Abstract
Abstract. Pure radar rainfall, station rainfall and radar-station merging products are analysed regarding extreme rainfall frequencies with durations from 5 min to 6 h and return periods from 1 year to 30 years. Partial duration series of the extremes are derived from the data and probability distributions are fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at the station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behaviour of the radar rainfall. The merging products between radar and station data on the other hand lead usually to an underestimation. They can only outperform the station observations for longer durations. The main problem for a good estimation of extremes seems to be the poor radar data quality.
Highlights
Design storms are required for the planning and evaluation of hydraulic structures and flood risk management in urban and rural catchments
Employing pure radar for the estimation leads to a significant underestimation, which is typical for comparisons between radar rainfall and station values
This study has investigated the benefit of radar data for the estimation of design rainfall
Summary
Design storms are required for the planning and evaluation of hydraulic structures and flood risk management in urban and rural catchments. The design storms are derived from frequency analyses of annual maximum rainfall or rainfall above a threshold for specific durations. The storms are usually condensed for different durations and frequencies to intensity-duration-frequency (IDF) curves or depth-durationfrequency curves (DDF) for a certain location. Short duration observations are often only available with poor spatial density, which demands regionalisation. There have been different studies about regionalisation of DDF curves over the last years (Durrans and Kirby, 2004; Johnson et al, 2016; Madsen et al, 2002). Scaling methods have been applied to derive IDF curves for short durations from better available daily observations (Yu et al, 2004)
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