Data-assimilation in flood
forecasting for the river Rhine
between Andernach and Düsseldorf
COR-JAN VERMEULEN
Introduction
238 recorded
floods in Europe
between
1975 and 2001
Introduction
Flood events
Deaths per events
Introduction
Huge investments in flood prevention, flood early
warning, flood mitigation measures and flood
management
FloodMan:
Near real-time flood forecasting, warning and
management
Introduction
• Data-assimilation of hydrological and hydraulic
parameters for flood forecasting
• Independent of the
computer models used
• Use of in-situ and
satellite data
• Pilot:
Rhine river, Germany
Data-assimilation
• Combining model estimates with measured
data
• Including measure of uncertainty for estimates
Pilot Rhine river
Flood forecasting system
• Rainfall-runoff Model (HBV)
• Water Transport Model
• Hydraulic Model (Sobek)
• Data-assimilation
Düsseldorf [744.2]
Wupper [703.3]
Erft [736.55]
Worringer Bruch [709.5.1]
Köln [688.0]
Köln-Langel [671.1]
Sieg [659.4]
Node (Gage)
Bonn [654.8]
Branch (influence of Ground
Retention Area
Tributary
Ahr [629.54]
Andernach [613.8]
Hydro-meteo
database
Data-assimilation
Hydrological
model
Filtered
model parameters
runoff prediction
Dataassimilation
Hydraulic
model
Filtered
water levels and flows
Prediction of
water levels and flows
Dataassimilation
actual
measurements
Weather
forecast
Hydrological
model
Forecast tributaries
Hydraulic
model
Flood forecast
Forecast
Flood forecasting system
• Data-assimilation hydrological model
• Sensitivity and uncertainty analysis
– Adaptation soil moisture content
– Adaptation upper zone
• All sub basins treated equally
• Use adaptation factors in forecasting
Flood forecasting system
• Data-assimilation hydraulic model
• Sensitivity and uncertainty analysis
– Parameter
Adaptation roughness
channel
Influence main
Uncertainty
Large discharges
Moderate
– Roughness
Adaptation lateral
main channel
Moderate
• Roughness
Desired accuracy
Dataassimilation
Bank section
Moderate
• Roughness
Until calculated
waterModerate
levels at Bonn and
Moderate
floodplain
Cologne “agree” with measurements
•
Discharge
Moderate
Large (?)
Sieg
Use adaptation
in forecasting
Groundwater
Small factors
Moderate/Large
(?)
Results
Sobek with and without data-assimilation (Köln)
0.2
difference measurement and Sobek
water level measured
difference measurement and Sobek assimilated
46
water level differences
0.15
45
0.1
44
0.05
0
43
-0.05
42
-0.1
41
-0.15
-0.2
23-Dec
24-Dec
25-Dec
26-Dec
27-Dec
28-Dec
29-Dec
30-Dec
40
31-Dec
Conclusions
data-assimilation in-situ data
• Large calculation time (10 minutes for a day)
• Relatively small changes parameters indicating:
– well calibrated hydraulic model
– robust data-assimilation algorithm
• Forecast pattern remains similar
• Average accuracy around 5 cm in water levels
Role of satellite data
• Use of satellite data in deducing water levels
• Additional information is to be used in dataassimilation of hydraulic model
• Satellite ‘measurements’ are, compared to insitu measurements:
– less accurate, but
– more detailed
Example satellite data
Possible role of satellite data
• No real flood maps based on EO-data available
for Rhine river, Germany
• Synthetic flood maps, using hydraulic model
and a digital terrain model
• Introducing inaccuracies (‘noise’) by modelling
errors in:
- geo referencing; and
- classification
Error in geo referencing
Error in classification
Procedure
Conclusions using flood maps
• Results depend on quality of satellite data
– high resolution
– low noise
• Flood maps to water levels
–
–
–
–
Area’s instead of cross-sections
stretches long enough (5 – 10 km)
straight river sections
gentle slopes, no steeps banks
• Opportunity
– comparison of flood extent calculated and
satellite data.
Conclusions FloodMan
• The flood forecasting system is robust and
ready to serve under operational conditions;
• In the pilot small improvement in the flood
forecast accuracy;
• Forecast including measure of uncertainty:
useful for decision making.
• Use of satellite data is promising, especially
for river systems with few gauging stations
– BUT high resolution satellite data needed
Further work
• Flood forecast systems with data-assimilation
on hydrological and hydraulic model are
implemented
• Different data-assimilation algorithms
• Data-assimilation to combine rainfall radar
data with in-situ measurements
• Use of satellite data to determine flood extent
in case of dike breach for:
– estimate width and depth of dike breach
– estimate discharge at dike breach