- Contact Information
- My Story
- Publications & Presentations
- Courses Taught
|Title||LTAR Data Coordinator|
702 Hardin Hall
3310 Holdrege Street
My name is Jane Okalebo and I am a research assistant professor at the School of Natural Resources at the University of Nebraska- Lincoln. Go Huskers!
My principle career objective is to contribute to sustainable environmental management.
I am interested in utilizing remote sensing and Geographical Information Systems - together with advanced technology - to address the climatic and environmental challenges of the 21st Century.
During my undergraduate studies in agricultural engineering, my dissertation study involved sub-surface irrigation of French beans using saline water in a controlled environment. The sub-irrigation was conducted using porous pots of varied porosity and hydro-conductivity. In 1999, I completed a graduate degree in soil science at the University of Reading, UK. My dissertation topic examined hydrological properties of various porous pots, two different soils and their interactive effect on sub-surface soil wetting patterns.
My interests in natural resources - and especially water, light and nutrients - led me to yet more interesting research. In 2002, I was admitted at the University of Toronto, Canada and attained a master's degree in forestry. My research project was entitled "Utilizing Tabu Search, an optimization search algorithm for optimization of Grevillea robusta agroforestry systems." With the aid of a WaNuLCAS (Water, Nutrient, Light Capture in Agroforestry Systems) simulation model, and the Tabu Search algorithm (implemented using Microsoft Visual Basic 6.0), decisions about tree spacing and duration of tree growth were recommended for maximized agroforestry management for specified locations in Kenya, Africa.
I joined the University of Nebraska- Lincoln in 2005 where I studied competition between weeds and crops. I worked on Fusarium lateritium and its contribution to biological soil suppressiveness of a soil in eastern Nebraska to velvetleaf (Abutilon theophrasti).
Hobbies: networking, volunteering at the local public schools, cooking, singing and reading.
- Presentation Type: Dissertation Defense
- Date: 7/14/2014
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% 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 Plains 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.
- Applied Climate and Spatial Science
Currently this page only displays grants that were awarded on 1/1/2009 to the present. If a grant was awarded prior to 1/1/2009 and is still active, it will not be displayed on this page.
|Grant Title||2016 Conference on Applied Statistics in Agriculture|
|Funding Source||IANR Travel Funds|