USE OF OVERLAP STUDIES TO EVALUATE METHOD CHANGES IN WATER CHEMISTRY PROTOCOLS

Long-term monitoring projects are usually plagued with method changes that occur in the midst of the monitoring record. Such changes can aff ect the data, resulting in observations of long-term trends that refle ct the change in methods rather than the monitored system. This articl e describes two statistical approaches to evaluate the effect of metho d changes, illustrated by several examples from the U.S. Environmental Protection Agency's Long-Term Monitoring Project, a study of the effe cts of acidic deposition on surface water chemistry. Structural regres sion models or paired t-tests were applied to various overlapping data sets to determine whether statistically significant differences existe d between methods. Statistically significant differences between metho d changes were seen for each of the following: different filter types, a change in anion analysis from colorimetric to ion chromatographic t echniques, and a change in sample collection method from an integrated hose sampler to a Kemmerer sampler. The characteristics under which e ach statistical approach was applied are discussed, as are considerati ons regarding calibration of the older portions of the data.