Jane Asiyo Okalebo, graduate student and SNR assistant geoscientist, will defend her doctoral degree dissertation, "An Evaluation of Climate-Land Surface Model Weather Forecasts for Nebraska: Phenological and Yield Sensitivities of Corn to Irrigation" at 3 p.m., July 14 in 901 Hardin Hall.
Okalebo's co-advisers are Ken Hubbard and Ayse Kilic. Her abstract:
Nebraska's climate is highly variable and is expected to change resulting in warmer spring and summer temperatures coupled with more erratic rainfall events. Groundwater records show that the Ogallala Aquifer levels are declining. These factors could result in large negative impacts on corn production in Nebraska where about 70 percent of corn is under irrigation. Weather forecasts and knowledge of the yield, phenological sensitivity of corn to water, temperature and Growing Degree Days (GDDs) are vital in establishing mitigation strategies given the looming weather changes and water resource scarcity. The research below was undertaken to serve as a basis for quantifying possible future impacts.
The usefulness of climate models and land surface models (LSM) hinges on their accuracy. Two candidate LSMs were evaluated: the Noah and the Community Land Surface Model (Version 3.5). The performance of WRF-Noah and WRF-CLM in predicting temperature and precipitation in Nebraska in a dry (2002), a moderate (2005), and a wet (2008) year were evaluated using observed station data downloaded from the High Plain Regional Climate Centre website and PRISM datasets from Oregon State University. These findings are useful in selecting useful models that can be applied to make weather predictions in the near future for yield predictions and decision making. In addition, the effects of microclimate on corn phenology and yield respectively were explored.
This included the influence of temperature and GDDs on corn phenology for both irrigated and rainfed fields. Results of this study can be used to support the selection of longer maturing hybrids that take advantage of increasing temperatures. The sensitivity of corn to water stress in different growth periods was examined. Since crops are not equally sensitive to growth in all stages of their development, a multiplicative empirical model was developed that utilizes actual and potential evapotranspiration as input in determining crop yields for Mead, Nebraska.. The model was calibrated and validated using multiple year corn yield data from the University of Nebraska's Carbon Sequestration Project (CSP) Agricultural Research Sites located near Mead, NE.
The new coefficients were not found to be an improvement over the Meyer coefficients (1993). These results support the fact that the robustness of a model depends on the range of conditions over which it is calculated. The model is a tool that can assess deficit irrigation strategies and the impact on yields offering a means of sustaining high yields in the future.