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Influence of the Amount of Available K Data on Uncertainty About Contaminant Transport Prediction

The effect of increasing the amount of hydraulic conductivity (K) data on the level of uncertainty about contaminant concentration predictions was examined. Contaminant concentrations were predicted using Monte Carlo numerical simulations with progressively more K information, and were compared to reference data obtained from a physical experiment. Increasing the amount of K data used in generating the aquifer's K field improved the measure of confidence in the predicted contaminant concentration. The normalized concentration interval with 95% confidence decreased from 1.29 to 0.75 when the amount of K data increased from 20 to 71. However, the trade‐off is the increase in the costs of aquifer investigation. Conducting Monte Carlo numerical simulations may help design an optimal aquifer investigation scheme, so that it can provide enough input data to predict concentrations with the desired level of confidence and at the same time avoid the excessive costs of aquifer investigation.