EXPLORATION OF MAXIMUM LIKELIHOOD METHOD IN EXTREME RAINFALL FORECASTING USING FOUR PROBABILITY DISTRIBUTIONS - THE CASE OF NORTHERN ALGERIA

T. BENKACI, N. MEZENNER, N. DECHEMI

Abstract


In this research, we have compared four probability distributions: lognormal, Gumbel, gamma and GEV using method of moments (MM) and maximum likelihood (MLE) parameters estimation that we have applied on extreme rainfall in North of Algeria. The main objective of this study is to explore the advantages of MLE method in extreme rainfall frequency analysis. The comparison between the two methods showed that method of moments gives generally better performances than maximum likelihood, especially for GEV distribution comparing to others distributions, this model (GEV) appears least efficient when skewness of data exceeds 1.2. We have concluded that lognormal distribution is the most efficient and stable and gives better simulation of annual maximum daily rainfall using the two methods for the North of Algeria.


Keywords


Rainfall, Flood, Forecasting, Frequency Analysis, Maximum Likelihood, Algeria.

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