Abstract:
This study focused on identification of perception level and determinant factors that
influence adaptation options to climate change on maize growing smallholder farmers in
Adama and Adami Tullu Jiddo Kombolcha districts of the central rift valley of Ethiopia.
Analysis of the study was based on a cross-sectional data collected through household
survey from the districts in February to March 2013. Representative samples of 233
households were interviewed, with 54% from Adama and the remaining 46% from Adami
Tullu Jiddo Kombolcha districts. Descriptive statistics and Multinomial logit model was
used to analyze the data. The finding of the study show that about 86% of interviewed
farm households perceived climate change as rise and hot in temperature and 83%
perceived the change of rainfall in quantity and timing. Econometric analysis result also
reveals that; education level, age and gender of the household head, family size, land
holding size and access to information have significant and positive influences on
households’ decision to employ various adaptation strategies to climate change. The
study also identified the most prioritized adaptation strategies by the households which
include: soil conservation and management, fertilizers application, off-farm works, crop
diversification, agro-forestry and use of improved seeds. Based on the findings, policies
and strategies that encourage participation of farmers in planning and application of
adaptation strategies with bottom-up approach is required for better anticipation of
climate change instead of focusing on reacting the impacts. This can be achieved through
increasing access to credit facilities, providing other sources of income for the
households, comprising climate change in education policy, access to crop insurance
schemes, improving extension system in view of climate change. Enhancing farmers’
organization for experience sharing which helps to strength public adaptation capacity
and improving institutional capacity to generate weather forecasting information at local
level.
