Articles | Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 309–327, 2015
Hydrol. Earth Syst. Sci., 19, 309–327, 2015

Research article 16 Jan 2015

Research article | 16 Jan 2015

What made the June 2013 flood in Germany an exceptional event? A hydro-meteorological evaluation

K. Schröter1,3, M. Kunz2,3, F. Elmer1,3, B. Mühr2,3, and B. Merz1,3 K. Schröter et al.
  • 1Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Section Hydrology, Potsdam, Germany
  • 2Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Karlsruhe, Germany
  • 3CEDIM – Center for Disaster Management and Risk Reduction Technology, Potsdam, Germany

Abstract. The summer flood of 2013 set a new record for large-scale floods in Germany for at least the last 60 years. In this paper we analyse the key hydro-meteorological factors using extreme value statistics as well as aggregated severity indices. For the long-term classification of the recent flood we draw comparisons to a set of past large-scale flood events in Germany, notably the high-impact summer floods from August 2002 and July 1954. Our analysis shows that the combination of extreme initial wetness at the national scale – caused by a pronounced precipitation anomaly in the month of May 2013 – and strong, but not extraordinary event precipitation were the key drivers for this exceptional flood event. This provides additional insights into the importance of catchment wetness for high return period floods on a large scale. The database compiled and the methodological developments provide a consistent framework for the rapid evaluation of future floods.

Short summary
Extreme antecedent precipitation, increased initial hydraulic load in the river network and strong but not extraordinary event precipitation were key drivers for the flood in June 2013 in Germany. Our results are based on extreme value statistics and aggregated severity indices which we evaluated for a set of 74 historic large-scale floods. This flood database and the methodological framework enable the rapid assessment of future floods using precipitation and discharge observations.