Developing early warning systems to predict water lead levels in tap water for private systems.

Lead is a chemical contaminant that threatens public health, and high levels of lead have been identified in drinking water at locations across the globe. Under-served populations that use private systems for drinking water supplies may be at an elevated level of risk because utilities and governing agencies are not responsible for ensuring that lead levels meet the Lead and Copper Rule at these systems. Predictive models that can be used by residents to assess water quality threats in their households can create awareness of water lead levels (WLLs).

Using a digital twin to explore water infrastructure impacts during the COVID-19 pandemic.

During the coronavirus disease 2019 (COVID-19) pandemic, the daily pattern of activities changed dramatically for people across the globe, as they socially distanced and worked remotely. Changes in daily routines created changes in water consumption patterns. Significant changes in water demands can affect the operation of water distribution systems, resulting in new patterns of flow, with implications for water age, pressure, and energy consumption.

Review of Modeling Methodologies for Managing Water Distribution Security.

Water distribution systems are vulnerable to hazards that threaten water delivery, water quality, and physical and cybernetic infrastructure. Water utilities and managers are responsible for assessing and preparing for these hazards, and researchers have developed a range of computational frameworks to explore and identify strategies for what-if scenarios. This manuscript conducts a review of the literature to report on the state of the art in modeling methodologies that have been developed to support the security of water distribution systems.