Presentation by Bastian Klein, Dennis Meißner and Silke Rademacher, BfG (DE), at the Delft-FEWS - International User Days, during Delft Software Days - Edition 2017. Thursday, 26 October 2017, Delft.

1. Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Pre-operational probabilistic water-level
forecasting with FEWS-BfG
Bastian Klein, Dennis Meißner, Silke Rademacher
Department M2 - Water Balance, Forecasting and Predictions
Federal Institute of Hydrology (BfG)
Delft-FEWS – International User Days
25./26. October 2017, Delft

2. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 2
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
The Waterway Rhine
Amongst the German waterways the River
Rhine takes an extraordinary position …
 The River Rhine is one of the world’s most
frequented inland waterways.
 The volume of goods transported on the
Rhine can be estimated at 310 million tons.
 The average number of vessels using the
Rhine each day is approx. 600 at the
Dutch-German border (~ 400 at Cologne).
 The fleet travelling on the Rhine waterway
can be estimated at about 6,900 vessels
(1,200 are pushed barges, 4,400 motor cargo
vessels and 1,300 tankers).
 Duisburg is the world’s largest inland port
(1350 ha area, 21 port basins, 200 km railway
track).

3. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 3
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Waterlevel Forecast River Rhine
River
Forecast station
Lateral Input
Hydrodynamic
Model Stretch
Hydrological
Model districts
Model Chain
www.ecmwf.int
P, T
Q
W
Hydrological
model
Hydrodynamic
model
Meteorological
model

4. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 4
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Probabilistic Forecasting
 Quantification of the meteorological forecast uncertainty by using meteorological
ensemble forecasts
 Problem: meteorological ensemble forecasts are generally underdispersiv and
biased
Application of the statistical post-processing method Ensemble Model Output
Statistics EMOS (Gneiting et al. 2005) to estimate the predictive uncertainty of
water level forecasts
0 4 7 142 3
ICON-EU
ICON
HRES
10
ENS
COSMO-LEPS
1 5 6
20
51
Vorhersagezeitraum
GEFS Reforecast 11
ICON-EPS 40

5. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 5
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Current Workflow Determinstic Forecasts
Meteorological
Forecasts
Observation
Meteorology
HBV
Observation
Runoff
AR-
Correction
SOBEK
ARIMA (0,1,0)
Correction
Observation
Waterlevel
www.elwis.de
Real Time
Waterlevel ForecastFlow Forecast

6. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 6
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Extended Workflow
Meteorological
Forecasts
Observation
Meteorology
HBV
Observation
Runoff
AR-
Correction
Real Time
Waterlevel ForecastFlow Forecast

7. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 7
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Extended Workflow
Meteorological
Forecasts
Observation
Meteorology
HBV
Observation
Runoff
AR-
Correction
EMOS ECC-T
Real Time
Waterlevel ForecastFlow Forecast

8. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 8
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Probabilistic Forecast
 Estimate parameters of the statistical post-processing method
Ensemble Output Statistics EMOS based on retrospective
forecasts with the current hydrological forecast system (hindcast)
Goal: maximize sharpness under the condition of good calibration
(reliability)

9. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 9
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Ensemble Model Output Statistics EMOS
   2
1
ˆ ˆ, , ,Mf y y y N  
1 1 2 2
ˆ ˆ ˆM Ma b y b y b y        
Predictive Normal Distribution
Mean normal distribution weighted mean of the ensemble members
Variance function of the variance of the ensemble
2 2
c d S   
Parameter estimation by minimizing probabilistic skill measure CRPS

10. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 10
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Probabilistic Hydrographs
 Hydrodynamic model needs hydrographs and no
probability distributions as input
 Ensemble Copula Coupling ECC-T is applied to
calculate runoff trajectories for the input gauges
 Space-time dependency of the raw ensemble is
retained

11. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 11
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Ensemble Copula Coupling

12. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 12
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Extended Workflow
Meteorological
Forecasts
Observation
Meteorology
HBV
Observation
Runoff
AR-
Correction
EMOS ECC-T SOBEK EMOS
AR-
Correction
Observation
Waterlevel
Public
Offline
Real Time
Archiv meteorol.
Forecasts
Observation
Meteorology
Hindcast
HBV
Observation
Runoff
AR-
Correction
ECC-T
Hindcast
SOBEK
Parameter
Estimation
EMOS
AR-
Correction
Observation
Waterlevel
Parameter
Estimation
EMOS
Waterlevel ForecastFlow Forecast
New Workflow Components

13. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 13
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Extended Workflow
Meteorological
Forecasts
Observation
Meteorology
HBV
Observation
Runoff
AR-
Correction
EMOS ECC-T SOBEK EMOS
ARIMA (0,1,0)
Correction
Observation
Waterlevel
Public
Offline
Real Time
Archiv meteorol.
Forecasts
Observation
Meteorology
Hindcast
HBV
Observation
Runoff
AR-
Correction
ECC-T
Hindcast
SOBEK
Parameter
Estimation
EMOS
ARIMA (0,1,0)
Correction
Observation
Waterlevel
Parameter
Estimation
EMOS
Waterlevel ForecastFlow Forecast
New Workflow Components
 Post-Processing of flow with EMOS and ECC
improves overall performance of forecasts
 !But! In pre-operational application problems with
ECC for some forecasts
 In the current pre-operational setting only post-
processing of waterlevels with EMOS
 Further development of EMOS-ECC flow post-
processing

14. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 14
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Verification

15. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 15
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
PDF-Report

16. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 16
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Product Generation
GeneralAdapter
Data Set
(scripts, logos,..)
HTML
Java Report PDF-
Converter
ReportsReport HTML-
Template
Export template
filled with info
GeneralAdapter Export DataSet
Run Batch file
Run R script
PDF-Report
Delft-FEWS EMOS quantiles, ECC ensemble traces, figures,tables
Delft-FEWS Workflow:
Run HBV flow ensemble forecasts, AR correction
Run SOBEK waterlevel ensemble forecasts, AR correction

17. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 17
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Summary
 Technical implementation of probabilistic waterlevel forecasts in the
operational forecasting system of BfG finished
 Since 04/2017 pre-operational 10 day probabilistic waterlevel
forecasts for 7 forecast gauges along the river Rhine are provided to
IMPREX Stakeholders
 Further development of the products based on the user feedback
 Planning: begin of year 2018 publication of operational probabilistic
waterlevel forecasts for the river Rhine to the public
 Development of methods to pre-process meteorological input data
and further development of the post-processing methods (flow and
waterlevel, event depended training of EMOS)

18. Delft-FEWS – International User Days - 25./26. October 2017, DelftSeite 18
Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Further Reading
Hemri, S. (2016): Probabilistic Forecasting Based on
Hydrometeorological Ensembles. Department of Mathematics,
Karlsruhe Institute of Technology. Dissertation
Hemri, S. & Klein, B. (2017), Analog Based Post-Processing of
Navigation-Related Hydrological Ensemble Forecasts. Water Resour.
Res.. Accepted Author Manuscript. doi:10.1002/2017WR020684
Hemri, S., D. Lisniak & B. Klein (2015), Multivariate postprocessing
techniques for probabilistic hydrological forecasting, Water Resour.
Res., 51, 7436–7451, doi:10.1002/2014WR016473
Klein, B., D. Meissner, S. Hemri & D. Lisniak (2015): Ermittlung der
prädiktiven Unsicherheit von hydrologischen Ensemblevorhersagen.
Bundesanstalt für Gewässerkunde. BfG-Bericht 1853.
doi:10.5675/BfG-1853

19. Funded under the
Horizon 2020 Framework Programme
of the European Union
Grant Agreement No 641811
Thank you very much for your attention!
Dr.-Ing. Bastian Klein
Department M2 - Water Balance, Forecasting and Predictions
Federal Institute of Hydrology (BfG)
Am Mainzer Tor 1, 56068 Koblenz, Germany
Tel.: +49 261/1306-5256
E-Mail: klein@bafg.de
www.bafg.de/vorhersage
Funding:
Funded under the Horizon
2020 Framework Programme
of the European Union
Grant Agreement No 641811