Spatio-temporal analysis of drought variability in central Ethiopia

Drought is a major problem in Ethiopia and particularly affects the agricultural and water sectors. This paper aims to assess the spatial and temporal drought variability of central Ethiopia. For this purpose, archival rainfall data recorded from 1989 to 2017 and the Gurage zone topographic maps were used. The five stations’ Standardized Precipitation Index (SPI) were combined with the geographical information system (GIS) to analyze the spatial distribution of drought events. The results show that a total number of 41 drought events were recorded in the region. The number of drought events reaches its maximum value in the year 1992, whereas Bui and Koshe contain the most frequent drought events. The spatial analysis of droughts verifies that most of the frequent and extreme events are recorded in the eastern part of the region. The lowland part of Gurage zone is very prone to drought. The grounded spatio-temporal drought risk events analysis has shown a possible threat to the water and rain-fed farming that has a cascading effect on the livelihoods of farmers. Moreover, the drought condition of the region is unpredictable and recurrent. This study recommends further study containing remaining statistical drought indices such as reconnaissance drought and streamflow drought index.


INTRODUCTION
A natural hazard is a natural occurrence that might have a negative effect on living organisms and the environment.
Natural hazard events can be classified into two broad categories: geophysical and biological (Burton et al. ).
Internal or external processes such as active diastrophism and climate changes are capable of changing landforms and activating natural hazards, which in some cases control human activities (Bathrellos et al. ). Among meteorological or climate hazards, drought and flood are common hazards for our ecosystem. Literally, drought is a period of below-average precipitation in a given region, resulting in lengthy shortages in the water supply, whether atmospheric, surface water, or groundwater. Scientists warn that global warming and climate change may result in more extensive droughts in the near future (Nagarajan ). These extensive droughts are likely to occur within the African continent due to its very low precipitation levels and high temperatures/pressure (Calow et al. ).
Droughts occur frequently in some parts of the world (Mishra & Singh ). A drought can last for years, or may be declared as drought after as few as 15 days, and if lasting for less than 15 days is declared a dry spell (Sivakumar ). Recurrent drought has a substantial impact on the ecosystem, agriculture and water sector of the affected region and harms the social, cultural, and economic life of the locality (Amsalu & Adem ). Extreme heat can significantly worsen drought conditions by hastening evaporation of soil and surface water and transpiration of plant leaf (Dai et al. ). Frequent drought is common in the tropics and significantly increases the chances of a famine, poverty, fragile ecosystem, and subsequent natural fires (Brando et al. ). Drought is one of the most devastating natural hazards, and has exerted negative impacts on industrial production, labor efficiency, agricultural production, electricity production, and groundwater potential (Omer ). In Ethiopia, recurrent drought has been observed in different time periods with diverse magnitude and dimensions since 1957 (Table 1).
Drought occurrence can be assessed in space and time through a sound basis of scientific use of historical data (Tsakiris et al. ). Currently, there are many statisticalbased drought indices, for example, the Reconnaissance Drought Index (RDI) and the Streamflow Drought Index (SDI). Also, the widely used Standardized Precipitation Index (SPI) and rainfall deciles can be used (Tigkas et al.

).
The common characteristics of the SPI and rainfall deciles are that they require a relatively small amount of data for their analysis and the results can be easily interpreted and stated that the possibility to estimate drought through evaporation rates using novel learning algorithms remains a vital task for agriculture and water resources management.
Drought is one of the most common climatic or meteorological hazards, and has significant impacts on the livelihoods and economy of Gurage zone. The use of longterm climate data can be employed to analyze the spatial and temporal drought characteristics, and the outcomes of such study would be helpful for better understanding drought behavior and for adaptation options. To fill the gap, SPI-12 and a topographic map were used to assess drought in Gurage zone, and the objective of this study is to assess spatio-temporal analysis of drought variability in central Ethiopia. This work will fill the gap in planning of water resource use, mitigation, and drought disaster prevention in the region.

Description of the study site
This study was conducted in Gurage zone, one of the admin- where T j and T i are the annual values in years j and i, j > I, respectively.
A positive value of S indicates an increasing trend whereas a negative value indicates a declining trend in the data. At a certain probability level H 0 is rejected in favor of H 1 if the absolute value of S equals or exceeds a specified value S α/2 , where S α/2 is the smallest S which has probability less than α/2 to appear in the case of no trend. For n ! 10, the statistic S is approximately normally distributed with the mean and variance as follows: The variance (σ 2 ) for the S statistic is defined by: where t i denotes the number of ties to an extent i. The summation term in the numerator is used only if the data series contains tied values. The standard test statistic Z s is calculated as follows: The test statistic Z s is used as a measure of the significance of the trend. In fact, this test statistic is used to test the null hypothesis, H o . If |Z s | is greater than Z α/2 , where α represents the chosen significance level, then the null hypothesis is rejected, implying that the trend is significant. According to the classification scale for SPI values, a positive value of the SPI denotes that rainfall at the study area is higher than average whereas a negative value of the SPI indicates that rainfall in the area is lower than normal (Du et al. ; Pei et al. ). A region will be considered as 'extreme wet' if the SPI value of the area is greater than or equal to þ2.00 and, oppositely, the region is considered as suffering drought if the SPI value of the area is less than À2.00 (Table 3).

RESULTS AND DISCUSSION
Missing data and consistency check The consistency of the rainfall data set was checked by the double-mass curve method and a plot of average cumulative annual rainfall data (as ordinate) against the abscissa. As shown in Figure 2, the double-mass curve ensured that all stations' data were consistent due to the fact that missed and outlier data were filled correctly.

Rainfall trend analysis
The annual rainfall in the four stations showed a decreasing trend by a factor of À0.2, À2.02, À8.8, and À3.21 mm per year at Bui, Butajira, Koshe, and Wolkite stations, respectively, but had an increasing trend at Imdibir station

Temporal trends of drought events
The Ethiopia.

Spatial patterns of drought incidence
The general agriculture of the area predominantly depends on bimodal rainfall, Kiremt (main rainy season) and Belg   During the period of study, the temporal analysis showed that there were times when the entire The spatial analysis of droughts verifies that most of the frequent and extreme events are recorded in the eastern part of the region. The lowland part of Gurage zone is very prone to drought, and the area needs drought hazard assessment mapping. The majority of the region experienced severe and extreme (SPI À1.50) drought events. Specifically, Imdibir, Butajira, and Koshe experienced extreme drought with risk peak value of SPI À 2) while Wolkite and Bui were affected by severe drought with risk peak value À1.8 to À1.63.
The study indicated that the region experienced unpredictable drought events at different time scales. The observed spatio-temporal drought risk events indicate a potential hazard to the rain-oriented agriculture, hence steadily affecting the regular farming system, and water and food security. The findings of this research could be important in strategic planning and operational applications like drought monitoring, platforms for early warning and preparedness, local-scale adaptation planning, and food security strategies and policy direction. The limitation of the study remains the lack of consistent, reliable, and recent years' data for the case due to malfunctioning and relocation of some stations in the region. This study recommends further research on remaining statistical drought indices such as RDI and SDI. Supplementary irrigation is recommended as the best adaptation option throughout the drought period.