With the existing state of issues related to global climate change, the accuracy of farmers’ perceptions of climate is critically important if they plan to implement appropriate adaptation measures in their farming. This article evaluated if farmers perceive the trends of local climate variability accurately, and was verified by the historical meteorological data analysis. Ordered probit perception models were applied in this study to determine the factors influencing the accuracy of farmer perception. It was observed that farmers’ perceptions of the rainfall amount during the early, mid, and late monsoon periods were highly accurate, and they also accurately perceived summer temperature change, but less accuracy of perception was observed of the temperate changes of the winter and monsoon seasons. Access to weekly weather information, participation in agricultural trainings, farming experience, and education level of the farmer were the major factors determining the accuracy of perception in this study. Based on the empirical results, this study suggested policy implications for (a) the locally specified weather information distribution, and (b) integration of weather information into agricultural training programs, which are available to the farming community to enhance the government implantation of the Myanmar Climate Smart Agriculture Strategy and Myanmar Climate Change Master Plan 2018–2030.
Agriculture is highly sensitive to climate change and understandings how the adaptation options improve the farming household’s adaptive capacity are critical to the agricultural policies. The study was carried out for the economic assessment of climate adaption options in rice-based farming system of Myanmar. The propensity score matching approach was applied to explore the existing adaptation options and its contribution on the farm income. In addition, the binary probit model was used to analyse the factors influencing those adaptation decisions. The erratic rainfall, especially dry spell period and unexpected rain during the critical crop growth, was the critical challenge of rice-based farming in the study. The timely operation of farm machineries was one of the major adaptation options for the farmers, followed by other options such as use of more agrochemicals and changing rice varieties including early maturity, high yielding and stress tolerant varieties. The combination of those adaptations gave additional 0.86-0.89 ton/ha yield, 152-158 USD/ha total return and 108-124 USD/ha profit to the adapter farmers. The institutional factors such as irrigation access, access to credit, access to weekly weather information and participation to agricultural training were critically important to the adaptation decision. Moreover, the social capital factors like farming experience, farm size and farm income share were also major influencing variables.
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