Bayesian Analysis of Energy Prices on Irrigation

Recent increases in the price of energy for pumping water and declining aquifers have resulted in a reevaluation of irrigation systems, techniques, and practices. Given various projected energy price increases, the agricultural producer is faced with the problem of selecting that strategy which minimizes the costs of irrigation over the life of the system. The available systems provide a range of choices from energy efficient capital intensive systems to less expensive systems which may utilize more energy. Since future energy costs are unknown, a choice must be made in which one of the variables is stochastic in nature. By considering the probabilities of future energy price increases, an irrigation system can be selected that minimizes long-run expected costs. A decision framework that may be utilized for optimal system selection is based on Bayesian decision theory, a method in which prior information is incorporated with additional information to estimate revised probabilities for decision making.