Abstract
Floods are the result of a complex interaction between meteorological event characteristics and pre-event catchment conditions. While the large-scale meteorological conditions have been classified and successfully linked to floods, this is lacking for the large-scale pre-event catchment conditions. Therefore, we propose to classify soil moisture as a key variable of pre-event catchment conditions and to investigate the link between soil moisture patterns and flood occurrence in the Elbe river basin. Soil moisture is simulated using a semi-distributed conceptual rainfall-runoff model over the period 1951–2003. Principal component analysis (PCA) and cluster analysis are applied successively to identify days of similar soil moisture patterns. The results show that PCA considerably reduced the dimensionality of the soil moisture data. The first principal component (PC) explains 75.71% of the soil moisture variability and represents the large-scale seasonal wetting and drying. The successive PCs express the spatial heterogeneous antecedent catchment conditions. By clustering the leading PCs, we detected large-scale soil moisture patterns which frequently occur before the onset of floods. In winter floods are initiated by overall high soil moisture content whereas in summer the flood initiating soil moisture patterns are diverse and less stable in time. The results underline the importance of large-scale pre-event catchment conditions in flood initiation.