Water quality monitoring with purpose: Using a novel framework and leveraging long-term data.

Water quality monitoring programs are developed to meet goals including attaining regulatory compliance, evaluating long-term environmental changes, or quantifying the impact of an emergency event. Methods for developing these programs often fail to address multiple aspects of development (hazard identification, parameter selection, monitoring locations/frequency) simultaneously. We develop a framework for monitoring program development that is both versatile and systematic, the Hazard Based Water Quality Monitoring Planning framework, and apply it to the Quabbin watershed in Massachusetts, USA. We use a novel application of dataset deconstruction of long-term water quality datasets and the Seasonal Kendall test for trends to evaluate the effects of sampling frequency on long-term trend detection at several watershed sites. Results showed that when sampling frequency is decreased, ability to detect statistically significant trends often decreases. Absolute error in trend slopes between biweekly (twice monthly) and reduced sampling frequencies was relatively small for specific conductance and turbidity but was high for total coliform, likely due to interannual variation in rainfall and temperature We found that no one sampling reduction method resulted in a consistently lower absolute error compared to the "truth" (biweekly sampling), highlighting the importance of evaluating conditions that may affect water quality at sites in different parts of a watershed. We demonstrate the framework's usefulness, particularly for parameter and sampling frequency selection, using methods that can be readily applied to other watershed systems.

Evaluating the impact of sampling design on drinking water quality monitoring program outcomes.

Drinking water suppliers around the world are required by regulations to sample and test water quality in their distribution systems with the intention of generating information that can be used to protect human health. Requirements for where samples must be collected can vary and guidance on how to select locations to meet these requirements is limited. There is a need to better define and evaluate the meaning of representative in the context of selecting locations for collecting grab samples while considering the regulatory context and resources available to suppliers. We develop sampling programs for monitoring disinfectant residual concentrations and compare the results and efficacy of these programs using synthetic water quality data for two example distribution systems. Results showed that achieving accurate estimates of worst quality conditions in a network was more likely than achieving accurate estimates of systemwide conditions, and that using constant locations makes it difficult to accurately represent systemwide conditions. Results also showed that timing of sample collection is likely important depending on factors such as consumer demand patterns, and that it is inappropriate to make conclusions about systemwide conditions when few samples are taken over an evaluation period. This research has implications for developing recommendations that water suppliers and regulators can use to design and evaluate effective sampling programs.