Degree Type


Date of Award


Degree Name

Master of Science



First Advisor

Brian K. Hornbuckle


An uncalibrated agricultural land surface model, Agro-IBIS, was validated at the sub-field scale using data collected at a local agricultural field site planted with maize in 2009, with a focus on capturing the spatial variability and accumulation rates of soil moisture and leaf area index. Capturing the variability was deemed important for evaluating the model's potential for inclusion as the land surface model in atmospheric models. An ensemble method of forcing the model with different combinations of input data was used in an attempt to produce the variability seen in measurements across the field. The model was able to produce a range of soil moisture similar to the range observed at the field site, though rates of soil water accumulation and drainage were much higher than observed. The spread in leaf area index measurements was not captured by the model, though the rate of leaf area accumulation was similar in both the field and the model. The model emerged the crop too early due to the lack of calibration, which led to a positive bias in leaf area. The bias in leaf area led to biases in a number of other variables, including sensible heat flux and in-canopy temperature. Despite the biases, which were expected due to the lack of calibration, the ability of Agro-IBIS to capture spatial variability in soil moisture at the sub-field scale make it a good candidate for coupling to other models.


Copyright Owner

Jason C Patton



Date Available


File Format


File Size

100 pages