This paper demonstrates the application of Markov chain model with non-stationary transition probabilities to study data of the Reservoir elevation of Shiroro dam in the dry and raining seasons. The result indicates an optimal of 40% and 49% transition probabilities at equilibrium for dry season and wet season respectively. The result confirms the reality on the ground that higher reservoir elevation is obtained more during the raining season. Conversely, the lower reservoir elevation is experienced largely in the dry season. The variation of the reservoir elevation directly affects the hydro electric power generation and the availability of the other dam resources. Markov chain model could be used as a predictive device for studying reservoir elevation of Shiroro dam. These predictions might be used for the management of the dam resources.
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