Data4Water
Thu., Feb. 15, 2018 – Berlin, Germany

Data4Water: Network of Excellence and Partnership in Smart Data for Water Management

The overall objective of the Horizon2020 project “Data4Water” is to support collaboration in the field of smart data driven e-services in water management, made available to the international community and specific stakeholders such as companies, citizens, and authorities. The consortium has a strong interdisciplinary character, with main focus on information technology. It contributes to a new, interdisciplinary network of excellence and partnership. For further information please join the Data4Water Network of Excellence and Partnership in Smart Data for Water Management.

About the speaker

Mariana Mocanu is Full Professor and Head of the Department of Computer Science and Engineering at the Faculty for Automatic Control and Computers at University Politehnica of Bucharest. She coordinates the H2020 Data4Water project.


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Water Research and Innovation for Sustainable Energy

This presentation introduces a spectrum of water-related research projects oriented at sustainable energy, which have been carried out at IHE Delft with partners from academia, industry and water management sectors. Water plays a key role in the renewable energy mix through hydropower production, but sustainable hydropower development, especially in countries from the Global South, remains a challenge. Past and ongoing research projects at IHE Delft will be presented, addressing hydropower assessment and development as part of integrated river basin management that requires balancing multiple river functions and users. These include projects regarding hydropower development with shared benefits in the Nile river basin, assessing hydropower potential in La Plata river basin, and minimizing environmental impact of hydropower development in Magdalena river basin of Colombia, Irrawaddy Basin of Myanmar and Zambezi Basin of Southern Africa. On the other hand, most water systems are energy consumers, with their pumping, water and wastewater treatment operations. Projects will be presented addressing optimal pumping operations of the water supply system in the city of Milan, Italy, as well as energy efficient water and waste-water treatment technologies that have been piloted in many countries, primarily in the Global South.

About the speakers

Ioana Popescu is an Associate Professor of Hydroinformatics at IHE Delft Institute for Water Education in Delft, The Netherlands. Her teaching and research focuses on computational methods, aspects of flood modeling and vulnerability related to floods, lake and reservoir modeling, and river systems. During her work, she has been involved in several European FP7 and H2020 research projects (IceWater, EnviroGRIDS, Lenvis, Floodsite) as well as other research projects related to development and application of modelling systems for water related areas. These research projects involved collaboration with partner institutions from all over the world.

Andreja Jonoski is an Associate Professor of Hydroinformatics at the IHE Delft Institute for Water Education in Delft, The Netherlands. He works in the field of hydroinformatics for more than two decades, primarily in the areas of modelling different water systems (groundwater aquifers, catchments, urban water supply systems) and their coupling with optimization algorithms for purposes of decision support. He has participated in several large European collaborative research projects related to the field of ICT and water management, involving partners from academia, water management and ICT industry. He has also participated in numerous hydroinformatics research, educational and capacity development projects with partners from Asia, Africa and Latin America.


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Digital Services for the Water-Energy Nexus

This talk introduces results from research and innovation projects aimed at designing, developing and deploying innovative digital services to support a more effective, efficient and sustainable water management in urban networks. Urban water supply service, from caption to transmission, storage, distribution and treatment, consumes a lot of energy: the amount of energy consumed by public water and wastewater utilities can achieve 30 % - 40 % of a municipality’s energy bill.

Data Analytics and Machine Learning approaches have been successfully applied to infer accurate water demand forecasting model, then used to predict water demand in the short term and optimize pump scheduling by storing water when energy price is lower. An accurate demand forecasting is crucial to avoid waste of energy while satisfying actual water demand.

Another relevant component of the energy costs for a water utility is related to (hidden) leakages and the need to supply more water than the actual demand to guarantee a satisfactory level of service (i.e. pressure over a given threshold within the network and satisfaction of the demand). The combination of hydraulic software simulation (typically EPANET 2.0) and Machine Learning can effectively support the detection and (pre-)localization of leaks: a limited set of pipes possibly affected by a leak is identified according to pressure and flow values measured from sensors spread into the network. The relation between these values and the possible location of the leak is inferred through Machine Learning by analysing a massive number of leakage scenarios simulated through hydraulic software simulation. Time to detect and localizing hidden leakages is therefore reduced, along with costs for physical investigation; on the other hand, the number of hidden leakages can be reduced leading to water and energy (and related costs) savings.

Asset management has a crucial role in the protection of the urban water critical infrastructures: not only for reducing the risk of possible leaks – and therefore simplifying leakage management – but also for enabling effective resilience management processes. Prioritizing rehabilitation actions, usually subject to budgetary constraints, is a core and strategic activity. In this case, approaches from network science, along with hydraulic software simulation, allowed for the development of a digital service to rank pipes according to their relevance with respect to overall connectivity, hydraulic stress and impact on the service level induced by a possible fault.

As these digital services address the “water-energy nexus”, they are more related to “water quantity”. It is anyway important to highlight that we are working on translating them on analogous “water quality” topics, such as: short-term forecasting of chemical/bacteriological concentrations, localization of pollution sources, optimal sensor location for increasing resilience of the network to propagation of pollutants or dangerous elements.

About the speakers

Francesco Archetti is Professor Emeritus of Computer Science and full Professor of Computer Science at the Department of Informatics, Systems and Communication (DISCo), University of Milano-Bicocca, and President of Consorzio Milano Ricerche. His research activities are focused on Data Analytics, Network Science, Probabilistic Modelling, Predictive Analytics, and Optimal Learning, with application to security, water management, logistics and cyber physical systems.

Antonio Candelieri is an Assistant Professor at the Department of Computer Science, Systems and Communication (DISCo), University of Milano-Bicocca. He received the Master Degree in Computer Engineering and the PhD in Operation Research at the University of Calabria. His research interest is focused on Machine Learning and Big/Stream/Network Data Analysis, Optimization, design and development of data-driven decision support services/systems. The main application domains addressed by his research are, among others, Smart Water Distribution Networks, Personalized and Sustainable Mobility, Health Care Intelligent Monitoring systems.


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The Transboundary Case Study DE-CZ-SK in the EU H2020 Project SIM4NEXUS

Within the HORIZON2020 project SIM4NEXUS (runtime June 2016 – May 2020), there are 10 regional case studies about “Nexus” policy impacts concerning the sectors climate, water, land, food, energy, and their interactions. The Potsdam Institute for Climate Impact Research (PIK) is involved in a transboundary case study covering East Germany, the Czech Republic, and Slovakia. This talk highlights the chosen research foci under the project goals and the approaches and data needs within this case study.

About the speaker

Tobias Conradt studied Geo-Ecology at the Technical University of Braunschweig and – after spending a few years in the media sector – started working at PIK in 2005. His main expertise is about eco-hydrological and agri-cultural yield modelling. In 2013, he got a PhD in Geo-Ecology and Hydrology from Potsdam University.


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Big Data Platforms and Space Technologies for Water Resource Management

The dynamics of water and the role of humans in the water cycle are not well understood largely because environmental and socio-economic analyses have traditionally been performed separately; and the methods, tools, and data needed for multidisciplinary work are not yet at the required level to satisfactory address problems posed in managing resources in aquatic environments. ICT can contribute to several areas of research such as better understanding of efficient use of water resources. Taking over and processing information from European systems for managing satellite data, products and services generated by Copernicus (satellite data via DHUS, Scihub, Land Monitoring Service, Emergency Management Service, Atmospheric Monitoring Service, Maritime Environment Monitoring Service, Climate Change Service, Security Service, DIAS) this presentation presents the main requirements for Big Data platforms to sustain Water Resource Management mechanisms. For example, WaM-DaM Schema can be integrated in new layers of Big Data Platforms (Spark, Flink, etc) and we propose the design of data interfaces that link integrated system models running within an HPC/Cloud environment to multiple data source.

About the speaker

Florin Pop is Associate Professor at the Department of Computer Science and Engineering at the University Politehnica of Bucharest. His general research interests are: Large-Scale Distributed Systems (design and performance), Grid Computing and Cloud Computing, Peer-to-Peer Systems, Big Data Management, Data Aggregation, Information Retrieval and Ranking Techniques, and Bio-Inspired Optimization Methods.


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Predicting Water Quality for Early Warning at Urban River Bathing Sites

Urban rivers are often subject of short term pollution events. Consequently, bathing in urban surface waters is still an exception in European cities. At the same time there are numerous initiatives trying to achieve, that urban surface waters can be used for recreational activities including bathing. In order to manage bathing waters properly the European bathing water directive (EC 2006/7) demands the elaboration of bathing water profiles in which sources of pollution have to be assessed. In this context, BMBF project FLUSSHYGIENE aims to gain a clearer understanding of the entry paths and dynamics of hygienic loads and thus to subsequently elaborate a sound basis for decision-making as well as the tools for managing multifunctional flowing waters in a way that the highest possible protection of public health can be guaranteed without compromising their economic functions. The presentation shows how an early warning at urban river bathing sites in Berlin river Havel can be developed and implemented based on readily available city data and a statistical modelling.

The project FLUSSHYGIENE is sponsored by the federal ministry of education and research under the sponsorship number 02WRS1278A, within the framework ReWaM (Regional Water Management).

About the speaker

Pascale Rouault graduated in 1994 from Ecole Nationale Polytechnique de Grenoble (INPG) as hydraulics and environment engineer. In Germany she worked at the Technische Universität Berlin (TUB) as senior scientist and received a PhD in hydraulics engineering in 2003. She has been working for many research projects and expertises in multidisciplinary projects in the hydraulics and water resources and management field dealing with both, theoretical and experimental solutions. She was then deputy manager of the Institute of Hydraulic Constructions (TUB) from 2004 to 2006. After one year at Berliner Wasserbetriebe working on RTC and numerical modelling she joined the Berlin Centre of Competence for Water (KWB) as project manager first, department manager since 2010, leading a team of eight researchers, and authorized representative since 2015. Her current works are on stormwater management, asset management of sewer systems, focusing mostly on the interface between urban drainage and water resource protection.


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Potentials of Digitalization in Complex Sewage Systems

Chair Fluidsystemdynamics focus on fluid flow machines and their systems. Main activities are in the combination of engineering and it to optimize the design and operation of fluidsystems, such as pumping systems, wind energy, washing machines, etc.. Some relevant projects within the sewage transport of complex networks will be demonstrated: intelligent pumping stations with diagnosis and active counter-reaction, communication between pumping stations to avoid CSO of connected pumping stations and concepts for urban rainwater and sewage management (KURAS). Additionally an outlook on possible projects within water and wastewater management supported with digitalization will be discussed.

About the speaker

Prof. Dr.-Ing. Paul Uwe Thamsen educated in mechanical engineering at Technical University Carolo-Wilhelmina in Braunschweig specialized on Fluid Flow Machines at well known Pfleiderer Institute. He published 1992 his doctor thesis about the “Operational Behaviour of Downhole Pumps with Inlet Distortions”. Since November 2003 he is Professor at Technical University Berlin, Chair of Fluiddynamics – Fluidmechanics in Machines and Systems. Research activities focus on complex fluidsystems like water and sewage systems, diagnosis,, cavitation, Particle Image Velocimetry (PIV), Laser Doppler Velocimetry (LDV), cooling systems for motors, fluid flow machines, centrifugal pumps and wind turbines.


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Research and Development for Urban Water Cycle Management

Berliner Wasserbetriebe provides 3.7M people with drinking water and wastewater services in the German capital region. This presentation will give an overview about the challenges of a sustainable management of the urban water cycle in Berlin. To take on these challenges, Berliner Wasserbetriebe engages in a number of R&D activities which will be briefly presented.

About the speaker

Alexander Sperlich is an engineer at the R&D department of Berliner Wasserbetriebe. Since joining Berliner Wasserbetriebe in 2010, he has been leading several research activities in the field of advanced nutrient removal, removal of trace organic chemicals and energy efficiency in advanced water and wastewater treatment. He holds a PhD (2010) and diploma (2004) in Environmental Engineering from Technische Universität Berlin.

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