This study aims at characterizing agricultural drought in Ethiopia and understanding the effects of drought on crop yield. Monthly, seasonal and annual Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) values were calculated using MODIS (MOD13Q1) from the year 2003 to 2017. The relationships between NDVI, VCI, and crop yield were examined to predict the possibility of drought impacts on crop productivity. We found that VCI and NDVI data provides consistent and spatially explicit information for operational drought monitoring in Ethiopia. Results also indicated that the most extreme agricultural drought in recent years occurred in 2003, 2004, 2008, 2009, and 2015. These findings also show that mild to severe droughts have a great chance of occurrence in Ethiopia. However, only severe drought has significant impacts on crops. The food crops yield data used in this study include cereals, legumes, and tubers. It was observed that cereals such as (Zea mays), teff (Eragrostis tef), haricot beans (Phaseolus vulgaris) are more sensitive to agricultural drought when compared to the tubers such as sweet potato (Ipomoea batatas) and taro (Colocasia esculenta). Thus, drought preparedness programs need to pay more attention to the cultivation of these crops under severe drought conditions.

This study examined students’ and teachers’ awareness of climate change and their willingness to adopt pro-environmental behaviour in Nsukka Local Government Area of Enugu State Nigeria, using sociographical variables. Participants were drawn from Senior Secondary 1–3 students, as well as their teachers, all from secondary schools across the rural and urban geographical divide. Sociographical factors that have considerable effects on awareness of climate change and willingness to adopt pro-environmental behaviour were ascertained using the instrument “Awareness of Climate Change and Pro-Environmental Behaviour Willingness Questionnaire (ACCPEBWQ),” made up of 44 items on a 4-point Likert type format. A sample of 312 students and 56 teachers was used for the study with descriptive, mean, t test, ANOVA statistics, and correlation techniques employed in data analysis. Gender of students shows a significant difference in awareness of climate change and willingness to embrace pro-environmental behaviour, with male students showing both higher awareness and willingness to engage in pro-environmental behaviour. For teachers, though no significant effects were established for different variables tested in the study, they had a significantly higher awareness of climate change mean scores than students. There was a high positive and significant relationship between the level of awareness of climate change and the level of willingness to adopt pro-environmental behaviour. The study calls for increased dissemination of climate change information among females and the association of climate change issues pto prevalent environmental conditions, for better comprehension by art students.

Increasing drought patterns with profound effects on livelihoods and food security have been documented in Ethiopia. From previous studies', assessments at various timescales, Ethiopia is regarded as a drought-prone country in East Africa. However, there is no documentation available. This paper investigates the spatiotemporal patterns of drought characteristics in 16 woredas (districts) as well as in the 14 homogeneous rainfall zones of homogeneous using monthly rainfall and temperature data over the period 1983 to 2020. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were computed using time-series meteorological data to depict the spatial extent of drought characteristics and patterns at 4- and 12-month timescales. Within the period investigated, 12-month, 2015, and 2019 recorded the most extreme countrywide drought. The most prolonged drought duration lasted for 12 months in 2015. Although Ethiopia is a drought-prone country, the frequency, magnitude, and severity vary spatially by region. In planning for future actions, particular emphasis must be paid to the northeastern, eastern, northwestern, and southeastern parts of the country, which are more vulnerable. The findings could potentially influence and redirect national drought management and disaster preparedness programs for the affected areas.

The consequences of prolonged precipitation-deficient periods are primarily substantial water deficit. The spatial characteristics of drylands and various socioeconomic factors worsen droughts’ impacts and deepen poverty among agrarian communities, with attendant food security (stability dimension) implications. This study utilizes a combination of climate, remote sensing and field survey data to obtain first-hand information on the impacts of recent (2015 and 2017) droughts on crop yield in southern Tigray, northern Ethiopia. Annual and seasonal rainfall, annual and seasonal Normalized Difference Vegetation Index (NDVI) and Deviation of NDVI (Dev-NDVI), and monthly Standardized Precipitation Index (SPI) (SPI-1, SPI-3 and SPI-12) for June to October, were considered as likely factors that could relate with yield and yield loss in the area. Correlation and multiple linear stepwise regression statistical techniques were used to determine drought-yield relationships, and identify more accurate predictors of yield and yield losses in each of the drought years. The area witnessed a more widespread precipitation deficit in 2015 than in 2017, where the lowland area recorded entire crop (sorghum) losses. Also, droughts manifested spatiotemporal variations and impacts across the two different agroecologies—primarily reduction in vegetation amounts, coinciding with the planting and maturing stages of barley and sorghum. Crop failures, therefore, translated to food shortages and reduced income of smallholder farmers, which denotes food insecurity in the time of droughts. Seasonal rainfall and June Dev-NDVI predicted 66.9% of 2015 barley and sorghum yield-loss, while NDVI predicted 2017 sorghum yield by 96%. Spate irrigation should be further popularized in the low-lying areas of Raya Azebo to augment for future deficiencies in the kiremt rainfall.

The incidence and magnitude of hazards in Africa are escalating. Extant knowledge base of disaster risk (DR) trends, factors, and hotspots is lacking for the continent. Here we applied random forest machine learning regressions, spatial stratified heterogeneity, and hotspot analyses on INFORM data to identify DR patterns, factors and interactions, and notable risk hotspots. We show that although DR is generally decreasing in Africa, the Eastern, Southern, and Western regions record increasing DR. Physical exposure to floods, epidemics, and violent conflicts are hazard drivers of DR in Africa. Other significant DR drivers are mostly clustered under vulnerable groups and poor infrastructural coping capacities. Human hazards interact with other factors, exhibiting the highest influences on DR. Precisely, 19 out of 53 African countries in this study are DR hotspots. Eritrea is identified as a new hotspot. Targeted policies, resilience building, vulnerability reduction measures and comprehensive sustainability‐infused solutions are required for DR reduction and sustainable development in Africa.