Climate has always been a dynamic entity affecting natural systems through the consequence ofrnits variability and change. Agriculture is the most vulnerable and sensitive sector that is seriouslyrnaffected by the impact of climate variability and change, which is usually manifested throughrnrainfall variability and recurrent drought. In dryland semiarid areas of Ethiopia, including largernpart of East Shewa zone, agricultural drought and crop failure have been common, and farmersrninhabiting the area experience extreme temporal and spatial variability of rainfall in croppingrnseason with frequent and longer dry spells. This makes them vulnerable to the risk of agriculturalrndrought. Thus, in order to adapt and/or mitigate the impact of agricultural drought, agriculturalrndrought assessment has to form one dimension of research to be done whereas the use ofrnremote sensing and GIS techniques provides wide scope in drought risk detection and mapping.rnConsequently, this study was conducted in East Shewa zone with the objective of assessingrnagricultural drought risk and preparing agricultural drought risk zone map using satellite data.rnTo assess and examine spatiotemporal variation of seasonal agricultural drought patterns andrnseverity, three drought indices namely, Water requirement satisfaction index (WRSI), Standardrnprecipitation index (SPI) and NDVI anomaly are applied. A time series advanced very highrnresolution radiometer (AVHRR) NDVI and rainfall estimate (REF) satellite data for the years 1996-rn2008 were utilized as input data for the indices while grain yield data was used to validate thernstrength of indices in explaining the impact of agricultural drought. The result derived fromrnindices for the study period has shown that the 2000 to 2005 cropping seasons experiencedrnenhanced agricultural drought with observed spatial difference in severity level within EastrnShewa zone. However, the severity level was higher in 2000 and 2002 cropping seasons whereasrn2002 being the most severe of all. The impact of agricultural drought on crop production wasrnmeasured through estimation of yield reduction. Compared to other cropping seasons of thernanalysis period, yield reduction for the years 2000 to 2005 was also higher in the East Shewarnzone. Similarly, the year 2002 had highest reduction followed by that of the year 2000. Generallyrnit is revealed that index results are in agreement with results of yield reduction depicting thatrnyield reduction is largely attributed to agricultural drought. In order to evaluate the strength ofrnthe indices for expressing the existence of agricultural drought, simple regression analysis ofrnindices results with total grain yield was computed. The result revealed that WRSI, SPI and NDVIrnanomaly express 76, 64 and 54 percent of variability of the grain yield in that order. Thus, WRSIrncan be a good indicator for occurrence of agricultural drought. Agricultural risk map of EastrnShewa zone was produced by integrating the drought frequency maps derived from the threerndrought indices in order to guide future prioritization of adaptation and mitigation options forrnagricultural drought prone areas. The result indicates that East Shewa zone is classified intornslight, moderate and severe agricultural drought risk zone covering 17.18, 41.32 and 42.50rnpercent of the total geographical area respectively. Thus, this agricultural drought risk mappingrncan be useful to guide decision making process in drought monitoring and to reduce the risk ofrndrought on agricultural production and productivity.rnKey words: Agricultural drought, GIS, NDVI, Remote Sensing, SPI, WRSI