Rainfall Forecasting in Gasabo District Using Markov Chain Properties

Over the last decade, the whole world has undergone the atmosphere changes; as a result, the disasters such as floods, landslides, droughts and ground water declination have taken place. The same problem has remarkably affected the developing countries including Rwanda, due to the weakness of rainfall forecast, using meteorological historical data. The researcher developed a rainfall Markov chain model based on Rwandan meteorological data collected for 44 years (1971-2014). The findings from survey indicated the transition matrix and limiting states probabilities vector as p = [0.78 0.07 0.12 0.03],Þ = 1 å pi , got after 6 years. The correlation between states has been found, and revealed that there were other uncontrollable factors. The researcher recommends decision makers of Rwanda Meteorology Agency to adopt the markov chain model to provide and to disseminate the needed information about climate change early and do the forecasting.