Integrated systemwide model-based event detection algorithm

Security issues have become increasingly important within drinking water distribution systems, leading to the development of event detection algorithms (EDAs) to provide timely detection of intrusion events. The current study develops a systemwide event detection algorithm that integrates the alarm information from localized model-based EDAs at individual monitoring stations with the probabilistic contamination source identification algorithm to estimate the probability that a node-time pair may have been contaminated. An alarm threshold can be set on the resulting contamination probabilities, which results in a systemwide EDA that takes advantage of integrating the distributed detection at all sensors rather than relying on single sensors. The systemwide EDA was evaluated with two injection scenarios simulated at two different injection locations to assess performance when all sensors observed the event versus when only one sensor observed the event. The results showed that for both injection locations and both injection scenarios, the integrated systemwide EDA outperformed the use of only the localized EDA for a series of detection thresholds based upon a range of false positive rates. These results support the assumption that including information from multiple sensors would improve event detection performance.