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–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-3691 article 2020 Kalbusch, Andreza and Kalbusch, Andreza and Henning, Elisa and Henning, Elisa and Brikalski, Miqueias Paulo and Brikalski, Miqueias Paulo and de Luca, Felipe Vieira and de Luca, Felipe Vieira and Konrath, AndrΓ©a Cristina and Konrath, Andrea Cristina Impact of coronavirus (COVID-19) spread-prevention actions on urban water consumption Resources Conservation and Recycling 10.1016/j.resconrec.2020.105098 ABSTRACT This article aims to assess the impact of coronavirus (COVID-19) spread-prevention actions on water consumption, based on a case study in Joinville, Southern Brazil. Residential water consumption data, obtained through telemetry in two periods (before and after a governmental action imposing quarantine and social isolation), were analyzed. Complementarily, the analyses were also applied to the commercial, industrial and public consumption categories. For the analysis, Wilcoxon and Kruskal-Wallis non-parametric tests were applied and Prais-Winsten regression models were adjusted. The results of the Wilcoxon test show that there are significant differences between the analyzed periods, indicating a water consumption drop in the commercial, industrial and public categories, and an increase in the residential category. The regression model results confirm the effect of the restrictive actions in reducing consumption in non-residential categories. The results also indicate an increase in water consumption, which was steeper in apartment buildings than in houses, whether isolated or grouped in condominiums. A weak association was found between the variation in water consumption and the spatial distribution of buildings. Understanding water consumption related aspects is important to gather essential information to ensure the urban water supply system is resilient in a pandemic situation.
publications-3692 article 2020 Carriço, Nelson and Carriço, Nelson and Ferreira, Bruno and Ferreira, Bruno and Ferreira, Bruno and Barreira, Raquel and Barreira, Raquel and Antunes, André and Antunes, André and Antunes, André and Grueau, Cédric and Grueau, Cédric and Mendes, Ana Claudia Duarte and Mendes, A. and Covas, Dídia and Covas, Dídia and Monteiro, Laura and Monteiro, L. and Monteiro, Laura and Santos, João Filipe and Santos, J and Santos, J. and Santos, João Filipe and Santos, J and Brito, Isabel Sofía and Brito, I S and Brito, I. S. and Brito, Isabel Sofia and Brito, I S Data integration for infrastructure asset management in small to medium-sized water utilities. Water Science and Technology 10.2166/wst.2020.377 Abstract Water utilities collect, store and manage vast data sets using many information systems (IS). For infrastructure asset management (IAM) planning those data need to be processed and transformed into information. However, information management efficiency often falls short of desired results. This happens particularly in municipalities where management is structured according to local government models. Along with the existing IS at the utilities' disposal, engineers and managers take their decisions based on information that is often incomplete, inaccurate or out-of-date. One of the main challenges faced by asset managers is integrating the several, often conflicting, sources of information available on the infrastructure, its condition and performance, and the various predictive analyses that can assist in prioritizing projects or interventions. This paper presents an overview of the IS used by Portuguese water utilities and discusses how data from different IS can be integrated in order to support IAM.
publications-3693 article 2021 Lüdtke, Deike U. and Lüdtke, Deike U. and Luetkemeier, Robert and Luetkemeier, Robert and Schneemann, Michael and Schneemann, Michael and Liehr, Stefan and Liehr, Stefan Increase in Daily Household Water Demand during the First Wave of the Covid-19 Pandemic in Germany Water 10.3390/w13030260 Precautionary measures and governmental regulations during the COVID-19 pandemic’s first wave have drastically altered daily activities and hence water consumption patterns Many people had to change their working routines, the organization of childcare and hygiene practices While first evidence appears on the impacts of COVID-19 on, e g , carbon emissions, energy demand and water treatment, even indicating an unexpected increase in water consumption during that period, no study has investigated the pandemic’s sole and in-depth implications for water supply so far This paper investigates hourly and daily water consumption volumes of a utility in northern Germany for the first wave of the pandemic We performed a linear mixed model to compare the 2020 daily water consumption volumes with previous years We eliminated the effects of climate using Bayesian statistic in order to carve out and estimate the original COVID-19 effect We also compared hourly water consumption of similar time periods and calculated the percentage difference between 2020 and the two previous years Our results reveal about 14 3\% (3 968 m3) higher residential water consumption per day with higher morning and evening demand peaks during the day We hypothesis that the reasons for the increasing water demand may be found in changed behavioral routines with an important question for water utilities, if and which of these new dynamics may persist after COVID-19 and hence pose a challenge for long-term infrastructure planning
publications-3694 article 2015 Berglund, Emily Zechman and Berglund, Emily Zechman Using Agent-Based Modeling for Water Resources Planning and Management Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000544 AbstractAgent-based systems have been developed for many scientific applications and simulation studies to model a group of actors and their interactions based on behavioral rules. Agent-based models and multiagent systems simulate the emergence of system-level properties based on the actions of adaptive agents that interact with other agents, react to environmental signals, and optimize decisions to achieve individual goals. In water resources planning and management, agent-based modeling has been applied to explore, simulate, and predict the performance of infrastructure design and policy decisions as they are influenced by human decision making, behaviors, and adaptations. The goal of this paper is to provide a comprehensive introduction to agent-based modeling for water resources researchers, students, and practitioners, and to explore water resources systems as complex adaptive systems that can be studied using agent-based modeling. Agent-based modeling is defined, and the characteristics of complex ...
publications-3695 article 2006 Mounce, S. R. and Mounce, Stephen R. and Machell, John and Machell, John Burst detection using hydraulic data from water distribution systems with artificial neural networks Urban Water Journal 10.1080/15730620600578538 This paper presents research into the application of artificial neural networks (ANNs) for analysis of data from sensors measuring hydraulic parameters (flow and pressure) of the water flow in treated water distribution systems. Two neural architectures (static and time delay) are applied for time series pattern classification from the perspective of detecting leakage. Results are presented using data from an experimental site in a distribution system of a UK water company in which bursts were simulated by hydrant flushing. Field trials have shown how ANNs can be used effectively for a leakage detection task. Both static and time delay ANNs learned patterns of leaks/bursts. The time delay neural network showed improved performance over the static network. It is concluded that the effectiveness of an ANN in discovering relationships within the data is dependent upon two key factors: availability of sufficient exemplars and data quality.
publications-3696 article 1997 Savic, Dragan and Walters, Godfrey A. and Walters, G. A. Genetic Algorithms for Least-Cost Design of Water Distribution Networks Journal of Water Resources Planning and Management 10.1061/(asce)0733-9496(1997)123:2(67) This paper describes the development of a computer model GANET that involves the application of an area of evolutionary computing, better known as genetic algorithms, to the problem of least-cost design of water distribution networks. Genetic algorithms represent an efficient search method for nonlinear optimization problems; this method is gaining acceptance among water resources managers/planners. These algorithms share the favorable attributes of Monte Carlo techniques over local optimization methods in that they do not require linearizing assumptions nor the calculation of partial derivatives, and they avoid numerical instabilities associated with matrix inversion. In addition, their sampling is global, rather than local, thus reducing the tendency to become entrapped in local minima and avoiding dependency on a starting point. Genetic algorithms are introduced in their original form followed by different improvements that were found to be necessary for their effective implementation in the optimization of water distribution networks. An example taken from the literature illustrates the approach used for the formulation of the problem. To illustrate the capability of GANET to efficiently identify good designs, three previously published problems have been solved. This led to the discovery of inconsistencies in predictions of network performance caused by different interpretations of the widely adopted Hazen-Williams pipe flow equation in the past studies. As well as being very efficient for network optimization, GANET is also easy to use, having almost the same input requirements as hydraulic simulation models. The only additional data requirements are a few genetic algorithm parameters that take values recommended in the literature. Two network examples, one of a new network design and one of parallel network expansion, illustrate the potential of GANET as a tool for water distribution network planning and management.
publications-3697 article 2010 Puust, Raido and Puust, Raido and Kapelan, Zoran and Kapelan, Zoran and Savić, Dragan and Savic, Dragan and Koppel, Tarmo and Koppel, T. A review of methods for leakage management in pipe networks Urban Water Journal 10.1080/15730621003610878 Leakage in water distribution systems is an important issue which is affecting water companies and their customers worldwide. It is therefore no surprise that it has attracted a lot of attention by both practitioners and researchers over the past years. Most of the leakage management related methods developed so far can be broadly classified as follows: (1) leakage assessment methods which are focusing on quantifying the amount of water lost; (2) leakage detection methods which are primarily concerned with the detection of leakage hotspots and (3) leakage control models which are focused on the effective control of current and future leakage levels. This paper provides a comprehensive review of the above methods with the objective to identify the current state-of-the-art in the field and to then make recommendations for future work. The review ends with the main conclusion that despite all the advancements made in the past, there is still a lot of scope and need for further work, especially in area of rea...
publications-3698 article 2013 Shafiee, M. Ehsan and Shafiee, M. Ehsan and Zechman, Emily M. and Zechman, Emily M. An agent-based modeling framework for sociotechnical simulation of water distribution contamination events Journal of Hydroinformatics 10.2166/hydro.2013.158 In the event that a contaminant is introduced to a water distribution network, a large population of consumers may risk exposure. Selecting mitigation actions to protect public health may be difficult, as contamination is a poorly predictable dynamic event. Consumers who become aware of an event may select protective actions to change their water demands from typical demand patterns, and new hydraulic conditions can arise that differ from conditions that would be predicted when demands are considered as exogenous inputs. Consequently, the movement of the contaminant plume in the pipe network may shift from its expected trajectory. A sociotechnical model is developed here to integrate agent-based models of consumers with an engineering water distribution system model and capture the dynamics between consumer behaviors and the water distribution system for predicting contaminant transport and public exposure. Consumers are simulated as agents with behaviors, including movement, water consumption, exposure, reduction in demands, and communication with other agents. As consumers decrease their water use, the location of the contaminant plume is updated and the amount of contaminant consumed by each agent is calculated. The framework is tested through simulating realistic contamination scenarios for a virtual city and water distribution system.
publications-3699 article 2016 Galdiero, Enzo and Galdiero, Enzo and Paola, Francesco De and Paola, Francesco De and Fontana, Nicola and Fontana, Nicola and Giugni, Maurizio and Giugni, Maurizio and Savić, Dragan and Savic, Dragan Decision support system for the optimal design of district metered areas Journal of Hydroinformatics 10.2166/hydro.2015.023 The establishment of district metered areas (DMAs) is widely recognized as one of the most effective techniques for the optimal management of water distribution networks (WDNs). However, its implementation in real cases is a very challenging task that requires decision aiding. In this work, a comprehensive methodology for the optimal design of DMAs is presented and discussed. The proposed approach consists of a two-objectives optimization problem subjected to a number of constraints related to the topology of the network, financial issues and the network hydraulics. A multi-objective evolutionary algorithm (MOEA) is combined with tools from graph theory for the solution of the problem. The validation of the model and the calibration of the parameters are performed through the application to a well-known example from the literature. Low cost as compared to the budget and a good saving in leakage are obtained.
publications-3700 article 2017 Shafiee, M. Ehsan and Shafiee, M. Ehsan and Berglund, Emily Zechman and Berglund, Emily Zechman Complex Adaptive Systems Framework to Simulate the Performance of Hydrant Flushing Rules and Broadcasts during a Water Distribution System Contamination Event Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000744 AbstractIn the event that a contaminant is introduced to a water distribution system, utility managers must respond quickly to protect public health. Mitigation strategies specify response actions,...