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Background Below-normal availability of water for a considerable period of time induces occurrence of drought. This paper investigates the Spatio-temporal characteristics of meteorological drought under changing climate. The climate change was analyzed using delta based statistical downscaling approach of RCP 4.5 and RCP 8.5 in R software packages. The meteorological drought was assessed using the Reconnaissance Drought Index (RDI). Results The result of climate change projections showed that the average annual minimum temperature will be increased by about 0.8–2.9 °C. The mean annual maximum temperature will be also increased by 0.9–3.75 °C. The rainfall projection generally showed an increasing trend, it exhibited an average annual increase of 3.5–13.4 % over the study area. The projected drought events reached its maximum severity indicated extreme drought in the years 2043, 2044, 2073, and 2074. The RDI value shows drought will occurred after 1–6 and 2–7 years under RCP 4.5 and RCP 8.5 emission scenarios respectively over the study area. Almost more than 72 % of the current and future spatial coverage of drought in the study area will be affected by extreme drought, 22.3 % severely and 5.57 % also moderate drought. Conclusions Therefore, the study helps to provide useful information for policy decision makers to implement different adaptation and mitigation measures of drought in the region.

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tickborne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.

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