Mathematical modelling of contaminant transport in riverbank filtration systems

Analytical study of contaminant transport in riverbank filtration (RBF) systems is significant in providing a guide for managing and operating drinking water supplies from pumping wells. The pumping process and the distance of the pumping well from the river are two important factors for producing p...

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Main Author: M. Mustafa, Shaymaa
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://eprints.utm.my/id/eprint/79188/1/ShaymaaMMustafaPFS2017.pdf
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spelling my-utm-ep.791882018-10-04T03:28:38Z Mathematical modelling of contaminant transport in riverbank filtration systems 2017 M. Mustafa, Shaymaa QA Mathematics Analytical study of contaminant transport in riverbank filtration (RBF) systems is significant in providing a guide for managing and operating drinking water supplies from pumping wells. The pumping process and the distance of the pumping well from the river are two important factors for producing permissible drinking water from the system. Simulation of the impact of pumping rate and pumping time on contaminant transport based on analytical studies are not yet extensive. Thus, there is a lack of mathematical models for RBF systems to determine the shortest distance of the pumping well to the river, that produces quality water. This research aimed to provide a mathematical model based on advection dispersion equation and Green’s function approach to determine the potential effects of pumping rate and pumping time, on one and two-dimensional contaminant transport models in RBF systems. The model would be able to show how the pumping time and pumping rate affect the contaminant concentration in RBF systems. By considering an inverse problem, the Green’s function solution was applied to the problem in order to determine the shortest distance from the pumping well to the river, to increase the percentage of the quality of river water. This distance was computed when the contaminants were released from a few scenario which include a single polluted river and two polluted rivers. The distance evaluated was based on three simulated scenarios containing the varying pumping times, pumping rates and different initial concentrations from the river. The model was assessed using parameters related to nitrate (NO3) compound obtained from RBF pilot project which had been conducted in Malaysia. The results confirmed the suitability of the proposed model in simulating the effect of pumping process on the quality of the produced water and in locating the pumping well. The proposed model is helpful in providing guide to manage the existing RBF systems as well as in establishing new sites. 2017 Thesis http://eprints.utm.my/id/eprint/79188/ http://eprints.utm.my/id/eprint/79188/1/ShaymaaMMustafaPFS2017.pdf application/pdf en public phd doctoral Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic QA Mathematics
spellingShingle QA Mathematics
M. Mustafa, Shaymaa
Mathematical modelling of contaminant transport in riverbank filtration systems
description Analytical study of contaminant transport in riverbank filtration (RBF) systems is significant in providing a guide for managing and operating drinking water supplies from pumping wells. The pumping process and the distance of the pumping well from the river are two important factors for producing permissible drinking water from the system. Simulation of the impact of pumping rate and pumping time on contaminant transport based on analytical studies are not yet extensive. Thus, there is a lack of mathematical models for RBF systems to determine the shortest distance of the pumping well to the river, that produces quality water. This research aimed to provide a mathematical model based on advection dispersion equation and Green’s function approach to determine the potential effects of pumping rate and pumping time, on one and two-dimensional contaminant transport models in RBF systems. The model would be able to show how the pumping time and pumping rate affect the contaminant concentration in RBF systems. By considering an inverse problem, the Green’s function solution was applied to the problem in order to determine the shortest distance from the pumping well to the river, to increase the percentage of the quality of river water. This distance was computed when the contaminants were released from a few scenario which include a single polluted river and two polluted rivers. The distance evaluated was based on three simulated scenarios containing the varying pumping times, pumping rates and different initial concentrations from the river. The model was assessed using parameters related to nitrate (NO3) compound obtained from RBF pilot project which had been conducted in Malaysia. The results confirmed the suitability of the proposed model in simulating the effect of pumping process on the quality of the produced water and in locating the pumping well. The proposed model is helpful in providing guide to manage the existing RBF systems as well as in establishing new sites.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author M. Mustafa, Shaymaa
author_facet M. Mustafa, Shaymaa
author_sort M. Mustafa, Shaymaa
title Mathematical modelling of contaminant transport in riverbank filtration systems
title_short Mathematical modelling of contaminant transport in riverbank filtration systems
title_full Mathematical modelling of contaminant transport in riverbank filtration systems
title_fullStr Mathematical modelling of contaminant transport in riverbank filtration systems
title_full_unstemmed Mathematical modelling of contaminant transport in riverbank filtration systems
title_sort mathematical modelling of contaminant transport in riverbank filtration systems
granting_institution Universiti Teknologi Malaysia, Faculty of Science
granting_department Faculty of Science
publishDate 2017
url http://eprints.utm.my/id/eprint/79188/1/ShaymaaMMustafaPFS2017.pdf
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