AWARDS is a rule-based program that uses artificial intelligence techniques. It predicts the potential for fields receiving agricultural waste applications to degrade water quality. Input data required by AWARDS include the physical features, management practices, and crop nutrient needs for all fields scheduled to receive these nutrients. Based on a series of rules AWARDS analyzes the data and categorizes each field as acceptable or unacceptable for agricultural waste applications. The acceptable fields are then ranked according to their potential for pollutant loading.
To evaluate the validity of the AWARDS field ranking system, it was compared to pollutant loading output from GLEAMS, a complex computer model. GLEAMS simulated the characteristics of each field ranked by AWARDS. Comparison of the AWARDS field ranking to the GLEAMS pollutant loading was favorable where ground water and both surface and ground water were to be protected and less favorable where surface water was to be protected. The rule base in AWARDS may need to be refined to provide more reasonable results where surface water is the resource of concern.