Date of Graduation
Master of Science in Environmental Engineering (MSEnE)
Second Committee Member
Third Committee Member
Biological sciences, Applied sciences, Earth sciences, Blue water, Ceres-maize, Green water, Maize, Yield
The CERES-Maize model was evaluated in its capacity to predict both regional maize yield and water use within the United States Department of Agriculture (USDA) Economic Research Service (ERS) Region 1 between the years 1997-2007. A grid based, geospatially explicit method was developed to express the various rainfed and irrigated maize cultivars grown across the region. Overall, the calibrated model compared well for both physiological and yield parameters, producing significant linear relationships (p
The calibrated and validated CERES-Maize model was used to predict potential evapotranspiration and yield under three IPCC weather scenarios for the year 2050 to evaluate crop production under climate change. Regional evapotranspiration was predicted to increase for both rainfed and irrigated maize; however, declines were predicted in rainfed evapotranspiration for the states of Indiana and Ohio. Regional maize yields were predicted to increase under both rainfed and irrigation conditions compared to the baseline (1997-2007) conditions. Despite the increases in overall maize yield projected across the region as a whole, large declines were observed in certain areas such as Illinois, Indiana, and Ohio under rainfed conditions and South Dakota under irrigated conditions. Overall irrigation demands declined in Nebraska and South Dakota. The results suggest that maize production could improve under climate change scenarios, and shifts in production to western locations could maximize production in 2050.
Johnston, R. Z. (2013). Using the CERES-Maize Model to Create a Geographically Explicit Grid Based Estimate of Corn Yield Under Climate Change Scenarios. Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/722