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For the drainage basin of the Rhine upstream of the Netherlands (165 000 km2) long-duration sequences of multi-site daily precipitation have to be generated as part of a new methodology to reduce the uncertainties in the design water levels for flood protection. A stochastic rainfall generator for the Rhine basin has been developed for this purpose. Besides precipitation, daily temperatures are also generated in order to account for the effects of snowmelt and frozen soils. For coupling with hydrological (HBV) and hydraulic models daily precipitation and temperature are generated for 134 sub-catchments. The project is commissioned by the National Institute for Inland Water Management and Waste Water Treatment (RIZA).
Our weather generator for the Rhine basin (upstream of Lobith) makes use of the non-parametric nearest-neighbour resampling scheme. Nearest-neighbour resampling has been introduced in 1996 in the hydrological literature by U. Lall, B. Rajagopalan and A. Sharma at Utah State University, Logan. The main advantage of a non-parametric resampling technique is that it preserves the spatial association of daily rainfall over the drainage basin and the dependence between daily rainfall and temperature. To reproduce the autocorrelation structure of the data, a new day is resampled from the historical data by conditioning on the generated values for the previous day. Only the k nearest neighbours of the latter are considered for resampling. Summary statistics of the daily precipitation and temperature fields as well as atmospheric circulation indices have been used to find the nearest neighbours in the historical data. The choice of k turns out to be rather crucial for the reproduction of autocorrelation coefficients and properties of extreme multi-day rainfall.
Several 1000-year simulations have been performed to study the occurrence of unprecedented events. Figure 1 compares the 10-day winter maximum precipitation amounts in ten 1000-year simulations with the corresponding observed 10-day maxima. The largest 10-day precipitation amounts in a number of the 1000-year simulations exceed those in the observed data considerably.
Figure 1. Gumbel plots of the 10-day maxima of basin average precipitation in winter (October - March) for 35 years of observations (from 1961-1995) and for ten 1000-year simulations.
For the German part of the Rhine basin (105 000 km2), the spatial distribution of the 10-day rainfall in one of these so called super events is shown in Figure 2.
Figure 2. Spatial distribution of 10-day rainfall in a simulated extreme event in the German part of the Rhine basin (with an area-average 10-day rainfall amount of 141 mm).
A similar resampling technique for (sub-)daily rainfall has been developed for the Meuse basin. Currently we are working on an extension for the Meuse to generate synthetic data under climate change conditions based on simulations with the KNMI regional climate model RACMO.
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Jules Beersma