Integrating fuzzy logic with Pearson correlation to optimize contaminant detection in water distribution system with uncertainty analyses Shabbir Ahmed Osmani & Bijit Kumar Banik & Hazrat Ali Received: 13 November 2018 /Accepted: 10 May 2019 # Springer Nature Switzerland AG 2019 Abstract An effective detection algorithm, supervising an online water system, is expected to monitor changes in water quality due to any contamination. However, contemporary event detection methods are often criti- cized for their high false detection rates as well as for their low true detection rates. This study proposes two new event detection methods for contamination that use multi-objective optimization by investigating the corre- lation between multiple types of conventional water quality sensors. While the first method incorporates non-dominated sorting genetic algorithm II (NSGA-II) with the Pearson correlation Euclidean distance (PE) method in order to maximize the probability of detection (PD) and to minimize the false alarm rate (FAR), the second method introduces fuzzy logic in order to estab- lish a degree of correlations ranking that replaces the correlation relationship indicator threshold. Optimiza- tion is performed by using NSGA-II in the second method. The results of this study show that the incorpo- ration of fuzzy logic with NSGA-II in event detection method have produced better results in event detection. The results also show that both methods detect all true events without producing any false alarm rates. Moreover, an uncertainty analysis on input sensor signals is per- formed to test the robustness of the fuzzy logic-based event detection method by employing the widely used Monte Carlo simulation (MCS) technique. Four different scenarios of uncertainty are analyzed, in particular, and the findings suggest that the proposed method is very effective in minimizing false alarm rates and maximizing true events detection, and hence, it can be regarded as one of the novel approaches to demonstrate its application in the development of an event detection algorithm. Keywords Contamination event . Fuzzy logic . Monte Carlo simulation . NSGA-II . Optimization . Pearson correlation Introduction Numerous studies have provided the evidence that the inadequate management of water distribution system has led to different types of outbreaks of illness in both developed and developing countries (St 1988; Herwaldt et al. 1991; Moore et al. 1993; Hrudey et al. 2003). Particularly in the USA, almost 9000 cases of illness from 57 outbreaks have been reported between 1981 and 2010 (Kramer et al. 1996; Levy et al. 1998; Lee et al. 2002; Blackburn et al. 2004; Liang et al. 2006; Brunkard et al. 2011). While the causes and the ranges of chemical and microbial hazards behind these contaminations are diverse, Khan et al. (2001) claimed Environ Monit Assess (2019) 191:441 https://doi.org/10.1007/s10661-019-7533-x S. A. Osmani Department of Civil Engineering, Leading University, Ragib Nagar, South Surma, Sylhet, Bangladesh B. K. Banik (*) Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh e-mail: bijit-cee@sust.edu H. Ali Department of Civil Engineering, Chittagong University of Engineering & Technology, Chattogram 4349, Bangladesh