Mapping groundwater quality in the Netherlands

Maps of 25 groundwater quality variables were obtained by estimating 4 km × 4 km block median concentrations. Estimates were presented as approximate 95% confidence intervals related to four concentration levels mostly obtained from critical levels for human consumption. These maps were based on measurements from 425 monitoring sites of national and provincial groundwater quality monitoring networks. The estimation procedure was based on a stratification by soil type and land use. Within each soil-land use category, measurements were interpolated. Spatial dependence between measurements and regional differences in mean level were taken into account. Stratification turned out to be essential: no or partial stratification (using either soil type or land use) results in essentially different maps. The effect of monitoring network density was studied by leaving out the 173 monitoring sites of the provincial monitoring networks. Important changes in resulting maps were assigned to loss of information on short-distance variation, as well as loss of location-specific information. For 12 variables, maps of changes in groundwater quality were made by spatial interpolation of short-term predictions calculated for each well screen from time series of yearly measurements over 5–7 years, using a simple regression model for variation over time and taking location-specific time-prediction uncertainties into account.

From a policy point of view, the resulting maps can be used either for quantifying diffuse groundwater contamination and location-specific background concentrations (in order to assist local contamination assessment) or for input and validation of policy supporting regional or national groundwater quality models. The maps can be considered as a translation of point information obtained from the monitoring networks into information on spatial units, the size of which is used in regional groundwater models. The maps enable location-specific network optimization. In general, the maps give little reason for reducing the monitoring network density (wide confidence intervals).