Analysis of Rainfall Trends (1979-2013) Using Non Parametric Test in North West, Ethiopia

Abstract

It is well known that climate change has been contributing to change in amount of rainfall worldwide. This research was conducted in Northeast parts of Ethiopia with a particular reference to Northwest Ethiopia. This area had been distressing from recurrent droughts and faced water scarcity several times. The threat is still hampering the life and agricultural activities of the people. The objective of this study was to determine the existence of trend and rainfall frequency analyses using Mann- Kendall test and Sen's slope estimator techniques. Standardized rainfall  anomaly  index,  rainfall  concentration  index and  coefficient  of  variation  were  also used to describe rainfall variability. Thirty five years of observational data for total annual rainfall recorded at meteorological station of the area was obtained from the National Meteorology Service Agency of Ethiopia. The result of the study elucidated that there are rising rates of rainfall in some months and decreasing trend in some other months obtained by these statistical tests. However, the overall rainfall trends were not statistically significant (p< 0.05), but it was highly variably. The trend of the series for individual 12 months from January to December in the Mann-Kendall test are -0.103, -0.402, -0.321, -0.103, -0.025, -0.022, 0.284, 0.190, 0.170,-0.027, 0.106, -0.039, respectively. The rainfall concentration index revealed that 30% of years with values of PCI >16 in Northwest Ethiopia showed poor and irregular monthly distribution of rainfall. The coefficient variation of the study area was 39% which confirmed high inter-annual variability. The results of this study are in good agreement with the findings of early studies. To conclude, policy makers and practitioners should propose strategies and plans by taking a rainfall variability impacts on livelihoods of rural farming community into consideration and similar work in adjacent districts will be required to better understand the processes responsible for those trends and to properly place them in their larger context.