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Generator of Rainfall and Discharge Extremes (GRADE) for the Rhine and Meuse basins; Final report of GRADE 2.0

M Hegnauer, JJ Beersma, HFP van den Boogaard, TA Buishand, RH Passchier

Currently the design discharges for the rivers Rhine and Meuse are based on a statistical analysis of observed discharges.
A new method has been developed to derive the design discharges and associated flood hydrographs for the rivers Rhine and Meuse. Stochastic simulation of the weather and hydrologicalhydrodynamic modeling are the key elements of this method. The new instrument, called GRADE (Generator of Rainfall And Discharge Extremes), is meant to provide an alternative, more physically based method for the estimation of the design discharge. The GRADE method includes the following components:
Component 1: Stochastic weather generator
The stochastic weather generators used for the Meuse and Rhine basins produce daily rainfall and temperature series. The stochastic weather generator is based on nearest neighbour resampling and produces rainfall and temperature series that preserve the statistical properties of the original series.
Component 2: HBV model
The HBV rainfall-runoff model calculates the runoff from the synthetic precipitation and temperature series. Temperature is needed to account for temporal snow storage as well as evapotranspiration losses.
Component 3: Hydrologic and hydrodynamic routing
This component of GRADE routes the runoff generated by HBV through the main river. For the Meuse the Sobek hydrodynamic model is used for the main river stretch between Chooz (on the French/Belgian border) and Borgharen, and for the Rhine for the main stretch from Maxau to Lobith. For the Rhine, two models are used, one where the effect of flooding of the dikes in Germany is incorporated in the model and one without flooding behind dikes.
The individual GRADE components were tested extensively. The precipitation series simulated by the weather generator preserve the statistical properties of observed daily precipitation, in particular the distributions of multi-day winter precipitation. The HBV models were calibrated using a GLUE (Generalized Likelihood Uncertainty Estimation) analysis and validated for historical flood events. For small sub-basins of the river Rhine, with a response to precipitation of less than a day (with many of these in Switzerland), the HBV-models perform less well. For larger sub-basins however, and for the whole Rhine and Meuse basins, the simulated discharges fit well to the corresponding observed discharge series for many gauging stations. The hydrodynamic routing component was tested for the same historical period as for the HBV model. The simulated discharge series were compared with the observed discharges at the gauging stations at Lobtih (Rhine) and Borgharen (Meuse). Annual discharge maxima are satisfactorily reproduced.
Long simulations with GRADE (of length 50,000-year) are performed and frequency discharge curves and flood hydrographs are derived. The frequency discharge curves reproduce the distributions of the observed annual maximum discharges well. Extreme discharge peaks on the Rhine are substantially reduced by upstream flooding. As a result of flooding the flood hydrograph becomes flatter. The effect of flooding cannot be taken into account in the current method of deriving design discharges and corresponding flood hydrographs.
The uncertainty in the components of GRADE as well as the overall uncertainty in the GRADE simulations is quantified. Two major sources of uncertainty are evaluated, which are the uncertainty in the current precipitation climate (owing to the limited length of the historical precipitation series used in the weather generator) and the uncertainty in the hydrological modeling. For the latter use is made of the results from the GLUE analysis. The combined uncertainty is obtained for return periods up to 100,000 years. As a result of upstream flooding in the Rhine the width of the uncertainty band for the frequency-discharge curve is reduced considerably. The uncertainty of flooding parameters is not taken into account. A sensitivity analysis showed that the impact of flooding is most sensitive to variations in the dike height.
Altogether, GRADE provides a more physically based (and thus more realistic) assessment of extreme discharge statistics and corresponding hydrographs, compared to the current method especially for the Rhine at Lobith in the discharge range where upstream flooding occurs as a result of the current hydraulic conditions.
GRADE has a large potential for applications in wider sense. The method can, for example, also be used for "what-if' scenario analysis. The effect of changes in river geometry (e.g. retention measures), differences in land use or climate change can be taken into account relatively easy. Although this report mainly shows the results at the Dutch border gauging stations Lobith and Borgharen, with GRADE it is also possible to provide the same (statistical) information for other locations in the river basins.

Bibliografische gegevens

M Hegnauer, JJ Beersma, HFP van den Boogaard, TA Buishand, RH Passchier. Generator of Rainfall and Discharge Extremes (GRADE) for the Rhine and Meuse basins; Final report of GRADE 2.0
2014, Deltares, Delft, Netherlands, 2014

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