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Having a robust drought monitoring system for Ethiopia is crucial
to mitigate the adverse impacts of droughts. Yet, such monitoring
system still lacks in Ethiopia, and in the Upper Blue Nile (UBN)
basin in particular. Several drought indices exist to monitor
drought, however, these indices are unable, individually, to
provide concise information on the occurrence of meteorological,
agricultural and hydrological droughts. A combined drought index
(CDI) using several meteorological, agricultural and hydrological
drought indices can indicate the occurrence of all drought types,
and can provide information that facilitates the drought management
decision-making process. This thesis proposes an impact-based
combined drought index (CDI) and a regression prediction model of
crop yield anomalies for the UBN basin. The impact-based CDI is
defined as a drought index that optimally combines the information
embedded in other drought indices for monitoring a certain impact
of drought, i.e. crop yield for the UBN. The developed CDI and the
regression model have shown to be effective in indicating historic
drought events in UBN basin. The impact-based CDI could potentially
be used in the future development of drought monitoring in the UBN
basin and support decision making in order to mitigate adverse
drought impacts.
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