Application of Agent-Based Modeling in Agricultural Productivity in Rural Area of Bahir Dar, Ethiopia

Effective weather forecast information helps smallholder farmers improve their adaptation to climate uncertainties and crop productivity. The main objective of this study was assess the impact adoption on We coupled agent-based productivity models farmers’ management decisions maize under different rainfall scenarios in Ethiopia. A household survey conducted with 100 households from 5 villages used validate model. model (ABM) analyzed behaviors dry, wet, normal conditions. ABM results data were then as input sources for Our show that farming based improved yield 17% 30% dry wet seasons, respectively. rates due intervillage interactions, connections, radio, agriculture extension services, accuracy brought additional yields into Kebele compared non-forecast users. findings help local policy makers understand information. Results can be develop agricultural programs where rainfed is common.