Regional analysis of annual maximum and partial duration flood data by nonparametric and L-moment methods

Abstract

The analysis of annual maximum (AM) flood series has revealed unimodal and multimodal probability density functions for floods in the Provinces of Ontario and Quebec, Canada. Based on density function shapes and the timing of floods, Ontario and Quebec have been divided into nine homogeneous regions reflecting similar flood generating mechanisms. A similar analysis of peak over threshold or partial duration (PD) data also revealed unimodality and bimodality linked to flood-generating mechanisms. These results point out deficiencies in currently used parametric approaches for both AM and PD series, since traditional regional flood frequency analysis procedures assume that all floods within a homogeneous region are generated by the same, often unimodal distribution. The analysis of AM and PD series using L-moments revealed that while the overall series did not appear to be unimodal, separate rainfall and snowmelt PD series extracted from the same data set could each be described by unimodal distributions. L-moment tests confirmed that separate rainfall and snowmelt PD series statistics are homogeneous but the overall series is heterogeneous. A regional relationship is developed using nonparametric analysis on the AM and PD flood series. Using the Geographic Information System methodology, mapping was performed for the site-specific L_coefficient of variation and the average snowpack depth. This analysis revealed an apparent correspondence between these variables.