Contaminant Spread Forecasting and Confirmatory Sampling Location Identification in a Water-Distribution System

Abstract

AbstractWhile significant emphasis has been placed on contamination warning system design, event detection, and source identification, relatively little emphasis has been placed on characterizing contaminant spread and confirmatory sampling. This study developed algorithms that utilize contamination source probabilities to forecast contaminant spread, which is then used to identify confirmatory sampling locations to maximize contaminant spread information based on entropy concepts. The algorithms were applied to simulated contamination scenarios using one small network with five-sensor locations, and one large network with 5-, 10-, 20-, or 50-sensor locations. The first step in the forecasting process was to identify the past contamination probability using existing sensor information and a probabilistic contamination source identification algorithm. In general, the past contamination status of the nodes was either correctly identified or did not have enough information to classify; incorrect classificati...