Frequency Analysis of Extreme Mean Annual Rainfall Events - Masereka, E.M.; Otieno, F.A.O.; Ochieng, G.M.; Snymand, J. (Organising Committee, CIGR 2016, 2016)
Frequency analysis of extreme mean annual rainfall events is important to water resource planners at catchment level because mean annual rainfall is an important parameter in determining mean annual runoff. Mean annual runoff is an important input in determining surface water available for water resource infrastructure development. The objective of this study was to carry out frequency analysis of extreme low mean annual rainfall events in 8 rainfall zones in the Sabie River catchment in South Africa. Peaks Below Threshold (PBT) method was applied to extract extreme low mean annual rainfall events from 85 year record. Candidate Model Identification Criterion (CMIC) and Least Sum of Statistic Model Selection Criterion (LSSMSC) were applied to identify the best fit models for the frequency analysis. Parameters were estimated by maximum likelihood method. Quantile-Quantile (Q-Q) and Probability-Probability (P-P) plots were applied to evaluate the performance of the model selection criteria. From the study, the quantiles at return periods of 5, 10, 25, 50, 100 and 200 years for each of 8 rainfall zones in Sabie River catchment were obtained. Based on the results of the study, no single probability distribution function or model is the best fit for frequency analysis of extreme low mean annual rainfall events in all 8 rainfall zones Sabie River catchment.
Keywords: least sum of statistics model selection criterion; Best fit probability distribution function; Candidate model identification criterion