Drought Incidence, Modeling and Prediction in Bilate River Watershed, Central Rift Valley of Ethiopia
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Date
2025-12-01
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Addis Abeba Universty
Abstract
Drought poses extreme risks to semi-arid regions like Ethiopia's Central Rift Valley, which includes the Bilate River Watershed (BRW). This PhD research presents a comprehensive assessment of the dynamics of drought in the BR W using historical analysis, spatial observation, susceptibility modeling, and future climatic projections. Past meteorological droughts (1981-2019) were first explained with multiple indices (SPI, SPEI, RDI, eRDI, scPDSI) for seven stations. Correlation and Fleiss' kappa analyses revealed that SPI and SPEI at 6- and 9-month timescales performed best, identifying major droughts (e.g., 1984/85 , 199912000, 2002/3, 2009). Theory of Runs showed increased severity in the southern BRW and increased frequency in other areas. The Mann-Kendall tests confirmed a significant increasing trend in drought conditions at Hossana and Wulbareg station within the watershed.
Satellite remote sensing (Google Earth Engine, MODIS) was utilized to analyze spatial drought patterns (2000-2022) using VCI, TCI, and VHI for the May-October period. The VHI identified 2002, 2009, 2015, and 2022 as years of severe drought with extensive coverage (up to 70% area), primarily affecting southern, central, and southwestern parts. Spatial autocorrelation (Moran's I) confirmed high drought clustering, especially in severe years, with frequency analysis identifying the southern BR W as being most vulnerable. Building upon the observed patterns, an integrated model for drought susceptibility was developed using geospatial technique and Analytic Hierarchy Process (AHP) based on fifteen climatic, hydrological, soil, vegetation, topographic, water index, and socio-economic variables. AHP identified rainfall, temperature, evapotranspiration, and soil moisture as the major drivers. The model identified that 70.2% and 23.2% of the watershed fell in moderate and severe susceptibility categories, respectively, grouped together in the central and southern parts. ROC analysis validation (AVC= 0.701) showed adequate model performance.
Then, using the SPEI index and bias-corrected CMIP6 simulations (SSP2-4.5, SSP5-8.5), drought projections for the twenty-first century (2015-2100) were produced. The frequency, intensity, and length of droughts increased dramatically during the 21st century, according to higher-level statistical calculations. This was especially true under the high-emission scenario SSP5-8.5, with peak intensity predicted in the middle of the century (2045-2054). These changes suggest drier conditions will be emerging during the period from the mid-2060s to the late-2080s, alongside the potential enhancement of multi-year drought cycles and increased extremes. Power spectral analysis suggested the potential enhancement of multi-year drought cycles (3.75-7.5 years) under high emission scenario.
EOF analysis showed high spatially coherent drought pattern alongside persistent secondary spatial contrast. Analysis of the return period indicated that SSP5-8.5 had more extremes and greater variability. The consistent identification of spatial vulnerabilities, the confirmation of historical trends in some stations, and the alarming future projections demand proactive, and spatially targeted drought risk management and adaptation strategies. Overall, this research presents multidimensional evidence and concludes that the BRW faces significantly intense drought risks, highlighting the need for immediate and focused efforts to enhance watershed resilience. Keywords: Drought Indices, Trend Analysis, GEE, Modeling, Spatial Autocorrelation, CMIP6 Projections, Bilate River Watershed, Rift Valley of Ethiopia
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Keywords
Drought Indices Trend Analysis GEE Modeling Spatial Autocorrelation CMIP6 Projections Bilate River Watershed Rift Valley of Ethiopia