Stochastic Modelling of Daily Rainfall for Decision Making in Water Management in Benin (West Africa)

Abstract

The pattern and amount of rainfall are among the most important factors that affect directly or indirectly all sectors depending on water availability (such as agriculture, water supply, hydroelectricity production, etc.). Knowledge of dry and wet spell characteristics of rainfall plays an important role in the management of water resources. The objective of this paper is to apply stochastic process for describing and analyzing the daily rainfall pattern in Benin. To this end, this study used first and second-order Markov chain to analyse the wet and dry spells and then used one-parameter exponential and two-parameter gamma distributions to produce wet day rainfall amount. The results of rainfall occurrence revealed that the probabilities of having two successive dry days and the probabilities of having three successive dry days are highest among all other transitions probabilities. Moreover, analysis of the characteristics of dry and wet spells duration reveals that dry spell duration fluctuates around the mean more than the wet spell duration. Regarding daily rainfall generation, the use of the mean absolutely relative error performance criteria allows us to conclude that the two-parameter gamma distribution is consistently better than the one-parameter exponential distribution at simulating rainfall in the study area at daily, monthly and yearly scale.