Abstract
In order to plan effective agricultural and water resource projects, it is necessary to understand the spatial and temporal variability of rainfall. Although it is one of the most drought-hit countries in the world, almost no study has ever been conducted in characterising the rainfall pattern of the arid and semi-arid regions of Ethiopia. In this study, rainfall data of the past 50 years was used to study the basic statistical characteristics of the rainfall of this region. Annual and monthly rainfall was fitted to the theoretical probability distributions and the best distributions describing the data at respective stations were determined. Probability of wet days and dry periods of different durations was determined. It has been found that both annual and monthly rainfall at different stations was described by different probability distributions. There is high variation of rainfall pattern among the stations. Heavier rainfall events are infrequent but they make up a significant percentage of the total rainfall. In arid and semi-arid regions where both the amount and frequency of rainfall occurrence is low, it is essential to take into account the unique rainfall characteristics in such regions. Water SA Vol.32 (3) 2006: pp.429-436
Highlights
Rainfall is the most important environmental factor limiting agricultural activities in the arid and semi-arid regions of the tropics
Assaita and Gode are relatively arid as a result of low rainfall and high evapotranspiration in these areas
Annual rainfall recorded at eight rain-gauge stations in arid and semi-arid regions of Ethiopia was fitted to five probability distribution functions
Summary
Rainfall is the most important environmental factor limiting agricultural activities in the arid and semi-arid regions of the tropics. Soil moisture management in semi-arid and arid areas of the tropics is faced with limited and unreliable rainfall and high variability in rainfall pattern (Kipkorir, 2002). It is very hard for hydrologists to measure, collect and store hydrological data such as rainfall and runoff. The available data are limited and may contain some gaps in the series. The gaps in the data can be filled or the series extended to a longer period using mathematical equations. Some of the most common and important probability distributions used in hydrology are the normal, lognormal, gamma, Weibul and Gumbel (Aksoy, 1999). The Weibul and Gumbel distributions are used for extreme values of hydrological variables
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