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The European FloodForecasting system
HEPEX Workshop, 08-10 March 2004
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The EFFS: the facts
• Project EFFS was sponsored by the 5th Framework Programme of the European Commission.
• Duration 01/03/2000 – 31/09/2003 (42 months).• EC financial contribution: 1.8 M€ over 3,5 years.• 11 institues + 8 NAS institutes= 19 partners in
total.
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EFFS Project Objectives
• EFFS aims at developing a prototype of a flood forecasting system for the European countries for up to 10 days ahead.
• The main emphasis is on the medium-range lead time, i.e 4 to 10 days.
• The prototype is designed at providing pre-warningto local water and flood forecasting authorities across Europe.
• The system should permit encapsulation of pre-existing hydrological and river routing models already tested and used by local authorities.
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EFFS “Mother” Consortium
• Original Consortium: 11 institutes• 3 Weather services (DWD, DMI, ECMWF)• 3 Universities (Lancaster, Bristol, Bologna)• 2 Research Centres (Delft Hydraulics, JRC)• 2 National Hydro-meteorological Services (SHMI, BAFG)• 1 National Water Management Authority (RIZA)
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EFFS “Mother” Consortium
Univ LancasterUniv. BristolECMWF
WL|Delft,RIZA
SMHI
JRC IspraUniv. Bologna
DWDDMI
GRDC/BFG
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EFFS NAS-1 amendment
• In June 2002 an EFFS amendment is approved to include 8 additional institutes from the Newly Associated States (NAS) in view of the enlargement of the EU.
• Amendment financed with ~ 4 k€ over 1 year• New opportunities: Data from river systems in
Eastern Europe are made available for sharing within the consortium.
• Results of hydrological and river routing models can be compared.
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EFFS NAS-1 Partners
SHMU-SKSlovak UT-SK
Vituki Plc
NIMH-RO
GGI-LT
NIMH-BG
IMWM-PL
Uni Ljubljana-SI
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EFFS Project Organigramm
WP 4: Building a geographical DB
UNI Bristol
WP 3 Hydrological data collection
GRDC
WP 10 Dissemination of forecasts & warnings
SHMI
WP 6 Downscaling and validating meteorological forecasts
DMI
WP 5 Parameter and forecast uncertainty estimation
Lancaster
WP 7 Development of the European-scale FF system
JRC
WP 8 Application, validation &comparison of watershed models
Uni Bologna
WP 9 Set-up & testing of prototype system
RIZA
WP 1 Co-ordinator & interface with EC
WL-Delft Hydraulics
WP 2 Meteorological data collection & supply
DWD
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EFFS structure
Hydrological ModelsSoil, land-use,model parameters
P,T,….
River routers
Weather forecastup to 10 days ahead
1. Global model2. HIRLAM3. EPS4. HIRLAM Mini-EPS
conversion from GRIB toNEFIS format
1. Sobek
2. Muskingam-Cunge
1. Overtopping?
2. Defence structurecollapse?
Inundation modelling
save in DB
save in DB
Operational testing
Warning
meteo and hydro data from hydrological networks
EFFS open-architecture platform
postprocessing
save in DB
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Numerical Weather forecasts
• ECMWF supplies medium range meteorological data from their deterministic model and from their Ensemble Prediction System (EPS).
• DWD and DMI supply deterministic high resolution short range forecasts from their High Resolution Local Area Model (HIRLAM).
• HIRLAM is initialised through Global ECMWF model output
• The high-resolutions forecasts make it possible to estimate the impact of horizontal resolution of the atmospheric predictions on water level forecasts.
• In addition, DMI is experimenting with mini ensembles with the aim to investigate uncertainties in the precipitation forecasts.
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High Resolution Local AreaModel nested domains
Courtesy Danish Meteorological Institute
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Precipitation hindcast
Courtesy Deutscher Wetterdienst
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Hydrological measuring networksin flood forecasting
• The operation of a river basin-scale flood forecasting system, and in particular of a continental-scale system, as EFFS, requires regular update through measured data.
• Which data are required?
1. Precipitation 2. Temperature 3. Synoptic weather data4. Discharge data at critical locations5. Water level data at critical locations
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Measuremement network for the RhineBasin
DWD meteorological stations
Stream flow gauges
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Data acquisition in EFFS•The following scheme shows the data-stream from measuring networks to the EFFS is performed.
•The data acquisition was led by the GRDC in Work-Package 3.
Courtesy GRDC
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Utilisation of measured data in the flood forecasting system
• The regularly update measurement form the hydrological networks are used for the following purpose:
• In now-casting (extremely short lead-time, max 24 hrs) directly measured precipitation data form gauges and radar are used to drive models.
• in EFFS (mdium-range lead-time) hydrological and hydraulic models are updated (data assimilation) through data measured over the 2 weeks precedent the begin of the forecast.
Hattingen / Ruhr -1993 flood event • The data are transferred from the
loggers over FTP into the data-base of the flood forecasting system.
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Hydrological modelling
• Different hydrological models are used within the EFFS system:
1. HBV (SHMI) semi-distributed model the entire Rhine Basin (calibrated at the BFG, Koblenz) representing the Rhine Basin up to Switzerland through 134 sub-basins.
2. LISFLOOD (JRC) raster-based model for simulation of continental river basins at 5 sqkm resolution. Used in particular for Rhine, Odra, Danube.
3. TopKapi (Uni Bologna) for simulation of the Po river basin
N.B.: The system is however conceived as “open “ allowing any other model to be incorporated through an appropriate model-adapter.
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LISFLOOD model
Courtesy Joint Research Centre
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River routing
• Lateral inflows into the main river system are calculated by thehydrological model (e.g. HBV).
• The water is subsequently routed along the main river system (e.g. Rhine).
• Within the EFFS river routing is performed with the WL | Delft Hydraulics Saint-Venant model SOBEK.
• Discharge Q and water level height H at critical sections are calculated.
• Effects of engineering structures such as weirs, locks and bridges are included in the schematisation.
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River routing
Lippe [814.50]
Emscher [797.80]
Wisper [540.30]
Nette [608.70]
Saynbach [599.90]Wied [610.20]
Ruhr [780.10]
Wupper [703.30]Erft [736.55]
Sieg [659.4]
Ahr [629.45]
Selz[518.80] Modau [473.70]
Weschnitz [454.70]
Speyerbach [400.20] Queich [384.80]
Pfinz [380.70]Alb [371.20]
Nahe[529.10]
Lobith [862.2]
Wesel [814.0]
Ruhrort [780.8]
Düsseldorf [744.2]
Cologne [688.0]
Bonn [654.8]
Andernach [613.8] Moselle [592.3]
Lahn [585.7]
Kaub [546.2]
Nahe [529.1]
Mainz [498.3]
Main[496.6]
Worms [443.4]
Neckar [428.2]
Maxau [362.3]
Rees [837.4]
Sobek modelMoselle [592.3]
1
2
3
4
5 6
7
8
9 10
12
11
16
15
14
13
17
8
7
4
1
Neckar [428.2]
Main [496.6]Lippe [814.50]
Emscher [797.80]
Ruhr [780.10]
Wupper [703.30]Erft [736.55]
Sieg [659.4]
Ahr [629.45]
Lobith [862.2]
Wesel [814.0]
Ruhrort [780.8]
Düsseldorf [744.2]
Cologne [688.0]
Bonn [654.8]
Andernach [613.8]
Rees [837.4]
12
11
16
15
14
13
17
48 hourforecastWSD
Model A
Model B
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Floodplain inundation modelling
• Once water overtops a dyke and invades lowlands (e.g. polders), 2-D flood-wave propagation modelling is needed to forecast the extent of the inundation.
• Inundation modelling within EFFS can be performed by two different models:
1. The 2D inundation of the University of Bristol and JRC (LISFLOOD-FP.
2. The Delft 2D inundation model.
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Inundation Modeling River Severn (UK)Raw LiDAR data(6 x 3 km domain)
Topography map
Vegetation height map
Inundation modelling results
Courtesy University of Bristol
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Uncertainty
• Flood forecasting cannot be separated form the problem of the uncertainty inherent to the input, model structure and parameter values.
• Any flood forecasting system is made up by a cascade of models, usually :
• Each model contains parameters which lie within a range, i.e. their exact value is not known.
• In addition the inputs (e.g. rainfall) as well as the initial conditions are affected by uncertainty.
• Subsequently the predictions lead to a bandwidth of forecasted values, which may over- or underestimate the actual water levels.
Meteo Hydrology Routing Inundation
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Model integration: prototype FEWS
• The modeling steps needed in a flood forecasting system are integrated through an integration platform (shell-tool).
• The shell-tool is designed as open and re-usable software system.
• The system is adaptable to different hydrological and hydraulic models through model-adapters.
• The platform is linked to a data-base system.• Results of various model runs are saved and retrieved
subsequently from the DB.• Within the shell-tool model runs, analysis of results and
postprocessing are facilitated.
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The Open-Architecture Platform
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Testing of the prototype
• The EFFS is being tested within the frame of the project in a semi-operational fashion by the Dutch institute RIZA on the river Rhine.
• Several hundreds of forecasts have been carried out though direct access to DWD weather forecast data and subsequent running of the model cascades.
• The predicted water levels are compared directly with the ones measured at the German-Dutch border flow measuring station.
• Results of these test-runs will be presented later on in the conference.
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Flood Warning & dissemination
• Once a high water is forecast by the system, decision need to be made if evacuation is necessary.
• False alarms can be as damaging as not issuing a warning at the right moment.
• Decisions stay ultimately with the forecaster and need use of historical records for verification and uncertainty reduction.
• A systematic approach to address this issue is matter of ongoing research.
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Summary
• The outlined system components will be addressed by the project partners through dedicated sessions during this conference.
• Results and applications of various project applications will be presented.
• Systematic quantification and handling of the inherent uncertainties on forecast results are a complex issue which needs particular attention from a research point of view.
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• Keith Beven• Paul Bates• Erdmann Heise• Tony Hollingsworth• Bo Holst • Michael Hils
• Jaap Kwadijk• Ad de Roo • Kai Sattler • Eric Sprokkereef • Ezio Todini
The conference organisation would like to wish you a pleasant stay and is looking forward to fruitful discussion!
Thank you very much for your attention.
ContributionsTo this presentation have contributed the following people :