4.4.3.2 Incremental to discrete sample comparisons

Occasionally, it may be desirable to consider comparing or combining discrete data and ISM data. Conceptually, this can only be done when specific conditions are met:

  • The design for selecting the discrete samples is known (i.e., simple random sampling, adaptive cluster sampling, etc.), and the discrete sample set is representative of the entire DU (i.e., the sampling design was statistically based and not biased).

  • The samples have been collected using the same collection method or methods similar enough to ensure equivalent particle size distributions between types of samples.

  • The samples are representative of the same soil conditions (e.g., soil type, depth).

  • The samples have been processed in a laboratory using the same sample preparation method or methods similar enough to ensure equivalent digestion and extraction of contaminants from the sample matrix for analysis.

  • The samples have been analyzed in a laboratory using the same analytical method or methods similar enough to ensure equivalent analytic results.

  • The quality of both data sets is understood (via data validation reports) such that it is known that the data are appropriate for the intended use.

One must be very cautious in how information is compared or combined between DUs since it is likely that one or more of these conditions will be violated to some degree, and in practice, there are no established methods for combining discrete and ISM data.