Evaluation and application of chlorine decay models for humanitarian emergency water supply contexts

Wu, Hongjian; Dorea, Caetano C.

doi:10.1080/09593330.2021.1920626

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…It is clear that the data of the NaOCl disinfection reaction cannot be fit by the first order and second order reaction of the Harriet Chick model. Wu et al [44] showed the same conclusion in their study. The general power low (Eq.…”

Section: Effects Of Initial Coliform Bacteria Concentrationsupporting

confidence: 72%

The Effects of Operating Variables on Efficancy of Water Disinfection by Sodium Hypochlorite Using Al-Wathba Wastewater

Namoos

Abdul-Wahab

Abdul‐Majeed

2023

IJCPE

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The aim of this investigation was to study the impact of various reaction parameters on wastewater taken from Al-Wathba water treatment plant on Tigris River in south of Baghdad, Iraq with sodium hypochlorite solution. The parameters studied were sodium hypochlorite dose, contact time, initial fecal coliform bacteria concentration, temperature, and pH. In a batch reactor, different concentrations of sodium hypochlorite solution were used to disinfect 1L of water. The amount of hypochlorite ions in disinfected water was measured using an Iodimetry test for different reaction times, whereas the Most Probable Number (MPN) test was used to determine the concentration of coliform bacteria. Total Plate Count (TPC) was utilized in this study to count the number of colonies of common bacteria. Reaction variables that were examined showed that the increase in temperature, pH, and reaction time caused the concentration of Coliform bacteria to decrease, which in turn caused an accumulation-related increase in OCl- concentration. The optimum values of temperature and reaction pH were determined to be 8 and 29o C respectively. The kinetics of the reaction was examined in this study, and the results showed that Selleck model's order of reaction is two, with rate constants of 1.3791x10-5, 3.0806x10-5, and 5.738x10-5 L/(mole min) at 20o, 29o, and 37o C, respectively.

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Section: Effects Of Initial Coliform Bacteria Concentrationsupporting

confidence: 72%

The Effects of Operating Variables on Efficancy of Water Disinfection by Sodium Hypochlorite Using Al-Wathba Wastewater

Namoos

Abdul-Wahab

Abdul‐Majeed

2023

IJCPE

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“…Recent studies have developed deterministic, process-based models of FRC decay during household storage that output point predictions of the post-distribution FRC concentration [6,16,17]. However, deterministic models cannot quantify the uncertainty in post-distribution FRC decay.…”

Section: Introductionmentioning

confidence: 99%

Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?

et al. 2022

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Ensuring sufficient free residual chlorine (FRC) up to the time and place water is consumed in refugee settlements is essential for preventing the spread of waterborne illnesses. Water system operators need accurate forecasts of FRC during the household storage period. However, factors that drive FRC decay after water leaves the piped distribution system vary substantially, introducing significant uncertainty when modelling point-of-consumption FRC. Artificial neural network (ANN) ensemble forecasting systems (EFS) can account for this uncertainty by generating probabilistic forecasts of point-of-consumption FRC. ANNs are typically trained using symmetrical error metrics like mean squared error (MSE), but this leads to forecast underdispersion forecasts (the spread of the forecast is smaller than the spread of the observations). This study proposes to solve forecast underdispersion by training an ANN-EFS using cost functions that combine alternative metrics (Nash-Sutcliffe efficiency, Kling Gupta Efficiency, Index of Agreement) with cost-sensitive learning (inverse FRC weighting, class-based FRC weighting, inverse frequency weighting). The ANN-EFS trained with each cost function was evaluated using water quality data from refugee settlements in Bangladesh and Tanzania by comparing the percent capture, confidence interval reliability diagrams, rank histograms, and the continuous ranked probability. Training the ANN-EFS using the cost functions developed in this study produced up to a 70% improvement in forecast reliability and dispersion compared to the baseline cost function (MSE), with the best performance typically obtained by training the model using Kling-Gupta Efficiency and inverse frequency weighting. Our findings demonstrate that training the ANN-EFS using alternative metrics and cost-sensitive learning can improve the quality of forecasts of point-of-consumption FRC and better account for uncertainty in post-distribution chlorine decay. These techniques can enable humanitarian responders to ensure sufficient FRC more reliably at the point-of-consumption, thereby preventing the spread of waterborne illnesses.

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Evaluation of Process-Based Ensemble Models for Forecasting Point-of-Consumption Free Residual Chlorine in Refugee Settlements

De Santi,

Snieder,

Ali

et al. 2024

Lecture Notes in Civil Engineering

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Evaluation and application of chlorine decay models for humanitarian emergency water supply contexts

Cited by 4 publications

References 23 publications

The Effects of Operating Variables on Efficancy of Water Disinfection by Sodium Hypochlorite Using Al-Wathba Wastewater

The Effects of Operating Variables on Efficancy of Water Disinfection by Sodium Hypochlorite Using Al-Wathba Wastewater

Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts?

Evaluation of Process-Based Ensemble Models for Forecasting Point-of-Consumption Free Residual Chlorine in Refugee Settlements

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