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.
1.2 Drought monitoring
1.3 Problem statement
1.4 Research objectives
1.5 Main steps in research methodology
1.6 Research significance and innovation
1.7 Description of the study area
1.8 Dissertation structure
2. Spatio-temporal assessment of meteorological drought under the influence of varying record length
2.2 Stations selection and data analysis
2.3 Selection of the Probability Distribution Function (PDF) for the Standardized Precipitation Index (SPI)
2.4 Methodology of experiments
2.5 Results and discussion
3. Comparison of the performance of six drought indices in assessing and characterising historic drought events
3.3 Drought indicators
3.5 Results and discussion
4. Developing a combined drought index and prediction model to monitor drought-related crop yield reduction
4.4 Results and discussion
5. Application of Earth observation data for developing a combined drought index and crop yield prediction model
5.4 Results and discussion
5.5 Prediction models of crop yield anomalies
6. Summary, conclusions and recommendations
Appendix A: Gamma distribution based SPI calculation
Appendix B: Time series of drought indices
Appendix C: Spider web plots of drought indicator results for selected stations
Appendix D: Scatter plots of drought indices versus crop yield anomalies
Appendix E: The regression equations developed for the selected eight zones and for the four crops
IHE Delft PhD programme leads to a deepening of a field of specialisation. PhD fellows do scientific research, often with conclusions that directly influence their region. At IHE Delft, PhD researchers from around the world participate in problem-focused and solution-oriented research on development issues, resulting in an inspiring research environment. PhD fellows work together with other researchers from many countries dealing with topics related to water and the environment.
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