Reply on RC1

Abstract

Rainfall depth-duration-frequency (DDF) curves are required for the design of several water systems and protection works. These curves are typically generated from the station data by fitting a theoretical distribution to the annual extremes (AMS). The aim of this study is to investigate the use of different data types and methods for estimating reliable DDF curves covering whole Germany. The following three questions are investigated for the evaluation and regionalisation of the DDF curves in Germany: i) which is the best local estimation method, ii) which regionalisation method shows best performance, and iii) which data sets should be used and how they should be integrated. For this purpose, two competitive DDF-procedures for local estimation (Koutsoyiannis et al. 1998, Fischer and Schumann, 2018) and two for regional estimation (kriging theory vs index-based) are implemented and compared. Available station data from the German Weather Service (DWD) for Germany are employed, which includes; 5000 daily stations with more than 40 years available, 1261 high resolution (1 min) recordings with observations period between 10 and 20 years, and finally 133 high resolution (1min) recordings with 60–70 years of observations. The performance of the selected approaches is evaluated by cross-validation, where the local DDFs from the long sub-hourly time series are considered the true reference. The results reveal that the best approach for the estimation of the DDF curves in Germany is by first deriving the local extreme value statistics based on Koutsoyiannis et al. 1998 framework, and later use the kriging regionalisation of long sub-hourly time series with the short sub-hourly time series acting as an external drift. The integration of the daily stations proved to be useful only for DDF values of very low return period (T<10 years), but not doesn’t introduce any improvement for higher return periods (T≥10 years).