The four layers show show the flash flood impacts impact levels forecasted for the upcoming five days, summarised by sub-at the catchment level. This forecasted impact level is estimated by intersecting a flash flood hazard forecast with the static exposure layer data on a risk matrix. Both the flash flood hazard and the exposure data are split into three categories to create the risk matrix. The low, medium, and high values for flash flood hazard 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 (i) :
- 8-year gauge-adjusted OPERA data
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- 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 relative combined exposure respectively exposure are 1.0-1.3, 1.3-1.6 and 1.6-2.0 respectively. 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.
This combination of flash flood hazard with exposure capture the variation in population density and critical infrastructure in rural, suburban, and urban areas in Europe.This gives impact levels for the river network cells. For each of the 4 lead time aggregation windows (0-6h, 7-24h, 25-48h, 49-120h), the cells show the maximum impact level forecasted throughout the window. To then provide a quicker overview of the affected areas, this sub-catchment overview is created by shading the sub-catchments create this catchment level summary, the catchments are shaded according to the 90th percentile of the impact level of all cells forecasted within it. 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 where in the impact matrix the catchment lies. There is also some additional information on the number of people, education, health and energy generation facilities potentially affected.