The purpose of this project was to develop a simulation tool to assess overall contaminant warning system (CWS) performance under various contamination event scenarios and to incorporate specific sensor performance characteristics in the tool to more realistically assess how sensor operational parameters can influence overall system performance. A sensor simulator was configured to mimic such sensor attributes as sensitivity, sampling rate, and drift using various mathematical and statistical algorithms. The spatial and temporal features of chemical contamination events were modeled using a pipe model of a real water distribution system and EPANET. The resulting contaminant pulse shapes at specific locations within the distribution system were combined with normal water quality background signals and processed through the sensor simulator. The sensor-altered signal was then further processed through a second event detection algorithm. Contaminant event detection statistics were then compiled and analyzed to assess overall system performance. 

This study has shown that simulation methods can be successfully used to evaluate contaminant warning system designs for user-specified chemical contamination events. Specific sensor performance attributes can be configured within the simulation to allow comparison of various commercial sensor options in a utility-specific contaminant warning system design. Initial testing results reveal that most commercial sensors perform equally well in chemical contamination events of moderate intensity with sensor sampling frequency being one of the most important sensors attributes that influences overall system performance.