Graduate Studies


First Advisor

Dr. Hongfeng Yu

Second Advisor

Dr. Haishun Yang

Date of this Version



A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professors Haishun Yang and Hongfeng Yu. Lincoln, Nebraska: December, 2019

Copyright 2019 Saeideh Samani


Nitrogen (N) is an essential nutrient for many crops including corn and soybean. However, its leaching into groundwater is a serious cause of concern for environmental and public health. The amount of N leaching is closely linked to soil water drainage and rainfall. Prediction of N leaching in cropping systems is critical to the improvement of crop management through the reduction of N leaching. Visualizations can help understand uncertainty in the prediction of N leaching in soil. The uncertainty in N leaching originates from uncertainty in many parameters, such as weather predictions, soil properties, and the information entered by the user (e.g. N fertilizer). We have developed a platform to assist comprehending the relationship between various input parameters and N leaching. Our platform can reveal N leaching with uncertainty analysis and visualization of different parameters.

Adviser: Professors Haishun Yang and Hongfeng Yu