Randomized Stratified Sampling Methodology for Water Quality in Distribution Systems

Abstract

Water utilities rely on samples collected from the distribution system to assure the quality of drinking water delivered to customers. However, few utilities employ a systematic sampling protocol to collect these samples. This paper presents a methodology that involves random selection of sample locations and time of sample collection to minimize bias and variance in results. For a given sampling goal, system-specific knowledge is incorporated into the sampling design through definition of appropriate stratification variables, selection of sample size, and sample allocation. The sampling designs produced by this methodology provide a measurement of water quality along with an estimate of statistical precision, with insights into significant factors affecting water quality. The methodology is illustrated using a synthetic data set from a distribution system water quality model to assess sampling designs and results for a mid-sized water utility.