Application of Classification Trees for Predicting Disinfection By-Product Formation Targets from Source Water Characteristics

Abstract

Abstract

Formation and speciation of disinfection by-products (DBPs) depend on source water constituents. Many studies have sought to model the formation of DBPs using both source water and in-plant operational data, and although sometimes highly predictive of DBP formation, these models are limited in their applicability. To create regional models that could apply to multiple plants within a watershed, classification trees were used to predict finished water DBP parameters from source water constituents collected at multiple locations in a watershed. Data were from a field study conducted in the Monongahela River in southwestern PA from May, 2010 to September, 2012, incorporating six different sites. Classification trees were used to predict violation of, or compliance with, four threshold values that have regulatory and operational significance, namely, the total trihalomethanes (TTHMs) maximum contaminant level (MCL) (regulatory standard of 80 μg/L), 80% of the TTHMs MCL (64 μg/L), a bromine incorporation factor of 0.75, and 50% brominated THMs by mass. The classification trees demonstrated accuracies of 76–83%. Fluorescence measurements were selected in all classification trees, demonstrating their utility in DBP predictive models. Furthermore, model validation using data from each collection site demonstrated the potential use of classification models across this spatially variable region for drinking water plants unable to collect their own source water data. Thus, classification trees provide a valuable tool for creating watershed-level source water-based DBP models.