Contaminant mass discharge estimation in groundwater based on multi-level point measurements: a numerical evaluation of expected errors.

Different methods for the field-scale estimation of contaminant mass discharge in groundwater at control planes based on multi-level well data are numerically analysed for the expected estimation error. We consider "direct" methods based on time-integrated measuring of mass flux, as well as "indirect" methods, where estimates are derived from concentration measurements. The appropriateness of the methods is evaluated by means of modelled data provided by simulation of mass transport in a three-dimensional model domain. Uncertain heterogeneous aquifer conditions are addressed by means of Monte-Carlo simulations with aquifer conductivity as a random space function. We investigate extensively the role of the interplay between the spatial resolution of the sampling grid and aquifer heterogeneity with respect to the accuracy of the mass discharge estimation. It is shown that estimation errors can be reduced only if spatial sampling intervals are in due proportion to spatial correlation length scales. The ranking of the methods with regard to estimation error is shown to be heavily dependent on both the given sampling resolution and prevailing aquifer heterogeneity. Regarding the "indirect" estimation methods, we demonstrate the great importance of a consistent averaging of the parameters used for the discharge estimation.