Two regional estimation schemes, based on, respectively, partial duration series (PDS) and annual maximum series (AMS), are compared. The PDS model assumes a generalized Pareto (GP) distribution for modeling threshold exceedances corresponding to a generalized extreme value (GEV) distribution for annual maxima. First, the accuracy of PDS/GP and AMS/GEV regional index-flood T-year event estimators are compared using Monte Carlo simulations. For estimation in typical regions assuming a realistic degree of heterogeneity, the PDS/GP index-flood model is more efficient. The regional PDS and AMS procedures are subsequently applied to flood records from 48 catchments in New Zealand. To identify homogeneous groupings of catchments, a split-sample regionalization approach based on catchment characteristics is adopted. The defined groups are more homogeneous for PDS data than for AMS data; a two-way grouping based on annual average rainfall is sufficient to attain homogeneity for PDS, whereas a further partitioning is necessary for AMS. In determination of the regional parent distribution using L-moment ratio diagrams, PDS data, in contrast to AMS data, provide an unambiguous interpretation, supporting a GP distribution.