Title: The role of community-based watershed development in reducing farmers’ vulnerability to climate change and variability in the northwestern highlands of Ethiopia
Abstract: Community-based watershed development (CBWD) has been implemented in Ethiopia since the last three decades. However, the benefits of these watershed development interventions for climate change adaptation are not well documented. This study, therefore, assesses the contributions of CBWD in reducing farmers' vulnerability to the impacts of climate change and variability in the northwestern highlands of Ethiopia. Data were collected from systematically selected 157 households using questionnaire. The questionnaire consists of questions on climate, ecosystem and households' livelihood capital. Livelihood Vulnerability Index (LVI) and Inter-governmental Panel on Climate Change Livelihood Vulnerability Index (IPCC-LVI) methods were used to generate vulnerability indices. Vulnerability indices computed for three conserved watersheds were compared with one non-conserved watershed using one-way ANOVA test. LVI score for ecosystem related indicators was significantly low for Adef Wuha compared to the non-conserved watershed. Similarly, LVI scores generated from agriculture, wealth and social indicators were low for Tija Baji and Guansa watersheds. On the other hand, the IPCC-LVI result did not show significant differences in exposure; however, sensitivity scores of conserved watersheds were significantly lower compared to the non-conserved. The adaptive capacities of two conserved watersheds (Guansa and Tija Baji) were also significantly lower as compared to the non-conserved. The overall (composite) vulnerability of watersheds generated from both methods (LVI and IPCC-LVI) showed that the conserved watersheds were less vulnerable to climate change compared to the non-conserved. The findings suggest that CBWD is an important strategy to reduce vulnerability of smallholder farmers to the ongoing and future climate change.
Publication Year: 2018
Publication Date: 2018-11-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 6
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot