Abstract:
The accumulation of extreme rainfall events over the catchment trigger floods which impact on society and lead to loss property and life. Therefore, reliable analysis of extreme rainfall has importance for heavy precipitations prediction and flood risks mitigation. This study have examined the extreme rainfall events emphasizing on the analysis of Annual maximum daily rainfall during the years 1981-2016 over Sebeya catchment. The utilized rainfall data were extracted from the three stations Kanama Pfunda and Gisenyi Aero installed in the catchment in accordance of Rwanda meteorology Agency. The trend lines in identified annual maximum daily rainfall series showed that the amounts extreme rainfall in Sebeya catchment has increased over 36 years but with weak significance level. By using Easyfit software, General Extreme value distribution was selected to model the Annual Maximum Daily Rainfall series and Kolmogorov Simonov (K-S), Chi-Square and Anderson Darling were used for Goodness of Fit tests to accept null Hypothesis that series fit the model. P-P plots indicated that the annual maximum daily rainfall data points fall along the diagonal straight-line and indicate that GEV fitted the data for all three stations. From the frequency analysis, the exceedance probability and recurrence interval plot were constructed using linear scale the and the analysis shows that the catchment receives rainfall depths between 50-30mm which is classified in medium risk with 40% to 98% of probability to exceed and a recurrence interval of once in one and 2 years. The high risk rainfall events have exceedance probability of 20-1% with the return period of once in 5, 10, 23 and 65 years. In comparing the extreme daily rainfall which were likely to trigger floods in Sebeya catchment with daily maximum discharge indicates that is weak correlated due to various hydrological characteristics of the catchment.
