Constraints and Suggestions in Adopting Seasonal Climate Forecasts by Farmers in South India

Abstract

The main objective of this study was to determine constraints and suggestions of farmers towards adopting seasonal climate forecasts. It addresses the question: Which forms of providing forecasts will be helpful to farmers in agricultural decision making? For the study, farmers were selected from Andhra Pradesh state of South India. One hundred and eighty farmers were interviewed to obtain information on problems and suggestions in adopting climate forecasts. Statistical data analyses (frequencies, percentages) were made to draw results. Absence of location specific climate forecasts followed by poor reliability and failure of the majority of climate forecasts, with poor extension service in climate prediction, forecasts in the media not answering operational needs and low conviction of climate prediction were the major problems reported through farmers. Provide location specific climate forecasts by improving infrastructure at village level, improve credibility of forecasts with proper accountability, improve accuracy of climate forecasts by frequent updating, making climate forecasts in the media relevant to operational needs and improve extension service in climate prediction with frequent visits by extension personnel along with use of different teaching materials and methods, were the different suggestions offered by farmers. This paper determines constraints faced by farmers in adopting climate forecasts, along with suggestions to overcome them. It is clear that participatory engagement to understand farmers’ needs and adoption constraints is crucial to realizing the value of climate prediction. To achieve adoption of forecasts, forecasts need to be more accurate, reliable, relevant to agricultural decisions and better communicated. With agricultural systems becoming more susceptible to climate variability, this study helps and guides policymakers in considering the spatial reliability of climate prediction in relation to the spatial scale at which the information may be used.