Abstract
Soil solarization is a non-chemical treatment of agricultural soil for the control of soil-borne pathogens and pests. To be most effective, the solarization process is undertaken when ambient temperatures are highest, often causing growers to lose the most productive time of year. Pre-solarization amendment of soil with organic matter has been shown to raise peak soil temperatures and possibly shorten the time required for effective soil treatment. Reliable predictive tools are necessary to characterize the solarization process and to minimize the opportunity cost incurred by farmers due to growing season abbreviation but current models do not accurately predict temperatures for soils with internal heat generation due the microbial breakdown of the soil amendment. To address the need for a more robust model, a first-order source term was developed in the course of this thesis to model the internal heat source during amended soil solarization. This source term was then incorporated into an existing “soil only” model and validated against data collected from amended soil field trials conducted at the Kearney Agricultural Center. The expanded model outperformed both the existing stable-soil model and a constant source term model, predicting daily peak temperatures to within 0.1˚C during the critical first week of solarization.