomed further out and if you don't know the specific timesteps when flash flooding is possible. After using the catchment summary layers to identify the catchments and time windows where flash flood impacts are possible, the animation from the TAMIR - impact forecasts layer can be used to identify the specific 1 km grid cells and timesteps where impacts are possible.
