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Article summary:
1. This article examines the use of residual disinfectant data to calibrate a water quality model (WQM) under unknown or uncertain demands by calibrating a residential demand multiplier pattern (DMP).
2. Two artificial scenarios and one real case study are investigated to verify and validate the proposed methodology.
3. Results from the artificial case studies indicate that the proposed methodology can estimate the demands and calibrate WQM parameters correctly, while results from the real case study indicate that the original WQM calibration was performed using underestimated WDS demands.
Article analysis:
This article provides an in-depth analysis of how residual disinfectant data can be used to calibrate a water quality model (WQM) under unknown or uncertain demands by calibrating a residential demand multiplier pattern (DMP). The article is well-structured and clearly outlines its objectives, research methods, results, and conclusions. The authors provide two artificial scenarios and one real case study to verify and validate their proposed methodology, which helps to ensure its accuracy and reliability. Furthermore, tracer test data is used to validate the estimated demands from the real case study, providing further evidence for its trustworthiness.
The article does not appear to have any major biases or unsupported claims; however, it does not explore any potential counterarguments or risks associated with using this method for calibration. Additionally, it does not present both sides of an argument equally; rather, it focuses solely on presenting evidence in favor of its proposed methodology without considering any potential drawbacks or alternative approaches. As such, readers should be aware that this article may be slightly biased towards promoting its own approach over other possible solutions.