Ensuring compliance with EPA regulations under the Safe Drinking Water Act is crucial for managing Disinfection Byproducts (DBPs) in drinking water, which form when disinfectants react with natural materials. To proactively address this challenge, the City of Baltimore implemented a predictive modeling approach using historical monthly DBP data from 2013 to 2023. By analyzing trends, seasonal variations, and correlations, the model forecasts DBP levels up to two years in the future, providing early warnings for potential exceedances. This approach enables the City to optimize water treatment processes, allocate resources efficiently, and plan for infrastructure upgrades while ensuring regulatory compliance. By prioritizing practicality over complexity, the City leverages time-series analysis to deliver actionable insights, transitioning from reactive responses to strategic, long-term water quality management. This paper highlights the value of accessible data and practical tools in safeguarding public health and enhancing operational efficiency.
Yazdekhasti et al. (Thu,) studied this question.