Using spatial models and kriging techniques to optimize long‐term ground‐water monitoring networks: a case study

Abstract

AbstractIn a pilot project, a spatial and temporal algorithm (geostatistical temporal–spatial or GTS) was developed for optimizing long‐term monitoring (LTM) networks. Data from two monitored ground‐water plumes were used to test the algorithm. The primary objective was to determine the degree to which sampling, laboratory analysis, and/or well construction resources could be pared without losing key statistical information concerning the plumes. Optimization of an LTM network requires an accurate assessment of both ground‐water quality over time and trends or other changes in individual monitoring wells. Changes in interpolated concentration maps over time indicate whether ground‐water quality has improved or declined. GTS separately identifies temporal and spatial redundancies. Temporal redundancy may be reduced by lengthening the time between sample collection. Spatial redundancy may be reduced by removing wells from the network which do not significantly impact assessment of ground‐water quality.Part of the temporal algorithm in GTS involves computation of a composite temporal variogram to determine the least redundant overall sampling interval. Under this measure of autocorrelation between sampling events, the lag time at which the variogram reaches a sill is the sampling interval at which same‐well measurements lack correlation and are therefore non‐redundant. The spatial algorithm assumes that well locations are redundant if nearby wells offer nearly the same statistical information about the underlying plume. A well was considered redundant if its removal did not significantly change: (i) an interpolated map of the plume; (ii) the local kriging variances in that section of the plume; and (iii) the average global kriging variance. To identify well redundancy, local kriging weights were accumulated into global weights and used to gauge each well's relative contribution to the interpolated plume map. By temporarily removing that subset of wells with the lowest global kriging weights and re‐mapping the plume, it was possible to determine how many wells could be removed without losing critical information.Test results from the Massachusetts Military Reserve (MMR) indicated that substantial savings in sampling, analysis and operational costs could be realized by utilizing GTS. Annual budgetary savings that would accrue were estimated at between 35 per cent and 5 per cent for both LTM networks under study.Copyright © 2002 John Wiley & Sons, Ltd.