The optimisation of production plans is an important topic in agriculture, often related to diversification and specialisation as the classical instruments of coping with production risk. Although the measurement of embedded risk is often inaccurate, it is nevertheless necessary for decision making to describe the common behaviour of different variables in a model. Imprecisely defined relationships influence the “right” choice, why it is important to find a good approximation of the real circumstances. In financial science, copula functions are frequently used instead of correlation coefficients to model joint price behaviour, because of the possibility to link the marginal distributions on multifarious ways. By now, agricultural science makes less use of this method. This research uses the concept of “partly nested Archimedean copula” to model the relationship between different crop yields and compares it with a correlation based approach. The analysis focuses the differences of the approaches in the context of production planning and the use of weather derivatives.