County level calibration strategy to evaluate peanut irrigation water use under different climate change scenarios

Abstract

Regional scale simulation of crop yield is challenging due to the spatial variability of soil properties, crop varieties, management practices and weather conditions. Point-based crop models are commonly used for spatial simulation with increased availability of high-resolution spatial datasets. However, it is still difficult to calibrate crop models well due to the spatial variability of model inputs. The focus of this work was to determine if a single set of cultivar and soil parameters could be calibrated to simulate county level peanut yield and to evaluate the effects of irrigation to mitigate potential climate change impacts on peanut yield. Model input data for fourteen seasons and five major peanut producing counties was assembled and used for model calibration. Three seasons of data were withheld and used for an independent evaluation. Overall, peanut growth duration and county level yields were simulated well with a set of optimum cultivar and soil parameters for each county. The model calibration showed that simulated maturity dates and yields were in good agreement with the observed county level values reported by NASS, giving an overall R2 of 0.71 and 0.73 and RMSE values of 6 days and 333 kg/ha, respectively. The model also generated good simulations of maturity dates and yield for the three evaluation seasons, with an overall R2 of 0.83 and 0.76 and RMSE values of 5 days and 429 kg/ha, respectively. The results from future climate simulations indicated that the rainfed yields will suffer from increasing daytime temperature and an irrigation strategy could potentially offset the heat and water stress to maintain higher peanut production in the Southeastern USA. This study can enhance the accuracy of simulating the impact of climate change on crop production by providing a calibration and evaluation strategy that aggregates spatial heterogeneity of model inputs at the regional scale. Further research should test this method for other crops and more model applications, such as nitrogen leaching, groundwater use and fertilizer management.