Climate variability impacts on agricultural output in East Africa

Mubenga-Tshitaka, Jean Luc; Dikgang, Johane; Mwamba, John Weirstrass Muteba; Gelo, Dambala

doi:10.1080/23322039.2023.2181281

Cited by 6 publications

(2 citation statements)

References 86 publications

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“…It also relates to many risks to rain-fed agriculture, such as shortage of water associated with seasonality of the rainfall or due to excessive evapotranspiration or both, the occurrence of flood and soil erosion due to a high amount or intensity of rainfall or both, water logging and soil acidity caused by the seasonal high-intensity rainfall, and soil salinity caused by high rates of evapotranspiration. These risks can significantly constrain rain-fed agricultural practices and crop productivity [2,5,7,9,41,42]. It is important to note that the prevalence, severity, and effects of these climate variability-induced agricultural challenges vary spatially across the Abbay basin [16].…”

Section: Implications For Targeting Green Water Management Technologiesmentioning

confidence: 99%

“…An annual-based north-south oscillation of overhead solar radiation over Ethiopia determines the location of the Inter Tropical Convergence Zone (ITCZ), then by the direction and magnitude of rain-producing wind flow [4]. The impact of climate on rain-fed agriculture is not only caused by inter-annual rainfall variability but also by fluctuations in annual rainfall cycles, length of growing period (LGP), rainfall intensity, rainfall onset and cessation dates, and outbreaks of climate-related crop diseases and pests [5][6][7]. Temperature also determines the spatial and temporal distribution of green water and crop productivity in the rain-fed agriculture system by influencing the rate of water loss from the soil through evapotranspiration [7,8].…”

Section: Introductionmentioning

confidence: 99%

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Homogenous Climatic Regions for Targeting Green Water Management Technologies in the Abbay Basin, Ethiopia

Tibebe,

Degefu,

Bewket

et al. 2023

Climate

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Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and the selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimal number of climate clusters. The k-means clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture, and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. This study also provided a methodological framework that can be used in the other river basins of Ethiopia and, indeed, elsewhere.

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Section: Implications For Targeting Green Water Management Technologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Homogenous Climatic Regions for Targeting Green Water Management Technologies in the Abbay Basin, Ethiopia

Tibebe,

Degefu,

Bewket

et al. 2023

Climate

View full text Add to dashboard Cite

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Influence of climate-smart technologies on the success of livestock donation programs for smallholder farmers in Rwanda

Kandulu,

Zuo,

Wheeler

et al. 2024

Mitig Adapt Strateg Glob Change

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Climate change threatens the livelihoods of Sub-Saharan African farmers through increased droughts. Livestock donation programs offer a potential solution, but their effectiveness under climate stress remains unclear. This study assesses the economic viability of integrating climate-smart technologies (cowsheds and biogas plants) into these programs in Rwanda. Using a stochastic benefit–cost analysis from the beneficiary perspective, we evaluate the net gains for households receiving heifers compared to the current program. Our findings reveal that integrating climate-smart technologies significantly enhances economic viability. Households with cows and climate-smart technologies can possibly realise net benefits 3.5 times higher than the current program, with benefit–cost ratios reaching 5:1. Beyond economic benefits, adopting biogas reduces deforestation, greenhouse gas emissions, and respiratory illness risks. This study demonstrates that integrating climate-smart technologies into livestock donation programs can generate positive economic, environmental, and health benefits, leading to more resilient and sustainable smallholder systems. However, overcoming implementation challenges requires tailored policy packages addressing local barriers.

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Panel threshold effect of climate variability on agricultural output in Eastern African countries

Mubenga-Tshitaka,

Gelo,

Dikgang

et al. 2024

Cogent Economics & Finance

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Climate variability impacts on agricultural output in East Africa

Cited by 6 publications

References 86 publications

Homogenous Climatic Regions for Targeting Green Water Management Technologies in the Abbay Basin, Ethiopia

Homogenous Climatic Regions for Targeting Green Water Management Technologies in the Abbay Basin, Ethiopia

Influence of climate-smart technologies on the success of livestock donation programs for smallholder farmers in Rwanda

Panel threshold effect of climate variability on agricultural output in Eastern African countries

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