Development of an Agent-Based Model for Weather Forecast Information Exchange in Rural Area of Bahir Dar, Ethiopia

Abstract

Smallholder farmers in Ethiopia are vulnerable to climate change impacts due to their low adaptive capacity and dependence on rainfed agriculture. Thus, a successful weather forecast system may bring significant economic and social value to the community. The main objectives of this study were to identify the key information exchange agents, understand the information flow path, rank the relative importance of the different information dissemination pathways, and determine weather forecast adoption. We conducted a household survey in five villages of Rim Kebele in Bahir Dar area and found that farmers communicate with four main agents with regard to information exchange. We developed an agent-based model to learn the adoption rates of weather forecast information. Agriculture extension agents were found to be the most influential members of the community. Farmers’ communicating with neighboring village farmers showed higher adoption. Our results show at least twice that improvements in communication network attain higher adoption rates. Radio has also demonstrated positive uptake of information. We also found that forecast accuracy of 70% is sufficient to achieve high adoption rates. Our findings might help decision-makers recognize critical information flow pathways and their relative importance, and identify barriers to disseminating weather forecast information in the community.