Abstract:
Rain variability in space and time is one of the most relevant characteristics of tropical rain forest
that is associated with economic, social and ecological implications. Extreme rain events have
significant environmental consequences that cause considerable damages in urban as well as in
rural areas. Temporal variability of precipitation is a key factor influencing the structure and
function of semiarid ecosystems. The climate of the Dire Dawa Administration is being located
in an arid and semi-arid part of the country and dominated by various inter-related factors,
altitude being the most determinant factor and the temporal variability of precipitation affects
the runoff process. This resulted in flash flood disasters and drought during recent years and
requires an urgent course of mitigation measures to alleviate the associated problems. This
requires detail information regarding the temporal distribution of annual, seasonal and monthly
rainfall pattern in the region. The present study has been carried out for 20 different probability
distribution {gamma (2P, 3P), generalized gamma (3P, 4P), logistic, log-logistic (2p, 3p), log
gamma, normal, lognormal (2P, 3P), Weibull (2P, 3P), Pearson 5 (2P, 3P), pearson 6 (3P, 4P),
log-pearson 3, generalized extreme value and Gumbel’s maximum distribution } and associated
goodness of fit test using Kolmogorov Smirnov, Anderson Darling and Chi-Squared tests.
Temporal rainfall variability is assessed using statistical trend analysis of the monthly, seasonal
and annual rainfall using the Mann–Kendall test, the Sen’s slope estimator and spearman’s Rho
test. It was observed that according to Kolmogorov Smirnov and Anderson Darling test,
Generalized Extreme value distribution fits well to the rainfall data occupying 45% and 40%
respectively and the log logistic (3p) obtained 32% according to Anderson Darling. Among these
distributions 41% of the rainfall follows general extreme value while 24% and 18% of the Dire
Dawa Administration rainfall gamma (2p) and log logistic (3p) distribution respectively. The best
distribution for one day maximum rainfall received during different months in a 39 year was
Generalized Extreme Value and it can be seen that April month received the highest amount of
one day maximum rainfall (25%) followed by January, March and August with the same percent
of (13%). The minimum rainfall of 27.4 mm rainfall can be expected to occur with 97.5 per cent
probability and one year return period and a maximum of 137.5 mm rainfall can be received with
one per cent probability and 200 year return period. There are rising rates of precipitation in some
months and decreasing trend in some other months obtained by Mann-Kendall Test together with
the Sen’s Slope and Spearman’s Rho test, Statistically significant negative were found for both
Mann-Kendall test and Spearman’s Rho in February at 10% significance level and positive trends
were found in July (1% and 5% significance level) and November (5% significance level),
statistically significant negative were also found for Spearman’s Rho test in April at 10%
significance level. While no significant trends were found for other months. Therefore it can be
concluded that there is evidence of some change in the trend of precipitation of the region.