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 â–˛ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-4211 article 2016 Yoo, Do Guen and Yoo, Do Guen and Jung, Donghwi and Jung, Donghwi and Jung, Donghwi and Kang, Doosun and Kang, Doosun and Kim, Joong Hoon and Kim, Joong Hoon and Kim, Joong Hoon and Lansey, Kevin and Lansey, Kevin E and Lansey, Kevin E. and Lansey, Kevin E Seismic Hazard Assessment Model for Urban Water Supply Networks Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000584 AbstractA new seismic reliability evaluation model is proposed that quantifies the impact of earthquakes on hydraulic behavior of water supply networks. Probabilistic seismic events are produced in the target areas, and the depth of earthquake failure is evaluated by seismic reliability indicators. The developed model was applied to several case studies and used for an intensive examination on how a water supply system hydraulically responds to a seismic event and what system characteristics influence the system’s performance in the event of an earthquake. First, the system reliability of a real network in South Korea when subjected to earthquakes of various magnitudes and locations was quantified. Next, the reliabilities of full and simplified network models were evaluated to investigate how system layouts affect the reliability evaluation. Finally, networks with different configurations, pipe sizes, and system densities were compared with respect to the seismic reliability and various seismic damage ind...
publications-4212 article 2005 Berry, Jonathan W. and Fleischer, Lisa and Fleischer, Lisa and Hart, William E. and Phillips, Cynthia A. and Watson, Jean-Paul Sensor Placement in Municipal Water Networks Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2005)131:3(237) We present a model for optimizing the placement of sensors in municipal water networks to detect maliciously injected contaminants. An optimal sensor configuration minimizes the expected fraction of the population at risk. We formulate this problem as a mixed-integer program, which can be solved with generally available solvers. We find optimal sensor placements for three test networks with synthetic risk and population data. Our experiments illustrate that this formulation can be solved relatively quickly and that the predicted sensor configuration is relatively insensitive to uncertainties in the data used for prediction.
publications-4213 article 2008 Krause, Andreas and Leskovec, Jure and Guestrin, Carlos and VanBriesen, Jeanne M. and Faloutsos, Christos Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2008)134:6(516) The problem of deploying sensors in a large water distribution network is considered, in order to detect the malicious introduction of contaminants. It is shown that a large class of realistic objective functionsβ€”such as reduction of detection time and the population protected from consuming contaminated waterβ€”exhibits an important diminishing returns effect called submodularity. The submodularity of these objectives is exploited in order to design efficient placement algorithms with provable performance guarantees. The algorithms presented in this paper do not rely on mixed integer programming, and scale well to networks of arbitrary size. The problem instances considered in the approach presented in this paper are orders of magnitude (a factor of 72) larger than the largest problems solved in the literature. It is shown how the method presented here can be extended to multicriteria optimization, selecting placements robust to sensor failures and optimizing minimax criteria. Extensive empirical evidence ...
publications-4214 article 2004 Watson, Jean-Paul and Greenberg, Harvey J. and Hart, William E. A Multiple-Objective Analysis of Sensor Placement Optimization in Water Networks 10.1061/40737(2004)456 Terrorism concerns have recently led to increased interest in the potential use of sensors to detect malicious attacks on municipal water systems. A key deployment issue is identifying where the sensors should be placed in order to maximize the level of protection. Researchers have proposed several algorithms for constructing such sensor placements, each optimizing with respect to a different design objective. The use of disparate objectives raises several questions, in particular (1) What is the relationship between optimal placements obtained under different design objectives? and (2) Is there any risk in focusing on speci?c design objectives? To answer these questions, we develop mixed-integer linear programming models for the sensor placement problem over a range of design objectives. Using two real-world water systems, we show that optimal solutions with respect to one design objective are typically highly sub-optimal with respect to other design objectives. The implication is that robust algorithms for the sensor placement problem must carefully and simultaneously consider multiple, disparate design objectives.
publications-4215 article 2006 Murray, Regan and Uber, James G. and Janke, Robert Model for Estimating Acute Health Impacts from Consumption of Contaminated Drinking Water Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2006)132:4(293) Disease transmission models predict the spread of disease over time through susceptible, infected, and recovered populations, and are commonly used to design public health intervention strategies. A modified disease model is linked to flow and transport models for water distribution systems in order to predict the health risks associated with use of contaminated water. The proposed framework provides information about the spatial and temporal distribution of health risks in distribution systems and is useful for understanding the vulnerability of drinking water systems to contamination events, as well as for designing public health and water utility strategies to reduce risks.
publications-4216 article 2009 Yang, Y. Jeffrey and Haught, Roy C. and Goodrich, James A. Real-time contaminant detection and classification in a drinking water pipe using conventional water quality sensors: techniques and experimental results. Journal of Environmental Management 10.1016/j.jenvman.2009.01.021
publications-4217 article 1997 Kumar, Arun and Kumar, Arun and Kumar, Arun and Kansal, Mitthan Lal and Arora, Geeta Identification of Monitoring Stations in Water Distribution System Journal of Environmental Engineering 10.1061/(asce)0733-9372(1997)123:8(746) The location of water quality monitoring stations in a water distribution system should be such that the network is represented with the minimum number of monitoring stations. The present guidelines do not describe how the sampling locations are to be optimally identified. The concept of β€_x009c_pathwaysβ€_x009d_ helps in reducing the number of monitoring stations and shows that the best set of stations is that which maximizes the demand coverage of the network. The optimal locations are then identified using integer programming. However, dimensionality of the integer programming increases manifold with the increase in network size and for multiple demand patterns. In this study, modifications in this procedure are suggested to reduce the computational efforts and to make the procedure simpler. The present study identifies the location of monitoring stations from the hydraulics of flow and eliminates the use of cumbersome integer programming. The algorithm is illustrated with the help of two examples.
publications-4218 article 1998 Zierolf, M.L. and Polycarpou, Marios M. and Uber, James G. Development and autocalibration of an input-output model of chlorine transport in drinking water distribution systems IEEE Transactions on Control Systems and Technology 10.1109/87.701351 Chlorine concentrations within drinking water distribution systems (DWDS) must be maintained between an Environmental Protection Agency enforced minimum and maximum values driven by formation of harmful disinfectant byproducts. The DWDS input-output (I-O) model developed expresses the chlorine concentration at a given pipe junction and time as a weighted average of exponentially decayed values of the concentrations at all adjacent upstream junctions. The upstream junction concentrations are known if they are a chlorine treatment point, or can be calculated in the same manner as the original unknown junction concentration. This is the basis for a recursive procedure with which the I-O model backtracks through the DWDS until all paths from consumption to treatment are found. Since the I-O model finds all paths from treatment to a given measurement, the reaction rate associated with chlorine decay at the pipe wall can be adjusted to improve predicted chlorine concentrations.
publications-4219 article 2002 Deb, Kalyanmoy and Pratap, Amrit and Agarwal, Sameer and Meyarivan, T. A fast and elitist multiobjective genetic algorithm: NSGA-II IEEE Transactions on Evolutionary Computation 10.1109/4235.996017 Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (where M is the number of objectives and N is the population size); (2) their non-elitism approach; and (3) the need to specify a sharing parameter. In this paper, we suggest a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN/sup 2/) computational complexity is presented. Also, a selection operator is presented that creates a mating pool by combining the parent and offspring populations and selecting the best N solutions (with respect to fitness and spread). Simulation results on difficult test problems show that NSGA-II is able, for most problems, to find a much better spread of solutions and better convergence near the true Pareto-optimal front compared to the Pareto-archived evolution strategy and the strength-Pareto evolutionary algorithm - two other elitist MOEAs that pay special attention to creating a diverse Pareto-optimal front. Moreover, we modify the definition of dominance in order to solve constrained multi-objective problems efficiently. Simulation results of the constrained NSGA-II on a number of test problems, including a five-objective, seven-constraint nonlinear problem, are compared with another constrained multi-objective optimizer, and the much better performance of NSGA-II is observed.
publications-4220 article 2005 Nilsson, Kenneth A. and Buchberger, Steven G. and Clark, Robert M. Simulating Exposures to Deliberate Intrusions Into Water Distribution Systems Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2005)131:3(228) A well-known network solver ~EPANET! and a novel water-use generator ~PRPsym! were linked in Monte Carlo computer experiments to simulate a deliberate biochemical assault on a municipal drinking-water distribution system. The attack was modeled as a steady 6-hour injection delivering 3,600 g of a soluble conservative contaminant to a single node on the main line in a small town. Migration of the contaminant plume was tracked for 55 hours throughout the pipe network, and the cumulative mass loading was computed at four target nodes strategically located on looping links and dead-end branches. This exercise was repeated for 1,000 independent trials to establish a baseline distribution of consumer dose exposures at the target nodes. A battery of simulation experiments was then performed to examine the sensitivity of the nodal load distributions to various system characteristics and water-use patterns. Results show that variability in the total mass load received at a node can be apportioned between the variability in the water-use volume and variability in the mean delivered concentration. Overall, however, the operation of the network storage tank had the greatest influence on the nodal mass loadings. This study demonstrates that Monte Carlo techniques are a useful tool for simulating the dynamic perfor- mance of a municipal drinking-water supply system, provided that a calibrated model of realistic network operations is available.