Application of Remote Sensing for Delineation of Drought Vulnerable Areas in Amhara Region
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Date
2007-07
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Addis Ababa Universty
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. A droughts impact constitutes losses of life, human suffering
and damage to economy and environment. Droughts have been a recurring feature of the
Ethiopian climate therefore study of historical droughts may help in the delineation of
major areas facing drought risk and thereby management plans can be formulated by the
government authorities to cope with the disastrous effects of this hazard. The Amhara
region is prone to extreme climate events such as drought. Successive years of low and
erratic rainfall have left large areas of the region in severe drought that resulted in
crop failure, water shortage and has raised serious food security concerns for 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 work an effort has been made to
derive drought vulnerable areas facing agricultural drought by use of temporal images
from NOAA-AVHRR (8km) and MODIS (500m) based Normalized Difference
Vegetation Index (NDVI) (1981- 2007) and (2000 to 2003) respectively. A deviation of
the current NDVI with the long-term mean NDVI, and the Vegetation Condition
Index (VCI) derived from the AVHRR and MODIS used in this study for drought
detection, monitoring and real time prediction. The results clearly indicate that the
temporal and spatial characteristics of drought in Amhara region detected and mapped
by the DEVNDVI, and VCI indices. These results were validated by ground truth data such
as precipitation and agricultural crop yield. The validation result shows that there
is a strong correlation between the satellite derived indices and the ground truth
data, both precipitation and agricultural production yield for most of the
Zones Amhara region. Correlation and regression analysis was performed between
NDVI, drought indices, precipitation and agricultural yield. The NDVI and rainfall was
found to be highly correlated in water limiting areas. Apart from this, the highest NDVIrainfall
correlation associated with three -month time lag shows rainfall event induced
vegetation growth in subsequent periods. The NDVI-rainfall correlation was found to be
highly influenced by mean rainfall condition and vegetation types. It is therefore
concluded that temporal variations of NDVI are closely linked with precipitation. The
inter sensor relationships were also developed based on data from specific months and
the monthly models explain up to 95 percent of variability in the data of two sensors
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Keywords
Delineation of Drought Vulnerable