'All models are wrong, how do we know which are useful?'--looking back at the 2006 Darcy Lecture Tour.

Hydrology is modeling, starting from the moment a hydrologist stands on a hill and develops a concept of the system; continuing with application of an analytical model such as Darcy’s law, the Theis equation, or chemical equilibria; and sometimes extending to elaborate numerical models. Darcy created the first quantitative ground water model in 1856, driven by the practical goal of providing a clean water supply to Dijon, France. It was clearly useful because it not only served his immediate purpose, but hydrologist still call upon it daily. Today we strive to solve complex ground water flow and transport problems, and we are asked to use model results to make decisions without the luxury of a long assessment period. Consequently, the ground water profession is searching for appropriate approaches for developing conceptual models, evaluation which models are useful, and describing the uncertainty associated with their predictions. Formulation of a reasonable set of alternative conceptual models, coupled with quantitative representation (which may range from simple to complex), is critical to the process. In spite of its apparent simplicity, this task is more difficult than numerical modeling because it reaches beyond consideration of scientific principles and quantitative algorithms into the realm of human nature and judgment. The problem is exacerbated by the dense, opaque character of the subsurface that makes data acquisition expensive, causing us to accomplish the work with sparse, uncertain information. Nevertheless, movements to meet this challenge are gaining momentum in the ground water profession. Currently available practical approaches to the problem are presented in down-to-earth terms and future challenges are