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-4181	article	2012	Tao, Tao and Tao, Tao and Tao, Tao and Tao, Tao and Lu, Ying-jun and Lu, Ying-jun and Fu, Xiang and Fu, Xiang and Xin, Kunlun and Xin, Kun-lun and Xin, Kunlun and Xin, Kun-lun	Identification of sources of pollution and contamination in water distribution networks based on pattern recognition	Journal of Zhejiang University Science	10.1631/jzus.a1100286	An intrusion of contaminants into the water distribution network (WDN) can occur through storage tanks (via animals, dust-carrying bacteria, and infiltration) and pipes. A sensor network could yield useful observations that help identify the location of the source, the strength, the time of occurrence, and the duration of contamination. This paper proposes a methodology for identifying the contamination sources in a water distribution system, which identifies the key characteristics of contamination, such as location, starting time, and injection rates at different time intervals. Based on simplified hypotheses and associated with a high computational efficiency, the methodology is designed to be a simple and easy-to-use tool for water companies to ensure rapid identification of the contamination sources, The proposed methodology identifies the characteristics of pollution sources by matching the dynamic patterns of the simulated and measured concentrations. The application of this methodology to a literature network and a real WDN are illustrated with the aid of an example. The results showed that if contaminants are transported from the sources to the sensors at intervals, then this method can identify the most possible ones from candidate pollution sources. However, if the contamination data is minimal, a greater number of redundant contamination source nodes will be present. Consequently, more data from different sensors obtained through network monitoring are required to effectively use this method for locating multi-sources of contamination in the WDN.
publications-4182	article	2007	Rico-Ramirez, Vicente and Frausto-HernΓ΅ndez, Sergio and Diwekar, Urmila M. and HernΓ΅ndez-Castro, Salvador	Water networks security: A two-stage mixed-integer stochastic program for sensor placement under uncertainty	Computers & Chemical Engineering	10.1016/j.compchemeng.2006.08.012
publications-4183	article	2011	Liu, Li and Liu, Li and Sankarasubramanian, A. and Sankarasubramanian, A. and Ranjithan, S. Ranji and Ranjithan, S. Ranji	Logistic regression analysis to estimate contaminant sources in water distribution systems	Journal of Hydroinformatics	10.2166/hydro.2010.106	Accidental or intentional contamination in a water distribution system (WDS) has recently attracted attention due to the potential hazard to public health and the complexity of the contaminant characteristics. The accurate and rapid characterization of contaminant sources is necessary to successfully mitigate the threat in the event of contamination. The uncertainty surrounding the contaminants, sensor measurements and water consumption underscores the importance of a probabilistic description of possible contaminant sources. This paper proposes a rapid estimation methodology based on logistic regression (LR) analysis to estimate the likelihood of any given node as a potential source of contamination. Not only does this algorithm yield location-specific probability information, but it can also serve as a prescreening step for simulationβ€optimization methods by reducing the decision space and thus alleviating the computational burden. The applications of this approach to two example water networks show that it can efficiently rule out numerous nodes that do not yield contaminant concentrations to match the observations. This elimination process narrows down the search space of the potential contamination locations. The results also indicate that the proposed method efficiently yields a good estimation even when some noise is incorporated into the measurements and demand values at the consumption nodes.
publications-4184	article	2008	Baranowski, T. M. and Baranowski, T. M. and LeBoeuf, Eugene J. and LeBoeuf, Eugene J.	Consequence Management Utilizing Optimization	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2008)134:4(386)	Following the identification of a contaminant in a water distribution network, a variety of response actions must be examined in order to implement the most beneficial consequence management strategy. Optimization techniques can be employed to determine the cost/benefit of reducing impacts to the network from contamination by isolating and/or flushing the system. In this current effort, we employ a genetic algorithm to minimize contaminant concentrations in a network while minimizing the cost of demand alteration. Application of this technique to two relatively simple networks demonstrates the usefulness of this optimization method as a consequence management strategy to reduce contaminant concentration. For the EPANET Example 1 network, the optimal response solution included closure of two pipes and alteration of the demand at one node, reducing the total network concentration by 95\%, with a 73\% increase in total network demand. For the Anytown network, the optimal response solution included altering the demand at four nodes, which resulted in a 12\% increase in total network demand, while closing four pipes reduced the total network concentration by 54\%.
publications-4185	article	2011	Davis, Michael J. and Janke, Robert	Patterns in Potential Impacts Associated with Contamination Events in Water Distribution Systems	Journal of Water Resources Planning and Management	10.1061/(asce)wr.1943-5452.0000084	Properly designing contamination warning systems requires an understanding of potential public health impacts for a range of contaminated water systems and a wide range of contaminants. To address this need, we determined potential impacts for 12 actual systems serving populations ranging from βΌ 104 to over 106 persons by simulating contamination events for the systems. We found several consistent patterns in the estimated impacts (defined as the size of the population receiving an ingestion dose above a given level). Significant impacts, those similar to worst-case impacts, result from injections of contaminants at only a minority of nodes. For contaminants with high thresholds for adverse effects, significant exposures are concentrated near the injection location, and impacts are not sensitive to population served. However, for contaminants with low thresholds, significant exposures are present over a significant fraction of the system, and impacts are sensitive to population. When exposures are concent...
publications-4186	article	2010	Alfonso, Leonardo and Jonoski, Andreja and Solomatine, Dimitri	Multiobjective Optimization of Operational Responses for Contaminant Flushing in Water Distribution Networks	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2010)136:1(48)	Contamination emergency in water distribution systems is a complex situation where optimal operation becomes important for public health. In case of emergency corrective operational actions for flushing the pollutant out of the network are needed, which have to be fast and accurate. Under such a stressful situation, trial-and-error simulation experiments with the hydrodynamic and water quality models cannot be applied since significant number of model evaluations may be required to identify the optimal solution. This paper presents a methodology for finding sets of operational interventions in a supply network for flushing a contaminant by minimizing the impact on the population. The situation is treated as both single- and multiobjective optimization problem, which is solved by using evolutionary optimization approaches, in combination with the EPANET solver engine. The methodology is tested on a simple imaginary network configuration, as well as on a real case study for the city of Villavicencio in Colombia. The results prove the usefulness of the approach for advising the operators and decision makers.
publications-4187	article	2006	Snyder, Lawrence V.	Facility Location Under Uncertainty: A Review	Iie Transactions	10.1080/07408170500216480	Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made the development of models for facility location under uncertainty a high priority for researchers in both the logistics and stochastic/robust optimization communities. Indeed, a large number of the approaches that have been proposed for optimization under uncertainty have been applied to facility location problems. This paper reviews the literature on stochastic and robust facility location models. Our intent is to illustrate both the rich variety of approaches for optimization under uncertainty that have appeared in the literature and their application to facility location problems. In a few instances for which examples in facility location are not available, we provide examples from the more general logistics l...
publications-4188	article	2011	Houseβ€Peters, Lily and House-Peters, Lily and Chang, Heejun and Chang, Heejun	Urban Water Demand Modeling: Review of Concepts, Methods, and Organizing Principles	Water Resources Research	10.1029/2010wr009624	[1]In this paper, we use a theoretical framework of coupled human and natural systems to review the methodological advances in urban water demand modeling over the past 3 decades. The goal of this review is to quantify the capacity of increasingly complex modeling techniques to account for complex human and natural processes, uncertainty, and resilience across spatial and temporal scales. This review begins with coupled human and natural systems theory and situates urban water demand within this framework. The second section reviews urban water demand literature and summarizes methodological advances in relation to four central themes: (1) interactions within and across multiple spatial and temporal scales, (2) acknowledgment and quantification of uncertainty, (3) identification of thresholds, nonlinear system response, and the consequences for resilience, and (4) the transition from simple statistical modeling to fully integrated dynamic modeling. This review will show that increasingly effective models have resulted from technological advances in spatial science and innovations in statistical methods. These models provide unbiased, accurate estimates of the determinants of urban water demand at increasingly fine spatial and temporal resolution. Dynamic models capable of incorporating alternative future scenarios and local stochastic analysis are leading a trend away from deterministic prediction.
publications-4189	article	2002	Clark, Robert M. and Clark, Robert M. and Sivaganesan, Mano and Sivaganesan, Mano	Predicting Chlorine Residuals in Drinking Water: Second Order Model	Journal of Water Resources Planning and Management	10.1061/(asce)0733-9496(2002)128:2(152)	A major objective of drinking water treatment is to provide water that is both microbiologically and chemically safe for human consumption. Drinking water chlorination, therefore, poses a dilemma. Chemical disinfection reduces the risk of infectious disease, but the interaction between chemical disinfectants and precursor materials in source water may result in potentially harmful by-products. Chlorine consumption results in the formation of by-products, and the loss of chlorine residual reduces protection against potentially pathogenic bacteria. Therefore, much effort has been invested in characterizing the loss of chlorine residuals in raw and treated water. This paper presents a mathematical model based on the use of two second-order terms for predicting this loss or decay.
publications-4190	article	2006	Wang, Zhong and Polycarpou, Marios M. and Uber, James G. and Shang, Feng	Adaptive control of water quality in water distribution networks	IEEE Transactions on Control Systems and Technology	10.1109/tcst.2005.859633	Based on investigating the spatially distributed input-output relationship of disinfectant residual in water distribution networks, this brief paper formulates the water quality control problem of multiple nodes in a decomposed adaptive control framework, with special consideration on the periodic variation of parameter uncertainty due to varying consumer demands. The water distribution network is decomposed to subnetworks based on the effect of the decay of chlorine concentration. The periodic parametric uncertainty is represented by a Fourier series with on-line parameter estimation of the unknown coefficients. A simulation example is provided to illustrate the performance of the algorithm in a real water distribution network.