Management of chlorine dosing rates in urban water distribution networks using online continuous monitoring and modeling

The aim of this study is to present the results of a research which was undertaken to manage chlorine dosing rates in a real water distribution network using online continuous monitoring and modeling. The study area was divided into 18 district metered areas (DMAs) where the water pressure and flow rate measurements to each DMA were online and continuous. Besides, online water quality sensors were installed at eight different locations and a bimonthly water quality measurement and sampling program was carried out. The data sets required to set, calibrate and verify the hydraulic and chlorine models were derived from the online continuous monitoring and sampling program. Eight chlorine management scenarios that take into consideration the extreme conditions found out during the online monitoring and sampling were utilized. The study revealed that online monitoring provides excellent data sets for chlorine modeling and management that enables automatic application of chlorine dosing.

[1]  Miguel A. Mariño,et al.  Multi-objective Coverage-based ACO Model for Quality Monitoring in Large Water Networks , 2012, Water Resources Management.

[2]  Ni-Bin Chang,et al.  A rule-based decision support system for sensor deployment in small drinking water networks , 2012 .

[3]  J. Hall,et al.  2.14 – On-line Water Quality Monitoring for Drinking Water Contamination , 2014 .

[4]  L. A. Rossman The EPANET water quality model , 1994 .

[5]  Robert M. Clark,et al.  Modeling Water Quality in Distribution Systems , 2012 .

[6]  Robert M. Clark,et al.  Modeling Chlorine Residuals in Drinking‐Water Distribution Systems , 1994 .

[7]  I. E. Karadirek,et al.  Occurrence of Trihalomethanes in Chlorinated Groundwaters with Very Low Natural Organic Matter and Bromide Concentrations , 2010 .

[8]  R. Clark,et al.  Predicting Chlorine Residuals in Drinking Water: Second Order Model , 2002 .

[9]  D. Reckhow,et al.  A two-site chlorine decay model for the combined effects of pH, water distribution temperature and in-home heating profiles using differential evolution. , 2014, Water research.

[10]  Selami Kara,et al.  Implementation of Hydraulic Modelling for Water-Loss Reduction Through Pressure Management , 2012, Water Resources Management.

[11]  Ivan Stoianov,et al.  In-pipe water quality monitoring in water supply systems under steady and unsteady state flow conditions: a quantitative assessment. , 2012, Water research.

[12]  Don J. Wood Slurry Flow in Pipe Networks , 1980 .

[13]  H. Muhammetoglu,et al.  Urban Water Pipe Networks Management Towards Non‐Revenue Water Reduction: Two Case Studies from Greece and Turkey , 2014 .

[14]  Robert M. Clark,et al.  MODELING DISTRIBUTION-SYSTEM WATER QUALITY; DYNAMIC APPROACH , 1988 .

[15]  W. King,et al.  Case-control study of bladder cancer and chlorination by-products in treated water (Ontario, Canada) , 1996, Cancer Causes & Control.

[16]  Charles N. Haas,et al.  Kinetics of wastewater chlorine demand exertion , 1984 .

[17]  G. Ozolins,et al.  WHO guidelines for drinking-water quality. , 1984, WHO chronicle.

[18]  Velitchko G. Tzatchkov,et al.  Modeling of Drinking Water Distribution Networks Using Stochastic Demand , 2012, Water Resources Management.

[19]  Walter M. Grayman,et al.  USE OF DISTRIBUTION SYSTEM WATER QUALITY MODELS IN SUPPORT OF WATER SECURITY , 2006 .

[20]  Robert M. Clark,et al.  Algorithm for Mixing Problems in Water Systems , 1985 .

[21]  Feng Shang PATH-DEPENDENT APPROACH TO ESTIMATE CHLORINE WALL DEMAND COEFFICIENT IN WATER DISTRIBUTION SYSTEM , 2005 .

[22]  Hurevren Kilic,et al.  On the usage of artificial neural networks in chlorine control applications for water distribution networks with high quality water , 2011 .

[23]  W. Grayman,et al.  Kinetics of chlorine decay , 1997 .

[24]  Pratim Biswas,et al.  A model for chlorine concentration decay in pipes , 1993 .