Project Description

FEWS – Flood Early Warning System, Switzerland

Keywords: flood forecasting, flood early warning system (FEWS), rainfall runoff modelling, hydrodynamic modelling

Assignment Since the year 2000 Deltares is still involved in the development of the Delft-FEWS forecasting system (FEWS-FOEN) for the Swiss Federal Office for the Environment (FOEN). FEWS-FOEN prepares daily reports on water conditions and discharge forecasts for Switzerland. The modelling system used is currently primarily based around the HBV model developed by the Swedish Meteorological and Hydrological Institute (SMHI). Recently there has been a drive to integrate also other (regional) modelling systems as PREVAH and WaSiM-ETH that provide more spatial detail. Figure 1: Delft-FEWS Explorer

FEWS - Flood Early Warning System, Switzerland

Introduction The Rhine river is the most important river basin in Switzerland and originates in the Swiss mountains. The hydrology of the Swiss Rhine is complicated by the combination of rain and snow as well as a number of lakes of various sizes that need to be incorporated in a flood forecasting model. In FEWS-FOEN, use is made of the Delft-FEWS, the standard software of Deltares for flood forecasting systems. Project area The project area includes all the tributaries of the Rhine and Rhone rivers in Switzerland (Figure 2).

Figure 2: FEWS-FOEN current model coverage HBV in the Rhine river basin is implemented for 62 basins, based on hydrological units. Each sub-basin is subdivided into elevation zones. Up to the altitude of 2000 m.a.s.l. these zones have an elevation interval of 100 m and between 2000 to 4500 m.a.s.l. the interval is 250 m. A further subdivision of each elevation zone is based on land use with a distinction into forest, open land (field), glacier and lake. Recently, regional models as WaSiM-ETH (Figure 3) for the Rhone and Emme basins and PREVAH for the Sihl and Linth basins were integrated into FEWS-FOEN. Forecast models Two types of models are normally used in a forecasting system: rainfall-runoff models and hydrodynamic river flow models. In FEWS-FOEN both types are combined in the HBV and WaSiM-ETH rainfall-runoff models, using incorporated hydrologic routing and a special reservoir module in HBV. The PREVAH semi distributed hydrological model is linked to the hydrodynamic model FLORIS in FEWS-FOEN. Output of the (semi) distributed models is routed into the HBV model chain. The motivation to integrate regional distributed hydrological models into FEWS-FOEN is that experience showed that the HBV conceptual model did not quite capture the dynamic response of (higher elevation) catchments. In the coming years FOEN plans to integrate additional regional models into FEWS-FOEN.

Figure 3: Structure of WaSiM-ETH FEWS philosophy Delft-FEWS is an open environment for the application of various modelling tools build-up around a central database. A set of standard tools related to data handling is available. This includes modules for importing and exporting data, validation of data, interpolation of data (both filling gaps in time, as well as in space) and transformation of series (aggregation, disaggregation, and transformation). The concept of Delft-FEWS is shown in Figure 4.

Figure 4: Concept of Delft-FEWS Furthermore, Delft-FEWS makes use of a so-called general adapter (Figure 5), which allows a Client to continue to use its own models. Model input data such as rainfall or input discharges time series can be exported from Delft-FEWS and model results such as runoff, water levels and discharges time series can be imported in Delft-FEWS. For hydrological and hydraulic models, model wrappers are available that convert model result files to FEWS files.

Delft-FEWS• import• validation• transformation / interpolation• data hierarchy• general adapter• export / report• administration (data, forecasts)• viewing (data, forecasts)• archiving• …

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FEWS – Flood Early Warning System, Switzerland

Figure 5: General Adapter Operation of FEWS-FOEN FEWS-FOEN includes a number of workflows which perform different steps of the flood warning process. The user can display and edit data in the user interface, import data, run forecasts and analyse and display results.

Importing data Data that are imported into FEWS-FOEN include meteorological observations and forecasts as well as hydrological observations. The meteorological forecasts are made available as gridded data by Swiss Meteorological Institute (SMA) and European Centre for Medium-Range Weather Forecasts (ECMWF). The SMA forecasts over a period of 72 hours and has a resolution of approximately 7 km, with the parameters precipitation, temperature, wind speed, dewpoint, global radiation and sunshine duration. The ECMWF forecasts cover a period of 240 hours (10 days) and include the same parameters. In Figure 6 the gridded meteorological input is shown for COSMO-2.

Figure 6: Spatial Display with meteorological forecasts

Preprocessing of data After the observed time series have been completed and converted to the correct parameters some further processing

need to be done in order to prepare the time series for using in the hydrological models. The main processing tasks on the time series are: Interpolate the observed meteorological time series to

catchments and elevation zones in HBV basins Compute vapor pressure from dewpoint temperature Compute the zero degree altitude levels for each HBV

catchment for snow calculations (Figure 7) The latter activity is included, because snow plays an important role in the hydrology of the Swiss mountain rivers and as such has obtained ample attention during the development of the FEWS-FOEN. The HBV, PREVAH en WaSiM-ETH models have a snow module included. In HBV snow calculations are made separately for each elevation/vegetation zone within a sub-basin. The model computes the snow storage from the accumulated snowfall and snow melt. The snow pack is assumed to retain melt water as long as the amount does not exceed a certain fraction of the snow. When temperature decreases below a predefined value, this water refreezes. The refreezing rate is a certain fraction of the melt rate.

Figure 7: Spatial Display with zero degree lines

Figure 8: Interpolated temperature for the Rhone catchment

General AdapterModule

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1: Export model inputs2: Run pre-adapter3: Run model4: Run post-adapter5 Import model results

FEWS - Flood Early Warning System, Switzerland

P.O. Box 177, 2600 MH Delft, The Netherlands, T +31 (88) 33 58 273, F +31 (88) 33 58 582, international@deltares.nl, www.deltares.nl Deltares is registered with the trade register of the Chamber of Commerce Haaglanden with number 41146461, as Foundation 'Stichting Deltares'.

Special attention is given to the lakes in Switzerland, which can have a large impact on the behaviour of the hydrological system during floods, especially those that are regulated. Some of the lakes form groups, such as the Bodensee/Untersee and the Murtensee, Neuenburgersee and Bielersee. Especially the latter is a complicated system as it witnesses flow in two directions depending on the particular situation during the year (Figure 9).

Figure 9: Bielersee / Neuenburgersee within a 3-lake system After all data preparation and processing tasks are completed, the hydrological and hydraulic models are used to simulate catchment discharges and lake water levels. The complete simulation is split up in an update run and a forecast run. The update run is executed using as many observed meteorological and hydrological time series as possible. After the update run has been completed a forecast can be made from the states produced by the update run. The forecast run uses the imported meteorological forecast grids. Average catchment values are derived from the meteorological forecast grids for the HBV catchments, while for the WASIM-ETH model the meteorological grids are downscaled (Figure 10). Figure 10 presents how the update and forecast run for WASIM-ETH are implemented in FEWS-FOEN.

Figure 10: Integration of WaSiM-ETH in FEWS-FOEN The model results from HBV, WaSiM-ETH and PREVAH are post-processed by using the FEWS ARMA error module. The module is used to improve the reliability of forecasts by attempting to identify the structure of the error that is made by the forecasting module during the modelling phase where both the simulated and observed values are available, and then applying this structure to the forecast values. This ARMA module requires input series from the observed hydrological data, the update run and the forecast run. The results of the forecast runs are visualized in the Delft-FEWS explorer window that indicated whether or not a certain pre-defined warning level has been exceeded (Figure 11). Figure 11: FEWS Explorer with a warning level icon