We examine the predictive performance of various flood regionalisation methods for the ungauged catchment case, based on a jack-knifing comparison of locally estimated and regionalised flood quantiles for 575 Austrian catchments, 122 of which have a record length of 40 years or more. The main result is that spatial proximity is a significantly better predictor of regional flood frequencies than are catchment attributes. A method that combines spatial proximity and catchment attributes yields the best predictive performance. This is a novel method proposed in this paper which is based on kriging and takes differences in the length of the flood records into account. It is shown that short flood records contain valuable information which can be exploited by the proposed method. A method that uses only spatial proximity performs second best. The methods that only use catchment attributes perform significantly poorer than those based on spatial proximity. These are a variant of the Region Of Influence (ROI) approach, applied in an automatic mode, and multiple regressions. It is suggested that better predictive variables and similarity measures need to be found to make these methods more useful. A stratified analysis suggests that in wet catchments all regionalisation methods perform better than they do in dry catchments.