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-4401 article 2006 Panebianco, Silke and Panebianco, Silke and Pahl‐Wostl, Claudia and Pahl-Wostl, Claudia Modelling socio-technical transformations in wastewater treatment—A methodological proposal Technovation 10.1016/j.technovation.2005.09.017
publications-4402 article 2006 Cozzolino, Luca and Mucherino, Carmela and Pianese, D. and Pirozzi, Francesco Positioning, within water distribution networks, of monitoring stations aiming at an early detection of intentional contamination Civil Engineering and Environmental Systems 10.1080/10286600600789359 A stochastic approach is proposed, aiming at the optimal allocation of increasing sets of monitoring stations for the early detection of the intentional contamination of water distribution networks. The approach is based on the use of the Monte Carlo technique for the generation of a number of time-varying hydraulic scenarios, each consisting of a succession of steady conditions related to different users’ water demands. Given a time-varying hydraulic scenario, and chosing an injection node, the spreading of the contaminant through the network is evaluated by means of a Lagrangian advection model, and the arrival times to all the potential monitoring stations are calculated. If these operations are accomplished for all the source nodes, and for each of the time-varying hydraulic scenarios, a statistical analysis allows for the allocation of the monitoring stations which maximise the number of upstream nodes characterised by arrival times less than a pre-assigned value (early warning time).
publications-4403 article 2007 Kapelan, Zoran and Kapelan, Zoran and Savić, Dragan and Savic, Dragan and Walters, Godfrey A. and Walters, Godfrey A. Calibration of Water Distribution Hydraulic Models Using a Bayesian-Type Procedure Journal of Hydraulic Engineering 10.1061/(asce)0733-9429(2007)133:8(927) Estimating model parameters is a difficult, yet critical step in the use of water distribution system models. Most of the optimization-based approaches developed so far concentrate primarily on efficient and effective ways of obtaining optimal calibration parameter values. At the same time, very little effort has been made to determine the uncertainties (i.e., errors) associated with those values (and related model predictions). So far, this has typically been done using the first-order second moment (FOSM) method. Even though reasonably computationally efficient, the FOSM approach relies on several restrictive assumptions and requires computationally demanding calculation of derivatives. To overcome these limitations, the recently developed shuffled complex evolution metropolis (SCEM-UA) global optimization algorithm is linked to the Epanet2 hydraulic model and used to solve a least-squares-type calibration problem. The methodology is tested and verified on the Anytown literature case study. The main advantage of the SCEM-UA algorithm over existing approaches is that both calibration parameter values and associated uncertainties can be determined in a single optimization model run. In addition, no model linearity or parameter normality assumptions have to be made nor any derivatives calculated. The main drawback of the SCEM-UA methodology is that it could, potentially, be computationally demanding, although this is not envisaged as a major problem with current computers.
publications-4404 article 2007 Balling, Robert C. and Balling, Robert C. and Gober, Patricia and Gober, Patricia Climate Variability and Residential Water Use in the City of Phoenix, Arizona Journal of Applied Meteorology and Climatology 10.1175/jam2518.1 Abstract In this investigation, how annual water use in the city of Phoenix, Arizona, was influenced by climatic variables between 1980 and 2004 is examined. Simple correlation coefficients between water use and annual mean temperature, total annual precipitation, and annual mean Palmer hydrological drought index values are +0.55, −0.69, −0.52, respectively, over the study period (annual water use increases with higher temperature, lower precipitation, and drought). Multivariate analyses using monthly climatic data indicate that annual water use is controlled most by the overall state of drought, autumn temperatures, and summer-monsoon precipitation. Model coefficients indicate that temperature, precipitation, and/or drought conditions certainly impact water use, although the magnitude of the annual water-use response to changes in climate was relatively low for an urban environment in which a sizable majority of residential water use is for outdoor purposes. People’s perception of the landscape’s water n...
publications-4405 article 2007 Leskovec, Jure and Leskovec, Jure and Krause, Andreas and Krause, Andreas and Guestrin, Carlos and Guestrin, Carlos and Faloutsos, Christos and Faloutsos, Christos and VanBriesen, Jeanne M. and VanBriesen, Jeanne M. and Glance, Natalie S. and Glance, Natalie S. and Glance, Natalie and Glance, Natalie Cost-effective outbreak detection in networks 10.1145/1281192.1281239 Given a water distribution network, where should we place sensors toquickly detect contaminants? Or, which blogs should we read to avoid missing important stories?. These seemingly different problems share common structure: Outbreak detection can be modeled as selecting nodes (sensor locations, blogs) in a network, in order to detect the spreading of a virus or information asquickly as possible. We present a general methodology for near optimal sensor placement in these and related problems. We demonstrate that many realistic outbreak detection objectives (e.g., detection likelihood, population affected) exhibit the property of "submodularity". We exploit submodularity to develop an efficient algorithm that scales to large problems, achieving near optimal placements, while being 700 times faster than a simple greedy algorithm. We also derive online bounds on the quality of the placements obtained by any algorithm. Our algorithms and bounds also handle cases where nodes (sensor locations, blogs) have different costs. We evaluate our approach on several large real-world problems,including a model of a water distribution network from the EPA, andreal blog data. The obtained sensor placements are provably near optimal, providing a constant fraction of the optimal solution. We show that the approach scales, achieving speedups and savings in storage of several orders of magnitude. We also show how the approach leads to deeper insights in both applications, answering multicriteria trade-off, cost-sensitivity and generalization questions.
publications-4406 article 2007 Pahl‐Wostl, Claudia and Pahl-Wostl, Claudia The implications of complexity for integrated resources management Environmental Modelling and Software 10.1016/j.envsoft.2005.12.024
publications-4407 article 2008 Giustolisi, Orazio and Giustolisi, Orazio and Kapelan, Zoran and Kapelan, Zoran and Savić, Dragan and Savic, Dragan Extended Period Simulation Analysis Considering Valve Shutdowns Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2008)134:6(527) Planned (e.g., regular maintenance) and unplanned (e.g. pipe burst) interruptions occur regularly in water distribution systems leading to their reduced performance. This paper presents an extended period simulation model capable of assessing system’s performance under these conditions. The extended period simulation model is based on the recently developed steady-state pressure driven hydraulic model and is capable of calculating pressures, flows, and hence actual water demands delivered under modified network topology conditions (caused by the use of isolation valves). The model is accompanied by several reliability indicators which can be used to assess system’s performance under interruptions. The above-mentioned methodology is demonstrated on a real-life case study in Italy. The role of isolation valve design and uncertainty in valve operability is analyzed and discussed. The case study results obtained demonstrate that the least cost design/rehabilitation of water distribution systems is likely to r...
publications-4408 article 2008 Berry, Jonathan W. and Berry, Jonathan W. and Berry, Jonathan W. and Carr, Robert D. and Hart, William E. and Hart, William Eugene and Leung, Vitus J. and Phillips, Cynthia Ann and Phillips, Cynthia Ann and Phillips, Cynthia A. and Watson, Jean-Paul and Watson, Jean-Paul and Watson, Jean-Paul On the Placement of Imperfect Sensors in Municipal Water Networks 10.1061/40941(247)129 We consider the problem of optimally placing water quality sensors in municipal water networks under the assumption that sensors may fail. We give a non-linear formulation of the problem, then a linearization of this formulation in the form of a mixed-integer program (MIP). We explore the scalability limits of this formulation, then use it as a bounding procedure for a local search heuristic that optimizes the same objective: minimizing the expected impact of a contamination event. This heuristic can find optimal or near-optimal solutions on networks with over ten thousand junctions. 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-4409 article 2008 Preis, Ami and Preis, Ami and Ostfeld, Avi and Ostfeld, Avi and Asce, Member Optimal Sensors Layout for Contamination Source Identification in Water Distribution Systems 10.1061/40941(247)127 This paper presents a methodology for optimally allocating sensors for solving the contamination source identification problem in water distribution systems (i.e., finding the optimal layout of a given number of sensors which maximizes the likelihood of contamination source identification). The model is comprised of two stages: at the first stage the water network is divided into influence zones based on the network configuration and hydraulics. Thereafter, all possible combinations of placing the given number of sensors at the different influence zones are tested for their ability to identify contamination sources for a set of pollution events (i.e., a set of contamination injections from different parts of the network, with different injection mass, duration, and starting times). A genetic algorithm framework is used for the contamination source identification. The GA is coupled with EPANET and applied to disclose pollution event characteristics (i.e., injection time, duration, and concentration) using the sensors measured data. The GA fitness function is of a least square type measuring the Euclidean distance between computed and measured concentrations at the sensor locations. The genetic algorithm decision variables (i.e., each genetic algorithm string) incorporate: (1) the contaminant injection node; (2) the injection mass rate; (3) the injection starting time; and (4) the injection duration. The global minimum for a least square minimization problem is known (i.e., zero) and thus when obtained, the contamination source is identified. At the second stage the combination that maximizes the contamination source identification likelihood is used as the search space at which only nodes from this combination can be selected as possible sensors locations. The result of the two search processes is the optimal sensors layout that maximizes the contamination source identification likelihood. The effectiveness of the method is demonstrated through two example applications.
publications-4410 article 2008 Isovitsch, Shannon L. and VanBriesen, Jeanne M. Sensor Placement and Optimization Criteria Dependencies in a Water Distribution System Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(2008)134:2(186) A water distribution system was analyzed for optimal sensor placement based on different intrusion scenarios and optimization criteria. The spatial distributions of the selected sensor networks were analyzed and compared using a geographic information system to determine spatial trends in sensor placement. Frequency, average nearest neighbor, and spatial autocorrelation analyses indicated the different intrusion scenarios and optimization criteria created networks with sensors in similar locations and with the same placement order, particularly for the first few sensors placed. Thus, sensor networks based on different optimization criteria and attack scenarios are expected to offer similar protection to the water distribution system. The relationship between sensor location and water demand was also analyzed using a geographic information system and a chi-square analysis. Sensor locations selected by minimizing the volume of consumed contaminated water or minimizing the population affected are likely to coincide with network nodes with a high reachable average demand. Alternatively, sensor locations selected by maximizing the detection likelihood are likely to coincide with network nodes with a low reachable average demand.