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Published online by Cambridge University Press: 03 September 2012
Bias is a difference between model and reality. Bias can be introduced at any stage of the modelling process during a site characterisation or performance assessment programme. It is desirable to understand such bias so as to be able to optimally design and interpret a site characterisation programme. The objective of this study was to examine the source and effect of bias due to the assumptions modellers have to make because reality cannot be fully characterised in the prediction of ground-water fluxes. A well-defined synthetic “reality” was therefore constructed for this study. A limited subset of these data were independently interpreted and used to compute groundwater fluxes across specified boundaries in a cross section. The modelling results were compared to the “true” solutions derived using the full dataset. This study clarified and identified the large number of assumptions and judgements which have to be made when modelling a limited site characterisation dataset. It is concluded that bias is introduced at each modelling stage, and that it is not necessarily detectable by the modellers even if multiple runs with varied parameter values are undertaken.