Minimizing the impacts of contaminant intrusion in small water distribution networks through booster chlorination optimization

  • Nilufar Islam
  • Manuel J. Rodriguez
  • Ashraf Farahat
  • Rehan Sadiq
Original Paper
  • 21 Downloads

Abstract

Contaminant intrusion in a water distribution network (DN) has three basic pre-conditions: source of contaminant (e.g., leaky sewer), a pathway (e.g., water main leaks), and a driving force (e.g., negative pressure). The impact of intrusion can be catastrophic if residual disinfectant (chlorine) is not present. To avoid microbiological water quality failure, higher levels of secondary chlorination doses can be a possible solution, but they can produce disinfectant by-products which lead to taste and odour complaints. This study presents a methodology to identify potential intrusion points in a DN and optimize booster chlorination based on trade-offs among microbiological risk, chemical risk and life-cycle cost for booster chlorination. A point-scoring scheme was developed to identify the potential intrusion points within a DN. It utilized factors such as pollutant source (e.g., sewer characteristics), pollution pathway (water main diameter, length, age, and surrounding soil properties, etc.), consequence of contamination (e.g., population, and land use), and operational factors (e.g., water pressure) integrated through a geographical information system using advanced ArcMap 10 operations. The contaminant intrusion was modelled for E. Coli O156: H7 (a microbiological indicator) using the EPANET-MSX programmer’s toolkit. The quantitative microbial risk assessment and chemical (human health) risk assessment frameworks were adapted to estimate risk potentials. Booster chlorination locations and dosages were selected using a multi-objective genetic algorithm. The methodology was illustrated through a case study on a portion of a municipal DN.

Keywords

Contaminant intrusion Water distribution network Optimization Booster chlorination Disinfectant by-products Life-cycle cost Quantitative microbial risk assessment 

Abbreviations

A

Agricultural

AC

Asbestos cement

AHP

Analytic hierarchy process

BIF

Bromide incorporation factor

C

Commercial

CD

Comprehensive development

CHBr2Cl

Dibromochloromethane

CHBr3

Bromoform

CHBrCl2

Bromodichloromethane

CHCl3

Chloroform

CI

Cast iron

CIPRA

Cast Iron Pipe Research Association

CONC

Concrete

COP

Copper

ChRP

Chemical risk potential

DA

Dissemination area

DBPs

Disinfectant by-products

DFI

Driving force index

DI

Ductile iron

DIPRA

Ductile Iron Pipe Research Association

DN

Distribution network

FRC

Free residual chlorine

GA

Genetic algorithm

GIS

Geographical information system

GWT

Ground water table

HAAs

Haloacetic acids

HD

Health District

HDPE

High density polyethylene

I

Industrial

IRIS

Integrated risk information system

IRP

Intrusion risk potential

LCC

Life-cycle cost

LTESWTR

Long term enhanced surface water treatment rule

LUCI

Land use consequence index

LUW

Land use weight

MOGA

Multi objective genetic algorithm

MRP

Microbial risk potential

P/W

Public and Institutional

PD

Population density

PDCI

Population density consequence index

PSI

Pollution source index

PVC

Poly vinyl chloride

QMRA

Quantitative microbial risk assessment

RfD

Reference dose

RR

Rural residential

RU/RM

Urban residential

SCI

Soil corrosivity index

SCI-C

Soil corrosivity index for cementitious pipes

SCI-M

Soil corrosivity index for metallic pipes

SCI-P

Soil corrosivity index for plastic pipes

SF

Slope factor

SFI

Structural failure index

STEEL

Steel

SWTR

Surface water treatment rule

TTHM

Total trihalomethane

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Nilufar Islam
    • 1
  • Manuel J. Rodriguez
    • 2
  • Ashraf Farahat
    • 3
    • 4
  • Rehan Sadiq
    • 1
  1. 1.School of EngineeringUniversity of British Columbia (Okanagan Campus)KelownaCanada
  2. 2.École supérieure d’aménagement du territoire et développement régionalUniversité LavalQuebecCanada
  3. 3.College of Applied and Supporting StudiesKing Fahd University of Petroleum and Minerals (KFUPM)DhahranSaudi Arabia
  4. 4.Department of Physics, Faculty of ScienceAlexandria UniversityAlexandriaEgypt

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