ABSTRACT
To interpret the results of empirical studies, researchers need mathematical models of the processes they study. The successful development of technologies that use microbial reactions in suspension should be largely attributed to the fact that the designers of these technologies could use accurate, user-friendly mathematical models to interpret the results of experimental studies, such as the models used to quantify microbial growth kinetics. In a similar fashion, biofilm researchers need accurate, user-friendly mathematical models not only to predict the outcomes of biofilm processes but, more immediately, to interpret the results of biofilm studies. Despite the obvious progress in constructing mathematical models of biofilm processes (IWA Task Group on Biofilm Modeling 2006), these models still have difficulty in predicting the long-term effects of important variables, and, more importantly, in accommodating the results of empirical studies. The lack of accurate, user-friendly mathematical models that can be used to quantify effects deduced from the conceptual model of biofilm structure and activity inhibits progress in understanding biofilm processes because of the difficulties in interpreting the results of biofilm studies.
