Aquifer Testing, Mathematical Modeling, and Regulatory Risk

Mathematical modeling founded on a strong field data base can be a valuable tool for the analysis of ground-water contamination problems. The purposes of this paper are threefold: (1) we demonstrate the dilemma of a knowledgeable ground-water quality regulator whose regulatory decision-making process is confronted with the output of a mathematical model that is based on very limited field test data; (2) we demonstrate a method available to a knowledgeable regulator for assessing approximately a range of possible performances of a contaminated ground-water recovery well field using a range of input data derived from a very limited data base; and (3) we present a strong case for presenting mathematical model outputs as ranges of values rather than as unique solutions. A range is determined by an examination of the level of sophistication of the field data base. Our experience with 12 field sites wherein ground-water contamination has occurred has led us to conclude that field data are seldom, if ever, adequate to defend a unique solution from a mathematical model. Regulatory decisions generally can be reduced to minimization of risks based on the smallest range of model outputs that can be defended on the basis of the field data base. The more limited the field data base, the greater must be the range of defensible model outputs, and consequently, the greater the risk inherent in subsequent regulatory decisions. The knowledgeable regulator can assess the risks in the regulatory decision-making process only if he is able to assess the extent to which the field data base for the mathematical model output reflects state-of-the-art data collection and analysis technologies and methodologies. If an applicant for a permit or license submits a less than adequate data base and concomitantly a broad range of defensible model outputs, he inherently requests that the knowledgeable regulator accept a risk greater than that required if adequate aquifer testing techniques had been employed.