|Title:||Drought Risk Assessment Using Remote Sensing and GIS: A Case Study in Southern Zones, Tigray Region, Ethiopia|
|???metadata.dc.contributor.*???:||Dr. K.V. Suryabhagavan|
|Keywords:||Remote Sensing;GIS;Drought, NDVI, VCI,;Risk assessment|
|Abstract:||Drought is the most complex but least understood of all natural hazards. It is broadly defined as “severe water shortage”. Low rainfall and fall in agricultural production has mainly caused droughts. Drought causes loss of life, human and animal suffering and damage to economy and environment. The present study area is prone to extreme climate events such as drought. Successive years of low and erratic rainfall have left large areas of the southern zone in severe drought that resulted in crop failure, water shortage and has raised serious food security concerns in the region. Drought assessment and monitoring based on available weather data are tedious and time consuming. Beside that the data are not available in time to enable relatively accurate and timely large scale drought detection and monitoring. But, the satellite sensor data are consistently available, cost effective and can be used to detect the onset of drought, its duration and magnitude. In the present investigation an effort has been made to derive drought risk areas facing agricultural as well as meteorological drought using an eight-year time series of decadal satellite SPOT NDVI (Normalized Difference Vegetation Index) and rainfall data (1998-2005) respectively. A deviation of the current NDVI with the long-term mean NDVI, and the Vegetation Condition Index (VCI) derived from the SPOT used in this study for drought detection, monitoring and real time prediction. In this study, it is indicated that large proportion of the area, i.e. 31.45% (3009km2) is at moderate drought risk level, whereas 17% (1568km2) of the area accounted for high drought risk. It is also shown from the result Enderta, Hintalo Wajirat, eastern part of Raya Azebo and southern part of Alamata Woredas were more susceptible to drought. The results indicate that the two remote-sensing indices used, DEVNDVI, and VCI are complementary and were found to be sensitive indicators of drought conditions. Moreover, SPOT NDVI at 1km by 1km resolution, which incorporates the long-term NDVI, is also the best option for drought risk assessment.|
|Appears in Collections:||Thesis - Earth Sciences|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.