Spatial-temporal analysis of historical and projected drought events over Isiolo County, Kenya

• Published in: Theoretical and applied climatology 2022-04, Vol.148 (1-2), p.531-550
• Main Authors: Ochieng, Phillip, Nyandega, Isaiah, Wambua, Boniface
• Format: Article
• Language: English
• Subjects: Analysis; Aquatic Pollution; Aquatic resources; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Climate; Climate science; Climatology; Computation; Drought; Drought index; Drought trends; Droughts; Earth and Environmental Science; Earth Sciences; Eigenvectors; Empirical analysis; Identification; Kenya; Mean precipitation; Monthly; Original Paper; Orthogonal functions; Precipitation; Precipitation (Meteorology); Regional climates; soil; Soil temperature; Soil water; Spatial analysis; Spatial variability; Spatial variations; Temperature; time series analysis; Trends; Waste Water Technology; Water Management; Water Pollution Control; Water stress
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-022-03953-5

This study was to determine the spatiotemporal characteristics of historical and projected drought events throughout Isiolo County, Kenya, through using self-calibrating Palmer Drought Severity Index (scPDSI). The historical scPDSI was computed at monthly timescale using a 39-year long monthly mean precipitation, monthly average temperature, and climatological (1950–1996) soil available water holding capacity. The projected scPDSI under representative concentration pathways (RCPs) was computed using bias corrected monthly temperature and precipitation model output data from Coordinated Regional Climate Downscaling Experiment (CORDEX). ScPDSI runs have shown that more severe drought events dominated the period between 1980 and 2000. Mar 2046–Mar 2048 was identified under RCP4.5 to be the most severe drought lasting for 25 months, while under RCP8.5 run, Nov 2042–Nov 2046 was identified as the most severe drought with the duration of water stress anticipated to last for 49 months. The empirical orthogonal function (EOF) analysis results indicated that the two-leading eigenvectors accounted for over 85% of the spatial variability for both historical and projected droughts under the RCPs. Subsequently, the Mann-Kendall (MK) test was applied to the projected scPDSI, temperature, and precipitation time series in order to determine the local expected drought trends. The MK test of the identified significant increase in trend for temperatures under RCP8.5 and precipitation under RCP4.5 towards the end of the last decade under the study period is considered. Both scenarios showed a decline in trends of drought events in Isiolo County from 2020 to 2050.