Seasonal Rainfall Variability in Ethiopia and Its Long-Term Link to Global Sea Surface Temperatures

Spatiotemporal dynamics of ecosystem services in response to climate variability in Maze National Park and its environs, southwestern Ethiopia

Climate variability is one of the major factors affecting the supply of ecosystem services and the well-being of people who rely on them. Despite the substantial effects of climate variability on ecosystem goods and services, empirical researches on these effects are generally lacking. Thus, this study examines the spatiotemporal impacts of climate variability on selected ecosystem services in Maze National Park and its surroundings, in southwestern Ethiopia. We conducted climate trend and variability analysis by using the Mann-Kendall (MK) trend test, Sen's slope estimator, and innovative trend analysis (ITA). Relationships among ecosystem services and climate variables were evaluated using Pearson's correlation coefficient (r), while partial correlation was used to evaluate the relationship among key ecosystem services and potential evapotranspiration (PET). The MK tests show a decreasing trend for both mean annual and main rainy season rainfall, with Sen's slope (β) = -0.721 and β = -0.1.23, respectively. Whereas, the ITA method depicted a significant increase in the second rainy season rainfall (Slope(s) = 1.487), and the mean annual (s = 0.042), maximum (s = 0.024), and minimum (s = 0.060) temperature. Spatial correlations revealed significant positive relationships between ecosystem services and the mean annual rainfall and Normalized Difference Vegetation Index (NDVI), while negative correlations with the mean annual temperature. Additionally, temporal correlations highlighted positive relationships among key ecosystem services and the main rainy season rainfall. The maximum and minimum temperatures and ecosystem services were negatively correlated; whereas, there was strong negative correlations between annual (r = -0.929), main rainy season (r = -0.990), and second rainy season (r = -0.814) PET and food production. Thus, understanding the spatiotemporal variability of climate and the resulting impacts on ecosystem services helps decision-makers design ecosystem conservation and restoration strategies to increase the potential of the ecosystems to adapt to and mitigate the impacts of climate variability.

GIS-based spatio-temporal analysis of rainfall trends under climate change in different agro-ecological zones of Wolaita zone, south Ethiopia

Understanding the spatiotemporal dynamics of climatic conditions within a region is paramount for informed rural planning and decision-making processes, particularly in light of the prevailing challenges posed by climate change and variability. This study undertook an assessment of the spatial and temporal patterns of rainfall trends across various agro-ecological zones (AEZs) within Wolaita, utilizing data collected from ten strategically positioned rain gauge stations. The detection of trends and their magnitudes was facilitated through the application of the Mann-Kendall (MKs) test in conjunction with Sen's slope estimator. Spatial variability and temporal trends of rainfall were further analyzed utilizing ArcGIS10.8 environment and XLSTAT with R programming tools. The outcomes derived from ordinary kriging analyses unveiled notable disparities in the coefficient of variability (CV) for mean annual rainfall across distinct AEZs. Specifically, observations indicated that lowland regions exhibit relatively warmer climates and lower precipitation levels compared to their highland counterparts. Within the lowland AEZs, the majority of stations showcased statistically non-significant positive trends (p > 0.05) in annual rainfall, whereas approximately two-thirds of midland AEZ stations depicted statistically non-significant negative trends. Conversely, over half of the stations situated within highland AEZs displayed statistically non-significant positive trends in annual rainfall. During the rainy season, highland AEZs experienced higher precipitation levels, while the south-central midland areas received a moderate amount of rainfall. In contrast, the northeast and southeast lowland AEZs consistently received diminished rainfall across all seasons compared to other regions. This study underscores the necessity for the climate resilient development and implementation of spatiotemporally informed interventions through implementing region-specific adaptation strategies, such as water conservation measures and crop diversification, to mitigate the potential impact of changing rainfall patterns on agricultural productivity in Wolaita.

A multi-criteria decision analysis approach for ranking the performance of CMIP6 models in reproducing precipitation patterns over Abaya-Chamo sub-basin, Ethiopia

The most suitable multi-model ensemble set of general circulation models is used to reduce the uncertainty associated with GCM selection and improve the accuracy of the model simulations. This study evaluated the performance of 20 global climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in reproducing precipitation patterns over the Abaya-Chamo Sub-basin, Ethiopia. For the validation and selection of the models' capabilities, datasets from the Climate Hazards Infrared Precipitation with Stations (CHIRPS) were used after comparing them with ground observational datasets. The objective was to identify the most suitable multi-model ensemble (MME) of a subset of CMIP6 GCMs to capture the rainfall for the 1981-2014 period over the region. Climate Data Operators (CDOs) were used in climate data processing and extraction, and the Mann-Kendall test and Theil-Sen slope estimator methods were utilized to analyze the trends of the CMIP6 simulations. Four statistical metrics (Nash-Sutcliffe coefficient, percent bias, normalized root mean square error, and Kling-Gupta efficiency) were used to further assess the performance of the models. A multi-criteria decision analysis approach, namely, the technique for order preferences by similarity to an ideal solution (TOPSIS) method, was used to obtain the overall ranks of CMIP6 models and to select the best-performing CMIP6 model in the region. The results indicated that CHIRPS and most of the CMIP6 simulations generally reproduced bimodal precipitation patterns over the region. The CESM2-WACCM, NorESM2-MM, NorESM2-LM, and NorESM2-LM models performed better than the other models in reproducing seasonal patterns for the winter, spring, summer, and autumn seasons, respectively. On the other hand, FGOALS-f3-L revealed the trends of the reference datasets for all seasons. In terms of the NSE, PB, NRMSE, and KGE metrics, EC-Earth3-C, EC-Earth3, EC-Earth3-C, and EC-Earth-C, respectively, were considered good at representing the observed features of precipitation over the region. EC-Earth3-C,EC-Earth3, EC-Earth3-Veg-LR, ACCESS-CM2, MPI-ESM1-2-HR, and CNRM-CM6-1-HR exhibited the best performances in the Abaya-Chamo Sub-basin.

Spatiotemporal rainfall and temperature variability in Suha watershed, Upper Blue Nile Basin, Northwest Ethiopia

The aim of the study is to analyze the spatio-temporal variability and projection of rainfall and temperature (2021-2040) in Suha watershed, North West highlands of Ethiopia. The study used 4 km × 4 km reconstructed (blended) monthly rainfall and temperature data from National Meteorological Agency of Ethiopia (NMAE) and Royal Netherlands Meteorological Institute (KNMI) of Cen Trends v1 (0.25° × 0.25°), respectively. Mann-Kendall test, Sen's slope estimator, coefficient of variation, autoregressive integrated model , and the inverse distance weighted tool were used to analysis the rainfall and temperature variability for different timescale and agroecology. The coefficient of variation showed the existence of high seasonal variability than the year-to-year in the watershed. Kiremt (main rainy season) rainfall showed substantial inter-annual variability throughout the time of observation (1990-2020). Besides, the Mann-Kendall test and the Sen's slope estimator detected that except, Belg (little rainy season) rainfall, all the others including the annual exhibited a nonsignificant increasing trend at p < 0.05. Spatially, the upper part of the watershed is wetter than the lower portion and a large portion of it (40%) received 930-1024 mm of rainfall per year. The minimum temperature showed a decreasing trend (0.01 °C per year), while the maximum temperature exhibited the opposite result (0.02 °C per year). The seasonal variability in both cases showed mixed outcomes. Forty-two percent of the watershed experiences a minimum temperature of 10.6-12.0 °C, whereas 45% experiences a maximum temperature between 24.1 and 26.0 °C. Meanwhile, the projected result showed that there is a decreasing trend for mean annual rainfall and an increasing trend for mean annual temperature from 2021 to 2040. Hence, policymakers have to give priority to the designing and application of area-specific adaptive strategies to curb the impact of climate variability. Rainwater harvesting and small-scale irrigation practice could be possible options.

Modeling coffee (Coffea arabica L.) climate suitability under current and future scenario in Jimma zone, Ethiopia

Climate suitability is important for coffee (Coffea arabica L.) production in climate variability-prone regions like Ethiopia. The aim of this study was to assess the current and future climate suitability for the species in the Jimma zone under moderate (RCP4.5) and worst (RCP8.5) climate change scenarios. Field surveys and Worldclim and Paleoclim databases were used to capture 224 C. arabica species' location points and 9 bioclimatic data, respectively. The MaxEnt model with integration of ArcGis was used to simulate and characterize these data. The diagnostic outcome of the model showed that the anticipated climate change will increase the areas of suitability in the first and third coffee sub-zones, while there will be a decrease in the second sub-zone. Net suitability under the RCP4.5 would be decreased by 4.75 and 6.09% in the 2050s and 2070s, respectively. Indeed, under the RCP8.5, total suitability will be expected to be increased by 2.52% and 2.25% in the 2050s and 2070s, respectively. For the 2050s and 2070s, the suitability gap between RCP4.5 and RCP8.5 was estimated to be 401 km² and 1567 km², respectively. To summarize, with the exemption of RCP 8.5 within the 2070s, the suitability would be improved and come up short in all circumstances. To keep Arabica coffee in its original habitat, we suggest that the entire climate change adjustment procedures that are prearranged under the RCP4.5 ought to be executed to sustain the crop trees in its origin. Otherwise, moving the crop plant from impeded areas to suitable ones is crucial.

Effects of Climate Variability on Livestock productivity and Pastoralists Perception: The Case of Drought Resilience in Southeastern Ethiopia

This study examines the perception of the pastoral community on climate change and performance, resilience and adaptive capacity of livestock under climatic stress in southeastern Ethiopia. The study used a mixed research approach whereby quantitative and qualitative data were gathered from multiple sources to address the impacts of climate variability on livestock production and livelihood of pastoral-agro-pastoral communities of Guji zone. Data about pastoralist perception on climate change were collected from 198 randomly selected households using a semi-structured questionnaire. Furthermore, climate data were obtained from the national meteorological agency, and climatic water balance was assessed. The household survey result indicated increasing patterns of temperature (82.8%)and drought intensity (84.8%). Majority of respondents perceived decreasing trends of rainfall and feed availability. Similarly, the trend analysis of rainfall showed declining trends of annual (-4.7 mm/year), autumn (-4.5 mm) and winter (-0.54 mm). Rainfall Anomaly Index identifies 13 drought years over the past 32 years, of which 53.85% occurred between 2007- 2017. Significantly higher (p<0.01) cattle and small ruminants than camel per household died during the disastrous drought occurred in 2008/9 and 2015/16. Nonetheless, the result indicated significantly higher (p<0.01) amounts of milk yield (3.32 litre/day) of dairying camel during dry periods than cattle and small ruminants. Camel and goats are perceived as drought-resistant livestock species and cattle keepers shifting to have more camel and goat in response to prevailing drought in the study area. Poor attention is given to identify climate-smart/resilient livestock species and strains. Therefore, extensive investigations are required to select and identify purpose-specific camel and goat strains for drought-prone areas.

Spatiotemporal Trend Analysis of Temperature and Rainfall over Ziway Lake Basin, Ethiopia

Rainfall and temperature trends detection is vital for water resources management and decision support systems in agro-hydrology. This study assessed the historical (1983–2005) and future (2026–2100) rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) trends of the Ziway Lake Basin (Ethiopia). The daily observed rainfall and temperature data at eleven stations were obtained from the National Meteorological Agency (NMA) of Ethiopia, while simulated historical and future climate data were obtained from the Coupled Model Intercomparison Project 5 (CMIP5) datasets under Representative Concentration Pathways (RCP) of 4.5 and 8.5. The CMIP5 datasets were statistically downscaled by using the climate model data for hydrologic modeling (CMhyd) tool and bias corrected using the distribution mapping method available in the CMhyd tool. The performance of simulated rainfall, Tmax, and Tmin of the CMIP5 models were statistically evaluated using observation datasets at eleven stations. The results showed that the selected CMIP5 models can reasonably simulate the monthly rainfall, Tmax, and Tmin at the majority of the stations. Modified Mann–Kendall trend test were applied to estimate the trends of annual rainfall, Tmax, and Tmin in the historical and future periods. We found that rainfall experienced no clear trends, while Tmax, and Tmin showed consistently significant increasing trends under both RCP 4.5 and 8.5 scenarios. However, the warming is expected to be greater under RCP 8.5 than RCP 4.5 by the end of the 21st century, resulting in an increasing trend of Tmax and Tmin at all stations. The greatest warming occurred in the central part of the basin, with statistically significant increases largely seen by the end of the 21st century, which is expected to exacerbate the evapotranspiration demand of the area that could negatively affect the freshwater availability within the basin. This study increases our understanding of historic trends and projected future change effects on rainfall- and evapotranspiration-related climate variables, which can be used to inform adaptive water resource management strategies.

Performance Evaluation and Comparison of Satellite-Derived Rainfall Datasets over the Ziway Lake Basin, Ethiopia

Consistent time series rainfall datasets are important in performing climate trend analyses and agro-hydrological modeling. However, temporally consistent ground-based and long-term observed rainfall data are usually lacking for such analyses, especially in mountainous and developing countries. In the absence of such data, satellite-derived rainfall products, such as the Climate Hazard Infrared Precipitations with Stations (CHIRPS) and Global Precipitation Measurement Integrated Multi-SatellitE Retrieval (GPM-IMERG) can be used. However, as their performance varies from region to region, it is of interest to evaluate the accuracy of satellite-derived rainfall products at the basin scale using ground-based observations. In this study, we evaluated and demonstrated the performance of the three-run GPM-IMERG (early, late, and final) and CHIRPS rainfall datasets against the ground-based observations over the Ziway Lake Basin in Ethiopia. We performed the analysis at monthly and seasonal time scales from 2000 to 2014, using multiple statistical evaluation criteria and graphical methods. While both GPM-IMERG and CHIRPS showed good agreement with ground-observed rainfall data at monthly and seasonal time scales, the CHIRPS products slightly outperformed the GPM-IMERG products. The study thus concluded that CHIRPS or GPM-IMERG rainfall data can be used as a surrogate in the absence of ground-based observed rainfall data for monthly or seasonal agro-hydrological studies.

Past eight-year malaria data in Gedeo zone, southern Ethiopia: trend, reporting-quality, spatiotemporal distribution, and association with socio-demographic and meteorological variables

Background

Informed decision making is underlined by all tiers in the health system. Poor data record system coupled with under- (over)-reporting of malaria cases affects the country’s malaria elimination activities. Thus, malaria data at health facilities and health offices are important particularly to monitor and evaluate the elimination progresses. This study was intended to assess overall reported malaria cases, reporting quality, spatiotemporal trends and factors associated in Gedeo zone, South Ethiopia.

Methods

Past 8 years retrospective data stored in 17 health centers and 5 district health offices in Gedeo Zone, South Ethiopia were extracted. Malaria cases data at each health center with sociodemographic information, between January 2012 and December 2019, were included. Meteorological data were obtained from the national meteorology agency of Ethiopia. The data were analyzed using Stata 13.

Results

A total of 485,414 suspected cases were examined for malaria during the previous 8 years at health centers. Of these suspects, 57,228 (11.79%) were confirmed malaria cases with an overall decline during the 8-year period. We noted that 3758 suspected cases and 467 confirmed malaria cases were not captured at the health offices. Based on the health centers records, the proportions of Plasmodium falciparum (49.74%) and P. vivax (47.59%) infection were nearly equivalent (p = 0.795). The former was higher at low altitudes while the latter was higher at higher altitudes. The over 15 years of age group accounted for 11.47% of confirmed malaria cases (p < 0.001). There was high spatiotemporal variation: the highest case record was during Belg (12.52%) and in Dilla town (18,150, 13.17%, p < 0.001) which is located at low altitude. Monthly rainfall and minimum temperature exhibited strong associations with confirmed malaria cases.

Conclusion

A notable overall decline in malaria cases was observed during the eight-year period. Both P. falciparum and P. vivax were found at equivalent endemicity level; hence control measures should continue targeting both species. The noticed under reporting, the high malaria burden in urban settings, low altitudes and Belg season need spatiotemporal consideration by the elimination program.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05783-8.