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 Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-3991 article 2009 Vankayala, Praveen and Vankayala, Praveen and Sankarasubramanian, A. and Sankarasubramanian, A. and Ranjithan, S. Ranji and Ranjithan, S. Ranji and Mahinthakumar, G. and Mahinthakumar, Gnanamanikam Contaminant Source Identification in Water Distribution Networks Under Conditions of Demand Uncertainty Environmental Forensics 10.1080/15275920903140486 Water distribution systems are susceptible to accidental and intentional chemical or biological contamination that could result in adverse health impact to the consumers. This study focuses on a water distribution forensics problem, contaminant source identification, subject to water demand uncertainty. Due to inherent variability in water consumption levels, demands at consumer nodes remain one of the major sources of uncertainty. In this research, the nodal demands are considered to be stochastic in nature and are varied using Gaussian and Autoregressive models. A hypothetical source identification problem is constructed by simulating observations at the sensor nodes from an arbitrary contaminant source. A simulation-optimization approach is used to solve the source identification problem with EPANET tool as the simulator and Genetic Algorithm (GA) as the optimizer. The goal is to find the source location and concentration by minimizing the difference between the simulated and observed concentrations at...
publications-3992 article 2009 Helbling, Damian E. and VanBriesen, Jeanne M. Modeling residual chlorine response to a microbial contamination event in drinking water distribution systems. Journal of Environmental Engineering 10.1061/(asce)ee.1943-7870.0000080 Changes in chlorine residual concentrations in water distribution systems could be used as an indicator of microbial contamination. Consideration is given on how to model the behavior of chlorine within the distribution system following a microbial contamination event. Existing multispecies models require knowledge of specific reaction kinetics that are unlikely to be known. A method to parameterize a rate expression describing microbially induced chlorine decay over a wide range of conditions based on a limited number of batch experiments is described. This method is integrated into EPANET-MSX using the programmer’s toolkit. The model was used to simulate a series of microbial contamination events in a small community distribution system. Results of these simulations showed that changes in chlorine induced by microbial contaminants can be observed throughout a network at nodes downstream from and distant to the contaminated node. Some factors that promote or inhibit the transport of these chlorine demand...
publications-3993 article 2014 Rasekh, Amin and Brumbelow, Kelly Drinking water distribution systems contamination management to reduce public health impacts and system service interruptions Environmental Modelling and Software 10.1016/j.envsoft.2013.09.019
publications-3994 article 2012 Kumar, Jitendra and Brill, E. Downey and Mahinthakumar, Gnanamanikam and Ranjithan, S. Ranji Contaminant source characterization in water distribution systems using binary signals Journal of Hydroinformatics 10.2166/hydro.2012.073 This paper presents a simulation–optimization-based method for identification of contamination source characteristics in a water distribution system using filtered data from threshold-based binary water quality signals. The effects of quality and quantity of the data on the accuracy of the source identification methodology are investigated. This study also addresses the issue of non-uniqueness in contaminant source identification under various data availability conditions. To establish the robustness and applicability of the methodology, numerous scenarios are investigated for a wide range of contamination incidents associated with two different networks. Results indicate that, even though use of lower resolution sensors lead to more non-unique solutions, the true source location is always included among these solutions.
publications-3995 article 2009 Guidorzi, Marco and Franchini, Marco and Alvisi, Stefano A multi-objective approach for detecting and responding to accidental and intentional contamination events in water distribution systems Urban Water Journal 10.1080/15730620802566836 The protection against contamination events in water distribution systems involves two distinct phases: detection of the presence of a contaminant and implementation of actions to isolate and/or expel it rapidly. The problem of detection is confronted by installing a series of monitoring stations, strategically placed across the distribution system and consisting of sensors to detect the presence of contaminants. The actions to be implemented may include operations on distribution system devices (valves and hydrants) or injection of reagents to eliminate the contaminant, or simply alert users. The procedure proposed here attempts to address the problems related to the two phases by means of two consecutive optimisation processes, both of them performed off-line and assuming a specific 24-hour water demand sequence in each network node, whereas the accidental/intentional injection of contaminant can occur in any node and at any hour of the day. With reference to this vast range of possible injection scenar...
publications-3996 article 2015 Rasekh, Amin and Brumbelow, Kelly A dynamic simulation-optimization model for adaptive management of urban water distribution system contamination threats Applied Soft Computing 10.1016/j.asoc.2015.03.021 Dynamic simulation is performed to model water distribution system contamination.Dynamic optimization is used to track time-varying optimal response protocols.Dynamic models provide adaptive decision support for public health protection. Urban water distribution systems hold a critical and strategic position in preserving public health and industrial growth. Despite the ubiquity of these urban systems, aging infrastructure, and increased risk of terrorism, decision support models for a timely and adaptive contamination emergency response still remain at an undeveloped stage. Emergency response is characterized as a progressive, interactive, and adaptive process that involves parallel activities of processing streaming information and executing response actions. This study develops a dynamic decision support model that adaptively simulates the time-varying emergency environment and tracks changing best health protection response measures at every stage of an emergency in real-time. Feedback mechanisms between the contaminated network, emergency managers, and consumers are incorporated in a dynamic simulation model to capture time-varying characteristics of an emergency environment. An evolutionary-computation-based dynamic optimization model is developed to adaptively identify time-dependant optimal health protection measures during an emergency. This dynamic simulation-optimization model treats perceived contaminant source attributes as time-varying parameters to account for perceived contamination source updates as more data stream in over time. Performance of the developed dynamic decision support model is analyzed and demonstrated using a mid-size virtual city that resembles the dynamics and complexity of real-world urban systems. This adaptive emergency response optimization model is intended to be a major component of an all-inclusive cyberinfrastructure for efficient contamination threat management, which is currently under development.
publications-3997 article 2008 Preis, Ami and Ostfeld, Avi Multiobjective contaminant response modeling for water distribution systems security Journal of Hydroinformatics 10.2166/hydro.2008.061 Following the events of 9/11/2001 in the US, the world public awareness to possible terrorist attacks on water supply systems has increased significantly. The security of drinking water distribution systems has become a foremost concern around the globe. Water distribution systems are spatially diverse and thus are inherently vulnerable to intentional contamination intrusions. In this study, a multiobjective optimization evolutionary model for enhancing the response against deliberate contamination intrusions into water distribution systems is developed and demonstrated. Two conflicting objectives are explored: (1) minimization of the contaminant mass consumed following detection, versus (2) minimization of the number of operational activities required to contain and flush the contaminant out of the system (i.e. number of valves closure and hydrants opening). Such a model is aimed at directing quantitative response actions in opposition to the conservative approach of entire shutdown of the system until flushing and cleaning is completed. The developed model employs the multiobjective Non-Dominated Sorted Genetic Algorithm–II (NSGA-II) scheme, and is demonstrated using two example applications.
publications-3998 article 2011 Liu, Li and Ranjithan, S. Ranji and Mahinthakumar, Gnanamanikam Contamination Source Identification in Water Distribution Systems Using an Adaptive Dynamic Optimization Procedure Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000104 Contamination source identification involves the characterization of the contaminant source based on observations that stream from a set of sensors in a water distribution system (WDS). The streaming data can be processed adaptively to provide an estimate of the source characteristics at any time once the contamination event is detected. In this paper, an adaptive dynamic optimization technique (ADOPT) is proposed for providing a real-time response to a contamination event. A new multiple population–based search that uses an evolutionary algorithm (EA) is investigated. To address nonuniqueness in the initial stages of the search and prevent premature convergence of the EA to an incorrect solution, the multiple populations are designed to maintain a set of alternative solutions that represent various nonunique solutions. As more observations are added, the EA solutions not only migrate to better solution states but the number of solutions decreases as the degree of nonuniqueness diminishes. This new algori...
publications-3999 article 2012 Ηλιάδης, Δημήτριος Γ. and Eliades, Demetrios G. and Polycarpou, Marios M. and Polycarpou, Marios M. Water Contamination Impact Evaluation and Source-Area Isolation Using Decision Trees Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000203 AbstractThe security of drinking water distribution operation is an important issue that has received increasing interest within the last few years. The U.S. EPA has issued guidelines for water utilities regarding which qualitative and quantitative metrics to monitor, and what response actions to take from the moment a contamination event alarm has been triggered, until the contamination has been accommodated and the system has returned to normal operation. Expanded sampling is a type of response action in which the water utilities examine water quality at certain locations in the network after a contamination event has been detected to help evaluate the contamination impact and locate the source-area. In this work, we propose a computational approach, based on decision trees, for choosing a sequence of nodes in the distribution network to perform expanded sampling, such that the water contamination impact is evaluated and the source-area is isolated, with as few manual quality samplings as possible. To i...
publications-4000 article 2006 Berry, Jonathan W. and Hart, William E. and Phillips, Cynthia A. and Uber, James G. and Watson, Jean-Paul Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2006)132:4(218) We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal characteristics of contamination events and their impacts. Typical network water quality simulations track contaminant concentration and movement over time, computing contaminant concentration time series for each junction. Given this information, we can compute the impact of a contamination event over time and determine affected locations. This process quantifies the benefits of sensing contamination at different junctions in the network. Ours is the first MIP model to base sensor placement decisions on such data, compromising over many individual contamination events. The MIP formulation is mathematically equivalent to the well-known p -median facility location problem. We can exploit this structure to solve the MIP exactly or to approximately solve the problem with provable quality for large-scale problems.