Uncertainty Analysis and Calibration of Water Distribution Quality Models
type: CreativeWork
description: Water distribution system modeling can be used as a basis of planning and operation decisions. However, model accuracy and uncertainty will impact the model based decisions. Model prediction uncertainty results from uncertainty in model parameters that are determined through calibration or are based upon modeler judgment. The focus of this dissertation is the effect of uncertainties on water quality model estimates and calibration. The dissertation is centered around three journal articles and a technical note.In the first paper, the effect of parameter uncertainty on water quality in a distribution system under steady and unsteady conditions was analyzed by Monte Carlo simulation (MCS). Sources of uncertainties for water quality include decay coefficients, pipe diameter and roughness, and nodal spatial and temporal demands. The effect of individual parameter is discussed, as well as the combined effect of the parameters. It also describes the effect of flow patterns.A general calibration model is developed in the second paper for identifying wall decay coefficients. The problem is solved using the SFLA optimization algorithm that is coupled with hydraulic and water quality simulation models using the EPANET toolkit. The methodology is applied on two application networks. The study presents the effect of different field conditions such as the network with or without tanks, altering disinfectant injection policies, changing measurement locations, and varying the number of global wall decay coefficient on the estimated parameters. The numerical study also discusses whether the complexity of the system can be captured with fewer than the actual number of field parameters and if the number of the measurement locations is sufficient.The third paper conducts a study that considers a full calibration assessment for a water quality model in the distribution systems. The calibration process begins with estimating the the best fit wall decay coefficients. Next, the uncertaint…
abstract: Water distribution system modeling can be used as a basis of planning and operation decisions. However, model accuracy and uncertainty will impact the model based decisions. Model prediction uncertainty results from uncertainty in model parameters that are determined through calibration or are based upon modeler judgment. The focus of this dissertation is the effect of uncertainties on water quality model estimates and calibration. The dissertation is centered around three journal articles and a technical note.In the first paper, the effect of parameter uncertainty on water quality in a distribution system under steady and unsteady conditions was analyzed by Monte Carlo simulation (MCS). Sources of uncertainties for water quality include decay coefficients, pipe diameter and roughness, and nodal spatial and temporal demands. The effect of individual parameter is discussed, as well as the combined effect of the parameters. It also describes the effect of flow patterns.A general calibration model is developed in the second paper for identifying wall decay coefficients. The problem is solved using the SFLA optimization algorithm that is coupled with hydraulic and water quality simulation models using the EPANET toolkit. The methodology is applied on two application networks. The study presents the effect of different field conditions such as the network with or without tanks, altering disinfectant injection policies, changing measurement locations, and varying the number of global wall decay coefficient on the estimated parameters. The numerical study also discusses whether the complexity of the system can be captured with fewer than the actual number of field parameters and if the number of the measurement locations is sufficient.The third paper conducts a study that considers a full calibration assessment for a water quality model in the distribution systems. The calibration process begins with estimating the the best fit wall decay coefficients. Next, the uncertaint…
author: Pasha, Md Fayzul Kabir
language: EN
keywords: Water distribution, water quality, Monte Carlo simulation, uncertainty, Calibration
date published: 2006
date modified: 2026-07-24T00:55:23Z
provider: University of Arizona
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: The University of Arizona.

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10150/194289