Understanding Organic Nonpoint-Source Pollution in Watersheds via Pollutant Indicators, Disinfection By-Product Precursor Predictors, and Composition of Dissolved Organic Matter

The analytical techniques and instrumentation used to assess agricultural and rural nonpoint-source organic pollution loading are usually complex and expensive. There has been a strong demand for alternative methodologies to determine the presence and composition of organic pollutants and to predict their levels. In the current work, we investigated a simple and inexpensive approach combining excitation-emission matrix and support vector machine that measures pollution and predicts the levels of precursors to disinfection by-products, which are organic pollutants derived from agricultural and rural nonpoint sources in small watersheds. Through parallel factor analysis, a four-component model was developed to explain the composition of dissolved organic matter in water impacted by nonpoint-source pollution. Support vector classification and support vector regression with model components can use fluorescence properties as proxy indicators for nonpoint-source pollution. When the model components are used as input variables, formation potential of disinfection by-products can be predicted. This method provides water utilities managers with tools to control pollution, supervise aquatic environments, and ensure the safety of drinking water.