BARRIERS AND DISINCENTIVES TO QUALITY GROUNDWATER MODELING IN PRACTICE
This talk focuses on barriers and disincentives that are implicit, intrinsic, and insidious. Consider some examples. Disincentives include a desire to keep the client happy, minimizing costs or liability by taking advantage of the gray of uncertainty. You shade it almost white or almost black, whichever most benefits the client, but either case is the very definition of bias. Even more insidious is when the modeling team and client become essentially symbiotic, with the modelers loosing any perspective that what they are presenting is biased. Barriers include the level of training and resources available to the modeling team, and the restriction of computer programs to their own proprietary programs or perhaps only to widely used community programs, regardless of limitations they may have in algorithms, programing, or conceptual breadth and fitness. Barriers can be as silly as a decision to consider only the client's data, ignoring what may be a plethora of off-site information, much of it in the public domain. Or they can be as treacherous as a narrow view of an issue or conceptual model that ignores the broader context. Perhaps the most crippling barrier is that applied modellers get just "one shot" and then the project is over.