当前位置: X-MOL 学术J. Arid Environ. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Using farmer-based metrics to analyze the amount, seasonality, variability and spatial patterns of rainfall amidst climate change in southern Ethiopia
Journal of Arid Environments ( IF 2.7 ) Pub Date : 2020-04-01 , DOI: 10.1016/j.jaridenv.2019.104084
Logan Cochrane , Sophie C. Lewis , Mastawesha Misganaw Engdaw , Alec Thornton , Dustin J. Welbourne

Abstract Climate change will likely impact rainfall characteristics in particular locations; the amount, seasonality, variability and spatial patterns. In developing countries, this presents challenges for rural smallholder farmers as their livelihoods are largely based on rain-fed practices. Changes in climate patterns could increase farmers' vulnerability and the need for intervention. In this paper, we develop new metrics of analysis motivated by qualitative research with smallholder farmers. Previous research found that farmers' understanding of historical rainfall change is accurate, yet diverge from some research studies. We analyze meteorological station rainfall data using metrics that are familiar to smallholders. Farmers' perceptions of rainfall in southern Ethiopia were explored through interviews conducted in three communities. Our findings identified some forms of convergence, as well as divergence, in farmers' perception of rainfall trends and meteorological station data results. In asking the question ‘Why do data based on farmer experiences of rainfall variability differ from meteorological station data?’, we show that using existing data and applying farmer-influenced metrics can improve the information shared with farmers. We argue that, under further climate change, it will be increasingly important to convey meteorological information to farmers in ways that are relevant to them and their agricultural livelihoods.
更新日期:2020-04-01
down
wechat
bug