Integration of Incomplete Mixing at Junctions of Water Distribution Networks in Contamination Source Identification Tools

Abstract

The water quality models used in contamination source identification (CSI) tools assume complete mixing at the junctions of drinking water distribution networks. Two extensions of the contamination status algorithm (CSA)—a CSI tool that employs water quality models in a reverse-time manner—were accordingly developed in this study, one assuming complete mixing (CSA-CMX) and the other assuming incomplete mixing (CSA-IMX) at cross-junctions. Both algorithms identified contamination sources based on the results of grab sampling at iteratively suggested locations. The performances of CSA-CMX and CSA-IMX were evaluated through laboratory experiments using three contamination identification problems: CSA-IMX identified the contamination source in all three problems, whereas CSA-CMX identified the contamination source in only one. Furthermore, the specificity (i.e., the ability to distinguish the real contamination source from other possible contamination sources) was higher for CSA-IMX than for CSA-CMX in two of the three problems. Therefore, the incomplete mixing assumption was confirmed to be a crucial factor in CSI tools.