The Value of Seasonal Productivity Forecasting in Biofuel Plans

Abstract

Crop productivity is commonly assumed as a fixed parameter when developing agricultural plans. On the contrary, actual data prove that, even for the same soil at the same location, crop productivity is highly variable. It can be better interpreted as a random variable due to the meteorological conditions of the specific year. For the production of biodiesel, crops are easily substitutable and the farmer can chose every year between various alternatives. Without information on the seasonal meteorology, the farmers must select the crop to cultivate on the basis of the average productivity. However, changes in the meteorological situation may result in an inversion of crop profitability. As a result, a crop, that on average is less interesting, may become the best choice in a specific year. Given that seasonal forecasts based on long range climatic variables, such as ENSO, are becoming available, the paper examines their effectiveness in a biodiesel production plan for an area in Mato Grosso, Brazil. We formulate and solve a mathematical programming problem to determine the most efficient crop plan under different scenarios: no information about the seasonal meteorology, perfect information and meteorological forecasts with different precision. This allows to quantitatively evaluate how important the availability of seasonal productivity forecasting can be and shows that even a rough seasonal forecast, if systematically applied, may improve the average production and reduce the risk of traditional agricultural decisions.JRC.H.3-Forest Resources and Climat