On the Extreme Kumaraswamy-Epsilon Distribution and Its Application to Exceedances of Flood Peaks
DOI:
https://doi.org/10.62054/ijdm/0301.10Abstract
This study introduces and applies the Extreme Kumaraswamy-Epsilon (EKE) distribution to model exceedances of flood peaks data. The EKE distribution, derived from the Kumaraswamy generator with epsilon distribution as baseline, is a flexible five-parameter distribution capable of capturing complex tail behaviour in extreme hydrological events. Using biannual flood exceedance data from the Wheaton River near Carcross, Yukon Territory, the EKE model is evaluated alongside the Generalized Extreme Value (GEV) distribution. Goodness-of-fit measures including the log-likelihood, Akaike Information Criterion (AIC), and Kolmogorov–Smirnov (KS) test suggest that the EKE distribution provides a better fit, offering both statistical robustness and practical relevance for modelling flood extremes.
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Copyright (c) 2026 Isaac E. Gongsin, Pindar N. Dibal, Samaila J. Yaga (Author)
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