Integrating expert knowledge in environmental site characterization

The site characterization issue is the most essential task to be undertaken prior to the reclamation of a potentially contaminated site and it is composed of sampling, laboratory analysis, and data evaluation phases. We are primarily concerned with the data evaluation phase and we utilize a recently developed adaptive areal partitioning algorithm to characterize the site. Here, we enhance this approach by integrating expert knowledge (expert belief) into the fuzzy areal assessment scheme which derives information from sample data. We propose to allocate an adaptive weight to expert belief during the assessment. We compare the belief-integrated approach with the nonintegrated one on synthetically generated sites where both uniform and biased sampling have been applied independently. In biased sampling, the zones claimed to be highly contaminated (by the expert) are allocated a higher sampling density. We demonstrate that the belief-integrated approach outperforms the nonintegrated one both when the expert is correct or mistaken in his/her judgment irrespective of the sampling methodology