An Assessment of Crop Yield Sampling Techniques on Coal-Mined Land in Reclamation Using Monte Carlo Simulation.

In Illinois, evaluating prime farmland mined for coal is primarily done using crop yield testing.  Target crop yields for each mine site are established using an approved undisturbed reference location or another technical guideline such as the Agricultural Lands Productivity Formula (ALPF).  The ALPF integrates weather effects, high level management practices, as well as crop yield by soil type effects into a single equation used to develop a target crop yield to compare against crop yield of mined lands.  Crop yield is assessed by manually harvesting portions of crop rows throughout a field and obtaining grain yield estimates.  Selection of harvested rows is based on sampling points developed by a random number generator and specific mined land sampling criteria.  These sampling procedures are repeated each year that a field is in reclamation or more if multiple crops are grown in a year.  Typically, the crop yield estimates of all samples from a given cropping year are averaged together and used as a field productivity estimate to compare against a standard.  Currently, sampling is done to assess reclamation success of whole fields, and not parts of fields.  Because natural variability exists in crop yields (along with management factors) from year to year, selection of crop sample points is critical to adequately assess reclamation success.  In our study, Monte Carlo simulation was used to develop probability distributions of crop yield for fields meeting or failing to meet target yields based on sampling strategies.  We additionally examined the potential of using yield monitor technology in developing crop yield estimates for whole and partial fields.  Our research shows that the probability of meeting target crop yields is dependent upon crop sampling patterns, and that utilizing yield monitor technology may be preferable to hand harvesting.