Application of Remote Sensing and GIS to Characterize Agricultural Drought Conditions in North Wollo Zone, Amhara Regional State, Ethiopia

Abstract

Drought is the most complex but least understood of all natural hazards. Major food production in Ethiopia, especially in the Amhara Region, North Wollo Zone, is almost fully dependent on rain-fed agriculture and the area is often hit by periodic droughts. This drought causes serious economic, social, food security and environmental problems.  In this study, the Standardized Precipitation Evaporation Index (SPEI) and Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI), were applied to characterize the agricultural drought conditions in North Wollo Zone from 2000 to 2015. Correlation analysis was performed between NDVI and SPEI, rainfall and NDVI, VCI and rainfall, NDVI and Crop Yield Anomaly and SPEI and Crop Yield Anomaly. SPEI values were interpolated to get the spatial pattern of meteorological based drought. Ground based crop yield data was used to evaluate the drought monitoring index. Finally, the combined drought severity map was generated by overlaying the agricultural and meteorological drought severity maps. The results showed that there was good correlation between rainfall and NDVI (r=0.71), VCI and Rainfall (r = 0.77), NDVI and SPEI (r=0.82) and NDVI and Crop Yield anomaly, (r=0.78) and SPEI and Crop Yield Anomaly (r=0.83). The drought severity was analyzed from 2000 to 2015 based on satellite and climate data. The two years 2005 and 2015 were considered as drought years and 2009 and 2013 were taken as slight-drought years. The extent of drought severity was increased by increasing time scale. The combined risk map showed that approximately 5, 19.5, 33 and 42. 5% of the study area has faced by slight, moderate, severe and very severe risk, respectively. Drought from socio-economic aspect has not been studied. Besides, delineating areas under drought risk relevancy of risk assessment can be made more meaningful when the human population as well as livestock population under risk will be assessed. Therefore, it is recommended to include the socio-economic data to better understand the vulnerability factors.

Keywords: Agricultural drought, Meteorological drought, SPOT, NDVI and SPEI.