Many observed annual flood series exhibit reverse curvatures when plotted on lognormal probability paper. The occurrence of reverse curvature may be attributed to factors such as dominance of within-the channel or floodplain flow, seasonal variation in flood-producing storm types, variability in antecedent soil moisture and cover conditions, and a mixture of the probability distributions of observed flood series as a mixture of the probabilities of two lognormal distributions. Distribution parameters can be significantly biased if the observed flood series has outliers and inliers. The distributions of outliers and inliers for various size samples and at various probabilities or significance levels have been developed from extensive Monte Carlo experiments. The objective detection and modification of any outliers and inliers in an observed flood series is an integral part of the versatile flood frequency methodology. Results presented for flood series from 7 basins from different countries show the versatility and superiority of the proposed methodology.