Markovian approach for analysis and prediction of monthly precipitation field in the department of Sinfra ( Central-west of Côte d'Ivoire)
Authors: Vami Hermann N'GUESSAN BI , Mahaman Bachir SALEY, Sorin POP, Romulus TEREBECH, Bogdan Be, Eric Valere DJAGOUA ,Fernand Kouamé, Monica BORDA , Kouadio AFFIAN
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Regional rainfall trends in Ivory Coast, due to climate change, show a general decrease in rainfall over the entire country. This is likely to disrupt plans streams thereby reducing the availability of surface water resources. The objective therefore assigned to this work is to analyze the precipitation field while incorporating the effect of climate change. For field analysis of precipitation, the approach follows a markovian approach, which is a stochastic approach widely used to analyze and simulate the spatio-temporal evolution of a system from transition probabilities. The study was conducted on a time series of rainfall data (1966-2000) and showed that monthly precipitation echoes are well described by a Hidden Markov Model (HMM). The arkovian approach followed in this work has helped develop a model to analyze and forecast precipitation field in the department that of Sinfra that reflects reality with accuracy about 83 %.