Presentation
Time:
Master’s Thesis Defense: Saeideh Samani
Date:
10:00 am
Avery Hall
Room: 19
1144 T St
Lincoln NE 68508
Lincoln NE 68508
Additional Info: AVH
Master’s Thesis Defense: Saeideh Samani
Committee Members: Dr. Hongfeng Yu (Advisor) and Dr. Haishun Yang (Co-Advisor), Dr. Mohammad Rashedul Hasan and Dr. Lisong Xu
Abstract: 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 and water through the execution and analysis of numerous simulations. The uncertainty in N leaching originates from uncertainty in many parameters such as weather prediction data, soil data, and the information entered by the user (e.g. N fertilizer). Uncertainty can cause nitrogen loss and consumption. We developed a platform that assists agricultural scientists in comprehending the relationship between various input parameters and N leaching. Our platform reveals N leaching with analysis of uncertainty. In addition, we have illustrated N leaching using different methods including heat-map, contour map, and 3D visualization.
Committee Members: Dr. Hongfeng Yu (Advisor) and Dr. Haishun Yang (Co-Advisor), Dr. Mohammad Rashedul Hasan and Dr. Lisong Xu
Abstract: 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 and water through the execution and analysis of numerous simulations. The uncertainty in N leaching originates from uncertainty in many parameters such as weather prediction data, soil data, and the information entered by the user (e.g. N fertilizer). Uncertainty can cause nitrogen loss and consumption. We developed a platform that assists agricultural scientists in comprehending the relationship between various input parameters and N leaching. Our platform reveals N leaching with analysis of uncertainty. In addition, we have illustrated N leaching using different methods including heat-map, contour map, and 3D visualization.