Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID ▲	Type	Year	Authors	Title	Venue/Journal	DOI	Abstract
publications-4341	article	2004	Prasad, T. Devi and Prasad, T. Devi and Walters, Godfrey A. and Savic, Dragan	Booster Disinfection of Water Supply Networks: Multiobjective Approach	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2004)130:5(367)	Booster disinfection is the addition of disinfectant at some critical locations of a water distribution network such that disinfectant residuals are maintained at a level greater than the minimum for public health. Compared to conventional methods that apply disinfectant only at the source, booster disinfection can reduce the total disinfectant dose. The present work investigates the booster facility location and injection scheduling problem in water distribution networks. The problem is formulated as a multiobjective optimization model. The objectives are minimization of the total disinfectant dose and maximization of the volumetric demand within specified residual limits. Multiobjective genetic algorithms are used for solving the problem. The model utilizes the theory of linear superposition in water quality modeling for calculating concentration profiles at network nodes. Unlike previous models, the present multiobjective approach does not require pruning of monitoring nodes to find feasible solutions; all demand nodes are considered as monitoring nodes. Application of the model to an example problem reveals that there is a critical point in the level of constraint satisfaction, after which the disinfectant dosage rate increases significantly in order to satisfy a few remaining constraints.
publications-4342	article	2004	Propato, Marco and Propato, Marco and Uber, James G. and Uber, James G.	Linear least-squares formulation for operation of booster disinfection systems	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2004)130:1(53)	Maintaining a disinfectant residual in drinking water distribution networks is a challenge for water utilities. These challenges arise from the spatial and temporal distribution of water usage, and from chemical reactions that cause disinfectants to decay. A potential solution is booster chlorination, a strategy where disinfectant is reapplied within the network. Here, a linear least-squares problem is formulated to determine the optimal disinfectant injection rates that minimize variation in the system residual space-time distribution. Locations of booster stations are assumed known. The solution is simple and can be analytically derived in some cases. The problem formulation allows an arbitrary weight on the contribution of each consumer node disinfectant residual to the overall objective function; two possible weighting schemes are suggested. In a planning context, the method is shown to apply to network flows whose first and second moments are stationary. In contrast to previous approaches, the number...
publications-4343	article	2005	Farmani, Raziyeh and Farmani, Raziyeh and Walters, Godfrey A. and Walters, Godfrey A. and SaviΔ‡, Dragan and Savic, Dragan	Trade-off between Total Cost and Reliability for Anytown Water Distribution Network	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2005)131:3(161)	This paper investigates the application of multiobjective evolutionary algorithms to the identification of the payoff characteristic between total cost and reliability of a water distribution system using the well-known "Anytown" network as an example. An expanded rehabilitation problem is considered where the design variables are the pipe rehabilitation decisions, tank sizing, tank siting, and pump operation schedules. To provide flexibility, the network is designed and operated under multiple loading conditions. Inclusion of pump operation schedules requires consideration of water system operation over an extended period. The cost of the solution includes the capital costs of pipes and tanks as well as the present value of the energy consumed during a specified period. Optimization tends to reduce costs by reducing the diameter of, or completely eliminating, some pipes, thus leaving the system with insufficient capacity to respond to pipe breaks or demands that exceed design values without violating required performance levels. A resilience index is considered as a second objective to increase the hydraulic reliability and availability of water during pipe failures. Sensitivity analysis of solutions on the payoff curve generated by twin-objective optimization shows poor performance of these networks under random pipe failure or a pump being out of service. The minimum surplus head is added as a third objective to overcome the shortcomings of the resilience index. Results are presented for the payoff characteristics between total cost and reliability for 24 h design and five loading conditions.
publications-4344	article	2007	SchlΓΌterβ€¬, Maja and SchlΓΌter, Maja and Pahlβ€Wostl, Claudia and Pahl-Wostl, Claudia	Mechanisms of Resilience in Common-pool Resource Management Systems: an Agent-based Model of Water Use in a River Basin	Ecology and Society	10.5751/es-02069-120204	The concept of resilience is widely promoted as a promising notion to guide new approaches to ecosystem and resource management that try to enhance a system's capacity to cope with change. A variety of mechanisms of resilience specific for different systems have been proposed. In the context of resource management those include but are not limited to the diversity of response options and flexibility of the social system to adaptively respond to changes on an adequate scale. However, implementation of resilience-based management in specific real-world systems has often proven difficult because of a limited understanding of suitable interventions and their impact on the resilience of the coupled social-ecological system. We propose an agent-based modeling approach to explore system characteristics and mechanisms of resilience in a complex resource management system, based on a case study of water use in the Amudarya River, which is a semiarid river basin. Water resources in its delta are used to sustain irrigated agriculture as well as aquatic ecosystems that provide fish and other ecosystem services. The three subsystems of the social-ecological system, i.e., the social system, the irrigation system, and an aquatic ecosystem, are linked by resource flows and the allocation decision making of actors on different levels. Simulation experiments are carried out to compare the resilience of different institutional settings of water management to changes in the variability and uncertainty of water availability. The aim is to investigate the influence of (1) the organizational structure of water management, (2) information on water availability, and (3) the diversity of water uses on the resilience of the system to short and long-term water scarcity. In this paper, the model concept and first simulation results are presented. As a first illustration of the approach the performances of a centralized and a decentralized regime are compared under different scenarios of information on water availability. Under the given conditions of a regularly fluctuating inflow and compliance of agents with orders from a national authority, the centralized system performs better as long as irrigation is the only type of water use. Diversification of resource use, e.g., irrigation and fishing, increases the performance of the decentralized regime and the resilience of both. Systematic analysis of the performance of different system structures will help to identify properties and mechanisms of resilience. This understanding will be valuable for the identification, development, and evaluation of management interventions in specific river basins.
publications-4345	article	2008	Ghimire, Santosh R. and Barkdoll, Brian D.	A Heuristic Method for Water Quality Sensor Location in a Municipal Water Distribution System: Mass-Released Based Approach		10.1061/40941(247)110	There is interest in optimally locating water quality sensors in a water distribution system due to possible terrorist injections of a contaminant. This paper is part of a contest for the 8th Water Distribution System Analysis Symposium entitled "Battle of the Water Sensor Networks" (BWSN), which asks contestants to propose sensor designs for two networks and two numbers of sensors. The method of sensor location selection described here is a mass-based approach in which sensors are located at the junctions with the greatest mass released from the junctions. The rationale behind this method is that the mass of contaminant, in contrast to other variables, directly causes illness. The 5-sensor and 20-sensor designs are presented in the paper. This paper was presented at the 8th Annual Water Distribution Systems Analysis Symposium which was held with the generous support of Awwa Research Foundation (AwwaRF).
publications-4346	article	2008	Dorini, G. and Jonkergouw, Philip and Kapelan, Zoran and di Pierro, F. and Khu, Soon-Thiam and Savic, Dragan	An efficient algorithm for sensor placement in water distribution systems		10.1061/40941(247)101	The objective of this paper is to present an optimal sensor placement methodology to assist in the effective and efficient detection of accidental and/or intentional contaminant intrusion(s) in water distribution systems. The work presented here is done in response to call for papers for the Battle of the Water Sensors Networks (BWSN), at the Water Distribution Systems Analysis Symposium (2006). The above problem is formulated and solved as a constrained multiobjective optimisation problem. The four objectives are: (1) minimisation of the expected time of detection, (2) minimisation of the expected population affected prior to detection, (3) minimisation of the expected demand of contaminated water prior to detection and (4) maximisation of the detection likelihood. The constraint modelled is the pre-specified number of detection sensors used in the sampling design. Decision variables are the sensor network locations. The solution methodology proposed is based on the novel Noisy Cross-Entropy Sensor Locator (nCESL) algorithm. This algorithm is applied to the two competition networks under four base contamination scenarios (A, B, C and D) and two different numbers of sensors available (5 and 20). The results obtained demonstrate the effectiveness and efficiency of the sensor placement methodology proposed. Copyright ASCE 2006.
publications-4347	article	2008	Wu, Zheng Yi and Walski, Tom	MULTI OBJECTIVE OPTIMIZATION OF SENSOR PLACEMENT IN WATER DISTRIBUTION SYSTEMS		10.1061/40941(247)105	Placement of water quality sensor has received an increasing concern for timely providing the warning of possible contamination in a water system. Due to the large dimension of water distribution network and the difficulty for predicting where a contamination event occurs, it is a great challenge for engineers to come up with good sensor locations with any confidence to effectively detect possible contamination events. The problem is complicated by the fact that sensor location is evaluated against a number of objective criteria that may include the detection likelihood, the expected detection time, affected population and contaminated water consumption. A design that improves one objective may deteriorate another. In this paper, sensor placement is formulated as a multi objective optimization problem that is solved by using a competent genetic algorithm while the contamination events are simulated by the latest development of Monte Carlo method.
publications-4348	article	2008	Preis, Ami and Ostfeld, Avi	MULTIOBJECTIVE SENSOR DESIGN FOR WATER DISTRIBUTION SYSTEMS SECURITY		10.1061/40941(247)107	This paper presents a multiobjective model to optimal sensor design in water distribution systems as part of the battle of the water sensors networks (BWSN). Previous work on optimal sensor design for water distribution systems (WDS) focused on one objective (e.g., maximizing the detection likelihood of contamination events). In this study the Non-Dominated Sorted Genetic Algorithmβ€“II (NSGA-II) is implemented to tradeoff the following four conflicting objectives: (1) maximizing the detection likelihood; (2) minimizing the detection time; (3) maximizing the detection instrumentation redundancy; and (4) maximizing the contamination source identification likelihood (i.e., the likelihood to provide a unique solution to the inverse problem of contamination source identification for a given layout of sensors). The effectiveness of the multiobjective approach is demonstrated through using the two BWSN network examples, where Pareto fronts are plotted for each two objectives; for each three; and finally for all four.
publications-4349	article	2008	Poulin, Annie and Poulin, Annie and Mailhot, Alain and Mailhot, Alain and Grondin, Patrice and Grondin, Patrice and Delorme, L. D. and Delorme, Louis and Villeneuve, Jeanβ€Pierre and Villeneuve, Jean-Pierre	Optimization of Operational Response to Contamination in Water Networks		10.1061/40941(247)117	With emerging security issues, drinking water utilities are facing new challenges. New security strategies and emergency response plans should be implemented to face a range of possible threats. While not the most likely, drinking water contamination may be the most worrying in terms of public health, socio-economic and psychological impacts. In many previous studies, hydraulic and water quality simulation tools have been used to address security issues related to contamination. However, to our knowledge, no studies have yet focused on the elaboration of a strategy defining the field operations to implement, after contamination has been detected, to protect public health. This paper presents ongoing work defining an operational strategy based on optimizing a sequence of field operations. Three main objectives were defined in the context of this research project: 1) minimize the risk that contaminated water is consumed; 2) identify the valves to be closed to safely contain the contaminated water and proceed, as quickly as possible, to isolation operations; 3) define a set of operations to efficiently flush contaminated water from the network to quickly and safely return to a normal operation. It is assumed that a utility has installed a Contamination Early Warning System (CEWS) to physically secure the distribution network, and that a reliable public notification system is in place as well. A simplified version of a static sensor placement optimization model is used to locate contaminant detectors. Depending on which detector gives the first alarm, a potentially contaminated zone can be delineated and the spatial expansion of this zone can be traced through time. A heuristic algorithm based on a set of pragmatic, operational and safety rules to isolate contaminated zones is introduced. Considering simultaneous field manipulations and no limit on the number of response teams (2 persons, 1 specialized vehicle), a solution is sought to ensure that every operation required for isolation can be executed before contamination reaches isolation valves. An application example is presented for the small network of Valcourt (Quebec, Canada). Although the current work is based on simplifying assumptions regarding hydraulic and contaminant transport simulation, our isolation algorithm remains general and straightforward enough to be implemented under various modeling schemes. Future works will address the operational issues related to flushing contaminated water from previously isolated zones. This paper was presented at the 8th Annual Water Distribution Systems Analysis Symposium which was held with the generous support of Awwa Research Foundation (AwwaRF).
publications-4350	article	2008	Krause, Andreas and Leskovec, Jure and Isovitsch, Shannon L. and Xu, Jianhua and Guestrin, Carlos and VanBriesen, Jeanne M. and Small, Mitchell J. and Small, Mitchell and Fischbeck, Paul S.	Optimizing Sensor Placements in Water Distribution Systems Using Submodular Function Maximization		10.1061/40941(247)109	Drinking water distribution networks represent complex systems. Water flow rates in a water distribution system vary with time, with periodic features that reflect temporal variations in water demand by consumers. The intentional introduction of a contaminant disrupts the system and could theoretically be detected by a sensor or network of sensors placed at nodes (pipe junctions, reservoirs, storage tanks, or even individual consumer taps) in the system. Determining the best locations for placement of these sensors represents a significant research question, because the system has multiple states, the number of possible intrusion points is large, and the likely high cost of these sensors limits the number that can realistically be deployed. The optimal placement of these sensors to minimize the effect of an introduced contaminant on the population is a critical issue. Sensor placement for intrusion detection exhibits an important diminishing returns property: adding a sensor to a sensor network improves the detection ability less than adding it to a subset of the sensor network. We prove that this submodularity property holds for the objective functions that we consider for placing sensors, and exploit it by applying algorithms for maximizing monotonic submodular functions. Unlike existing optimization algorithms for selecting sensor placements, our efficient optimization procedure has strong theoretical performance guarantees. In spite of the problemβ€™s complexity, our algorithm is guaranteed to always find a solution that is at least within 63\% of the optimum, and will often find a (near-)optimal solution. This method is applied to two hypothetical distribution systems (129 nodes and 12,527 nodes) to determine optimal sensor placements for a sensor network of 5 or 20 sensors. Optimization was based on multiple criteria including: (1) minimizing time to detection, (2) minimizing population affected prior to detection, (3) minimizing expected demand for contaminated water prior to detection, and (4) maximizing detection likelihood. A base scenario and three derivative scenarios were used to test the sensor location optimization for the hypothetical systems. In order to compute accurately the objective criteria, we exhaustively simulated all possible attack scenarios, using distributed computation. Five optimization objective functions were considered (i.e., optimization on each of the four objectives independently and then an equally weighted multi-objective optimization). The two networks analyzed in this project illustrate how a sensor network of 20 sensors is more than β€_x009c_adequateβ€_x009d_ for the example distribution system of 129 nodes, while a much larger sensor network would be needed for β€_x009c_adequateβ€_x009d_ detection in the example large network of 12,527 nodes. The developed algorithms generalize to networks of arbitrary size and can be constrained by expert knowledge or rankings of scenario likelihood. Further, the optimization algorithms have potential applications for placement of sensors in other complex, dynamic systems.