ESTIMATING AQUIFER TRANSMISSIVITIES - ON THE VALUE OF AUXILIARY DATA

Groundwater quality modelling relies heavily on the knowledge of prefe rential flowpaths such as buried stream channels and their distributio n within the aquifer. This paper examines the extent to which these pa tterns may be identified by including auxiliary data, such as transver se electric resistances or specific capacities, when estimating the tr ansmissivity field. The analyses are based on two hypothetical aquifer s. The first involves a high transmissivity flowpath. The second is a realization of a correlated random field with the same spatial moments as the organised case. Monte Carlo simulations and cokriging estimate s are used to analyse the effect of the number of samples and their co rrelation with transmissivity on the width of the capture zone of a we ll. Results indicate that, in the organised case with no auxiliary inf ormation, the estimated widths are substantially biased. This bias can be reduced significantly by including auxiliary data, even when poorl y correlated to transmissivity. Auxiliary data also reduce the scatter (i.e. standard deviation) of the estimated widths significantly, whic h is a measure of the accuracy of the estimates. In the example used h ere, 70 samples of auxiliary data, which are correlated to transmissiv ity by r = 0.6, outweigh the information from 12 additional pumping te sts. For the case of the correlated random held, the benefit of using auxiliary data is much less pronounced both in terms of removing the b ias and in terms of accuracy (i.e. standard deviation). It is conclude d that auxiliary data are useful for estimating transmissivity fields in the context of groundwater quality modelling, particularly when cha nnelised how is to be expected.