Comparing quantitative probability of occurrence to a risk matrix approach: A study of chlorine residual data

Implementation of water safety planning methods globally has focused primarily on developing an evidence base to demonstrate the benefits of the WSP methodology for risk management in water systems. However, little work has been completed to understand the appropriateness of the risk matrix method currently used to capture levels of risk for system-specific hazardous events. This study examines two quantitative risk calculations (probability density functions and event trees) compared to the risk matrix method employed in water safety planning. This analysis was undertaken to understand if the risk matrix provides an accurate estimation of risk in a water system. Two data sets were collected from nine water supply systems, both continuous inline monitoring and grab samples collected in water distribution systems (discrete events) for chlorine residual data. Using quantitative risk calculations, our study found the risk matrix does not accurately estimate risk compared to water quality data from a water system. In thirty-four (77%) of the forty-four possible scenarios investigated, the risk matrix method provided an underestimation or overestimation compared to the probability calculated using water quality data. The probabilities calculated using continuous data and the event tree method provided the closest estimations to the risk matrix, indicating larger data sets with simpler methods may be more likely to match WSP results. The lack of accuracy obtained reveals the need for a re-evaluation of the risk matrix within a water safety plan (WSP), particularly for systems with data available to perform advanced risk analysis. The risk matrix method has been used historically for systems with little data; however, for water systems with advanced water quality monitoring, adding quantitative probability calculations to a water safety plan has the potential to increase accuracy of risk assessment in water safety planning.