Dionisios Nikolopoulos

Civil Engineer, MSc., PhD candidate

Participation in research projects

Participation as Researcher

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system

Published work

Publications in scientific journals

  1. D. Nikolopoulos, A. Ostfeld, E. Salomons, and C. Makropoulos, Resilience assessment of water quality sensor designs under cyber-physical attacks, Water, 13 (5), 647, doi:10.3390/w13050647, 2021.
  2. A. Liakopoulou, C. Makropoulos, D. Nikolopoulos, K. Monokrousou, and G. Karakatsanis, An urban water simulation model for the design, testing and economic viability assessment of distributed water management systems for a circular economy, Environmental Sciences Proceedings, 21 (1), 14, doi:10.3390/environsciproc2020002014, 2020.
  3. G. Moraitis, D. Nikolopoulos, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, Quantifying failure for critical water Infrastructures under cyber-physical threats, Journal of Environmental Engineering, 146 (9), doi:10.1061/(ASCE)EE.1943-7870.0001765, 2020.
  4. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, Cyber-physical stress-testing platform for water distribution networks, Journal of Environmental Engineering, 146 (7), 04020061, doi:10.1061/(ASCE)EE.1943-7870.0001722, 2020.
  5. D. Bouziotas, D. van Duuren, H. J. van Alphen, J. Frijns, D. Nikolopoulos, and C. Makropoulos, Towards circular water neighborhoods: Simulation-based decision support for integrated decentralized urban water systems, Water, 11 (6), 1227, doi:10.3390/w11061227, 2019.
  6. D. Nikolopoulos, H. J. van Alphen, D. Vries, L. Palmen, S. Koop, P. van Thienen, G. Medema, and C. Makropoulos, Tackling the “new normal”: A resilience assessment method applied to real-world urban water systems, Water, 11 (2), 330, doi:10.3390/w11020330, 2019.
  7. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A framework for dry period low flow forecasting in Mediterranean streams, Water Resources Management, 32 (15), 4911–1432, doi:10.1007/s11269-018-2060-z, 2018.
  8. C. Makropoulos, D. Nikolopoulos, L. Palmen, S. Kools, A. Segrave, D. Vries, S. Koop, H. J. van Alphen, E. Vonk, P. van Thienen, E. Rozos, and G. Medema, A resilience assessment method for urban water systems, Urban Water Journal, 15 (4), 316–328, doi:10.1080/1573062X.2018.1457166, 2018.
  9. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, European Water, 57, 337–343, 2017.

Book chapters and fully evaluated conference publications

  1. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, RISKNOUGHT: A cyber-physical stress-testing platform for water distribution networks, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.
  2. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Development of a distributed hydrological software application employing novel velocity-based techniques, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.
  3. D. Nikolopoulos, C. Makropoulos, D. Kalogeras, K. Monokrousou, and I. Tsoukalas, Developing a stress-testing platform for cyber-physical water infrastructure, 2018 International Workshop on Cyber-Physical Systems for Smart Water Networks (CySWater), New Jersey, 9–11, doi:10.1109/CySWater.2018.00009, 2018.
  4. D. Nikolopoulos, K. Risva, and C. Makropoulos, A cellular automata urban growth model for water resources strategic planning, 13th International Conference on Hydroinformatics (HIC 2018), Palermo, Italy, 3, 1557–1567, doi:10.29007/w43g, 2018.
  5. P. Dimas, D. Bouziotas, D. Nikolopoulos, A. Efstratiadis, and D. Koutsoyiannis, Framework for optimal management of hydroelectric reservoirs through pumped storage: Investigation of Acheloos-Thessaly and Aliakmon hydrosystems, Proceedings of 3rd Hellenic Conference on Dams and Reservoirs, Zappeion, Hellenic Commission on Large Dams, Athens, 2017.
  6. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  7. C. Makropoulos, V. Tsoukala, K. Belibassakis, A. Lykou, M. Chondros, P. Gourgoura, and D. Nikolopoulos, Managing flood risk in coastal cities through an integrated modelling framework supporting stakeholders’ involvement: the case of Rethymno, Crete, Proceedings of the 36th IAHR World Congress, The Hague, The Netherlands, 2015.

Conference publications and presentations with evaluation of abstract

  1. D. Nikolopoulos, P. Kossieris, and C. Makropoulos, Stochastic stress-testing approach for assessing resilience of urban water systems from source to tap, EGU General Assembly 2021, online, EGU21-13284, doi:10.5194/egusphere-egu21-13284, European Geosciences Union, 2021.
  2. G. Moraitis, D. Nikolopoulos, I. Koutiva, I. Tsoukalas, G. Karavokiros, and C. Makropoulos, The PROCRUSTES testbed: tackling cyber-physical risk for water systems, EGU General Assembly 2021, online, EGU21-14903, doi:10.5194/egusphere-egu21-14903, European Geosciences Union, 2021.
  3. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, RISKNOUGHT: Stress-testing platform for cyber-physical water distribution networks, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-19647, doi:10.5194/egusphere-egu2020-19647, 2020.
  4. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Distributed hydrological modelling using spatiotemporally varying velocities, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-13402, doi:10.5194/egusphere-egu2020-13402, 2020.
  5. G. Karavokiros, D. Nikolopoulos, S. Manouri, A. Efstratiadis, C. Makropoulos, N. Mamassis, and D. Koutsoyiannis, Hydronomeas 2020: Open-source decision support system for water resources management, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-20022, doi:10.5194/egusphere-egu2020-20022, 2020.
  6. L. M. Tsiami, E. Zacharopoulou, D. Nikolopoulos, I. Tsoukalas, N. Mamassis, A. Kallioras, and A. Efstratiadis, The use of Artificial Neural Networks with different sources of spatiotemporal information for flash flood predictions, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-7315, European Geosciences Union, 2019.
  7. D. Nikolopoulos, A. Efstratiadis, G. Karavokiros, N. Mamassis, and C. Makropoulos, Stochastic simulation-optimization framework for energy cost assessment across the water supply system of Athens, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-12290, European Geosciences Union, 2018.
  8. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, Low-flow analysis in Mediterranean basins, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18880, European Geosciences Union, 2018.
  9. E. Rozos, D. Nikolopoulos, A. Efstratiadis, A. Koukouvinos, and C. Makropoulos, Flow based vs. demand based energy-water modelling, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-6528, European Geosciences Union, 2015.
  10. A. Koukouvinos, D. Nikolopoulos, A. Efstratiadis, A. Tegos, E. Rozos, S.M. Papalexiou, P. Dimitriadis, Y. Markonis, P. Kossieris, H. Tyralis, G. Karakatsanis, K. Tzouka, A. Christofides, G. Karavokiros, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Integrated water and renewable energy management: the Acheloos-Peneios region case study, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4912, doi:10.13140/RG.2.2.17726.69440, European Geosciences Union, 2015.
  11. E. Anagnostopoulou, A. Galani, P. Dimas, A. Karanasios, T. Mastrotheodoros, E. Michailidi, D. Nikolopoulos, S. Pontikos, F. Sourla, A. Chazapi, S.M. Papalexiou, and D. Koutsoyiannis, Record breaking properties for typical autocorrelation structures, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-4520, doi:10.13140/RG.2.2.20420.22400, European Geosciences Union, 2013.

Presentations and publications in workshops

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 5th Hellenic Conference of Surveying Enginners, Athens, 2017.

Academic works

  1. D. Nikolopoulos, Development of geospatial urban growth models supporting urban water strategic planning: the case study of Rethymnon, Crete, MSc thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, November 2017.
  2. D. Nikolopoulos, Model development for conjunctive management of Acheloos and Peneios river basins, Diploma thesis, 214 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2015.

Research reports

  1. A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, N. Mamassis, D. Nikolopoulos, I. Tsoukalas, and P. Kossieris, First year synopsis, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 55 pages, December 2020.
  2. A. Efstratiadis, S. Manouri, D. Nikolopoulos, and I. Tsoukalas, Investigation of the water supply system's management for period March-September 2020, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 31 pages, March 2020.
  3. A. Koukouvinos, A. Efstratiadis, D. Nikolopoulos, H. Tyralis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Case study in the Acheloos-Thessaly system, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 98 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2015.

Details on research projects

Participation as Researcher

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system

    Duration: October 2008–November 2011

    Budget: €72 000

    Project director: N. Mamassis

    Principal investigator: D. Koutsoyiannis

    This research project includes the maintenance, upgrading and extension of the Decision Support System that developed by NTUA for EYDAP in the framework of the research project “Updating of the supervision and management of the water resources’ system for the water supply of the Athens’ metropolitan area”. The project is consisted of the following parts: (a) Upgrading of the Data Base, (b)Upgrading and extension of hydrometeorological network, (c) upgrading of the hydrometeorological data process software, (d) upgrading and extension of the Hydronomeas software, (e) hydrological data analysis and (f) support to the preparation of the annual master plans

Published work in detail

Publications in scientific journals

  1. D. Nikolopoulos, A. Ostfeld, E. Salomons, and C. Makropoulos, Resilience assessment of water quality sensor designs under cyber-physical attacks, Water, 13 (5), 647, doi:10.3390/w13050647, 2021.

    Water distribution networks (WDNs) are critical infrastructure for the welfare of society. Due to their spatial extent and difficulties in deployment of security measures, they are vulnerable to threat scenarios that include the rising concern of cyber-physical attacks. To protect WDNs against different kinds of water contamination, it is customary to deploy water quality (WQ) monitoring sensors. Cyber-attacks on the monitoring system that employs WQ sensors combined with deliberate contamination events via backflow attacks can lead to severe disruptions to water delivery or even potentially fatal consequences for consumers. As such, the water sector is in immediate need of tools and methodologies that can support cyber-physical quality attack simulation and vulnerability assessment of the WQ monitoring system under such attacks. In this study we demonstrate a novel methodology to assess the resilience of placement schemes generated with the Threat Ensemble Vulnerability Assessment and Sensor Placement Optimization Tool (TEVA-SPOT) and evaluated under cyber-physical attacks simulated using the stress-testing platform RISKNOUGHT, using multidimensional metrics and resilience profile graphs. The results of this study show that some sensor designs are inherently more resilient than others, and this trait can be exploited in risk management practices.

    Full text: http://www.itia.ntua.gr/en/getfile/2093/1/documents/water-13-00647.pdf (4403 KB)

    See also: https://www.mdpi.com/2073-4441/13/5/647

  1. A. Liakopoulou, C. Makropoulos, D. Nikolopoulos, K. Monokrousou, and G. Karakatsanis, An urban water simulation model for the design, testing and economic viability assessment of distributed water management systems for a circular economy, Environmental Sciences Proceedings, 21 (1), 14, doi:10.3390/environsciproc2020002014, 2020.

    The concept of Circular Economy, although not entirely new, has in recent years gained traction due to growing concern with regards to the Earth’s natural reserves. In this context, Sewer Mining, a wastewater management method based on extracting wastewater from local sewers for reuse applications, presents an interesting option that lies in the interplay between reuse at a household scale and centralized reuse at a wastewater treatment plant. As part of the EU-funded program NextGenWater, a new unit is being prepared for operation in Athens’s Plant Nursery, in Goudi. This paper examines the water flow within the proposed installation, using the Urban Water Optioneering Tool (UWOT). Further research is focused on the economic viability of Sewer Mining and the proposed investment. The results produced are promising regarding Sewer Mining’s capabilities and benefits, as well as its future prospects, in the hopes that this technology can provide an attractive alternative to conventional water sources within the urban water cycle.

    Full text: http://www.itia.ntua.gr/en/getfile/2060/1/documents/environsciproc-02-00014.pdf (992 KB)

    See also: https://www.mdpi.com/2673-4931/2/1/14

  1. G. Moraitis, D. Nikolopoulos, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, Quantifying failure for critical water Infrastructures under cyber-physical threats, Journal of Environmental Engineering, 146 (9), doi:10.1061/(ASCE)EE.1943-7870.0001765, 2020.

    This paper presents a failure quantification methodology to assess the impact of cyber-physical attacks (CPAs) on critical water infrastructures, such as water distribution networks, by mapping simulation-derived data onto metrics. The approach sets out a three-step profiling architecture to interpret the consequences of failures resulting from CPAs against several dimensions of integrity, adjusted through user-defined service levels. Failure is examined in terms of its magnitude, propagation, severity, and crest factor, while rapidity is used to infer available time slots to react. The methodology is operationalized through a dedicated tool designed to assist water-sector critical infrastructures gauge and assess CPAs. The approach is demonstrated on a benchmark water distribution system, and results and insights from the metrics are presented and discussed. It is argued that the approach and the tool that operationalizes its application can be useful to water companies that need to assess and compare cyber-physical threats and prioritize mitigation actions based on quantitative metrics.

    Full text: http://www.itia.ntua.gr/en/getfile/2059/1/documents/ASCEEE.1943-7870.0001765.pdf (1889 KB)

  1. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, Cyber-physical stress-testing platform for water distribution networks, Journal of Environmental Engineering, 146 (7), 04020061, doi:10.1061/(ASCE)EE.1943-7870.0001722, 2020.

    The water sector is facing emerging challenges, as cyber-physical threats target Supervisory Control and Data Acquisition (SCADA) systems of water utilities. A cyber-physical stress-testing platform is presented in this work, named RISKNOUGHT, which is able to model water distribution networks as cyber-physical systems, simulating the information flow of the cyber layer and the feedback interactions with the physical processes under control. RISKNOUGHT utilizes an EPANET-based solver for the physical process and a customizable network model for the SCADA system, capable of implementing complex control logic schemes within a simulation. The platform enables the development of composite cyber-physical attacks on various elements of the SCADA, including sensors, actuators, and PLCs, assessing the impact they have on the hydraulic response of the distribution network and the level of service. The platform is tested on a proof-of-concept benchmark network with promising results that demonstrate that the platform can form an innovative cyber-physical tool to support strategic planning and risk management.

    Full text: http://www.itia.ntua.gr/en/getfile/2046/1/documents/ASCEEE.1943-7870.0001722.pdf (7383 KB)

  1. D. Bouziotas, D. van Duuren, H. J. van Alphen, J. Frijns, D. Nikolopoulos, and C. Makropoulos, Towards circular water neighborhoods: Simulation-based decision support for integrated decentralized urban water systems, Water, 11 (6), 1227, doi:10.3390/w11061227, 2019.

    Centralized urban water management currently faces multiple challenges, both at the supply side and the demand side. These challenges underpin the need to progress to the decentralization of urban water, where multiple distributed technologies (water-aware appliances, rainwater harvesting, greywater recycling, sustainable urban drainage) are applied in an integrated fashion and as a supplement to centralized systems to design more resilient neighborhoods. However, the methods and tools to assess the performance of these distributed solutions and provide management support for integrated projects are still few and mostly untested in real, combined cases. This study presents a simulation-based framework for the quantitative performance assessment of decentralized systems at a neighborhood scale, where different technologies can be linked together to provide beneficial effects across multiple urban water cycle domains. This framework links an urban water cycle model, which provides a scenario-based simulation testbed for the response of the whole system, with key performance indicators that evaluate the performance of integrated decentralized solutions at a neighborhood scale. The demonstrated framework is applied to provide an ex ante evaluation of SUPERLOCAL, a newly developed area in Limburg, the Netherlands, designed as a circular, water-wise neighborhood where multiple decentralized technologies are combined.

    Full text: http://www.itia.ntua.gr/en/getfile/2030/1/documents/water-11-01227-v2.pdf (7693 KB)

    See also: https://www.mdpi.com/2073-4441/11/6/1227

  1. D. Nikolopoulos, H. J. van Alphen, D. Vries, L. Palmen, S. Koop, P. van Thienen, G. Medema, and C. Makropoulos, Tackling the “new normal”: A resilience assessment method applied to real-world urban water systems, Water, 11 (2), 330, doi:10.3390/w11020330, 2019.

    The water sector is, currently and for the foreseeable future, challenged by rising levels of uncertainty in demand and availability of water, in a context of aging infrastructure and limited investment. In order to support strategic planning, water companies need a way to assess how their system behaves when faced with a range of changing conditions (climatic trends, asset deterioration, behavioral patterns, etc.) as well as accidents/incidents and/or extreme events (wildcards). In this study, a resilience assessment methodology was demonstrated, with ‘stress tests’ alternative water system configurations (including systems designed with decentralized or distributed philosophies) under a range of scenarios and extreme events. A ‘resilience profile graph’ was developed to quantify the performance of each configuration. The methodology was applied to the real-world urban water system of Oasen, which supplies the eastern part of the Province of South Holland, where the current system configuration and two potential future configurations were tested (one decentralized and one distributed). We show how the concept of resilience, operationalized through this methodology, can assist long term decision making and support strategic infrastructure planning.

    Full text: http://www.itia.ntua.gr/en/getfile/1964/1/documents/water-11-00330.pdf (4563 KB)

    See also: https://www.mdpi.com/2073-4441/11/2/330

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A framework for dry period low flow forecasting in Mediterranean streams, Water Resources Management, 32 (15), 4911–1432, doi:10.1007/s11269-018-2060-z, 2018.

    The objective of this article is to provide a simple and effective tool for low flow forecasting up to six months ahead, with minimal data requirements, i.e. flow observations retrieved at the end of wet period (first half of April, for the Mediterranean region). The core of the methodological framework is the exponential decay function, while the typical split-sample approach for model calibration, which is known to suffer from the dependence on the selection of the calibration data set, is enhanced by introducing the so-called Randomly Selected Multiple Subsets (RSMS) calibration procedure. Moreover, we introduce and employ a modified efficiency metric, since in this modelling context the classical Nash-Sutcliffe efficiency yields unrealistically high performance. The proposed framework is evaluated at 25 Mediterranean rivers of different scales and flow dynamics, including streams with intermittent regime. Initially, signal processing and data smoothing techniques are applied to the raw hydrograph, in order to cut-off high flows that are due to flood events occurring in dry periods, and allow for keeping the decaying form of the baseflow component. We then employ the linear reservoir model to extract the annually varying recession coefficient, and, then, attempt to explain its median value (over a number of years) on the basis of typical hydrological indices and the catchment area. Next, we run the model in forecasting mode, by considering that the recession coefficient of each dry period ahead is a linear function of the observed flow at the end of the wet period. In most of the examined catchments, the model exhibits very satisfactory predictive capacity and is also robust, as indicated by the limited variability of the optimized model parameters across randomly selected calibration sets.

    Full text: http://www.itia.ntua.gr/en/getfile/1861/2/documents/Risva2018_Article_AFrameworkForDryPeriodLowFlowF.pdf (2268 KB)

    Other works that reference this work (this list might be obsolete):

    1. Tsihrintzis, V. A., and H. Vangelis, Water resources and environment, Water Resources Management, 32(15), 4813-4817, doi:10.1007/s11269-018-2164-5, 2018.
    2. Kapetas, L., N. Kazakis, K. Voudouris, and D. McNicholl, Water allocation and governance in multi-stakeholder environments: Insight from Axios Delta, Greece, Science of The Total Environment, 695, 133831, doi:10.1016/j.scitotenv.2019.133831, 2019.
    3. Azarnivand, A., M. Camporese, S. Alaghmand, and E. Dal, Simulated response of an intermittent stream to rainfall frequency patterns, Hydrological Processes, 34(3), 615-632, doi:10.1002/hyp.13610, 2020.
    4. Lee, D., H. Kim, I. Jung, and J. Yoon, Monthly reservoir inflow forecasting for dry period using teleconnection indices: A statistical ensemble approach, Applied Sciences, 10(10), 3470, doi:10.3390/app10103470, 2020.
    5. Nicolle, P., F. Besson, O. Delaigue, P. Etchevers, D. François, M. Le Lay, C. Perrin, F. Rousset, D. Thiéry, F. Tilmant, C. Magand, T. Leurent, and É. Jacob, PREMHYCE: An operational tool for low-flow forecasting, Proceedings of the International Association of Hydrological Sciences, 383, 381-389, doi:10.5194/piahs-383-381-2020, 2020.
    6. Tilmant, F., P. Nicolle, F. Bourgin, F. Besson, O. Delaigue, P. Etchevers, D. François, M. Le Lay, C. Perrin, F. Rousset, D. Thiéry, C. Magand, T. Leurent, et É. Jacob, PREMHYCE : un outil opérationnel pour la prévision des étiages, La Houille Blanche, 5, 37-44, doi:10.1051/lhb/2020043, 2020.

  1. C. Makropoulos, D. Nikolopoulos, L. Palmen, S. Kools, A. Segrave, D. Vries, S. Koop, H. J. van Alphen, E. Vonk, P. van Thienen, E. Rozos, and G. Medema, A resilience assessment method for urban water systems, Urban Water Journal, 15 (4), 316–328, doi:10.1080/1573062X.2018.1457166, 2018.

    Infrastructure planning for Urban Water Systems (UWSs) is challenged by, inter alia, increasing uncertainty in both demand and availability of water and aging infrastructure, and this is already impacting the climate-proofing of cities. In this context, the idea of resilience has been gradually embraced by the water sector, but the term itself is not yet universally defined, nor operationalised. Here, we propose a methodology to assess the resilience of a UWS, defining it as the degree to which the UWS continues to perform under increasing stress. A resilience assessment method is then proposed as a ‘stress-test’ of UWS configurations, under increasingly more stressful scenarios. We then demonstrate a toolbox assembled for the proposed analysis using, as a proof of concept, a semi-synthetic case study. Results are promising, suggesting that the approach could assist in the uptake and evolution of resilience thinking in strategic water infrastructure decision making, leading to water-wiser cities.

    Remarks:

    UWOT Demo: The WaterCity is available at: http://doi.org/10.5281/zenodo.1194795

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, European Water, 57, 337–343, 2017.

    Low flows commonly occur in rivers during dry seasons within each year. They often concur with increased water demand which creates numerous water resources management problems. This paper seeks for simple yet efficient tools for low-flow forecasting, which are easy to implement, based on the adoption of an exponential decay model for the flow recession curve. A statistical attribute of flows preceding the start of the dry period is used as the starting flow. On the other hand, the decay rate (recession parameter) is assumed as a linear function of the starting flow. The two parameters of that function are time-invariant, and they are optimized over a reference time series representing the low flow component of the observed hydrographs. The methodology is tested in the basins of Achelous, Greece, Xeros and Peristerona, Cyprus, and Salso, Italy. Raw data are filtered by signal processing techniques which remove the effect of flood events occurring in dry periods, thus allow-ing the preservation of the decaying form of the flow recession curve. Results indicate that satisfac-tory low flow forecasts are possible for Mediterranean basins of different hydrological behaviour.

    Remarks:

    Conference paper published in Special Issue of European Water: "10th Word Congress on Water Resources and Environment".

    Full text: http://www.itia.ntua.gr/en/getfile/1753/1/documents/EW_2017_57_47.pdf (859 KB)

    See also: http://www.ewra.net/ew/pdf/EW_2017_57_47.pdf

Book chapters and fully evaluated conference publications

  1. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, RISKNOUGHT: A cyber-physical stress-testing platform for water distribution networks, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.

    Full text:

  1. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Development of a distributed hydrological software application employing novel velocity-based techniques, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.

    The aim of this study is the development of an event-based distributed hydrological model, incorporating novel methodologies for estimating the effective rainfall and flow routing across the terrain and the hydrographic network (Risva 2018). We present two modelling configurations of the model, one for extracting the flood hydrograph (separating interflow) and one for the full hydrograph, at the basin outlet.

    Full text:

  1. D. Nikolopoulos, C. Makropoulos, D. Kalogeras, K. Monokrousou, and I. Tsoukalas, Developing a stress-testing platform for cyber-physical water infrastructure, 2018 International Workshop on Cyber-Physical Systems for Smart Water Networks (CySWater), New Jersey, 9–11, doi:10.1109/CySWater.2018.00009, 2018.

    Water supply and sanitation infrastructures are essential for our welfare, but vulnerable to several attacks, typically of physical and cyber types. Cyber-physical attacks on critical infrastructures include chemical and/or biological contamination, physical or communications disruption between the network elements and the supervisory SCADA. Due to the ever-changing landscape of the digital world and the rising concerns about security, there is an emerging need for conceptualizing critical infrastructure as cyber-physical systems and develop a holistic risk management framework for its physical and cyber protection. The framework aims to strengthen the capacities of water utilities to systematically protect their systems, determine gaps in security technologies and improve risk management approaches. Our work envisions the development of a stress testing modelling platform, able to simulate the water system as a complete cyber-physical infrastructure and investigate attack scenarios and possible mitigation measures.

    Full text: http://www.itia.ntua.gr/en/getfile/1965/1/documents/08434711.pdf (332 KB)

  1. D. Nikolopoulos, K. Risva, and C. Makropoulos, A cellular automata urban growth model for water resources strategic planning, 13th International Conference on Hydroinformatics (HIC 2018), Palermo, Italy, 3, 1557–1567, doi:10.29007/w43g, 2018.

    The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.

    Full text: http://www.itia.ntua.gr/en/getfile/1921/1/documents/A_Cellular_Automata_Urban_Growth_Model_for_Water_Resources_Strategic_Planning.pdf (2027 KB)

  1. P. Dimas, D. Bouziotas, D. Nikolopoulos, A. Efstratiadis, and D. Koutsoyiannis, Framework for optimal management of hydroelectric reservoirs through pumped storage: Investigation of Acheloos-Thessaly and Aliakmon hydrosystems, Proceedings of 3rd Hellenic Conference on Dams and Reservoirs, Zappeion, Hellenic Commission on Large Dams, Athens, 2017.

    In this study, a holistic approach for the optimal management of two large, multi-reservoir hydrosystems in Greece is analysed, applied in cases of multiple and conflicting water uses, such as hydroelectric production and the coverage of irrigation and drinking water demands. In general, the optimal management of such hydrosystems presents a strong challenge for engineers, due to the stochasticity of inflows and the non-linear nature of hydroelectric production. To manage the strong variability of renewable energy production, the use of the two studied cases of Acheloos-Thessaly and Aliakmonas as pump-storage systems is proposed. To explore the optimal management policies, the methodological framework of “Parameterisation-Simulation-Optimisation” (PSO) is applied, employed through the use of Hydronomeas software and its hydroelectric production optimization module. The goal of the analysis is the estimation of the capacity to generate firm energy with a preset high reliability level in both systems, as well as the assessment of the consequent economic benefit obtained with the optimal policies found through Hydronomeas. Moreover, the benefits of employing pump-storage schemes in order to provide a buffer for other renewable energy sources with strong variability, such as wind energy, is explored.

    Full text: http://www.itia.ntua.gr/en/getfile/1747/1/documents/fragmata2017.pdf (1070 KB)

    Additional material:

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    Low flows commonly occur in rivers during dry seasons within each year. They often concur with increased water demand which creates numerous water resources management problems. This paper seeks for simple yet efficient tools for low-flow forecasting, which are easy to implement, based on the adoption of an exponential decay model for the flow recession curve. A statistical attribute of flows preceding the start of the dry period is used as the starting flow, as for example the minimum flow of early April. On the other hand, the decay rate (recession parameter) is assumed as a linear function of the starting flow. The two parameters of that function are time-invariant, and they are optimised over a reference time series representing the low flow component of the observed hydrographs. The methodology is tested in the basins of Achelous, Greece, Xeros and Peristerona, Cyprus, and Salso, Italy. Raw data are filtered by simple signal processing techniques which remove the effect of flood events occurring in dry periods, thus allowing the preservation of the decaying form of the flow recession curve. Results indicate that satisfactory low flow forecasts are possible for Mediterranean basins of different hydrological behaviour.

    Additional material:

  1. C. Makropoulos, V. Tsoukala, K. Belibassakis, A. Lykou, M. Chondros, P. Gourgoura, and D. Nikolopoulos, Managing flood risk in coastal cities through an integrated modelling framework supporting stakeholders’ involvement: the case of Rethymno, Crete, Proceedings of the 36th IAHR World Congress, The Hague, The Netherlands, 2015.

    Full text: http://www.itia.ntua.gr/en/getfile/2062/1/documents/CP94_MANAGINGFLOODRISKINCOASTALCITIES_IAHR2015.pdf (1985 KB)

Conference publications and presentations with evaluation of abstract

  1. D. Nikolopoulos, P. Kossieris, and C. Makropoulos, Stochastic stress-testing approach for assessing resilience of urban water systems from source to tap, EGU General Assembly 2021, online, EGU21-13284, doi:10.5194/egusphere-egu21-13284, European Geosciences Union, 2021.

    Urban water systems are designed with the goal of delivering their service for several decades. The infrastructure will inevitably face long-term uncertainty in a multitude of parameters from the hydroclimatic and socioeconomic realms (e.g., climate change, limited supply of water in terms quantity and acceptable quality, population growth, shifting demand patterns, industrialization), as well as from the conceptual realm of the decision maker (e.g., changes in policy, system maintenance incentives, investment rate, expansion plans). Because urban water systems are overly complex, a holistic analysis involves the use of various models that individually pertain to a smaller sub-system and a variety of metrics to assess performance, whereas the analysis is accomplished at different temporal and spatial scales for each sub-system. In this work, we integrate a water resources management model with a water distribution model and a water demand generation model at smaller (household and district) scale, allowing us to simulate urban water systems “from source to tap”, covering the entire water cycle. We also couple a stochastic simulation module that supports the representation of uncertainty throughout the water cycle. The performance of the integrated system under long term uncertainty is assessed with the novel measure of system’s resilience i.e. the degree to which a water system continues to perform under progressively increasing disturbance. This evaluation is essentially a framework of systematic stress-testing, where the disturbance is described via stochastically changing parameters in an ensemble of scenarios that represent future world views. The framework is showcased through a synthesized case study of a medium-sized urban water system.

    Remarks:

    This research is carried out / funded in the context of the project “A resilience assessment framework for water supply infrastructure under long-term uncertainty: A Source-to-Tap methodology integrating state of the art computational tools” (MIS 5049174) under the call for proposals “Researchers' support with an emphasis on young researchers- 2nd Cycle”. The project is co-financed by Greece and the European Union (European Social Fund- ESF) by the Operational Programme Human Resources Development, Education and Lifelong Learning 2014-2020.”

    Full text: http://www.itia.ntua.gr/en/getfile/2124/1/documents/EGU21-13284_presentation-h273713.pdf (897 KB)

  1. G. Moraitis, D. Nikolopoulos, I. Koutiva, I. Tsoukalas, G. Karavokiros, and C. Makropoulos, The PROCRUSTES testbed: tackling cyber-physical risk for water systems, EGU General Assembly 2021, online, EGU21-14903, doi:10.5194/egusphere-egu21-14903, European Geosciences Union, 2021.

    Our modern urban environment relies on critical infrastructures that serve vital societal functions, such as water supply and sanitation, which are exposed to various threats of both physical and cyber nature. Despite the progress in protection and increased vigilance, long-established practices within the water utilities may rely on precarious methods for the characterization and assessment of threats, with uncertainty pertaining to risk-relevant data and information. Sources for uncertainty can be attributed to e.g. limited capabilities of deterministic approaches, siloed analysis of water systems, use of ambiguous measures to describe and prioritise risks or common security misconceptions. To tackle those challenges, this work brings together an ensemble of solutions, to form a novel, unified process of resilience assessment for the water sector against an emerging cyber-physical threat landscape e.g., cyber-attacks on the command and control sub-system. Specifically, the proposed framework sets out an operational workflow that combines, inter alia, a) an Agent-Based Modelling (ABM) approach to derive alternative routes to quantify risks considering the dynamics of socio-technical systems, b) an adaptable optimisation platform which integrates advanced multi-objective algorithms for system calibration, uncertainty propagation analysis and asset criticality prioritization and c) a dynamic risk reduction knowledge-base (RRKB) designed to facilitate the identification and selection of suitable risk reduction measures (RRM). This scheme is overarched by a cyber-physical testbed, able to realistically model the interactions between the information layer (sensors, PLCs, SCADA) and the water distribution network. The testbed is designed to assess the water system beyond normal operational capacity. It facilitates the exploration of emergent and unidentified threats and vulnerabilities leading to Low Probability, High Consequence (LPHC) events that systems are not originally designed to handle. It also evaluates alternative risk treatment options against case-appropriate indicators. The final product is the accretion of actionable information to integrate risk into decision-making in a practical and standardized form. Our work envisions to bring forth state-of-art technologies and approaches for the cyber-wise water sector. We aspire to enhance existing capabilities for large utilities and enable small and medium water utilities with typically less resources, to reinforce their systems’ resilience and be better prepared against cyber-physical and other threats.

    Full text: http://www.itia.ntua.gr/en/getfile/2122/1/documents/EGU21-14903_presentation.pdf (1404 KB)

  1. D. Nikolopoulos, G. Moraitis, D. Bouziotas, A. Lykou, G. Karavokiros, and C. Makropoulos, RISKNOUGHT: Stress-testing platform for cyber-physical water distribution networks, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-19647, doi:10.5194/egusphere-egu2020-19647, 2020.

    Emergent threats in the water sector have the form of cyber-physical attacks that target SCADA systems of water utilities. Examples of attacks include chemical/biological contamination, disruption of communications between network elements and manipulating sensor data. RISKNOUGHT is an innovative cyber-physical stress testing platform, capable of modelling water distribution networks as cyber-physical systems. The platform simulates information flow of the cyber layer’s networking and computational elements and the feedback interactions with the physical processes under control. RISKNOUGHT utilizes an EPANET-based solver with pressure-driven analysis functionality for the physical process and a customizable network model for the SCADA system representation, which is capable of implementing complex control logic schemes within a simulation. The platform enables the development of composite cyber-physical attacks on various elements of the SCADA including sensors, actuators and PLCs, assessing the impact they have on the hydraulic response of the distribution network, the quality of supplied water and the level of service to consumers. It is envisaged that this platform could help water utilities navigate the ever-changing risk landscape of the digital era and help address some of the modern challenges due to the ongoing transformation of water infrastructure into cyber-physical systems.

    Full text: http://www.itia.ntua.gr/en/getfile/2061/1/documents/EGU2020-19647.pdf (1199 KB)

  1. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Distributed hydrological modelling using spatiotemporally varying velocities, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-13402, doi:10.5194/egusphere-egu2020-13402, 2020.

    We present a distributed hydrological model with minimal calibration requirements, which represents the rainfall-runoff transformation and the flow routing processes. The generation of surface runoff is based on a modified NRCS-CN scheme. Key novelty is the use of representative CN values, which are initially assigned to model cells on the basis of slope, land cover and permeability maps, and adjusted to antecedent soil moisture conditions. For the propagation of runoff to the basin outlet two flow types are considered, i.e. overland flow across the terrain and channel flow along the river network. These are synthesized by employing a novel velocity-based approach, where the assignment of velocities along the river network is based on macroscopic hydraulic information. It also uses the concept of varying time of concentration, which is considered function of the average runoff intensity across the catchment. This configuration is suitable for event-based flood simulation and requires the specification of only two lumped inputs, which are either manually estimated or inferred through calibration. The model can also run in continuous mode, by employing a soil moisture accounting scheme that produces both the surface (overland) runoff and the interflow through the unsaturated zone. The two model configurations are demonstrated in the representation of observed flows across Nedontas river basin at South Peloponnese, Greece.

    Full text: http://www.itia.ntua.gr/en/getfile/2026/1/documents/EGU2020-13402-print.pdf (290 KB)

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-13402.html

  1. G. Karavokiros, D. Nikolopoulos, S. Manouri, A. Efstratiadis, C. Makropoulos, N. Mamassis, and D. Koutsoyiannis, Hydronomeas 2020: Open-source decision support system for water resources management, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-20022, doi:10.5194/egusphere-egu2020-20022, 2020.

    Over the last 30 years, numerous water resources planning and management studies in Greece have been conducted by using state-of-the-art methodologies and associated computational tools that have been developed by the Itia research team at the National Technical University of Athens. The spearhead of Itia’s research toolkit has been the Hydronomeas decision support system (which stands for “water distributer” in Greek) supporting multi-reservoir hydrosystem management. Its methodological framework has been based on the parameterization-simulation-optimization approach comprising stochastic simulation, network linear optimization for the representation of water and energy fluxes, and multicriteria global optimization, ensuring best-compromise decision-making. In its early stage, Hydronomeas was implemented in Object Pascal – Delphi. Currently, the software is being substantially redeveloped and its improved version incorporates new functionalities, several model novelties and interconnection with other programs, e.g., EPANET. Hydronomeas 2020 will be available at the end of 2020 as a free and open-source Python package. In this work we present the key methodological advances and improved features of the current version of the software, demonstrated in the modelling of the extensive and challenging raw water supply system of the city of Athens, Greece.

    Full text:

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-20022.html

    Other works that reference this work (this list might be obsolete):

    1. Koutiva, I., and C. Makropoulos, On the use of agent based modelling for addressing the social component of urban water management in Europe, Computational Water, Energy, and Environmental Engineering, 10(4), 140-154, doi:10.4236/cweee.2021.104011, 2021.

  1. L. M. Tsiami, E. Zacharopoulou, D. Nikolopoulos, I. Tsoukalas, N. Mamassis, A. Kallioras, and A. Efstratiadis, The use of Artificial Neural Networks with different sources of spatiotemporal information for flash flood predictions, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-7315, European Geosciences Union, 2019.

    For more than two decades, the use of artificial neural networks (ANNs) in hydrology has become an effective and efficient alternative against traditional modeling approaches, i.e. physically-based or conceptual. These can take advantage of any type of available information to predict the hydrological response of complex systems, with missing data and limited knowledge about the transformation mechanisms. A promising area of application is the real-time prediction of flood propagation, which is essential element of early warning and early notification systems. In this work we focus to flash floods, considering as areas of application two medium-scale catchments in Greece with substantially different characteristics. The first one is the highly urbanized river basin of Kephissos (380 km2), which is the main drainage channel of the Athens Metropolitan area, while the second is the rural catchment of Nedontas, SW Greece (120 km2). Both areas have been recently equipped with automatic hydrometric stations, while online rainfall data are also available at a representative number of meteorological stations. For the two case studies we investigate several setups of ANNs, in order to predict the river stage at the catchment outlet for several lead times, using different combinations of input sets, by means of upstream stage and point rainfall data.

    Full text:

  1. D. Nikolopoulos, A. Efstratiadis, G. Karavokiros, N. Mamassis, and C. Makropoulos, Stochastic simulation-optimization framework for energy cost assessment across the water supply system of Athens, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-12290, European Geosciences Union, 2018.

    The water supply of Athens is implemented through a complex hydrosystem, including four reservoirs, 350 km of main aqueducts, 15 pumping stations, more than 100 boreholes and 5 small hydropower plants. The management of this system is subject to multiple complexities and uncertainties, as well as conflicts between different water uses and environmental constraints. Yet, the key challenge arises from the need to minimize the operational cost of the system, mainly induced to energy consumption across pumping stations and boreholes, at the same time retaining its long-term reliability at the acceptable level of 99%, on annual basis. In general, the energy cost is low, since most of raw water is abstracted and conveyed via gravity, yet occasionally this may be substantially increased, due to the activation of auxiliary resources that require intense use of pumping stations. In order to assess this cost for several water demand scenarios and reliability levels, taking into account all aforementioned issues, we employ a stochastic simulation – optimization framework, implemented within the recently updated version of Hydronomeas software. The outcomes of these analyses are next used in order to estimate the cost of raw water arriving at the metropolitan area of Athens, as function of demand and reliability.

    Full text:

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, Low-flow analysis in Mediterranean basins, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18880, European Geosciences Union, 2018.

    In this work we examine the low flow characteristics of Mediterranean basins during the dry season. For convenience, we consider a six-month period, from mid-April to mid-October, which is generally characterized by limited precipitation and increased water demands. Our emphasis is given to the baseflow component, represented through a linear reservoir approach, key component of which is the recession rate. Classic indices, such as flow quantiles, are calculated along a simple exponential recession model. Our analysis aims to explain the significant variability of the recession rate across hydrological years and across river basins with different characteristics, in terms of extent, elevation, physiographical properties and runoff production. Results show that the recession rate is strongly correlated to characteristic hydrological signatures, and it is also a function of the basin area. The study applies to 25 Mediterranean basins across France, Spain, Cyprus, Italy and Greece, including some small catchments with intermittent flow regime.

    Full text:

  1. E. Rozos, D. Nikolopoulos, A. Efstratiadis, A. Koukouvinos, and C. Makropoulos, Flow based vs. demand based energy-water modelling, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-6528, European Geosciences Union, 2015.

    The water flow in hydro-power generation systems is often used downstream to cover other type of demands like irrigation and water supply. However, the typical case is that the energy demand (operation of hydro-power plant) and the water demand do not coincide. Furthermore, the water inflow into a reservoir is a stochastic process. Things become more complicated if renewable resources (wind-turbines or photovoltaic panels) are included into the system. For this reason, the assessment and optimization of the operation of hydro-power systems are challenging tasks that require computer modelling. This modelling should not only simulate the water budget of the reservoirs and the energy production/ consumption (pumped-storage), but should also take into account the constraints imposed by the natural or artificial water network using a flow routing algorithm. HYDRONOMEAS, for example, uses an elegant mathematical approach (digraph) to calculate the flow in a water network based on: the demands (input timeseries), the water availability (simulated) and the capacity of the transmission components (properties of channels, rivers, pipes, etc.). The input timeseries of demand should be estimated by another model and linked to the corresponding network nodes. A model that could be used to estimate these timeseries is UWOT. UWOT is a bottom up urban water cycle model that simulates the generation, aggregation and routing of water demand signals. In this study, we explore the potentials of UWOT in simulating the operation of complex hydrosystems that include energy generation. The evident advantage of this approach is the use of a single model instead of one for estimation of demands and another for the system simulation. An application of UWOT in a large scale system is attempted in mainland Greece in an area extending over 130x170 km2. The challenges, the peculiarities and the advantages of this approach are examined and critically discussed.

    Full text: http://www.itia.ntua.gr/en/getfile/1525/2/documents/Poster_UWOT.pdf (307 KB)

    Additional material:

  1. A. Koukouvinos, D. Nikolopoulos, A. Efstratiadis, A. Tegos, E. Rozos, S.M. Papalexiou, P. Dimitriadis, Y. Markonis, P. Kossieris, H. Tyralis, G. Karakatsanis, K. Tzouka, A. Christofides, G. Karavokiros, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Integrated water and renewable energy management: the Acheloos-Peneios region case study, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4912, doi:10.13140/RG.2.2.17726.69440, European Geosciences Union, 2015.

    Within the ongoing research project “Combined Renewable Systems for Sustainable Energy Development” (CRESSENDO), we have developed a novel stochastic simulation framework for optimal planning and management of large-scale hybrid renewable energy systems, in which hydropower plays the dominant role. The methodology and associated computer tools are tested in two major adjacent river basins in Greece (Acheloos, Peneios) extending over 15 500 km2 (12% of Greek territory). River Acheloos is characterized by very high runoff and holds ~40% of the installed hydropower capacity of Greece. On the other hand, the Thessaly plain drained by Peneios – a key agricultural region for the national economy – usually suffers from water scarcity and systematic environmental degradation. The two basins are interconnected through diversion projects, existing and planned, thus formulating a unique large-scale hydrosystem whose future has been the subject of a great controversy. The study area is viewed as a hypothetically closed, energy-autonomous, system, in order to evaluate the perspectives for sustainable development of its water and energy resources. In this context we seek an efficient configuration of the necessary hydraulic and renewable energy projects through integrated modelling of the water and energy balance. We investigate several scenarios of energy demand for domestic, industrial and agricultural use, assuming that part of the demand is fulfilled via wind and solar energy, while the excess or deficit of energy is regulated through large hydroelectric works that are equipped with pumping storage facilities. The overall goal is to examine under which conditions a fully renewable energy system can be technically and economically viable for such large spatial scale.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.17726.69440

    Other works that reference this work (this list might be obsolete):

    1. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32, 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    2. Stamou, A.-T., and P. Rutschmann, Optimization of water use based on the water-energy-food nexus concept: Application to the long-term development scenario of the Upper Blue Nile River, Water Utility Journal, 25, 1-13, 2020.

  1. E. Anagnostopoulou, A. Galani, P. Dimas, A. Karanasios, T. Mastrotheodoros, E. Michailidi, D. Nikolopoulos, S. Pontikos, F. Sourla, A. Chazapi, S.M. Papalexiou, and D. Koutsoyiannis, Record breaking properties for typical autocorrelation structures, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-4520, doi:10.13140/RG.2.2.20420.22400, European Geosciences Union, 2013.

    Record-breaking occurrences in hydrometeorological processes are often used particularly in communicating information to the public and their analysis offers the possibility of better comprehending extreme events. However, the typical comprehension depends on prototypes characterized by pure randomness. In fact the occurrence of record breaking depends on the marginal distribution and the autocorrelation function of the process as well the length of available record. Here we study the influence of the process autocorrelation structure on the statistics of record-breaking occurrences giving emphasis on the differences with those of a purely random process. The particular stochastic processes, which we examine, are the AR(1), AR(2) and ARMA(1,1), as well as the Hurst-Kolmogorov process. The necessary properties are calculated using either analytical methods when possible or Monte Carlo simulation. We also compare the model results with observed hydrometeorological time series.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.20420.22400

Presentations and publications in workshops

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 5th Hellenic Conference of Surveying Enginners, Athens, 2017.

    Low flows commonly occur in rivers during dry seasons within each year. They often concur with increased water demand which creates numerous water resources management problems. This paper seeks for simple yet efficient tools for low-flow forecasting, which are easy to implement, based on the adoption of an exponential decay model for the flow recession curve. A statistical attribute of flows preceding the start of the dry period is used as the starting flow. On the other hand, the decay rate (recession parameter) is assumed as a linear function of the starting flow. The two parameters of that function are time-invariant, and they are optimized over a reference time series representing the low flow component of the observed hydrographs. The methodology is tested in the basins of Achelous, Greece, Xeros and Peristerona, Cyprus, and Salso, Italy. Raw data are filtered by signal processing techniques which remove the effect of flood events occurring in dry periods, thus allow-ing the preservation of the decaying form of the flow recession curve. Results indicate that satisfac-tory low flow forecasts are possible for Mediterranean basins of different hydrological behaviour.

    Related works:

    • [15] Similar article (in English) presented in EWRA conference

    Full text: http://www.itia.ntua.gr/en/getfile/1752/1/documents/PSDATM_low_flows_article.pdf (1015 KB)

    Additional material:

Academic works

  1. D. Nikolopoulos, Development of geospatial urban growth models supporting urban water strategic planning: the case study of Rethymnon, Crete, MSc thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, November 2017.

    The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management and mitigation measures, waste-water treatment and water quality control. Strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. However, in contemporary studies, this rarely is the norm; commonly urban growth is used as a static input/scenario based on previous studies or general urban planning or the focus is shifted to the related population increase rather than its spatial allocation. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. Urban growth is an inherently complex phenomenon. It can be considered as a system of physical expansion and function transitions. It changes trough time by the interaction with many inter-related, mostly unknown, drivers and stimulant factors. These interactions create an open, non-linear, dynamic and emergent system. Thus, it is fundamentally difficult to accurately model and predict urban growth, if not entirely impossible. The focus of modelling urban growth should be in creating plausible results and models with good explanatory power, able to simulate and explore the complex urban dynamics, rather than precisely pinpoint future urban locations. A dominant family of such models in literature is “Cellular Automata” (CA) based: The area of interest is divided in discrete cells that are self-organized. These models operate by applying in each simulation step simple rules defining local interactions among neighboring cells. The vast number of local interactions can result in a complex and dynamic global behaviour, especially when stochastic disturbances and rules are introduced to the model. Their simple in defining, yet complex in outcomes, nature makes CA-based models suitable for urban growth simulation and prediction. Many model sub-types and hybrid interdisciplinary approaches have been proposed and tested extensively in research efforts. A robust, parsimonious in data requirements and flexible CA model is developed in this work, as part of a general methodology framework aimed to assist urban water strategic planning. Briefly, the proposed two-state (urban and non-urban land uses) CA model is conditioned (i.e., constrained) on external drivers and accounts for the allocation dynamics variability via stochastic internal mechanisms. Furthermore, special attention was given in the modularity of the model in order to provide the means for its straightforward extension and reproducibility. Finally, emphasis was given on optimizing the simulation speed (i.e., computational effort), a common weakness of most CA models. The model is comprised of two main modules, an external subsystem that generates the number of new urban cells in the next simulation step, making the model constrained to exogenous drivers, and an internal subsystem that allocates these cells spatially through the use of stochastic mechanisms that have descriptive properties. Each subsystem is calibrated to real data before the urban growth prediction. Specifically, the parameters of the internal CA model are calibrated against the similarity of the output to the real urban changes across a specific timespan, using various (weighted) metrics such as the modified Kappa coefficient of agreement (Ksim), shape parameters and number of clusters. Due to the stochastic nature of the model a Monte-Carlo technique is applied. The model is executed a pre-specified number of times and the median performance index is used as input to a genetic algorithm for optimization. An urban classifier model is developed alongside the CA model, in order to enable it to use open data from remote sensing sources, such us Landsat images. This is a key point of the methodology as in many cases suitable data for applying urban growth models is scarce. The urban classifier model uses an artificial neural network (ANN) structure utilizing not only multispectral bands as inputs, but also the multivariate texture info extracted by novel techniques from the satellite imagery, such as multi-variate variogram with spectral angle distance. Haralick-GLCM texture indices and multi-variogram based metrics are tested alongside multispectral data in a Monte-Carlo calibration scheme. Control samples for calibration and validation are randomly selected from a predefined pool (selected for the most recent image from basemaps, Google Earth etc.) and the classification performance is evaluated a thousand times. The set of parameters with the best distribution of performance is used to select a classifier type, that classifies the most recent satellite image (because control samples are readily applicable only for a recent image in most cases). The output of the classifier is then combined with an object-oriented hierarchical (in a temporal manner) classification methodology to derive the required historical land-use change timeseries from the other preceding images. The latter is required to calibrate the parameters of the CA model. The methodology is applied to the general area around Rethymno city in Crete, so as to include various settlements that differ significantly in size and patch density. The mixing of different land uses greatly increases the difficulty for both the urban classifier model and the CA. Also, historical data are scarce, incomplete and inaccurate. This paradoxically makes it an ideal case to demonstrate the robustness of the new methodology. The results are very promising, indicating that the methodology is capable of both identifying historical urban growth from open remote sensing data using the urban classifier model and simulating the complex nature of urban growth even in such unfavorable conditions via the CA model. Finally, hypothetical future water resources-related examples highlight practical aspects of the proposed methodology, after future urban growth predictions by the CA, in the context of modern urban water strategic planning.

  1. D. Nikolopoulos, Model development for conjunctive management of Acheloos and Peneios river basins, Diploma thesis, 214 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2015.

    Full text: http://www.itia.ntua.gr/en/getfile/1544/1/documents/thesis_nikolopoulos.pdf (22880 KB)

    Additional material:

Research reports

  1. A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, N. Mamassis, D. Nikolopoulos, I. Tsoukalas, and P. Kossieris, First year synopsis, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 55 pages, December 2020.

    Related project: Modernization of the management of the water supply system of Athens - Update

  1. A. Efstratiadis, S. Manouri, D. Nikolopoulos, and I. Tsoukalas, Investigation of the water supply system's management for period March-September 2020, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 31 pages, March 2020.

    Related project: Modernization of the management of the water supply system of Athens - Update

  1. A. Koukouvinos, A. Efstratiadis, D. Nikolopoulos, H. Tyralis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Case study in the Acheloos-Thessaly system, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 98 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2015.

    This report describes the validation of methodologies and computer tools that have been developed in the context of the research project, in the interconnected river basin system of Acheloos and Peneios. The study area is modelled as a hypothetically closed and autonomous (in terms of energy balance) system, in order to investigate the perspectives of sustainable development at the peripheral scale, merely based on renewable energy.

    Related project: Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO)

    Full text: http://www.itia.ntua.gr/en/getfile/1613/1/documents/Report_EE4a.pdf (8010 KB)