Assessing the Value of Seasonal Climate Forecasts on Farm-level Corn Production through Simulation Modeling

Rainfall variability greatly influences corn production. Thus, a skillful forecast is potentially of value to the farmers because it could help them make a number of crop management decisions including crop choice, variety selection, timing of planting, and input usage. The study aims to develop an approach in estimating the economic value of seasonal climate forecast (SCF) to corn farmers under climate uncertainty. It focuses specifically on corn farmers in Isabela using the historical climate data of Tuguegarao from 1951 to 2006. The CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate corn production and management practices of farmers to estimate the potential corn yields for wet and dry seasons under different El Nino Southern Oscillation (ENSO) conditions. The RAINMAN International software was used to generate SCF for El Nino, La Nina, and Neutral conditions. A decision tree analysis was applied in estimating the value of SCF information for corn farmers.