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PREDICTION OF FUTURE RAINFALL RECORD THROUGH THE MODELING OF EXTREME VALUE THEORY: A CASE STUDY OF MELK ZHAR IN THE SOUSS MASSA REGION OF MOROCCO
Keywords:
non-stationary generalized extreme value, generalized Pareto distribution, maximum likelihood estimation, AIC-BIC, return level, record valuesDOI:
https://doi.org/10.17654/0972361723024Abstract
The understanding of extreme rainfall by extreme value theory has become an essential element in the field of hydrology. In this paper, stationary and non-stationary GEV models are used to fit the annual maximum precipitation data in Melk Zhar, Souss Massa region in Morocco. The Akaike and Bayesian information criteria are used for evaluation of the performance of these models. It is concluded that the Gumbel model is identified as the most significant model for the annual maximum rainfall in Melk Zhar. Consequently, the future rainfall record is carefully estimated and compared to the yield return levels already obtained from the Gumbel model.
Received: February 7, 2023; Accepted: March 20, 2023; Published: April 12, 2023
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