Water Network Protection from Intentional Contamination by Sectorization

Each single phase of a water supply network, from water adduction to distribution to end-users, is exposed to many diverse potential sources of intentional contamination (or malicious attacks). One of the most dangerous threats is a backflow attack that occurs when a pump system, easily available on the market, is utilized to overcome the pressure gradient of network pipes. In this work, a simple backflow attack with cyanide being introduced into a real-water system is modeled and the most dangerous introduction points for a contaminant incident are defined. Moreover, the network vulnerability has been analyzed by computing the lethal dose of cyanide ingested by users and the total length of the contaminated water system. Eventually the effects of network partitioning and district isolation to protect water supply systems have been investigated. The results show how district closing - by network sectorization techniques used to improve leakage search and reduction - can significantly decrease contaminant diffusion and protect part of the users from cyanide uptake. Network sectorization can also reduce the risk of simple malicious attacks because several introduction points are necessary to have a massive negative impact on the network. Simulation results also show that in some cases water network partitioning may worsen water network protection and further studies are necessary to design water districts for network security and safety.

[1]  U. Diwekar,et al.  Water networks security: A two-stage mixed-integer stochastic program for sensor placement under uncertainty , 2005 .

[2]  S. Buchberger,et al.  MODELING THE PROPAGATION OF WATERBORNE DISEASE IN WATER DISTRIBUTION SYSTEMS: RESULTS FROM A CASE STUDY , 2008 .

[3]  Alfeu Sá Marques,et al.  District Metered Areas Design Under Different Decision Makers’ Options: Cost Analysis , 2013, Water Resources Management.

[4]  Armando Di Nardo,et al.  A DESIGN SUPPORT METHODOLOGY FOR DISTRICT METERING OF WATER SUPPLY NETWORKS , 2011 .

[5]  Lorenz T. Biegler,et al.  Contamination Source Determination for Water Networks , 2005 .

[6]  Angelo Leopardi,et al.  Pollution Source Identification of Accidental Contamination in Water Distribution Networks , 2008 .

[7]  Lorenz T. Biegler,et al.  Mixed-Integer Approach for Obtaining Unique Solutions in Source Inversion of Water Networks , 2006 .

[8]  Armando Di Nardo,et al.  A heuristic design support methodology based on graph theory for district metering of water supply networks , 2011 .

[9]  Dan Kroll,et al.  Methods for evaluating water distribution network early warning systems , 2010 .

[10]  Victor H. Alcocer-Yamanaka,et al.  Graph Theory Based Algorithms for Water Distribution Network Sectorization Projects , 2008 .

[11]  Ni-Bin Chang,et al.  Comparisons between a rule-based expert system and optimization models for sensor deployment in a small drinking water network , 2011, Expert Syst. Appl..

[12]  Stefano Alvisi,et al.  A multi-objective approach for detecting and responding to accidental and intentional contamination events in water distribution systems , 2009 .

[13]  Katherine A. Klise,et al.  Event Detection from Water Quality Time Series , 2007 .

[14]  Roy C. Haught,et al.  On–Line water quality parameters as indicators of distribution system contamination , 2007 .

[15]  Avi Ostfeld,et al.  Contamination Source Identification in Water Systems: A Hybrid Model Trees–Linear Programming Scheme , 2006 .

[16]  James A. Goodrich,et al.  Adaptive monitoring to enhance water sensor capabilities for chemical and biological contaminant detection in drinking water systems , 2006, SPIE Defense + Commercial Sensing.

[17]  Dragan Savic,et al.  Effects of Redesign of Water Systems for Security and Water Quality Factors , 2009 .

[18]  Larry W. Mays,et al.  Urban Water Supply Handbook , 2002 .

[19]  Mustafa M. Aral,et al.  Identification of Contaminant Sources in Water Distribution Systems Using Simulation-Optimization Method: Case Study , 2006 .

[20]  Chyr Pyng Liou,et al.  Modeling the Propagation of Waterborne Substances in Distribution Networks , 1987 .

[21]  Avi Ostfeld,et al.  The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms , 2008 .

[22]  Mark Gibson,et al.  Technologies and Techniques for Early Warning Systems to Monitor and Evaluate Drinking Water Quality: A State-of-the-Art Review , 2005 .

[23]  Pradyot Patnaik,et al.  A comprehensive guide to the hazardous properties of chemical substances , 2007 .