Applied Mathematics & Information Sciences

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Climate change represents great concern to the world as a result of extreme weather conditions, such as floods, droughts and heat waves, which are observed all over the world. The sustainanble development of developing nations is greatly affected because their economies are sensitive to these conditions. Extreme weather conditions have had devastating effect on human lives, infrastructure and the environment. Therefore, the present paper investigates the extremal behaviour of yearly maximum rainfall data of the Upper East Region of Ghana with Navrongo Municipality as a case study, using generalized extreme value distribution considering both stationary and non-stationary models. Data consist of yearly maximum rainfalls from January 1983 to December 2018 of Navrongo Municipality Municipality. The least and highest yearly maximum rainfalls recorded in Navrongo Municipality over the period under study are 173.5 mm and 455.5 mm respectively. The data are rightly skewed, leptokurtic and randomly distributed. The results suggests that the behaviour of the limiting distribution of the yearly maximum rainfall data follows a non-stationary Gumbel distribution. Return levels are estimated and are observed to be increasing over a period of time. This means that policy makers and the general public should consider implementing efficient flood mitigating strategies.

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