Ground Water Monitoring Statistics Update: Part II: Nonparametric Prediction Limits

Nonparametric prediction limits can be useful statistical tools for ground water monitoring at facilities regulated under RCRA Subtitle C. Subtitle D. and similar regulations. New, exact tables arc presented for both "1 of m" plans (m chances to gel one observation inbounds at each of r monitoring wells to avoid a statistically significant increase) and "California" plans (first or all of the next m-1 observations inbounds at each well). The tables provide per-constituent significance levels (false positive rates) as a function of the background sample size n. m. r, the prediction limit (the largest or the next to largest, background observation), and the confirmatory resampling plan selected.
When used in a monitoring program, future observations from several wells are compared with a prediction limit obtained from a common background sample. The table significance levels therefore depend critically on having IID (independent and identically distributed) observations. In particular, the false positive rate computations are not valid, and the procedures should not be used, with constituents whose measurements exhibit inherent spatial or systematic temporal variability.
Recent U.S. EPA guidance explicitly encourages controlling facility-wide false positive rates over both constituents and wells. Nonparametric prediction limits, particularly with California resampling plans, will have greater difficulty in meeting the new. lower per-constituent false positive rate goals than previous ones, especially if many constituents are involved. Nonetheless, nonparametric prediction limits remain superior to other commonly used procedures for dealing with data with high proportions of nondctects.