U.S. Environmental Protection Agency


Date of this Version



Published in ENVIRONMENTAL MODELLING, SOFTWARE AND DECISION SUPPORT: STATE OF THE ART AND NEW PERSPECTIVES, edited by A. J. Jakeman, A. A. Voinov, A. E. Rizzoli, & S. H. Chen (Amsterdam et al.: Elsevier, 2008).


Complexity and uncertainty have become critical considerations for environmental modelling applications, opening ne\v avenues for the use and development of models. Increasingly l110dels are being recognized as essential tools to learn, coml11unicate, explore and resolve the particulars of complex environmental problems (Sterman, 2002; Van den Belt, 2(04). However, this shift in the way in which models have been used has not always been accompanied by a concomitant shift in the way in which models have been conceived and implemented. Too often, models were conceived and built as predictive devices, aimed at capturing single, best, objective explanations. Considerations of uncertainty were often downplayed and even eliminated because it interfered with the modelling goals. This vie\v did not take into account that other uses (see Chapter 2) may require l110dels to be developed differently and thus required different ways for managing uncertainty.