Tigabu Muche
Climate has always been dynamic affecting natural systems through the consequence of its variability and change. Agriculture is the most vulnerable and sensitive sector that is seriously affected by the impact of manifested through rainfall variability and recurrent drought. In dry land semiarid areas of Ethiopia, including in the study areas, farmers inhabiting the area experience extreme temporal and spatial variability of rainfall in cropping season with frequent and longer dry spells. This makes them vulnerable to the risk of Meteorological Drought (MD). Thus, in order to adapt and/or mitigate the impact of MD, MD assessment has to form one dimension of research to be done whereas the use of MD indices and different soft wares provides wide scope in drought risk detection and mapping. Consequently, this study was conducted in Eastern Harerghe and Shinile Zones with the objective of assessing MD risk and preparing MD using Rainfall (RF). To assess and examine spatiotemporal variation of seasonal MD patterns and severity, a drought index namely, Standard Precipitation Index (SPI) anomalies are applied. To characterize temporal and spatial MD, rainfall data for a period of 36 years from (1980-2016) were utilized. The time of the seasonal transitions can also be an important control on drought, the result derived from index the annual trends of RF increased in Fedis; whereas, in Deder and Shinile woredas, it decreased with the time. The spatial distribution of drought frequency and its climate trend as well as different drought grades were obtained by employing the inverse distance weighting (IDW) interpolation method in ArcGIS 10.3.1 platform. In this study, the MD indices used to quantify the drought severity, frequency, trends, spatial pattern and its intensity. So, the annual high drought frequency mainly concentrated in the Eastern some areas of Fedis. From South to West part of Deder were observed slight to moderate drought. From slight to severe drought was largely experienced in shinile more than others study areas. Generally, the result revealed that SPI anomaly express decreased with the time over the study areas. Thus, the result indicated that the areas are classified into slight, moderate and severe MD risk zone. Thus, the MD study can be useful to guide decision making process in drought monitoring and to reduce the risk of drought on agricultural production and productivity.
