Nilufar Islam

Optimizing booster chlorination in water distribution networks: a water quality index approach

The optimization of chlorine dosage and the number of booster locations is an important aspect of water quality management in distribution networks. Booster chlorination helps to maintain uniformity and adequacy of free residual chlorine concentration, essential for safeguarding against microbiological contamination. Higher chlorine dosages increase free residual chlorine concentration but generate harmful by-products, in addition to taste and odor complaints. It is possible to address these microbial, chemical, and aesthetic water quality issues through free residual chlorine concentration. Estimating a water quality index (WQI) based on regulatory chlorine thresholds for microbial, chemical, and aesthetics criteria can help engineers make intelligent decisions. An innovative scheme for maintaining adequate residual chlorine with optimal chlorine dosages and numbers of booster locations was established based on a proposed WQI. The City of Kelowna (BC, Canada) water distribution network served to demonstrate the application of the proposed scheme. Temporal free residual chlorine concentration predicted with EPANET software was used to estimate the WQI, later coupled with an optimization scheme. Preliminary temporal and spatial analyses identified critical zones (relatively poor water quality) in the distribution network. The model may also prove useful for small or rural communities where free residual chlorine is considered as the only water quality criterion.

Evaluation of source water protection strategies: a fuzzy-based model.

Source water protection (SWP) is an important step in the implementation of a multi-barrier approach that ensures the delivery of safe drinking water. Available decision-making models for SWP primarily use complex mathematical formulations that require large data sets to perform analysis, which limit their use. Moreover, most of them cannot handle interconnection and redundancy among the parameters, or missing information. A fuzzy-based model is proposed in this study to overcome the above limitations. This model can estimate a reduction in the pollutant loads based on selected SWP strategies (e.g., storm water management ponds, vegetated filter strips). The proposed model employs an export coefficient approach and account for the number of animals to estimate the pollutant loads generated by different land usages (e.g., agriculture, forests, highways, livestock, and pasture land). Water quality index is used for the assessment of water quality once these pollutant loads are discharged into the receiving waters. To demonstrate the application of the proposed model, a case study of Page Creek was performed in the Clayburn watershed (British Columbia, Canada). The results show that increasing urban development and poorly managed agricultural areas have the most adverse effects on source water quality. The proposed model can help decision makers to make informed decisions related to the land use and resource allocation.

Assessing regulatory violations of disinfection by-products in water distribution networks using a non-compliance potential index

ABSTRACTInactivating pathogens is essential to eradicate waterborne diseases. However, disinfection forms undesirable disinfection by-products (DBPs) in the presence of natural organic matter. Many regulations and guidelines exist to limit DBP exposure for eliminating possible health impacts such as bladder cancer, reproductive effects, and child development effects. In this paper, an index named non-compliance potential (NCP) index is proposed to evaluate regulatory violations by DBPs. The index can serve to evaluate water quality in distribution networks using the Bayesian Belief Network (BBN). BBN is a graphical model to represent contributing variables and their probabilistic relationships. Total trihalomethanes (TTHM), haloacetic acids (HAA5), and free residual chlorine (FRC) are selected as the variables to predict the NCP index. A methodology has been proposed to implement the index using either monitored data, empirical model results (e.g., multiple linear regression), and disinfectant kinetics through EPANET simulations. The index’s usefulness is demonstrated through two case studies on municipal distribution systems using both full-scale monitoring and modeled data. The proposed approach can be implemented for data-sparse conditions, making it especially useful for smaller municipal drinking water systems.

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

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.

Optimizing Locations for Chlorine Booster Stations in Small Water Distribution Networks

AbstractIn this paper, an index-based approach is proposed to locate chlorine booster stations in a water distribution network (DN). Chlorination is a common practice for secondary disinfection, es...

Optimization of chlorination boosters in drinking water distribution network for Al-Khobar City in Saudi Arabia

Water quality management in distribution networks is directly related to spatial distribution of chlorine boosters and its dosages. Water chlorination is essential to reduce the effects of bacterial and other microbiological contaminants. A higher dosage of chlorine generates harmful by-products in addition to changes in drinking water’s taste and odor. The optimization of chlorine dosage is necessary to decrease the microbial contaminants that affect water quality. Once the chlorine threshold is determined for microbial contaminant, it will help decision makers suggest optimal values. These decisions can rely on the estimated water quality index (WQI). WQI is an index to evaluate water quality and can be linked to adequate residual chlorine with optimal booster dosage, numbers, and locations in water distribution network (WDN). The city of Al-Khobar, Saudi Arabia’s WDN was selected to validate the application of this study. Based on geographic location, the city Al-Khobar water network was divided into five zones. The initial temporal and spatial analysis pointed out poor water quality zones. EPANET, a modeling and simulating software, was applied to evaluate the WQI. Those EPANET results were then integrated with an optimization model. The optimization model suggested new chlorine booster locations to improve water quality in the city of Al-Khobar water distribution network.