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Quantifying hydraulic and water quality uncertainty to inform sampling of drinking water distribution systems. | LitMetric

AI Article Synopsis

  • - Sampling of drinking water distribution systems is essential for maintaining water quality, ensuring public health, and meeting regulatory standards, while also addressing customer complaints or emergencies.
  • - Accurate modeling of hydraulic and water quality dynamics is crucial for effective real-time responses during contamination events; however, uncertainties in model input parameters can lead to errors.
  • - This study analyzes how different uncertainties, like contaminant injection location and reaction rates, influence the size and spread of contaminant plumes in two water distribution systems, highlighting that injection location is the most significant factor.

Article Abstract

Sampling of drinking water distribution systems is performed to ensure good water quality and protect public health. Sampling also satisfies regulatory requirements and is done to respond to customer complaints or emergency situations. Water distribution system modeling techniques can be used to plan and inform sampling strategies. However, a high degree of accuracy and confidence in the hydraulic and water quality models is required to support real-time response. One source of error in these models is related to uncertainty in model input parameters. Effective characterization of these uncertainties and their effect on contaminant transport during a contamination incident is critical for providing confidence estimates in model-based design and evaluation of different sampling strategies. In this paper, the effects of uncertainty in customer demand, isolation valve status, bulk reaction rate coefficient, contaminant injection location, start time, duration and rate on the size and location of the contaminant plume are quantified for two example water distribution systems. Results show that the most important parameter was the injection location. The size of the plume was also affected by the reaction rate coefficient, injection rate and the injection duration, while the the exact location of the plume was additionally affected by the isolation valve status. Uncertainty quantification provides a more complete picture of how contaminants move within a water distribution system and provides more information when using modeling results to select sampling locations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733274PMC
http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0001005DOI Listing

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