Climate change, adaptation, and agricultural output

Regan, Patrick M.; Kim, Hyun; Maiden, Emily

doi:10.1007/s10113-018-1364-0

Cited by 25 publications

(10 citation statements)

References 43 publications

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“…The Dhidhessa River basin is one of the upper Blue Nile sub-basins that receive higher average annual rainfall (> 1600 mm), contribute more than 25% annual flow to the Blue Nile basin, covered with dense vegetation and with less steep topography compared to the northeastern sub-basins (Conway 2000). These imply studying climate trends at a sub-basin scales could improve the accuracy of predicting local and regional climate change impacts on water resource availability (Kim and Kaluarachchi 2009;Viviroli et al 2011), agriculture (Deressa and Hassan 2009;Schlenker and Lobell 2010;Philip et al 2014;Regan et al 2018), human health (McMichael et al 2006 and biodiversity (Chapungu and Nhamo 2016;Perović et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

et al. 2019

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Background: Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann-Kendall test and Sen's slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results: According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool subhumid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r 2 = 0.62) and negatively correlated to the minimum (r 2 = 0.58) and maximum (r 2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion: The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

et al. 2019

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“…This finding is important because it alerts stakeholders on the possible outcomes of an already bad situation. Also, there is evidence aligned with the view that areas of high poverty and low literacy rates often have low adaptive capacity as they are poorly equipped to adapt and respond to climate change, climate variability or extreme events [20,21,82]. Socio-economic disparities between regions, communities and even countries can trigger differences in the ability to respond to changes in climate.…”

Section: Discussionmentioning

confidence: 97%

Vulnerability of crop yields to variations in growing season precipitation in Uganda

Epule

New

2019

SN Appl. Sci.

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“…Another expected impact of future climate change is an increased occurrence of extreme weather events (Gezie 2019). While other studies showed that mean climate change may lead to asymmetrical responses in the frequency and intensity of severe weather events that can cause large-scale droughts, flooding, or severe reduction of crop yields in the study area (Milman and Arsano 2014;Regan et al 2019;Wakuma Abaya et al 2009), we did not consider single weather events in this study. As rainfall becomes more Fig.…”

Section: Discussionmentioning

confidence: 99%

Climate change impacts on potential maize yields in Gambella Region, Ethiopia

2021

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Changing climate conditions are supposed to have particularly strong impacts on agricultural production in the tropics with strong implications on food security. Ethiopia’s economy is profoundly dominated by agriculture, contributing to around 40% of the gross domestic product. Thereby, Ethiopia is one of the most vulnerable countries to the impact of climate change and has a wide gap in regional climate change impact studies. In this study, we systematically investigate climate change impacts on yields for the Gambella region in Ethiopia, exemplarily for maize. Here, we show how yields change until 2100 for RCPs 2.6, 4.5, and 8.5 from a climate model ensemble under rainfed and irrigated conditions. While rainfed yields decrease by 15% and 14% respectively for RCPs 2.6 and 4.5, yields decrease by up to 32% under RCP 8.5. Except for RCP 8.5, yields are not further decreasing after 2040–2069. We found that temperature increase, changing soil water availability, and atmospheric CO2 concentration have different effects on the simulated yield potential. Our results demonstrate the dominance of heat response under future climate conditions in the tropical Gambella region, contributing to 85% of total yield changes. Accordingly, irrigation will lose effectiveness for increasing yield when temperature becomes the limiting factor. CO2, on the other hand, contributes positively to yield changes by 8.9% for RCP 8.5. For all scenarios, the growing period is shorted due to increasing temperature by up to 29 days for RCP 8.5. Our results suggest that new varieties with higher growing degree days are primarily required to the region for adapting to future climate conditions.

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Climate change, adaptation, and agricultural output

Cited by 25 publications

References 43 publications

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

Vulnerability of crop yields to variations in growing season precipitation in Uganda

Climate change impacts on potential maize yields in Gambella Region, Ethiopia

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