Contamination Detection of Water with Varying Routine Backgrounds by UV-Spectrophotometry

Abstract

Water is a resource that affects every aspect of life. Intentional or accidental contamination events in the water supply system could have a tremendous impact on public health. Quick detection of such events can reduce the expected damage. Continuous online monitoring is the first line of defense for reducing contamination-associated damage. One of the available tools for such detection is ultraviolet (UV)-absorbance spectrophotometry, where the absorbance spectra are compared against a set of normal and contaminated water fingerprints. However, because there are many factors at play that affect this comparison, it is an elusive and tedious task. This study presents a new scheme for early detection of drinking water contamination events through UV absorbance. The detection mechanism is based on a new affinity measure, Fitness, which is flexible enough to identify the source of the drinking water being monitored and alert if contaminants are present. The potential of the method is presented in a set of comprehensive experiments with various contaminants in drinking water extracted directly from a real supply system with mixed sources.