A STATISTICAL ANALYSIS OF THE HISTORICAL RAINFALL DATA OVER EASTERN PROVINCE IN RWANDA
DOI:
https://doi.org/10.62103/unilak.eajst.10.10.118Keywords:
Statistical Analysis, Historical Rainfall Data, Eastern Province, RwandaAbstract
Rainfall is the climatic factor of maximum significance for the East African countries, with extreme occurrences resulting in droughts and floods, which are often associated with food, energy and water shortages, loss of life and property, and many other socio-economic disruptions. Aim of the study was to investigate the extent of possible trends in annual rainfall total, annual rainy days and seasonal rainfall totals in the eastern province of Rwanda. Thirty-five years daily rainfall observations from nine ground weather stations collected from Rwanda Meteorology Agency were used to visualize and test trend in rainfall patterns over Eastern Province of Rwanda. Mann Kendell trend analysis was used to test the significance of trend in annual rainfall totals, number of rain days and seasonal rainfall totals for both long and short rainy seasons. The study revealed that in March to May (MAM) rain season, three out of nine stations registered a decreasing trend and only one station registered a significant increasing trend. During September to December (SOND) rain season, two out of nine stations showed a significant increasing trend and the remaining stations have non-significant trend. On annual basis, two stations revealed a significant increasing trend whereas one station indicated a decreasing trend. Furthermore, the results show that two stations revealed a significant increasing and decreasing trend respectively whereas the remaining stations show a non-significant trend in rainy days. Based on the findings we do not have conclusive evidence on rainfall variability in Eastern Province. Therefore, the study recommends more analysis associating the impact of ENSO phenomena on rainfall distribution over the Eastern Province of Rwanda and a more detailed study of the intra-seasonal rainfall characteristics over the study area.