Christos Makropoulos

Professor, Civil Engineer, Dr. Engineer
c.makropoulos@itia.ntua.gr
+30 210 772 2886

Participation in research projects

Participation as Project Director

  1. Cost of raw water of the water supply of Athens

Participation as Researcher

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

Participation in engineering studies

  1. Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina

Published work

Publications in scientific journals

  1. S. Tsattalios, I. Tsoukalas, P. Dimas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Advancing surrogate-based optimization of time-expensive environmental problems through adaptive multi-model search, Environmental Modelling and Software, doi:10.1016/j.envsoft.2023.105639, 2023, (in press).
  2. D. Nikolopoulos, G. Moraitis, G. Karavokiros, D. Bouziotas, and C. Makropoulos, Stress-testing alternative water quality sensor designs under cyber-physical attack scenarios, Environmental Sciences Proceedings, 21 (1), 17, doi:10.3390/environsciproc2022021017, 2022.
  3. G. Moraitis, I. Tsoukalas, P. Kossieris, D. Nikolopoulos, G. Karavokiros, D. Kalogeras, and C. Makropoulos, Assessing cyber-physical threats under water demand uncertainty, Environmental Sciences Proceedings, 21 (1), 18, doi:10.3390/environsciproc2022021018, October 2022.
  4. G.-K. Sakki, I. Tsoukalas, P. Kossieris, C. Makropoulos, and A. Efstratiadis, Stochastic simulation-optimisation framework for the design and assessment of renewable energy systems under uncertainty, Renewable and Sustainable Energy Reviews, 168, 112886, doi:10.1016/j.rser.2022.112886, 2022.
  5. A. Efstratiadis, P. Dimas, G. Pouliasis, I. Tsoukalas, P. Kossieris, V. Bellos, G.-K. Sakki, C. Makropoulos, and S. Michas, Revisiting flood hazard assessment practices under a hybrid stochastic simulation framework, Water, 14 (3), 457, doi:10.3390/w14030457, 2022.
  6. P. Kossieris, I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Generic framework for downscaling statistical quantities at fine time-scales and its perspectives towards cost-effective enrichment of water demand records, Water, 13 (23), 3429, doi:10.3390/w13233429, 2021.
  7. 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.
  8. H. Elsayed, S. Djordjević, D. Savic, I. Tsoukalas, and C. Makropoulos, The Nile water-food-energy nexus under uncertainty: Impacts of the Grand Ethiopian Renaissance Dam, Journal of Water Resources Planning and Management - ASCE, 146 (11), 04020085, doi:10.1061/(ASCE)WR.1943-5452.0001285, 2020.
  9. 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.
  10. 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.
  11. I. Tsoukalas, P. Kossieris, and C. Makropoulos, Simulation of non-Gaussian correlated random variables, stochastic processes and random fields: Introducing the anySim R-Package for environmental applications and beyond, Water, 12 (6), 1645, doi:10.3390/w12061645, 2020.
  12. 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.
  13. 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.
  14. I. Koutiva, and C. Makropoulos, Exploring the effects of alternative water demand management strategies using an agent-based model, Water, 11 (11), 2216, doi:10.3390/w11112216, 2019.
  15. C. Makropoulos, and D. Savic, Urban hydroinformatics: past, present and future, Water, 11 (10), 1959, doi:10.3390/w11101959, 2019.
  16. 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.
  17. P. Kossieris, I. Tsoukalas, C. Makropoulos, and D. Savic, Simulating marginal and dependence behaviour of water demand processes at any fine time scale, Water, 11 (5), 885, doi:10.3390/w11050885, 2019.
  18. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.
  19. P. Kossieris, and C. Makropoulos, Exploring the statistical and distributional properties of residential water demand at fine time scales, Water, 10 (10), 1481, doi:10.3390/w10101481, 2018.
  20. Ε. Psarrou, I. Tsoukalas, and C. Makropoulos, A Monte-Carlo-based method for the optimal placement and operation scheduling of sewer mining units in urban wastewater networks, Water, 10 (2), 200, doi:10.3390/w10020200, 2018.
  21. I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018.
  22. I. Tsoukalas, S.M. Papalexiou, A. Efstratiadis, and C. Makropoulos, A cautionary note on the reproduction of dependencies through linear stochastic models with non-Gaussian white noise, Water, 10 (6), 771, doi:10.3390/w10060771, 2018.
  23. 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.
  24. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018.
  25. S. Baki, E. Rozos, and C. Makropoulos, Designing water demand management schemes using a socio-technical modelling approach, Science of the Total Environment, 622, 1590–1602, doi:10.1016/j.scitotenv.2017.10.041, 2018.
  26. C. Makropoulos, E. Rozos, I. Tsoukalas, A. Plevri, G. Karakatsanis, L. Karagiannidis, E. Makri, C. Lioumis, K. Noutsopoulos, D. Mamais, K. Ripis, and T. Lytras, Sewer-mining: A water reuse option supporting circular economy, public service provision and entrepreneurship, Journal of Environmental Management, 216, 285–298, doi:10.1016/j.jenvman.2017.07.026, 2018.
  27. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.
  28. I. Tsoukalas, C. Makropoulos, and S. Mihas, Identification of potential sewer mining locations: A Monte-Carlo based approach, Water Science and Technology, 76 (12), 3351–3357, doi:10.2166/wst.2017.487, 2017.
  29. E. Rozos, I. Tsoukalas, K. Ripis, E. Smeti, and C. Makropoulos, Turning black into green: Ecosystem services from treated wastewater, Desalination and Water Treatment, 91 (2017), 2017.
  30. G. Kochilakis, D. Poursanidis, N. Chrysoulakis, V. Varella, V. Kotroni, G. Eftychidis, K. Lagouvardos, C. Papathanasiou, G. Karavokiros, M. Aivazoglou, C. Makropoulos, and M. Mimikou, FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas, Open Geosciences, 8, 711–727, doi:10.1515/geo-2016-0068, 2016.
  31. G. Kochilakis, D. Poursanidis, N. Chrysoulakis, V. Varella, V. Kotroni, G. Eftychidis, K. Lagouvardos, C. Papathanasiou, G. Karavokiros, M. Aivazoglou, C. Makropoulos, and M. Mimikou, A web based DSS for the management of floods and wildfires (FLIRE) in urban and periurban areas, Environmental Modelling and Software, 86, 111–115, doi:10.1016/j.envsoft.2016.09.016, 2016.
  32. P. Kossieris, C. Makropoulos, E. Creaco, L. Vamvakeridou-Lyroudia, and D. Savic, Assessing the applicability of the Bartlett-Lewis model in simulating residential water demands, Procedia Engineering, 154, 123–131, 2016.
  33. E. Creaco, P. Kossieris, L. Vamvakeridou-Lyroudia, C. Makropoulos, Z. Kapelan, and D. Savic, Parameterizing residential water demand pulse models through smart meter readings, Environmental Modelling and Software, 80, 33–40, 2016.
  34. G. Karavokiros, A. Lykou, I. Koutiva, J. Batica, A. Kostaridis, A. Alves, and C. Makropoulos, Providing evidence-based, intelligent support for flood resilient planning and policy: the PEARL Knowledge Base, Water, 8 (9), 392, doi:10.3390/w8090392, 2016.
  35. E. Rozos, D. Butler, and C. Makropoulos, An integrated system dynamics – cellular automata model for distributed water-infrastructure planning, Water Science and Technology: Water Supply, 17 (6), doi:10.2166/ws.2016.080, 2016.
  36. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.
  37. I. Tsoukalas, and C. Makropoulos, A surrogate based optimization approach for the development of uncertainty-aware reservoir operational rules: the case of Nestos hydrosystem, Water Resources Management, 29 (13), 4719–4734, doi:10.1007/s11269-015-1086-8, 2015.
  38. I. Tsoukalas, and C. Makropoulos, Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty, Environmental Modelling and Software, 69, 396–413, doi:10.1016/j.envsoft.2014.09.023, 2015.
  39. D. Bouziotas, E. Rozos, and C. Makropoulos, Water and the City: Exploring links between urban growth and water demand management., Journal of Hydroinformatics, 17 (2), doi:10.2166/hydro.2014.053, 2015.
  40. P. Kossieris, S. Kozanis, A. Hashmi, E. Katsiri, L. Vamvakeridou-Lyroudia, R. Farmani, C. Makropoulos, and D. Savic, A web-based platform for water efficient households, Procedia Engineering, 89, 1128–1135, 2014.
  41. P. Kossieris, Panayiotakis, K. Tzouka, E. Rozos, and C. Makropoulos, An e-Learning approach for improving household water efficiency, Procedia Engineering, WDSA 2014, Bari, Italy, Water Distribution Systems Analysis, 2014.
  42. E. Rozos, C. Makropoulos, and C. Maksimovic, Rethinking urban areas: an example of an integrated blue-green approach, Water Science and Technology: Water Supply, 13 (6), 1534–1542, doi:10.2166/ws.2013.140, 2013.
  43. E. Rozos, and C. Makropoulos, Source to tap urban water cycle modelling, Environmental Modelling and Software, 41, 139–150, doi:10.1016/j.envsoft.2012.11.015, Elsevier, 1 March 2013.
  44. S.M. Papalexiou, D. Koutsoyiannis, and C. Makropoulos, How extreme is extreme? An assessment of daily rainfall distribution tails, Hydrology and Earth System Sciences, 17, 851–862, doi:10.5194/hess-17-851-2013, 2013.
  45. E. Rozos, and C. Makropoulos, Assessing the combined benefits of water recycling technologies by modelling the total urban water cycle, Urban Water Journal, 9 (1), doi:10.1080/1573062X.2011.630096, February 2012.
  46. E. Rozos, C. Makropoulos, and D. Butler, Design robustness of local water-recycling schemes, Journal of Water Resources Planning and Management - ASCE, 136 (5), 531–538, doi:10.1061/(ASCE)WR.1943-5452.0000067, 2010.
  47. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.
  48. C. Makropoulos, D. Koutsoyiannis, M. Stanic, S. Djordevic, D. Prodanovic, T. Dasic, S. Prohaska, C. Maksimovic, and H. S. Wheater, A multi-model approach to the simulation of large scale karst flows, Journal of Hydrology, 348 (3-4), 412–424, 2008.

Book chapters and fully evaluated conference publications

  1. V. Bellos, P. Kossieris, A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, P. Dimas, and C. Makropoulos, Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system, Proceedings of 7th IAHR Europe Congress "Innovative Water Management in a Changing Climate”, Athens, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.
  2. G.-K. Sakki, A. Efstratiadis, and C. Makropoulos, Stress-testing for water-energy systems by coupling agent-based models, Proceedings of 7th IAHR Europe Congress "Innovative Water Management in a Changing Climate”, Athens, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.
  3. P. Dimas, D. Nikolopoulos, and C. Makropoulos, Simulation framework for pipe failure detection and replacement scheduling optimization, e-Proceedings of the 5th EWaS International Conference, Naples, 556–563, 2022.
  4. V. Bellos, P. Kossieris, A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, P. Dimas, and C. Makropoulos, Fiware-enabled tool for real-time control of the raw-water conveyance system of Athens, Proceedings of the 39th IAHR World Congress, Granada, 2859–2865, doi:10.3850/IAHR-39WC2521716X20221468, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.
  5. 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.
  6. 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.
  7. 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.
  8. I. Tsoukalas, C. Makropoulos, and A. Efstratiadis, Stochastic simulation of periodic processes with arbitrary marginal distributions, 15th International Conference on Environmental Science and Technology (CEST2017), Rhodes, Global Network on Environmental Science and Technology, 2017.
  9. E. Rozos, I. Tsoukalas, K. Ripis, E. Smeti, and C. Makropoulos, Turning black into green: ecosystem services from treated wastewater, 13th IWA Specialized Conference on Small Water and Wastewater Systems, Athens, Greece, National Technical University of Athens, 2016, (in press).
  10. 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.
  11. I. Tsoukalas, P. Dimas, and C. Makropoulos, Hydrosystem optimization on a budget: Investigating the potential of surrogate based optimization techniques, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, 2015.
  12. E. Rozos, and C. Makropoulos, Preparing appropriate water policies for sd analysis: a broad-brush review on water conservation practices, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.
  13. E. Rozos, and C. Makropoulos, Urban regeneration and optimal water demand management, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.
  14. E. Rozos, Y. Photis, and C. Makropoulos, Water demand management in the expanding urban areas of south Attica, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.
  15. S. Baki, I. Koutiva, and C. Makropoulos, A hybrid artificial intelligence modelling framework for the simulation of the complete, socio-technical, urban water system, 2012 International Congress on Environmental Modelling and Software, Managing Resources of a Limited Planet, Leipzig, International Environmental Modelling and Software Society, 2012.
  16. I. Koutiva, and C. Makropoulos, Towards adaptive water resources management: simulating the complete socio-technical system through computational intelligence, Proceedings of the 12th International Conference on Environmental Science and Technology, A998–A1006, Rhodes, 2011.
  17. E. Rozos, S. Baki, D. Bouziotas, and C. Makropoulos, Exploring the link between urban development and water demand: The impact of water-aware technologies and options, Computing and Control for the Water Industry (CCWI) 2011, Exeter, UK, CCWI2011-311, University of Exeter, 2011.
  18. C. Makropoulos, E. Rozos, and D. Butler, Urban water modelling and the daily time step: issues for a realistic representation, 8th International Conference on Hydroinformatics 2009, Concepcion, Chile, Curran Associates, Inc., 57 Morehouse Lane Red Hook, NY 12571 USA, 2011.
  19. N. Evelpidou, N. Mamassis, A. Vassilopoulos, C. Makropoulos, and D. Koutsoyiannis, Flooding in Athens: The Kephisos River flood event of 21-22/10/1994, International Conference on Urban Flood Management, Paris, doi:10.13140/RG.2.1.4065.5601, UNESCO, 2009.
  20. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, V. Kaffes, C. Papathanasiou, and M. Mimikou, Multi-reservoir management with Open-MI, Proceedings of the 11th International Conference on Environmental Science and Technology, Chania, A, 788–795, Department of Environmental Studies, University of the Aegean, 2009.
  21. C. Makropoulos, E. Rozos, and C. Maksimovic, Developing An Integrated Modelling System For Blue-Green Solutions, HIC 2014 – 11th International Conference on Hydroinformatics, New York City, USA, HIC2014-216, August 2014.

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. 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.
  5. 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.
  6. G. Tzortzakis, E. Katsiri, G. Karavokiros, C. Makropoulos, and A. Delis, Tethys: sensor-based aquatic quality monitoring in waterways, 17th IEEE International Conference on Mobile Data Management (MDM), 329–332, doi:10.1109/MDM.2016.56, Porto, 2016.
  7. 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.
  8. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Handling time-expensive global optimization problems through the surrogate-enhanced evolutionary annealing-simplex algorithm, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5923, European Geosciences Union, 2015.
  9. C. Makropoulos, and E. Rozos, Managing the complete Urban Water Cycle: the Urban Water Optioneering Tool, SWITCH, Paris, France, 2011.
  10. E. Rozos, and C. Makropoulos, Ensuring water availability with complete urban water modelling, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, European Geosciences Union, 2011.
  11. E. Rozos, and C. Makropoulos, Assessing the combined benefits of water recycling technologies by modelling the total urban water cycle, International Precipitation Conference (IPC10), Coimbra, Portugal, 2010.

Presentations and publications in workshops

  1. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, and V. Kaffes, Multi-reservoir management with OpenMI, OpenMI-LIFE Pinios Workshop, Volos, 2009.
  2. C. Makropoulos, D. Koutsoyiannis, and A. Efstratiadis, Challenges and perspectives in urban water management, Local Govenance Conference: The Green Technology in the Cities, Athens, Ecocity, Central Association of Greek Municipalities, 2009.

Various publications

  1. E. Rozos, S. Kozanis, and C. Makropoulos, Integrated Modelling System, BGD internal project report, 31 January 2014.
  2. H. Perlman, C. Makropoulos, and D. Koutsoyiannis, The water cycle, http://ga.water.usgs.gov/edu/watercyclegreek.html, 19 pages, doi:10.13140/RG.2.2.11182.92480, United States Geological Survey, 2005.

Educational notes

  1. C. Makropoulos, A. Efstratiadis, and P. Kossieris, Lecture notes on Hydraulics and Hydraulic Works: Water Supply, 80 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, December 2019.
  2. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource Systems Optimzation - Hydroinformatics, 151 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2018.
  3. E. Rozos, and C. Makropoulos, Programming in Matlab for optimization problems, Athens, Greece, February 2011.
  4. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource System Optimization and Hydroinformatics, 307 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, April 2011.

Academic works

  1. C. Makropoulos, Spatial decision support for urban water management, 321 pages, Department of Civil and Environmental Engineering – Imperial College, London, London, 2003.

Research reports

  1. A. Efstratiadis, N. Mamassis, and C. Makropoulos, Synoptic report on the estimation of the capacity of water supply system of Athens, 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, 30 pages, October 2019.
  2. C. Makropoulos, D. Damigos, A. Efstratiadis, A. Koukouvinos, and A. Benardos, Synoptic report and final conclusions, Cost of raw water of the water supply of Athens, 32 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.
  3. C. Makropoulos, A. Efstratiadis, and A. Koukouvinos, Appraisal of financial cost and proposals for a rational management of the hydrosystem, Cost of raw water of the water supply of Athens, 73 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.
  4. C. Makropoulos, A. Koukouvinos, A. Efstratiadis, and N. Chalkias, Mehodology for estimation of the financial cost , Cost of raw water of the water supply of Athens, 40 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2010.

Engineering reports

  1. C. Maksimovic, H. S. Wheater, D. Koutsoyiannis, S. Prohaska, D. Peach, S. Djordevic, D. Prodanovic, C. Makropoulos, P. Docx, T. Dasic, M. Stanic, D. Spasova, and D. Brnjos, Final Report, Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina, Commissioner: Energy Financing Team, Switzerland, Contractors: CUW-UK, ICCI Limited, London, 2004.

Details on research projects

Participation as Project Director

  1. Cost of raw water of the water supply of Athens

    Duration: June 2010–December 2010

    Budget: €110 000

    Commissioned by: Fixed Assets Company EYDAP

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: C. Makropoulos

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

  1. OpenMI Life

    Duration: January 2006–December 2010

    The project's rationale lies in the Water Framework Directive,which demands an integrated approach to water management. This requires an ability to predict how catchment processes will interact. In most contexts, it is not feasible to build a single predictive model that adequately represents all the processes; therefore, a means of linking models of individual processes is required.The FP5 HarmonIT project's innovative and acclaimed solution, the Open Modelling Interface and Environment (OpenMI) met this need by simplifying the linking of hydrology related models.Its establishment will support and assist the strategic planning and integrated catchment management.

Details on engineering studies

  1. Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina

    Duration: April 2004–June 2004

    Commissioned by: Energy Financing Team, Switzerland

    Contractors:

    1. CUW-UK
    2. ICCI Limited

Published work in detail

Publications in scientific journals

  1. S. Tsattalios, I. Tsoukalas, P. Dimas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Advancing surrogate-based optimization of time-expensive environmental problems through adaptive multi-model search, Environmental Modelling and Software, doi:10.1016/j.envsoft.2023.105639, 2023, (in press).

    Complex environmental optimization problems often require computationally expensive simulation models to assess candidate solutions. However, the complexity of response surfaces necessitates multiple such assessments and thus renders the search procedure too laborious. Surrogate-based optimization is a powerful approach for accelerating convergence towards promising solutions. Here we introduce the Adaptive Multi-Surrogate Enhanced Evolutionary Annealing Simplex (AMSEEAS) algorithm, as an extension of SEEAS, which is another well-established surrogate-based global optimization method. AMSEEAS exploits the strengths of multiple surrogate models that are combined via a roulette-type mechanism, for selecting a specific metamodel to be activated in every iteration. AMSEEAS proves its robustness and efficiency via extensive benchmarking against SEEAS and other state-of-the-art surrogate-based global optimization methods in both theoretical mathematical problems and in a computationally demanding real-world hydraulic design application. The latter seeks for cost-effective sizing of levees along a drainage channel to minimize flood inundation, calculated by the time-expensive hydrodynamic model HEC-RAS.

    Full text: http://www.itia.ntua.gr/en/getfile/2266/1/documents/AMSEEAS.pdf (3595 KB)

  1. D. Nikolopoulos, G. Moraitis, G. Karavokiros, D. Bouziotas, and C. Makropoulos, Stress-testing alternative water quality sensor designs under cyber-physical attack scenarios, Environmental Sciences Proceedings, 21 (1), 17, doi:10.3390/environsciproc2022021017, 2022.

    Water systems are rapidly transforming into cyber-physical systems. Despite the benefits of remote control and monitoring, autonomous operation and connectivity, there is an expanded threat surface, which includes cyber-physical attacks. This study demonstrates a stress-testing methodology that focuses on assessing the performance of a contamination warning system, designed with alternative water quality (WQ) sensor placement strategies against cyber-physical attacks. The physical part of the attacks consists of backflow injection attacks with a contaminant, while the cyber part comprises cyber-attacks to the contamination warning system. The WQ sensor designs are generated with the Threat Ensemble Vulnerability Assessment and Sensor Placement Optimization Tool (TEVA-SPOT), based on optimizing various metrics. The coupled WDN and CPS operation, the deliberate contamination events, and the cyber-physical attacks, are simulated with the water system cyber-physical stress-testing platform RISKNOUGHT. Multidimensional resilience profile graphs are utilized to analyze performance, demonstrated in a benchmark case study. This type of assessment can be useful in risk assessment studies for water utilities as well as in WQ sensor placement optimization.

    Full text: http://www.itia.ntua.gr/en/getfile/2251/1/documents/environsciproc-21-00017.pdf (1778 KB)

    See also: https://www.mdpi.com/2673-4931/21/1/17

  1. G. Moraitis, I. Tsoukalas, P. Kossieris, D. Nikolopoulos, G. Karavokiros, D. Kalogeras, and C. Makropoulos, Assessing cyber-physical threats under water demand uncertainty, Environmental Sciences Proceedings, 21 (1), 18, doi:10.3390/environsciproc2022021018, October 2022.

    This study presents an approach for the assessment of cyber-physical threats to water distribution networks under the prism of the uncertainty which stems from the variability and stochastic nature of nodal water demands. The proposed framework investigates a single threat scenario under a spectrum of synthetic, yet realistic, system states which are driven by an ensemble of stochastically generated nodal demands. This Monte Carlo-type experiment enables the probabilistic inference about model outputs, and hence the derivation of probabilistic estimates over consequences. The approach is showcased for a cyber-physical attack scenario against the monitoring and control system of a benchmark network.

    Full text: http://www.itia.ntua.gr/en/getfile/2250/1/documents/environsciproc-21-00018.pdf (933 KB)

    See also: https://www.mdpi.com/2673-4931/21/1/18

  1. G.-K. Sakki, I. Tsoukalas, P. Kossieris, C. Makropoulos, and A. Efstratiadis, Stochastic simulation-optimisation framework for the design and assessment of renewable energy systems under uncertainty, Renewable and Sustainable Energy Reviews, 168, 112886, doi:10.1016/j.rser.2022.112886, 2022.

    As the share of renewable energy resources rapidly increases in the electricity mix, the recognition, representation, quantification, and eventually interpretation of their uncertainties become important. In this vein, we propose a generic stochastic simulation-optimization framework tailored to renewable energy systems (RES), able to address multiple facets of uncertainty, external and internal. These involve the system’s drivers (hydrometeorological inputs) and states (by means of fuel-to-energy conversion model parameters and energy market price), both expressed in probabilistic terms through a novel coupling of the triptych statistics, stochastics and copulas. Since the most widespread sources (wind, solar, hydro) exhibit several common characteristics, we first introduce the formulation of the overall modelling context under uncertainty, and then offer uncertainty quantification tools to put in practice the plethora of simulated outcomes and resulting performance metrics (investment costs, energy production, revenues). The proposed framework is applied to two indicative case studies, namely the design of a small hydropower plant (particularly, the optimal mixing of its hydro-turbines), and the long-term assessment of a planned wind power plant. Both cases reveal that the ignorance or underestimation of uncertainty may hide a significant perception about the actual operation and performance of RES. In contrast, the stochastic simulation-optimization context allows for assessing their technoeconomic effectiveness against a wide range of uncertainties, and as such provides a critical tool for decision making, towards the deployment of sustainable and financially viable RES.

    Full text: http://www.itia.ntua.gr/en/getfile/2229/1/documents/stochasticRES.pdf (6011 KB)

    See also: https://www.sciencedirect.com/science/article/pii/S1364032122007687

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

    1. Woon, K. S., Z. X. Phuang, J. Taler, P. S. Varbanov, C. T. Chong, J. J. Klemeš, and C. T. Lee, Recent advances in urban green energy development towards carbon neutrality, Energy, 126502, doi:10.1016/j.energy.2022.126502, 2022.

  1. A. Efstratiadis, P. Dimas, G. Pouliasis, I. Tsoukalas, P. Kossieris, V. Bellos, G.-K. Sakki, C. Makropoulos, and S. Michas, Revisiting flood hazard assessment practices under a hybrid stochastic simulation framework, Water, 14 (3), 457, doi:10.3390/w14030457, 2022.

    We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modelling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms to antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes are simulated by a hybrid 1D/2D modelling approach, which offers a good compromise between computational efficiency and accuracy. The proposed framework enables the estimation of the uncertainty of all flood-related quantities, by means of empirically-derived quantiles for given return periods. Finally, a set of easily applicable flood hazard metrics are introduced for the quantification of flood hazard.

    Full text: http://www.itia.ntua.gr/en/getfile/2170/1/documents/water-14-00457.pdf (6083 KB)

    See also: https://www.mdpi.com/2073-4441/14/3/457

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

    1. Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas, Forensic hydrology: a complete reconstruction of an extreme flood event in data-scarce area, Hydrology, 9(5), 93, doi:10.3390/hydrology9050093, 2022.
    2. Afzal, M. A., S. Ali, A. Nazeer, M. I. Khan, M. M. Waqas, R. A. Aslam, M. J. M. Cheema, M. Nadeem, N. Saddique, M. Muzammil, and A. N. Shah, Flood inundation modeling by integrating HEC–RAS and satellite imagery: A case study of the Indus river basin, Water, 14(19), 2984, doi:10.3390/w14192984, 2022.
    3. Vangelis, H., I. Zotou, I. M. Kourtis, V. Bellos, and V. A. Tsihrintzis, Relationship of rainfall and flood return periods through hydrologic and hydraulic modeling, Water, 14(22), 3618, doi:10.3390/w14223618, 2022.

  1. P. Kossieris, I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Generic framework for downscaling statistical quantities at fine time-scales and its perspectives towards cost-effective enrichment of water demand records, Water, 13 (23), 3429, doi:10.3390/w13233429, 2021.

    The challenging task of generating synthetic time series at finer temporal scales than the observed data, embeds the reconstruction of a number of essential statistical quantities at the desirable (i.e., lower) scale of interest. This paper introduces a parsimonious and general framework for the downscaling of statistical quantities, based solely on available information at coarser time scales. The methodology is based on three key elements: a) the analysis of statistics’ behaviour across multiple temporal scales; b) the use of parametric functions to model this behaviour; and c) the exploitation of extrapolation capabilities of the functions to downscale the associated statistical quantities at finer scales. Herein, we demonstrate the methodology using residential water demand records, and focus on the downscaling of the following key quantities: variance, L-variation, L-skewness and probability of zero value (no demand; intermittency), which are typically used to parameterise a stochastic simulation model. Specifically, we downscale the above statistics down to 1 min scale, assuming two scenarios of initial data resolution, i.e., 5 and 10 min. The evaluation of the methodology on several cases indicates that the four statistics can be well reconstructed. Going one step further, we place the downscaling methodology in a more integrated modelling framework for a cost-effective enhancement of fine-resolution records with synthetic ones, embracing the current limited availability of fine-resolution water demand measurements.

    Full text: http://www.itia.ntua.gr/en/getfile/2164/1/documents/water-13-03429.pdf (2042 KB)

    See also: https://www.mdpi.com/2073-4441/13/23/3429

  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. H. Elsayed, S. Djordjević, D. Savic, I. Tsoukalas, and C. Makropoulos, The Nile water-food-energy nexus under uncertainty: Impacts of the Grand Ethiopian Renaissance Dam, Journal of Water Resources Planning and Management - ASCE, 146 (11), 04020085, doi:10.1061/(ASCE)WR.1943-5452.0001285, 2020.

    Achieving a water, food, and energy (WFE) nexus balance through policy interventions is challenging in a transboundary river basin because of the dynamic nature and intersectoral complexity that may cross borders. The Nile basin is shared by a number of riparian countries and is currently experiencing rapid population and economic growth. This has sparked new developments to meet the growing water, food, and energy demands, alleviate poverty, and improve the livelihood in the basin. Such developments could result in basinwide cooperation or trigger conflicts among the riparian countries. A system dynamics model was developed for the entire Nile basin and integrated with the food and energy sectors in Egypt to investigate the future of the WFE nexus with and without the Grand Ethiopian Renaissance Dam (GERD) during filling and subsequent operation using basinwide stochastically generated flows. Different filling rates from 10% to 100% of the average monthly flow are considered during the filling process. Results suggest that the GERD filling and operation would affect the WFE nexus in Egypt, with the impact likely to be significant if the filling process occurred during a dry period. Food production from irrigated agriculture would be reduced by 9%–19% during filling and by about 4% during GERD operation compared with the case without it. The irrigation water supply and hydropower generation in Sudan will be reduced during the filling phase of the GERD, but this is expected to be improved during the dam operation phase as a result of the regulation afforded by the GERD. Ethiopian hydropower generation is expected to be boosted by the GERD during the filling and operation of the dam, adding an average of 15,000  GWh/year once GERD comes online. Lastly, the results reveal the urgency of cooperation and coordination among the riparian countries to minimize the regional risks and maximize the regional rewards associated with the GERD.

    See also: https://ascelibrary.org/doi/10.1061/%28ASCE%29WR.1943-5452.0001285

  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. I. Tsoukalas, P. Kossieris, and C. Makropoulos, Simulation of non-Gaussian correlated random variables, stochastic processes and random fields: Introducing the anySim R-Package for environmental applications and beyond, Water, 12 (6), 1645, doi:10.3390/w12061645, 2020.

    Stochastic simulation has a prominent position in a variety of scientific domains including those of environmental and water resources sciences. This is due to the numerous applications that can benefit from it, such as risk-related studies. In such domains, stochastic models are typically used to generate synthetic weather data with the desired properties, often resembling those of hydrometeorological observations, which are then used to drive deterministic models of the understudy system. However, generating synthetic weather data with the desired properties is not an easy task. This is due to the peculiarities of such processes, i.e., non-Gaussianity, intermittency, dependence, and periodicity, and the limited availability of open-source software for such purposes. This work aims to simplify the synthetic data generation procedure by providing an R-package called anySim, specifically designed for the simulation of non-Gaussian correlated random variables, stochastic processes at single and multiple temporal scales, and random fields. The functionality of the package is demonstrated through seven simulation studies, accompanied by code snippets, which resemble real-world cases of stochastic simulation (i.e., generation of synthetic weather data) of hydrometeorological processes and fields (e.g., rainfall, streamflow, temperature, etc.), across several spatial and temporal scales (ranging from annual down to 10-min simulations).

    Full text: http://www.itia.ntua.gr/en/getfile/2049/1/documents/water-12-01645.pdf (4754 KB)

    See also: https://www.mdpi.com/2073-4441/12/6/1645

  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. I. Koutiva, and C. Makropoulos, Exploring the effects of alternative water demand management strategies using an agent-based model, Water, 11 (11), 2216, doi:10.3390/w11112216, 2019.

    Integrated urban water management calls for tools that can analyze and simulate the complete cycle including the physical, technical, and social dimensions. Scientific advances created simulation tools able to simulate the urban water cycle as realistically as possible. However, even these tools cannot effectively simulate the social component and quantify how behaviors are shaped by external stress factors, such as climate and policies. In this work, an agent-based modeling tool, urban water agents' behavior (UWAB) is used to simulate the water demand behavior of households and how it is influenced by water demand management strategies and drought conditions. UWAB was applied in Athens, Greece to explore the effect of different water demand management strategies to the reliability of the Athens hydrosystem. The results illustrate the usability of UWAB to support decision makers in identifying how “strict” water demand management measures are needed and when and for how long to deploy them in order to alleviate potential water supply issues.

    Full text: http://www.itia.ntua.gr/en/getfile/2004/1/documents/water-11-02216.pdf (1665 KB)

    See also: https://www.mdpi.com/2073-4441/11/11/2216

  1. C. Makropoulos, and D. Savic, Urban hydroinformatics: past, present and future, Water, 11 (10), 1959, doi:10.3390/w11101959, 2019.

    Hydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the discipline’s past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation. Building on this state-of-art landscape, the paper then attempts to provide an overview of key developments that are coming up, on the discipline’s horizon, focusing on developments relevant to urban water management, while at the same time, highlighting important legal, ethical and technical challenges that need to be addressed to ensure that the brightest aspects of this potential future are realized. Despite obvious limitations imposed by a single paper’s ability to report on such a diverse and dynamic field, it is hoped that this work contributes to a better understanding of both the current state of hydroinformatics and to a shared vision on the most exciting prospects for the future evolution of the discipline and the water sector it serves.

    Full text: http://www.itia.ntua.gr/en/getfile/1989/1/documents/water-11-01959-v2.pdf (662 KB)

    See also: https://www.mdpi.com/2073-4441/11/10/1959

  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. P. Kossieris, I. Tsoukalas, C. Makropoulos, and D. Savic, Simulating marginal and dependence behaviour of water demand processes at any fine time scale, Water, 11 (5), 885, doi:10.3390/w11050885, 2019.

    Uncertainty-aware design and management of urban water systems lies on the generation of synthetic series that should precisely reproduce the distributional and dependence properties of residential water demand process (i.e., significant deviation from Gaussianity, intermittent behaviour, high spatial and temporal variability and a variety of dependence structures) at various temporal and spatial scales of operational interest. This is of high importance since these properties govern the dynamics of the overall system, while prominent simulation methods, such as pulse-based schemes, address partially this issue by preserving part of the marginal behaviour of the process (e.g., low-order statistics) or neglecting the significant aspect of temporal dependence. In this work, we present a single stochastic modelling strategy, applicable at any fine time scale to explicitly preserve both the distributional and dependence properties of the process. The strategy builds upon the Nataf’s joint distribution model and particularly on the quantile mapping of an auxiliary Gaussian process, generated by a suitable linear stochastic model, to establish processes with the target marginal distribution and correlation structure. The three real-world case studies examined, reveal the efficiency (suitability) of the simulation strategy in terms of reproducing the variety of marginal and dependence properties encountered in water demand records from 1-min up to 1-h.

    Full text: http://www.itia.ntua.gr/en/getfile/1950/1/documents/water-11-00885.pdf (6862 KB)

    See also: https://www.mdpi.com/2073-4441/11/5/885

  1. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.

    The generation of hydrometeorological time series that exhibit a given probabilistic and stochastic behavior across multiple temporal levels, traditionally expressed in terms of specific statistical characteristics of the observed data, is a crucial task for risk-based water resources studies, and simultaneously a puzzle for the community of stochastics. The main challenge stems from the fact that the reproduction of a specific behavior at a certain temporal level does not imply the reproduction of the desirable behavior at any other level of aggregation. In this respect, we first introduce a pairwise coupling of Nataf-based stochastic models within a disaggregation scheme, and next we propose their puzzle-type configuration to provide a generic stochastic simulation framework for multivariate processes exhibiting any distribution and any correlation structure. Within case studies we demonstrate two characteristic configurations, i.e., a three-level one, operating at daily, monthly and annual basis, and a two-level one to disaggregate daily to hourly data. The first configuration is applied to generate correlated daily rainfall and runoff data at the river basin of Achelous, Western Greece, which preserves the stochastic behavior of the two processes at the three temporal levels. The second configuration disaggregates daily rainfall, obtained from a meteorological station at Germany, to hourly. The two studies reveal the ability of the proposed framework to represent the peculiar behavior of hydrometeorological processes at multiple temporal resolutions, as well as its flexibility on formulating generic simulation schemes.

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

    1. Macian-Sorribes, H., J.-L. Molina, S. Zazo, and M. Pulido-Velázquez, Analysis of spatio-temporal dependence of inflow time series through Bayesian causal modelling, Journal of Hydrology, 597, 125722, doi:10.1016/j.jhydrol.2020.125722, 2021.
    2. Wang, Q., J. Zhou, K. Huang, L. Dai, B. Jia, L. Chen, and H. Qin, A procedure for combining improved correlated sampling methods and a resampling strategy to generate a multi-site conditioned streamflow process, Water Resources Management, 35, 1011-1027, doi:10.1007/s11269-021-02769-8, 2021.
    3. Brereton, R. G., P values and multivariate distributions: Non-orthogonal terms in regression models, Chemometrics and Intelligent Laboratory Systems, 210, 104264, doi:10.1016/j.chemolab.2021.104264, 2021.
    4. Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.
    5. Biondi, D., E. Todini, and A. Corina, A parsimonious post-processor for uncertainty evaluation of ensemble precipitation forecasts: An application to quantitative precipitation forecasts for civil protection purposes, Hydrology Research, 52(6), 1405-1422, doi:10.2166/nh.2021.045, 2021.
    6. Jahangir, M. S., and J. Quilty, Temporal hierarchical reconciliation for consistent water resources forecasting across multiple timescales: An application to precipitation forecasting, Water Resources Research, 58(6), e2021WR031862, doi:10.1029/2021WR031862, 2022.

  1. P. Kossieris, and C. Makropoulos, Exploring the statistical and distributional properties of residential water demand at fine time scales, Water, 10 (10), 1481, doi:10.3390/w10101481, 2018.

    Residential water demand consists one of the most uncertain factors posing extra difficulties in the efficient planning and management of urban water systems. Currently, high resolution data from smart meters provide the means for a better understanding and modelling of this variable at a household level and fine temporal scales. Having this in mind, this paper examines the statistical and distributional properties of residential water demand at a 15-minute and hourly scale, which are the temporal scales of interest for the majority of urban water modeling applications. Towards this, we investigate large residential water demand records of different characteristics. The analysis indicates that the studied characteristics of the marginal distribution of water demand vary among households as well as on the basis of different time intervals. Both month-to-month and hour-to-hour analysis reveal that the mean value and the probability of no demand exhibit high variability while the changes in the shape characteristics of the marginal distributions of the nonzero values are significantly less. The investigation of performance of 10 probabilistic models reveals that Gamma and Weibull distributions can be used to adequately describe the nonzero water demand records of different characteristics at both time scales.

    Full text: http://www.itia.ntua.gr/en/getfile/1904/1/documents/water-10-01481.pdf (23829 KB)

    See also: https://www.mdpi.com/2073-4441/10/10/1481/htm

  1. Ε. Psarrou, I. Tsoukalas, and C. Makropoulos, A Monte-Carlo-based method for the optimal placement and operation scheduling of sewer mining units in urban wastewater networks, Water, 10 (2), 200, doi:10.3390/w10020200, 2018.

    Pressures on water resources, which have increased significantly nowadays mainly due to rapid urbanization, population growth and climate change impacts, necessitate the development of innovative wastewater treatment and reuse technologies. In this context, a mid-scale decentralized technology concerning wastewater reuse is that of sewer mining. It is based on extracting wastewater from a wastewater system, treating it on-site and producing recycled water applicable for non-potable uses. Despite the technology’s considerable benefits, several challenges hinder its implementation. Sewer mining disturbs biochemical processes inside sewers and affects hydrogen sulfide build-up, resulting in odor, corrosion and health-related problems. In this study, a tool for optimal sewer mining unit placement aiming to minimize hydrogen sulfide production is presented. The Monte-Carlo method coupled with the Environmental Protection Agency’s Storm Water Management Model (SWMM) is used to conduct multiple simulations of the network. The network’s response when sewage is extracted from it is also examined. Additionally, the study deals with optimal pumping scheduling. The overall methodology is applied in a sewer network in Greece providing useful results. It can therefore assist in selecting appropriate locations for sewer mining implementation, with the focus on eliminating hydrogen sulfide-associated problems while simultaneously ensuring that higher water needs are satisfied.

    Full text: http://www.itia.ntua.gr/en/getfile/1903/1/documents/water-10-00200.pdf (8639 KB)

    See also: https://www.mdpi.com/2073-4441/10/2/200

  1. I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018.

    Hydrometeorological processes are typically characterized by temporal dependence, short‐ or long‐range (e.g., Hurst behavior), as well as by non‐Gaussian distributions (especially at fine time scales). The generation of long synthetic time series that resemble the marginal and joint properties of the observed ones is a prerequisite in many uncertainty‐related hydrological studies, since they can be used as inputs and hence allow the propagation of natural variability and uncertainty to the typically deterministic water‐system models. For this reason, it has been for years one of the main research topics in the field of stochastic hydrology. This work presents a novel model for synthetic time series generation, termed Symmetric Moving Average (neaRly) To Anything (SMARTA), that holds out the promise of simulating stationary univariate and multivariate processes with any‐range dependence and arbitrary marginal distributions, provided that the former is feasible and the latter have finite variance. This is accomplished by utilizing a mapping procedure in combination with the relationship that exists between the correlation coefficients of an auxiliary Gaussian process and a non‐Gaussian one, formalized through the Nataf's joint distribution model. The generality of SMARTA is stressed through two hypothetical simulation studies (univariate and multivariate), characterized by different dependencies and distributions. Furthermore, we demonstrate the practical aspects of the proposed model through two real‐world cases, one that concerns the generation of annual non‐Gaussian streamflow time series at four stations, and another that involves the synthesis of intermittent, non‐Gaussian, daily rainfall series at a single location.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.
    2. Cheng, Y., P. Feng, J. Li, Y. Guo, and P. Ren, Water supply risk analysis based on runoff sequence simulation with change point under changing environment, Advances in Meteorology, 9619254, doi:10.1155/2019/9619254, 2019.
    3. #Elsayed, H., S. Djordjević, and D. Savić, The Nile water, food and energy nexus – A system dynamics model, 7th International Computing & Control for the Water Industry Conference, Exeter, United Kingdom, 2019.

  1. I. Tsoukalas, S.M. Papalexiou, A. Efstratiadis, and C. Makropoulos, A cautionary note on the reproduction of dependencies through linear stochastic models with non-Gaussian white noise, Water, 10 (6), 771, doi:10.3390/w10060771, 2018.

    Since the prime days of stochastic hydrology back in 1960s, autoregressive (AR) and moving average (MA) models (as well as their extensions) have been widely used to simulate hydrometeorological processes. Initially, AR(1) or Markovian models with Gaussian noise prevailed due to their conceptual and mathematical simplicity. However, the ubiquitous skewed behavior of most hydrometeorological processes, particularly at fine time scales, necessitated the generation of synthetic time series to also reproduce higher-order moments. In this respect, the former schemes were enhanced to preserve skewness through the use of non-Gaussian white noise— a modification attributed to Thomas and Fiering (TF). Although preserving higher-order moments to approximate a distribution is a limited and potentially risky solution, the TF approach has become a common choice in operational practice. In this study, almost half a century after its introduction, we reveal an important flaw that spans over all popular linear stochastic models that employ non-Gaussian white noise. Focusing on the Markovian case, we prove mathematically that this generating scheme provides bounded dependence patterns, which are both unrealistic and inconsistent with the observed data. This so-called “envelope behavior” is amplified as the skewness and correlation increases, as demonstrated on the basis of real-world and hypothetical simulation examples.

    Full text: http://www.itia.ntua.gr/en/getfile/1848/1/documents/water-10-00771.pdf (14101 KB)

    See also: http://www.mdpi.com/2073-4441/10/6/771

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

    1. Papalexiou, S. M., Y. Markonis, F. Lombardo, A. AghaKouchak, and E. Foufoula‐Georgiou, Precise temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for stationary and non‐stationary processes, Water Resources Research, 54(10), 7435-7458, doi:10.1029/2018WR022726, 2018.
    2. Cheng, Y., P. Feng, J. Li, Y. Guo, and P. Ren, Water supply risk analysis based on runoff sequence simulation with change point under changing environment, Advances in Meteorology, 9619254, doi:10.1155/2019/9619254, 2019.
    3. Marković, D., S. Ilić, D. Pavlović, J. Plavšić, and N. Ilich, Multivariate and multi-scale generator based on non-parametric stochastic algorithms, Journal of Hydroinformatics, 21(6), 1102–1117, doi:10.2166/hydro.2019.071, 2019.
    4. Nazemi, A., M. Zaerpour, and E. Hassanzadeh, Uncertainty in bottom-up vulnerability assessments of water supply systems due to regional streamflow generation under changing conditions, Journal of Water Resources Planning and Management, 146(2), doi:10.1061/(ASCE)WR.1943-5452.0001149, 2020.
    5. Wang, Q., J. Zhou, K. Huang, L. Dai, B. Jia, L. Chen, and H. Qin, A procedure for combining improved correlated sampling methods and a resampling strategy to generate a multi-site conditioned streamflow process, Water Resources Management, 35, 1011-1027, doi:10.1007/s11269-021-02769-8, 2021.
    6. Zounemat-Kermani, M., A. Mahdavi-Meymand, and A. Hinkelmann, A comprehensive survey on conventional and modern neural networks: application to river flow forecasting, Earth Science Informatics, 14, 893-911, doi:10.1007/s12145-021-00599-1, 2021.
    7. Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.
    8. Jia, B., J. Zhou, Z. Tang, Z. Xu, X. Chen, and W. Fang, Effective stochastic streamflow simulation method based on Gaussian mixture model, Journal of Hydrology, 605, 127366, doi:10.1016/j.jhydrol.2021.127366, 2022.

  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. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018.

    Stochastic models in hydrology traditionally aim at reproducing the empirically derived statistical characteristics of the observed data rather than any specific distribution model that attempts to describe the usually non-Gaussian statistical behavior of the associated processes. SPARTA (Stochastic Periodic AutoRegressive To Anything) offers an alternative and novel approach which allows the explicit representation of each process of interest with any distribution model, while simultaneously establishes dependence patterns that cannot be fully captured by the typical linear stochastic schemes. Cornerstone of the proposed approach is the Nataf joint-distribution model, which is related with the Gaussian copula, combined with Gaussian periodic autoregressive processes. In order to obtain the target stochastic structure, we have also developed a computationally simple and efficient algorithm, based on a hybrid Monte-Carlo procedure that is used to approximate the required equivalent correlation coefficients. Theoretical and practical benefits of the proposed method, contrasted to outcomes from widely used stochastic models, are demonstrated by means of real-world as well as hypothetical monthly simulation examples involving both univariate and multivariate time series.

    Additional material:

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

    1. Papalexiou, S. M., Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency, Advances in Water Resources, 115, 234-252, doi:10.1016/j.advwatres.2018.02.013, 2018.
    2. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.
    3. Marković, D., S. Ilić, D. Pavlović, J. Plavšić, and N. Ilich, Multivariate and multi-scale generator based on non-parametric stochastic algorithms, Journal of Hydroinformatics, 21(6), 1102-1117, doi:10.2166/hydro.2019.071, 2019.
    4. #Elsayed, H., S. Djordjević, and D. Savić, The Nile water, food and energy nexus – A system dynamics model, 7th International Computing & Control for the Water Industry Conference, Exeter, United Kingdom, 2019.
    5. Nazemi, A., M. Zaerpour, and E. Hassanzadeh, Uncertainty in bottom-up vulnerability assessments of water supply systems due to regional streamflow generation under changing conditions, Journal of Water Resources Planning and Management, 146(2), doi:10.1061/(ASCE)WR.1943-5452.0001149, 2020.
    6. Barber, C., J. R. Lamontagne, and R. M. Vogel, Improved estimators of correlation and R2 for skewed hydrologic data, Hydrological Sciences Journal, 65(1), 87-101, doi:10.1080/02626667.2019.1686639, 2020.
    7. Dutta, R., and R. Maity, Temporal networks based approach for non‐stationary hydroclimatic modelling and its demonstration with streamflow prediction, Water Resources Research, 56(8), e2020WR027086, doi:10.1029/2020WR027086, 2020.
    8. Demetriou, E., G. Mallouppas, and C.Hadjistassou, Embracing carbon neutral electricity and transportation sectors in Cyprus, Energy, doi:10.1016/j.energy.2021.120625, 2021.
    9. Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.
    10. Zang, N., J. Zhu, X. Wang, Y. Liao, G. Cao, C. Li, Q. Liu, and Z. Yang, Eutrophication risk assessment considering joint effects of water quality and water quantity for a receiving reservoir in the South-to-North Water Transfer Project, China, Journal of Cleaner Production, 331, 129966, doi:10.1016/j.jclepro.2021.129966, 2021.
    11. Vanem, E., Analysing multivariate extreme conditions using environmental contours and accounting for serial dependence, Renewable Energy, doi:10.1016/j.renene.2022.11.033, 2022.

  1. S. Baki, E. Rozos, and C. Makropoulos, Designing water demand management schemes using a socio-technical modelling approach, Science of the Total Environment, 622, 1590–1602, doi:10.1016/j.scitotenv.2017.10.041, 2018.

    Although it is now widely acknowledged that urban water systems (UWSs) are complex socio- technical systems and that a shift towards a socio-technical approach is critical in achieving sustainable urban water management, still, more often than not, UWSs are designed using a segmented modelling approach. As such, either the analysis focuses on the description of the purely technical sub-system, without explicitly taking into account the system's dynamic socio- economic processes, or a more interdisciplinary approach is followed, but delivered through relatively coarse models, which often fail to provide a thorough representation of the urban water cycle and hence cannot deliver accurate estimations of the hydrosystem's responses. In this work we propose an integrated modelling approach for the study of the complete socio-technical UWS that also takes into account socio-economic and climatic variability. We have developed an integrated model, which is used to investigate the diffusion of household water conservation technologies and its effects on the UWS, under different socio-economic and climatic scenarios. The integrated model is formed by coupling a System Dynamics model that simulates the water technology adoption process, and the Urban Water Optioneering Tool (UWOT) for the detailed simulation of the urban water cycle. The model and approach are tested and demonstrated in an urban redevelopment area in Athens, Greece under different socio-economic scenarios and policy interventions. It is suggested that the proposed approach can establish quantifiable links between socio-economic change and UWS responses and therefore assist decision makers in designing more effective and resilient long-term strategies for water conservation.

  1. C. Makropoulos, E. Rozos, I. Tsoukalas, A. Plevri, G. Karakatsanis, L. Karagiannidis, E. Makri, C. Lioumis, K. Noutsopoulos, D. Mamais, K. Ripis, and T. Lytras, Sewer-mining: A water reuse option supporting circular economy, public service provision and entrepreneurship, Journal of Environmental Management, 216, 285–298, doi:10.1016/j.jenvman.2017.07.026, 2018.

    Water scarcity, either due to increased urbanisation or climatic variability, has motivated societies to reduce pressure on water resources mainly by reducing water demand. However, this practice alone is not sufficient to both protect resources and guarantee the quality of life water services underpin especially within a context of increased urbanisation. As such, the idea of water reuse has been gaining momentum for some time in the water sector and has recently found a more general context within the emerging concept of the Circular Economy. As a result of this growing trend, water recycling schemes at various scales have been applied worldwide. The most common scale of water reuse is reusing the effluent of a wastewater treatment plant for irrigation or industrial uses (e.g. cooling towers, or rinsing). This is favoured by economies of scale, but to be economically viable it requires that the recycled-water user is close enough to the treatment plant (and at a more or less similar or lower elevation), otherwise capital and operational costs for transmission getratherhigh. Another downside with this scale of (centralised) reuse is that this scheme does not break the monopoly of water supply, since it is again the water company that runs the treatment unit and provides the effluent for reuse and as such offers reduced benefits in terms of job creation, innovation drive and entrepreneurship. On the other side of the scale spectrum, at the level of the household, reuse options include mostly the reuse of grey water for non-potable uses (such as toilet flushing and garden irrigation). Although promising and with significant potential for demand reduction, this scale of reuse is not necessarily cost effective, with all costs borne by the end user, and usually relies on additional motivation, such as drought conditions or environmental attitudes to be implemented. This study argues for an intermediate scale of water reuse, termed sewer-mining, which is a water recycling scheme at the neighbourhood scale. We suggest it provides a feasible alternative reuse option when the geography of the wastewater treatment plant is problematic, it relies on mature treatment technologies and presents an excellent opportunity for Small Medium Enterprises (SME) to be involved in the water supply market, thus securing both environmental, social and economic benefits (including but not restricted to water for ecosystem services). To support this argument, we report on a pilot sewer mining application. The pilot, integrates to important subsystems: a packaged treatment unit and an Information and Communications Technology (ICT) infrastructure that would allow an operator to manage remotely several sewer mining units thus rendering the provided service economically viable even for SMEs. The paper reports on the pilot’s overall performance and critically evaluates the potential of the sewer mining idea to become a significant piece of the circular economy puzzle for water.

  1. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.

    Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 minute time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-minute time scale. The applicability of the methodology was assessed on a 5-minute rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

    Remarks:

    Temporary free access: https://authors.elsevier.com/c/1WHlB52cuBmT2

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2016.07.015

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Shrestha, A., M. S. Babel, S. Weesakul, and Z. Vojinovic, Developing intensity–duration–frequency (IDF) curves under climate change uncertainty: The case of Bangkok, Thailand, Water, 9(2), 145, doi:10.3390/w9020145, 2017.
    2. Li, X., A. Meshgi, X. Wang, J. Zhang, S. H. X. Tay, G. Pijcke, N. Manocha, M. Ong, M. T. Nguyen, and V. Babovic, Three resampling approaches based on method of fragments for daily-to-subdaily precipitation disaggregation, International Journal of Climatology, doi:10.1002/joc.5438, 2018.
    3. Papalexiou, S. M., Y. Markonis, F. Lombardo, A. AghaKouchak, and E. Foufoula‐Georgiou, Precise temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for stationary and non‐stationary processes, Water Resources Research, doi:10.1029/2018WR022726, 2018.
    4. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.
    5. Onof, C., and L.-P. Wang, Modelling rainfall with a Bartlett–Lewis process: New developments, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2019-406, 2019.

  1. I. Tsoukalas, C. Makropoulos, and S. Mihas, Identification of potential sewer mining locations: A Monte-Carlo based approach, Water Science and Technology, 76 (12), 3351–3357, doi:10.2166/wst.2017.487, 2017.

    Rapid urbanization affecting demand patterns, coupled with potential water shortages due to supply side impacts of climatic changes, has led to the emergence of new technologies for water and wastewater reuse. Sewer mining (SM) is a novel decentralized option that could potentially provide non-potable water for urban uses, including for example the irrigation of urban green spaces, providing a mid-scale solution to effective wastewater reuse. SM is based on extracting wastewater from local sewers and treatment at the point of demand and entails in some cases the return of treatment residuals back to the sewer system. Several challenges are currently in the way of such applications in Europe, including public perception, inadequate regulatory frameworks and engineering issues. In this paper we consider some of these engineering challenges, looking at the sewer network as a system where multiple physical, biological and chemical processes take place. We argue that prior to implementing SM, the dynamics of the sewer system should be investigated in order to identify optimum ways of deploying SM without endangering the reliability of the system. Specifically, both wastewater extraction and sludge return could result in altering the biochemical process of the network, thus unintentionally leading to degradation of the sewer infrastructure. We propose a novel Monte-Carlo based method that takes into account both spatial properties and water demand characteristics of a given area of SM deployment while simultaneously accounting for the variability of sewer network dynamics in order to identify potential locations for SM implementation. The outcomes of this study suggest that the method can provide rational results and useful guidelines for upscale SM technologies at a city level.

    Full text: http://www.itia.ntua.gr/en/getfile/1909/1/documents/wst076123351.pdf (459 KB)

    See also: https://iwaponline.com/wst/article/76/12/3351-3357/38389

  1. E. Rozos, I. Tsoukalas, K. Ripis, E. Smeti, and C. Makropoulos, Turning black into green: Ecosystem services from treated wastewater, Desalination and Water Treatment, 91 (2017), 2017.

    To reduce the impact of urban effluents on the environment, strict regulatory requirements have been set up for the disposal of wastewater, in most parts of the western world, requiring treatment before disposal. At the same time, the urban environment requires water inflows to satisfy a range of urban water demands, and the corresponding water abstractions put pressure on (often scarce) water resources. A suggested synergistic solution is to use the effluents from treatment plants as an alternative resource for irrigation or for industrial uses. Despite the existence of numerous successful applications, this practice is not very common mainly because of increased capital and operational costs, usually exceeding the cost of fresh water. A possible response of the market to this drawback could be to introduce in-situ small scale treatment units to cover local water needs. In this study, we assess the benefits of such a compact wastewater treatment unit that is used to provide water for irrigating an urban green area. Apart from the aesthetic improvement, the evaporative cooling (latent heat), which reduces the air temperature, is expected to have a positive impact on thermal comfort. A pilot scheme was deployed in KEREFYT, the research centre of the Athens Water Supply and Sewerage Company (EYDAP). This scheme was simulated with the UWOT model to estimate heat fluxes and the results were fed into Energy2D (a model that simulates heat transfer) to estimate the expected temperature drop. The results are promising and suggest that these technologies could play an important role in a more sustainable, circular water economy.

    Full text: http://www.itia.ntua.gr/en/getfile/1715/1/documents/Manuscript_subm2_CM.pdf (636 KB)

  1. G. Kochilakis, D. Poursanidis, N. Chrysoulakis, V. Varella, V. Kotroni, G. Eftychidis, K. Lagouvardos, C. Papathanasiou, G. Karavokiros, M. Aivazoglou, C. Makropoulos, and M. Mimikou, FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas, Open Geosciences, 8, 711–727, doi:10.1515/geo-2016-0068, 2016.

    A web-based Decision Support System, named FLIRE DSS, for combined forest fire control and planning as well as flood risk management, has been developed and is presented in this paper. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of the web based DSS without the need of local installation of complex software and their maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in such a way plan its efficient elimination. Also, during dry periods, agencies can implement “what-if” scenarios for areas that are prone to fire and thus have available plans for forest fire management in case such scenarios occur. Flood services include flood maps and flood-related warnings and become available to relevant authorities for visualization and further analysis on a daily basis. When flood warnings are issued, relevant authorities may proceed to efficient evacuation planning for the areas that are likely to flood and thus save human lives. Real-time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real-time, and a high resolution weather forecast grid supports flood modeling as well as the development of “what-if” scenarios for the fire modeling. All these can be accessed by various computer sources including PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. All these methods and tools provide the end users with the necessary information to design an operational plan for the elimination of the fire events and the efficient management of the flood events in almost real time. Concluding, the FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.

    Full text: http://www.itia.ntua.gr/en/getfile/1766/1/documents/FLIRE.pdf (1400 KB)

  1. G. Kochilakis, D. Poursanidis, N. Chrysoulakis, V. Varella, V. Kotroni, G. Eftychidis, K. Lagouvardos, C. Papathanasiou, G. Karavokiros, M. Aivazoglou, C. Makropoulos, and M. Mimikou, A web based DSS for the management of floods and wildfires (FLIRE) in urban and periurban areas, Environmental Modelling and Software, 86, 111–115, doi:10.1016/j.envsoft.2016.09.016, 2016.

    The FLIRE DSS is a web-based Decision Support System for the combined forest and flood risk management and planning. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of web based DSS with no need of local complex infrastructure and maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in that way to plan its efficient elimination. Also, they can implement “what-if” scenarios for areas prone to fire and thus develop plans for forest fire management. Flood services include flood maps and flood-related warnings; these become available to relevant authorities for visualization and further analysis on a daily basis. Real time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real time and a high resolution weather forecast grid support flood modeling and “what-if” scenarios for the fire modeling. The innovations of the FLIRE DSS are the use of common Earth Observation (EO) data as the backbone of the system to produce data for the support of fire and flood models, the common use of weather related information, the distributed architecture of the system and the web-based access of it with no need for installation of dedicated software. All these can be accessed by all means of computer sources like PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.

    Full text: http://www.itia.ntua.gr/en/getfile/1764/1/documents/FLIRE_paper.pdf (730 KB)

  1. P. Kossieris, C. Makropoulos, E. Creaco, L. Vamvakeridou-Lyroudia, and D. Savic, Assessing the applicability of the Bartlett-Lewis model in simulating residential water demands, Procedia Engineering, 154, 123–131, 2016.

    This paper presents the set-up and application of the Bartlett-Lewis clustering mechanism to simulate residential water demand at fine, i.e. sub-hourly, time scales. Two different variants of the model, i.e., the original and the random-parameter model, are examined. The models are assessed in terms of preserving the main statistical characteristics and temporal properties of demand series at a range of fine time scales, i.e., from 1-min up to 15-min. The comparison against the typical Poisson rectangular pulse model showed that clustering mechanism enables a better reproduction of demand characteristics at levels of aggregation other than those used in the fitting procedure.

    See also: http://doi.org/10.1016/j.proeng.2016.07.429

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

    1. Onof, C., and L.-P. Wang, Modelling rainfall with a Bartlett–Lewis process: New developments, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2019-406, 2019.

  1. E. Creaco, P. Kossieris, L. Vamvakeridou-Lyroudia, C. Makropoulos, Z. Kapelan, and D. Savic, Parameterizing residential water demand pulse models through smart meter readings, Environmental Modelling and Software, 80, 33–40, 2016.

    This paper proposes a method for parameterizing the Poisson models for residential water demand pulse generation, which consider the dependence of pulse duration and intensity. The method can be applied to consumption data collected in households through smart metering technologies. It is based on numerically searching for the model parameter values associated with pulse frequencies, durations and intensities, which lead to preservation of the mean demand volume and of the cumulative trend of demand volumes, at various time aggregation scales at the same time. The method is applied to various case studies, by using two time aggregation scales for demand volumes, i.e. fine aggregation scale (1 min or 15 min) and coarse aggregation scale (1 day). The fine scale coincides with the time resolution for reading acquisition through smart metering whereas the coarse scale is obtained by aggregating the consumption values recorded at the fine scale. Results show that the parameterization method presented makes the Poisson model effective at reproducing the measured demand volumes aggregated at both time scales. Consistency of the pulses improves as the fine scale resolution increases.

    See also: http://doi.org/10.1016/j.envsoft.2016.02.019

  1. G. Karavokiros, A. Lykou, I. Koutiva, J. Batica, A. Kostaridis, A. Alves, and C. Makropoulos, Providing evidence-based, intelligent support for flood resilient planning and policy: the PEARL Knowledge Base, Water, 8 (9), 392, doi:10.3390/w8090392, 2016.

    While flood risk is evolving as one of the most imminent natural hazards and the shift from a reactive decision environment to a proactive one sets the basis of the latest thinking in flood management, the need to equip decision makers with necessary tools to think about and intelligently select options and strategies for flood management is becoming ever more pressing. Within this context, the PEARL intelligent knowledge-base (PEARL KB) of resilience strategies is presented here as an environment that allows end-users to navigate from their observed problem to a selection of possible options and interventions worth considering within an intuitive visual web interface assisting advanced interactivity. Incorporation of real case studies within the PEARL KB enables the extraction of (evidence-based) lessons from all over the word, while the KB’s collection of methods and tools directly supports the optimal selection of suitable interventions. The Knowledge-Base also gives access to the PEARL KB FRI tool, which is an online tool for resilience assessment at a city level available to authorities and citizens. We argue that the PEARL KB equips authorities with tangible and operational tools that can improve strategic and operational flood risk management by assessing and eventually increasing resilience, while building towards the strengthening of risk governance. The online tools that the PEARL KB gives access to, were demonstrated and tested in the city of Rethymno, Greece.

    Full text: http://www.itia.ntua.gr/en/getfile/1649/1/documents/water-08-00392.pdf (12503 KB)

  1. E. Rozos, D. Butler, and C. Makropoulos, An integrated system dynamics – cellular automata model for distributed water-infrastructure planning, Water Science and Technology: Water Supply, 17 (6), doi:10.2166/ws.2016.080, 2016.

    Modern distributed water-aware technologies (including, for example, grey water recycling and rainwater harvesting) enable water reuse at the scale of household or neighbourhood. Nevertheless, even though these technologies are in some cases economically advantageous, they have a significant handicap compared to the centralized urban water management options: it is not easy to estimate a priori the extent and the rate of the technology spread. This disadvantage is amplified in case of additional uncertainty due to expansion of an urban area. This overall incertitude is one of the basic reasons the stakeholders involved in urban water are sceptical about the distributed technologies, even in the cases these appear to have lower cost. In this study, we suggest a methodology that attempts to cope with this uncertainty by coupling a Cellular Automata and a System Dynamics model. The Cellular Automata model is used to create scenarios of urban expansion including the suitability of installing water-aware technologies for each new urban area. Then, the System Dynamics model is used to estimate the adoption rate of the technologies. Various scenarios based on different economic conditions and water prices are assessed. The suggested methodology is applied to an urban area in Attica, Greece.

  1. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.

    In water resources optimization problems, the objective function usually presumes to first run a simulation model and then evaluate its outputs. However, long simulation times may pose significant barriers to the procedure. Often, to obtain a solution within a reasonable time, the user has to substantially restrict the allowable number of function evaluations, thus terminating the search much earlier than required. A promising strategy to address these shortcomings is the use of surrogate modeling techniques. Here we introduce the Surrogate-Enhanced Evolutionary Annealing-Simplex (SEEAS) algorithm that couples the strengths of surrogate modeling with the effectiveness and efficiency of the evolutionary annealing-simplex method. SEEAS combines three different optimization approaches (evolutionary search, simulated annealing, downhill simplex). Its performance is benchmarked against other surrogate-assisted algorithms in several test functions and two water resources applications (model calibration, reservoir management). Results reveal the significant potential of using SEEAS in challenging optimization problems on a budget.

    Related works:

    • [77] Early presentation if EGU conference

    Full text: http://www.itia.ntua.gr/en/getfile/1587/2/documents/SEEAS_paper.pdf (4310 KB)

    Additional material:

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

    1. Dariane , A. B., and M. M. Javadianzadeh, Towards an efficient rainfall–runoff model through partitioning scheme, Water, 8, 63, doi:10.3390/w8020063, 2016.
    2. Yaseen, Z. M., O. Jaafar, R. C. Deo, O. Kisi, J. Adamowski, J. Quilty, and A. El-Shafie, Boost stream-flow forecasting model with extreme learning machine data-driven: A case study in a semi-arid region in Iraq, Journal of Hydrology, 542, 603-614, doi:10.1016/j.jhydrol.2016.09.035, 2016.
    3. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
    4. #Christelis, V., V. Bellos, and G. Tsakiris, Employing surrogate modelling for the calibration of a 2D flood simulation model, Sustainable Hydraulics in the Era of Global Change: Proceedings of the 4th IAHR Europe Congress (Liege, Belgium, 27-29 July 2016), A. S. Erpicum, M. Pirotton, B. Dewals, P. Archambeau (editors), CRC Press, 2016.
    5. Salazar, J. Z., P. M. Reed, J. D. Quinn, M. Giuliani, and A. Castelletti, Balancing exploration, uncertainty and computational demands in many objective reservoir optimization, Advances in Water Resources, 109, 196-210, doi:10.1016/j.advwatres.2017.09.014, 2017.
    6. Christelis, V., and A. Mantoglou, Physics-based and data-driven surrogate models for pumping optimization of coastal aquifers, European Water, 57, 481–488, 2017.
    7. #Thandayutham, K., E. Avital, N. Venkatesan, and A. Samad, Design and analysis of a marine current turbine, Proceedings of ASME 2017 Gas Turbine India Conference and Exhibition, GTINDIA2017-4912, V001T02A014, Bangalore, India, doi:10.1115/GTINDIA2017-4912, 2017.
    8. Christelis, V., R. G. Regis, and A. Mantoglou, Surrogate-based pumping optimization of coastal aquifers under limited computational budgets, Journal of Hydroinformatics, 20(1), 164-176, doi:10.2166/hydro.2017.063, 2018.
    9. Christelis, V., and A. G. Hughes, Metamodel-assisted analysis of an integrated model composition: an example using linked surface water – groundwater models, Environmental Modelling and Software, 107, 298-306, doi:10.1016/j.envsoft.2018.05.004, 2018.
    10. Zischg, A. P., G. Felder, M. Mosimann, V. Röthlisberger, and R. Weingartner, Extending coupled hydrological-hydraulic model chains with a surrogate model for the estimation of flood losses, Environmental Modelling and Software, 108, 174-185, doi:10.1016/j.envsoft.2018.08.009, 2018.
    11. Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers using seawater intrusion models of variable-fidelity and evolutionary algorithms, Water Resources Management, 33(2), 555-558, doi:10.1007/s11269-018-2116-0, 2019.
    12. Thandayutham, K., L. K. Mishra, and A. Samad, Optimal design of a marine current turbine using CFD and FEA, Proceedings of the Fourth International Conference in Ocean Engineering (ICOE2018), K. Murali, V. Sriram, A. Samad, N. Saha (editors), Lecture Notes in Civil Engineering, 23, 675-690, doi:10.1007/978-981-13-3134-3, 2019.
    13. Christelis, V., G. Kopsiaftis, and A. Mantoglou, Performance comparison of multiple and single surrogate models for pumping optimization of coastal aquifers, Hydrological Sciences Journal, 64(3), 336-349, doi:10.1080/02626667.2019.1584400, 2019.
    14. Cai, X., L. Gao, X. Li, and H-. Qiu, Surrogate-guided differential evolution algorithm for high dimensional expensive problems, Swarm and Evolutionary Computation, 48, 288-311, doi:10.1016/j.swevo.2019.04.009, 2019.
    15. Huot, P.-L., A. Poulin, C. Audet, and S. Alarie, A hybrid optimization approach for efficient calibration of computationally intensive hydrological models, Hydrological Sciences Journal, 64(9), 1204-1222, doi:10.1080/02626667.2019.1624922, 2019.
    16. Jahandideh-Tehrani, M., O. Bozorg-Haddad, and H. A. Loáiciga, Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview, Environmental Monitoring and Assessment, 191:439, doi:10.1007/s10661-019-7581-2, 2019.
    17. Sandoval, S., and J.-L. Bertrand-Krajewski, From marginal to conditional probability functions of parameters in a conceptual rainfall-runoff model: an event-based approach, Hydrological Sciences Journal, 64(11), 1340-1350, doi:10.1080/02626667.2019.1635696, 2019.
    18. Zhao, C. S., T. L. Pan, J. Xi, S. T. Yang, J. Zhao, X. J. Gan, L. P. Hou, and S. Y. Ding, Streamflow calculation for medium-to-small rivers in data scarce inland areas, Science of The Total Environment, 693, 133571, doi:10.1016/j.scitotenv.2019.07.377, 2019.
    19. Monteil, C., F. Zaoui, N. Le Moine, and F. Hendrickx, Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm, Hydrology and Earth System Sciences, 24, 3189-3209, 10.5194/hess-24-3189-2020, 2020.
    20. Muhammed, K. A., and R. Farmani, Energy optimization using a pump scheduling tool in water distribution systems, ARO – The Scientific Journal of Koya University, 8(1), 112-123, doi:10.14500/aro.10635, 2020.
    21. #Castro-Gama M., C. Agudelo-Vera, and D. Bouziotas, A bird’s-eye view of data validation in the drinking water industry of the Netherlands, The Handbook of Environmental Chemistry, Springer, Berlin, Heidelberg, doi:10.1007/698_2020_609, 2020.
    22. Xai, W., C. Shoemaker, T. Akhtar, and M.-T. Nguyen, Efficient parallel surrogate optimization algorithm and framework with application to parameter calibration of computationally expensive three-dimensional hydrodynamic lake PDE models, Environmental Modelling and Software, 135, 104910, doi:10.1016/j.envsoft.2020.104910, 2021.
    23. Saadatpour, M., S. Javaheri, A. Afshar, and S. S. Solis, Optimization of selective withdrawal systems in hydropower reservoir considering water quality and quantity aspects, Expert Systems with Applications, 184, 115474, doi:10.1016/j.eswa.2021.115474, 2021.
    24. Zhao, T., and B. Minsker, Efficient metamodel approach to handling constraints in nonlinear optimization for drought management, Journal of Water Resources Planning and Management, 147(12), doi:10.1061/(ASCE)WR.1943-5452.0001476, 2021.
    25. Anahideh, H., J. Rosenberger, and V. Chen, High-dimensional black-box optimization under uncertainty, Computers & Operations Research, 137, 105444, doi:10.1016/j.cor.2021.105444, 2022.
    26. Pang, M., E. Du, C. A. Shoemaker, and C. Zheng, Efficient, parallelized global optimization of groundwater pumping in a regional aquifer with land subsidence constraints, Journal of Environmental Management, 310, 114753, doi:10.1016/j.jenvman.2022.114753, 2022.
    27. Lu, W., W. Xia, and C. A. Shoemaker, Surrogate global optimization for identifying cost-effective green infrastructure for urban flood control with a computationally expensive inundation model, Water Resources Research, 58(4), e2021WR030928, doi:10.1029/2021WR030928, 2022.

  1. I. Tsoukalas, and C. Makropoulos, A surrogate based optimization approach for the development of uncertainty-aware reservoir operational rules: the case of Nestos hydrosystem, Water Resources Management, 29 (13), 4719–4734, doi:10.1007/s11269-015-1086-8, 2015.

    Operation of large-scale hydropower reservoirs is a complex problem that involves conflicting objectives, such as hydropower generation and water supply. Deriving optimal operational rules is a challenging task due to the non-linearity of the system dynamics and the uncertainty of future inflows and water demands. A common approach to derive optimal control policies is to couple simulation models with optimization algorithms. This paper in order to investigate the performance of a future reservoir and safely infer about its significance employs stochastic simulation, thus long synthetically generated time-series and a multi-objective version of the Parameterization-Simulation-Optimization (PSO) framework to develop uncertainty-aware operational rules. Furthermore, in order to handle the high computational effort that ensues from that coupling we investigate the potential of a surrogate-based multi-objective optimization algorithm, ParEGO. The PSO framework is deployed with WEAP21 water resources management model as simulation engine and MATLAB for the implementation of optimization algorithms. A comparison between NSGAII and ParEGO optimization algorithms is performed to assess the effectiveness of the proposed algorithm. The aforementioned comparison showed that ParEGO provides efficient approximations of the Pareto front while reducing the computational effort required. Finally, the potential benefit and the significance of the future reservoir is underlined.

    Full text: http://www.itia.ntua.gr/en/getfile/1569/1/documents/tsoukalas_WRM.pdf (2008 KB)

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

    1. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
    2. Christelis, V., and A. G. Hughes, Metamodel-assisted analysis of an integrated model composition: an example using linked surface water – groundwater models, Environmental Modelling and Software, doi:10.1016/j.envsoft.2018.05.004, 2018.

  1. I. Tsoukalas, and C. Makropoulos, Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty, Environmental Modelling and Software, 69, 396–413, doi:10.1016/j.envsoft.2014.09.023, 2015.

    Developing long term operation rules for multi-reservoir systems is complicated due to the number of decision variables, the non-linearity of system dynamics and the hydrological uncertainty. This uncertainty can be addressed by coupling simulation models with multi-objective optimisation algorithms driven by stochastically generated hydrological timeseries but the computational effort required imposes barriers to the exploration of the solution space. The paper addresses this by (a) employing a parsimonious multi-objective parameterization-simulation-optimization (PSO) framework, which incorporates hydrological uncertainty through stochastic simulation and allows the use of probabilistic objective functions and (b) by investigating the potential of multi-objective surrogate based optimisation (MOSBO) to significantly reduce the resulting computational effort. Three MOSBO algorithms are compared against two multi-objective evolutionary algorithms. Results suggest that MOSBOs are indeed able to provide robust, uncertainty-aware operation rules much faster, without significant loss of neither the generality of evolutionary algorithms nor of the knowledge embedded in domain-specific models.

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

    1. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
    2. Christelis, V., and A. G. Hughes, Metamodel-assisted analysis of an integrated model composition: an example using linked surface water – groundwater models, Environmental Modelling and Software, doi:10.1016/j.envsoft.2018.05.004, 2018.
    3. Christelis, V., G. Kopsiaftis, and A. Mantoglou, Performance comparison of multiple and single surrogate models for pumping optimization of coastal aquifers, Hydrological Sciences Journal, doi:10.1080/02626667.2019.1584400, 2019.

  1. D. Bouziotas, E. Rozos, and C. Makropoulos, Water and the City: Exploring links between urban growth and water demand management., Journal of Hydroinformatics, 17 (2), doi:10.2166/hydro.2014.053, 2015.

    Urban water management is currently understood as a socio-technical problem, including both technologies and engineering interventions as well as socio-economic dimensions and contexts vis a vis both end users and institutions. In this framework, perhaps the most important driver of urban water demand, at the intersection between engineering, social and economic domains, is urban growth. This paper examines aspects of the interplay between the dynamics of urban growth and the urban water cycle. Specifically, a cellular automata urban growth model is re-engineered to provide growth patterns at the level of detail needed by an urban water cycle model. The resulting toolkit is able to simulate spatial changes in urban areas while simultaneously estimating their water demand impact under different water demand management scenarios, with an emphasis on distributed technologies whose applicability depends on urban form. The method and tools are tested in the case study of Mesogeia, Greece and conclusions are drawn, regarding both the performance of the urban growth model and the effectiveness of different urban water management practices.

    Full text: http://www.itia.ntua.gr/en/getfile/1501/1/documents/Water-And-The-City_Preprint.pdf (763 KB)

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

    1. Bouziotas, D., and M. Ertsen, Socio-hydrology from the bottom up: A template for agent-based modeling in irrigation systems, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2017-107, 2017.

  1. P. Kossieris, S. Kozanis, A. Hashmi, E. Katsiri, L. Vamvakeridou-Lyroudia, R. Farmani, C. Makropoulos, and D. Savic, A web-based platform for water efficient households, Procedia Engineering, 89, 1128–1135, 2014.

    The advent of ICT services on water sector offers new perspective towards sustainable water management. This paper presents an innovative web-based platform, targeting primarily the household end-users. The platform enables consumers to monitor and control, on real-time basis, the water and energy consumption of their household providing valuable information and feedback. At the same time, the platform further supports end-users to modify and improve their consumption profile via an interactive educational process that comprises a variety of online tools and applications. This paper discusses the rationale, structure and technologies upon which the platform has been developed and presents an early prototype of the various tools, applications and facilities.

    Full text: http://www.itia.ntua.gr/en/getfile/1590/1/documents/kossieris_procedia2014.pdf (1131 KB)

  1. P. Kossieris, Panayiotakis, K. Tzouka, E. Rozos, and C. Makropoulos, An e-Learning approach for improving household water efficiency, Procedia Engineering, WDSA 2014, Bari, Italy, Water Distribution Systems Analysis, 2014.

    This paper, presents the development of an e-learning platform, associated with smart metering infrastructure, developed in Moodle. The platform aims to support further householders to improve the water efficiency of their household by understanding their current consumption and identifying practices, technologies that can save water. The platform is built around an interactive, multi-stage, educational process, which begins with a preparatory ("Exposing") stage in which the users receive useful information and feedback about their "water identity", continuous through a self-assessment ("Understanding") stage and finally provides (customized) smart and cost-effective tips and suggestions ("Acting" stage). This paper presents the components of the platform, including, inter alia, FAQ's, quizzes, advanced water calculators and customized tips.

    Full text: http://www.itia.ntua.gr/en/getfile/1502/3/documents/Paper_0272_Panagiotis_Kossieris_.pdf (554 KB)

    Additional material:

  1. E. Rozos, C. Makropoulos, and C. Maksimovic, Rethinking urban areas: an example of an integrated blue-green approach, Water Science and Technology: Water Supply, 13 (6), 1534–1542, doi:10.2166/ws.2013.140, 2013.

    The provision of high quality urban water services, the assets of which are often conceptualised as ‘blue infrastructure’, is essential for public health and quality of life in the cities. On the other hand, parks, recreation grounds, gardens, green roofs and in general ‘green infrastructure’, provide a range of (urban) ecosystem services (incl. quality of life and aesthetics) and could also be thought of as inter alia contributors to the mitigation of floods, droughts, noise, air pollution and Urban Heat Island (UHI) effects, improvement of biodiversity, amenity values and human health. Currently, these ‘blue’ and ‘green’ assets/infrastructure are planned to operate as two separate systems despite the obvious interactions between them (for example, low runoff coefficient of green areas resulting in reduction of stormwater flows, and irrigation of green areas by potable water in increasing pressure on water supply system). This study explores the prospects of a more integrated ‘blue-green’ approach – tested at the scale of a household. Specifically, UWOT (the Urban Water Optioneering Tool) was extended and used to assess the potential benefits of a scheme that employed locally treated greywater along with harvested rainwater for irrigating a green roof. The results of the simulations indicated that the blue-green approach combined the benefits of both ‘green’ and ‘blue’ technologies/services and at the same time minimised the disadvantages of each when installed separately.

  1. E. Rozos, and C. Makropoulos, Source to tap urban water cycle modelling, Environmental Modelling and Software, 41, 139–150, doi:10.1016/j.envsoft.2012.11.015, Elsevier, 1 March 2013.

    The continuous expansion of urban areas is associated with increased water demand, both for domestic and non-domestic uses. To cover this additional demand, centralised infrastructure, such as water supply and distribution networks tend to become more and more complicated and are eventually over-extended with adverse effects on their reliability. To address this, there exist two main strategies: (a) Tools and algorithms are employed to optimise the operation of the external water supply system, in an effort to minimise risk of failure to cover the demand (either due to the limited availability of water resources or due to the limited capacity of the transmission system and treatment plants) and (b) demand management is employed to reduce the water demand per capita. Dedicated tools do exist to support the implementation of these two strategies separately. However, there is currently no tool capable of handling the complete urban water system, from source to tap, allowing for an investigation of these two strategies at the same time and thus exploring synergies between the two. This paper presents a new version of the UWOT model (Makropoulos et al., 2008), which adopts a metabolism modelling approach and is now capable of simulating the complete urban water cycle from source to tap and back again: the tool simulates the whole water supply network from the generation of demand at the household level to the water reservoirs and tracks wastewater generation from the household through the wastewater system and the treatment plants to the water bodies. UWOT functionality is demonstrated in the case of the water system of Athens and outputs are compared against the current operational tool used by the Water Company of Athens. Results are presented and discussed: The discussion highlights the conditions under which a single source-to-tap model is more advantageous than dedicated subsystem models.

    Additional material:

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

    1. Rozos, E., A methodology for simple and fast streamflow modelling, Hydrological Sciences Journal, doi:10.1080/02626667.2020.1728475, 2020.

  1. S.M. Papalexiou, D. Koutsoyiannis, and C. Makropoulos, How extreme is extreme? An assessment of daily rainfall distribution tails, Hydrology and Earth System Sciences, 17, 851–862, doi:10.5194/hess-17-851-2013, 2013.

    The upper part of a probability distribution, usually known as the tail, governs both the magnitude and the frequency of extreme events. The tail behaviour of all probability distributions may be, loosely speaking, categorized in two families: heavy-tailed and light-tailed distributions, with the latter generating more “mild” and infrequent extremes compared to the former. This emphasizes how important for hydrological design is to assess correctly the tail behaviour. Traditionally, the wet-day daily rainfall has been described by light-tailed distributions like the Gamma, although heavier-tailed distributions have also been proposed and used, e.g. the Lognormal, the Pareto, the Kappa, and others. Here, we investigate the issue of tails for daily rainfall by comparing the up- per part of empirical distributions of thousands of records with four common theoretical tails: those of the Pareto, Lognormal, Weibull and Gamma distributions. Specifically, we use 15 029 daily rainfall records from around the world with record lengths from to 163 yr. The analysis shows that heavier-tailed distributions are in better agreement with the observed rainfall extremes than the more often used lighter tailed distributions, with clear implications on extreme event modelling and engineering design.

    Remarks:

    The initial version of the article and the discussion in Hydrology and Earth System Sciences Discussions (9, 5757–5778, 2012) can be seen at http://dx.doi.org/10.5194/hessd-9-5757-2012.

    Full text: http://www.itia.ntua.gr/en/getfile/1231/1/documents/hess-17-851-2013.pdf (3389 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-17-851-2013

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Breinl, K., T. Turkington and M. Stowasser, Stochastic generation of multi-site daily precipitation for applications in risk management, Journal of Hydrology, 498, 23-35, 2013.
    2. #Adirosi, E., L. Baldini, F. Lombardo, F. Russo and F. Napolitano, Comparison of different fittings of experimental DSD, AIP Conference Proceedings, 1558, 1669-1672, 2013.
    3. Hitchens, N. M., H. E. Brooks and R. S. Schumacher, Spatial and temporal characteristics of heavy hourly rainfall in the United States, Mon. Wea. Rev, 141, 4564–4575, 2013.
    4. Panagoulia, D., and E. I. Vlahogianni, Non-linear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates, Hydrological Processes, 28(4), 2281–2292, 2014.
    5. Serinaldi, F., and C. G. Kilsby, Simulating daily rainfall fields over large areas for collective risk estimation, Journal of Hydrology, 10.1016/j.jhydrol.2014.02.043, 2014.
    6. Serinaldi, F., and C. G. Kilsby, Rainfall extremes: Toward reconciliation after the battle of distributions, Water Resources Research, 50 (1), 336-352, 2014.
    7. Breinl, K., T. Turkington and M. Stowasser, Simulating daily precipitation and temperature: a weather generation framework for assessing hydrometeorological hazards, Meteorological Applications, 10.1002/met.1459, 2014.
    8. Alghazali, N. O. S., and D. A. H. Alawadi, Fitting statistical distributions of monthly rainfall for some Iraqi stations, Civil and Environmental Research, 6 (6), 40-46, 2014.
    9. Neykov, N. M., P. N. Neytchev and W. Zucchini, Stochastic daily precipitation model with a heavy-tailed component, Natural Hazards and Earth System Sciences, 14 (9), 2321-2335, 2014.
    10. Salinas, J. L., A. Castellarin, A. Viglione, S. Kohnová and T. R. Kjeldsen, Regional parent flood frequency distributions in Europe – Part 1: Is the GEV model suitable as a pan-European parent?, Hydrol. Earth Syst. Sci., 18, 4381-4389, 10.5194/hess-18-4381-2014, 2014.
    11. #Keighley, T., T. Longden, S. Mathew and S. Trück, Quantifying Catastrophic and Climate Impacted Hazards Based on Local Expert Opinions, FEEM Working Paper No. 093.2014, 2014.
    12. Serinaldi, F., and C.G. Kilsby, Stationarity is undead: Uncertainty dominates the distribution of extremes, Advances in Water Resources, 77, 17-36, 2015.
    13. Li, Z., Z. Li, W. Zhao and Y. Wang, Probability modeling of precipitation extremes over two river basins in northwest of China, Advances in Meteorology, art. no. 374127, 10.1155/2015/374127, 2015.
    14. Adirosi, E., L. Baldini, L. Lombardo, F. Russo, F. Napolitano, E. Volpi and A. Tokay, Comparison of different fittings of drop spectra for rainfall retrievals, Advances in Water Resources, 83, 55-67, 2015.
    15. Cavanaugh, N.R., A. Gershunov, A.K. Panorska and T.J. Kozubowski, The probability distribution of intense daily precipitation, Geophysical Research Letters, 42 (5), 1560-1567, 2015.
    16. Sherly, M., S. Karmakar, T. Chan and C. Rau, Design rainfall framework using multivariate parametric-nonparametric approach, J. Hydrol. Eng., 10.1061/(ASCE)HE.1943-5584.0001256, 04015049, 2015.
    17. Bellprat, O., F.C. Lott, C. Gulizia, H.R. Parker, L.A. Pampuch, I. Pinto, A. Ciavarella, P.A. Stott, Unusual past dry and wet rainy seasons over Southern Africa and South America from a climate perspective, Weather and Climate Extremes, 9, 36-46, 2015.

  1. E. Rozos, and C. Makropoulos, Assessing the combined benefits of water recycling technologies by modelling the total urban water cycle, Urban Water Journal, 9 (1), doi:10.1080/1573062X.2011.630096, February 2012.

    This study investigates the potential benefits of new technologies, modern appliance, and innovative techniques that help to improve the performance of the urban water cycle. Urbanisation is a major source of additional pressures (both qualitative and quantitative) on the environment. For example abstractions to cover the increased demands for water supply or alterations of the topographic and geomorphologic properties of the land cover result in considerable changes to the dynamics of the hydrosystem (change of average and maximum values of flows). Sustainable, water-aware technologies, like SUstainable Drainage Systems (SUDS) and rainwater harvesting schemes, can be implemented to reduce these adverse effects. These technologies introduce interactions between the components of the urban water cycle. Rainwater harvesting for example, apart from the potable water demand reduction, may have significant influence on the generated runoff. Consequently, an integrated modelling of the urban water cycle is necessary for the simulation of the water-aware technologies and the identification of their combined benefits. In this study, two hypothetical developments implement rainwater harvesting schemes and SUDS, and are simulated using the Urban Water Optioneering Tool (UWOT), which is able of using rainfall time series of arbitrary time step. The two hypothetical developments were studied to investigate the contribution of the water-aware technologies to the minimisation of the environmental pressures. Significantly different urban density was assigned to these developments to highlight the influence of urban density on the efficiency and reliability of the water-aware technologies. The results indicate that: (a) water-saving schemes like rainwater harvesting and greywater treatment can reduce significantly the pressures of new developments (e.g. reduction of potable water demand by 27%); (b) the reliability of the water-aware technologies decreases with urban density; (c) if localised rainwater harvesting is implemented then the efficiency of the water appliances influences considerably the generated runoff.

    Additional material:

  1. E. Rozos, C. Makropoulos, and D. Butler, Design robustness of local water-recycling schemes, Journal of Water Resources Planning and Management - ASCE, 136 (5), 531–538, doi:10.1061/(ASCE)WR.1943-5452.0000067, 2010.

    The implementation of local water recycling and reuse practices is considered as a possible approach to managing issues of water scarcity. The sustainable design and implementation of a water recycle/reuse scheme has to achieve an optimum compromise between costs (including energy) and benefits (potable water demand reduction). Another factor that should be taken into account is the influence of potential changes in climatic conditions to the scheme’s efficiency. These issues were assessed in this study using the urban water optioneering tool. Two water-recycling schemes, a rainwater harvesting and a combination of rainwater harvesting and local greywater recycling, were assessed. The trade-off between potable water demand reduction, capital/operational cost, and energy consumption of the two schemes was derived under three basic climatic conditions (oceanic, Mediterranean, and desert) using evolutionary optimization. Furthermore, the impact of changing climatic conditions on the suggested schemes was analyzed to assess the robustness of the proposed design choices to climatic changes. The results indicate that schemes that are efficient in their use of local greywater are less susceptible to changes in climatic conditions, while schemes based exclusively on rainwater harvesting are more susceptible to changes the more efficient they become.

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

    1. Tong Thi Hoang Duong, Avner Adin, David Jackman, Peter van der Steen, Kala Vairavamoorthy, Urban water management strategies based on a total urban water cycle model and energy aspects – Case study for Tel Aviv, Urban Water Journal, Vol. 8, Iss. 2, 2011.
    2. Dragan A. Savić, Josef Bicik, Mark S. Morley, A DSS generator for multiobjective optimisation of spreadsheet-based models, Environmental Modelling and Software, Volume 26, Issue 5, May 2011, Pages 551-561, ISSN 1364-8152
    3. Newman, J. P., G. C. Dandy, and H. R. Maier, Multiobjective optimization of cluster-scale urban water systems investigating alternative water sources and level of decentralization, Water Resources Research, doi:10.1002/2013WR015233, 2014.

  1. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.

    Since 1990 extensive funds have been spent on research in climate change. Although Earth Sciences, including climatology and hydrology, have benefited significantly, progress has proved incommensurate with the effort and funds, perhaps because these disciplines were perceived as “tools” subservient to the needs of the climate change enterprise rather than autonomous sciences. At the same time, research was misleadingly focused more on the “symptom”, i.e. the emission of greenhouse gases, than on the “illness”, i.e. the unsustainability of fossil fuel-based energy production. Unless energy saving and use of renewable resources become the norm, there is a real risk of severe socioeconomic crisis in the not-too-distant future. A framework for drastic paradigm change is needed, in which water plays a central role, due to its unique link to all forms of renewable energy, from production (hydro and wave power) to storage (for time-varying wind and solar sources), to biofuel production (irrigation). The extended role of water should be considered in parallel to its other uses, domestic, agricultural and industrial. Hydrology, the science of water on Earth, must move towards this new paradigm by radically rethinking its fundamentals, which are unjustifiably trapped in the 19th-century myths of deterministic theories and the zeal to eliminate uncertainty. Guidance is offered by modern statistical and quantum physics, which reveal the intrinsic character of uncertainty/entropy in nature, thus advancing towards a new understanding and modelling of physical processes, which is central to the effective use of renewable energy and water resources.

    Remarks:

    Blogs and forums that have discussed this article: Climate science; Vertical news; Outside the cube.

    Update 2011-09-26: The removed video of the panel discussion of Nobelists entitled “Climate Changes and Energy Challenges” (held in the framework of the 2008 Meeting of Nobel Laureates at Lindau on Physics) which is referenced in footnote 1 of the paper, still cannot be located online. However, Larry Gould has an audio file of the discussion here.

    Full text: http://www.itia.ntua.gr/en/getfile/878/17/documents/hess-13-247-2009.pdf (1476 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-13-247-2009

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry, HESS Opinions "Crash tests for a standardized evaluation of hydrological models", Hydrology and Earth System Sciences, 13, 1757-1764, 2009.
    2. Hunt, D. V. L., I. Jefferson, M. R. Gaterell, and C. D. F. Rogers, Planning for sustainable utility infrastructure, Proceedings of the Institution of Civil Engineers – Urban Design and Planning, 162(DP4), 187-201, 2009.
    3. Makropoulos, C. K., and D. Butler, Distributed water infrastructure for sustainable communities, Water Resources Management, 24(11), 2795-2816, 2010.
    4. Jódar, J., J. Carrera, and A. Cruz, Irrigation enhances precipitation at the mountains downwind, Hydrology and Earth System Sciences, 14, 2003-2010, 2010.
    5. #Ladanai, S., and J. Vinterbäck, Biomass for Energy versus Food and Feed, Land Use Analyses and Water Supply, Report 022, Swedish University of Agricultural Sciences, ISSN 1654-9406, Uppsala, 2010.
    6. Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham, The influence of constrained fossil fuel emissions scenarios on climate and water resource projections, Hydrology and Earth System Sciences, 15, 1879-1893, 2011.
    7. #Montanari, A, Uncertainty of hydrological predictions, In: P. Wilderer (ed.) Treatise on Water Science, Vol. 2, 459–478, Oxford Academic Press, 2011.
    8. #Willems, P., J. Olsson, K. Arnbjerg-Nielsen, S. Beecham, A. Pathirana, I. Bulow Gregersen, H. Madsen, V.-T.-V. Nguyen, Practices and Impacts of Climate Change on Rainfall Extremes and Urban Drainage, IWA Publishing, London, 2012.
    9. Andrés-Doménech, I., A. Montanari and J. B. Marco, Efficiency of storm detention tanks for urban drainage systems under climate variability, Journal of Water Resources Planning and Management, 138 (1), 36-46, 2012.
    10. Montanari, A., Hydrology of the Po River: looking for changing patterns in river discharge, Hydrology and Earth System Sciences, 16, 3739-3747, doi:10.5194/hess-16-3739-2012, 2012.
    11. Voulvoulis, N., Water and sanitation provision in a low carbon society: The need for a systems approach, Journal of Renewable and Sustainable Energy, 4(4), 041403, doi:10.1063/1.3665797, 2012.
    12. #Skaggs, R., K. A. Hibbard, T. C. Janetos, and J. S. Rice, Climate and energy-water-land system interactions, Technical report to the U.S. Department of Energy in Support of the National Climate Assessment, Report No. PNNL-21185, Pacific Northwest National Laboratory, Richland, WA, 152 pp., 2012.
    13. Gunasekara, N. K., S. Kazama, D. Yamazaki and T. Oki, The effects of country-level population policy for enhancing adaptation to climate change, Hydrol. Earth Syst. Sci., 17, 4429-4440, 2013.
    14. Nastos, P. T., N. Politi, and J. Kapsomenakis, Spatial and temporal variability of the aridity index in Greece, Atmospheric Research, 19, 140-152, 2013.
    15. Hrachowitz, M., H.H.G. Savenije, G. Blöschl, J.J. McDonnell, M. Sivapalan, J.W. Pomeroy, B. Arheimer, T. Blume, M.P. Clark, U. Ehret, F. Fenicia, J.E. Freer, A. Gelfan, H.V. Gupta, D.A. Hughes, R.W. Hut, A. Montanari, S. Pande, D. Tetzlaff, P.A. Troch, S. Uhlenbrook, T. Wagener, H.C. Winsemius, R.A. Woods, E. Zehe, and C. Cudennec, A decade of Predictions in Ungauged Basins (PUB) — a review, Hydrological Sciences Journal, 58(6), 1198-1255, 2013.
    16. Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari and G. and Blöschl, Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene, Hydrology and Earth System Sciences, 17, 5013-5039, 2013.
    17. #Voulvoulis, N., The potential of water reuse as a management option for water security under the ecosystem services approach, Win4Life Conference, Tinos Island, Greece, 2013.
    18. Dette, H., and K. Sen, Goodness-of-fit tests in long-range dependent processes under fixed alternatives, ESAIM: Probability and Statistics, 17, 432-443, 2013.
    19. Ilich, N., An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series, Hydrological Sciences Journal, 59 (1), 85-98, 2014.
    20. Jain, S., Reference climate and water data networks for India, Journal of Hydrologic Engineering, 20(4), 02515001, doi:10.1061/(ASCE)HE.1943-5584.0001170, 2015.
    21. Voulvoulis, N., The potential of water reuse as a management option for water security under the ecosystem services approach, Desalination and Water Treatment, 53 (12), 3263-3271, doi:10.1080/19443994.2014.934106, 2015.
    22. #Rohli, R. V., Overview of applied climatology and water/energy resources, Selected Readings in Applied Climatology, R. V. Rohli and T. A. Joyner (editors), 144-155, Cambridge Scholars Publishing, 2015.
    23. #Kim, S.S.H., J.D. Hughes, D. Dutta, and J. Vaze, Why do sub-period consistency calibrations outperform traditional optimisations in streamflow prediction? Proceedings of 21st International Congress on Modelling and Simulation, 2061-2067, Gold Coast, Australia, 2015.
    24. Kim, S. S. H., J. D. Hughes, J. Chen, D. Dutta, and J. Vaze, Determining probability distributions of parameter performances for time-series model calibration: A river system trial, Journal of Hydrology, 530, 361–371, doi:10.1016/j.jhydrol.2015.09.073, 2015.
    25. Clark, C., Two rural temperature records in Somerset, UK, Weather, 70(10), 280-284, doi:10.1002/wea.2512, 2015.
    26. Tsonis, A. A., Randomness: a property of the mathematical and physical systems, Hydrological Sciences Journal, 61(9), 1591-1610, doi:10.1080/02626667.2014.992434, 2016.
    27. Di Baldassarre, G., L. Brandimarte, and K. Beven, The seventh facet of uncertainty: wrong assumptions, unknowns and surprises in the dynamics of human-water systems, Hydrological Sciences Journal, 61(9), 1748-1758, doi:10.1080/02626667.2015.1091460, 2016.
    28. Chrs, C. C., Models, the establishment, and the real world: Why do so many flood problems remain in the UK?, Journal of Geoscience and Environment Protection, 5, 44-59, doi:10.4236/gep.2017.52004, 2017.
    29. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
    30. Madani, E. M., P. E. Jansson, and I. Babelon, Differences in water balance between grassland and forest watersheds using long-term data, derived using the CoupModel, Hydrology Research, 49(1), 72-89, doi:10.2166/nh.2017.154, 2018.
    31. #Oliveira da Silva Araújo, R. C., L. Gomes Lourenço, O. Siena, and C. A. da Silva Müller, Inovação e sustentabilidade na produção e uso de energia: uma meta-análise, Sustentabilidade e Responsabilidade Social em Foco – Volume 4, Capítulo 3, Organização Editora Poisson, doi:10.5935/978-85-93729-64-5.2018B001, 2018.
    32. Biondi, D., and E. Todini, Comparing hydrological post‐processors including ensembles predictions into full predictive probability distribution of streamflow, Water Resources Research, 54(12), 9860-9882, doi:10.1029/2017WR022432, 2018.
    33. Dahlke, H. E., G. T. LaHue, M. R. L. Mautner, N. P. Murphy, N. K. Patterson, H. Waterhouse, F. Yang, and L. Foglia, Managed aquifer recharge as a tool to enhance sustainable groundwater management in California: Examples from field and modeling studies, Advances in Chemical Pollution, Environmental Management and Protection, 3, 215-275, doi:10.1016/bs.apmp.2018.07.003, 2018.
    34. Giudici, F., A. Castelletti, E. Garofalo, M. Giuliani, and H. R. Maier, Dynamic, multi-objective optimal design and operation of water-energy systems for small, off-grid islands, Applied Energy, 250, 605-616, doi:10.1016/j.apenergy.2019.05.084, 2019.
    35. Tzanakakis, V. A., A. N. Angelakis, N. V. Paranychianakis, Y. G. Dialynas, and G. Tchobanoglous, Challenges and opportunities for sustainable management of water resources in the island of Crete, Greece, Water, 12(6), 1538, doi:10.3390/w12061538, 2020.
    36. Ayzel, G., L. Kurochkina, and S. Zhuravlev, The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff, Hydrological Sciences Journal, doi:10.1080/02626667.2020.1762886, 2020.
    37. Yang, W., F. Jin, Y. Si, and Z. Li, Runoff change controlled by combined effects of multiple environmental factors in a headwater catchment with cold and arid climate in northwest China, Science of The Total Environment, 756, 143995, doi:10.1016/j.scitotenv.2020.143995, 2021.
    38. Kourgialas, N. N., A critical review of water resources in Greece: The key role of agricultural adaptation to climate-water effects, Science of the Total Environment, 775, 145857, doi:10.1016/j.scitotenv.2021.145857, 2021.
    39. #Eslamian S., and S. Parvizi, Engineering Hydrology: Impact on Sustainable Development, Climate Action, Encyclopedia of the UN Sustainable Development Goals, Leal Filho W., Azul A.M., Brandli L., Özuyar P.G., Wall T. (eds), Springer, Cham, doi:10.1007/978-3-319-71063-1_134-1, 2021.
    40. Lemonis, A. S. Skroufouta, and E. Baltas, An economic evaluation towards sustainability: The case of a hybrid renewable energy system in Greece, American Journal of Environmental and Resource Economics, 7(1), 37-47, doi:10.11648/j.ajere.20220701.15, 2022.
    41. Cui, Y., J. Jin, X. Bai, S. Ning, L. Zhang, C. Wu, and Y. Zhang, Quantitative evaluation and obstacle factor diagnosis of agricultural drought disaster risk using connection number and information entropy, Entropy, 24(7), 872, doi:10.3390/e24070872, 2022.
    42. Antwi, K., G. Adu, S. Adu, and J. Appiah-Yeboah, Physical and fuel properties of Bambusa Vulgaris of different age groups and their effect on producing biofuel, South-East European Forestry, 13(1), 53-64, doi:10.15177/seefor.22-05, 2022.
    43. Caixeta F., A. M. Carvalho, P. Saraiva, and F. Freire, Sustainability-focused excellence: A novel model integrating the water-energy-food nexus for agro-industrial companies, Sustainability, 14(15), 9678, doi:10.3390/su14159678, 2022.
    44. Angelakis, A. N., J. Krasilnikoff, and V. A. Tzanakakis, Evolution of water technologies and corresponding philosophy and sciences focusing on the Hellenic world through the millennia, Water, 14, 3149, doi:10.3390/w14193149, 2022.

  1. C. Makropoulos, D. Koutsoyiannis, M. Stanic, S. Djordevic, D. Prodanovic, T. Dasic, S. Prohaska, C. Maksimovic, and H. S. Wheater, A multi-model approach to the simulation of large scale karst flows, Journal of Hydrology, 348 (3-4), 412–424, 2008.

    The possible effects of water transfer through a tunnel from Fatnicko Polje to Bileca Reservoir on the hydrologic regime of the Bregava River located in Eastern Herzegovina, in an area characterised by a predominantly karstic terrain, are studied. Three different simulation models of the area were developed and their predictions compared under a range of current and future hydrological and operational management conditions. These are based on a range of modelling approaches from a simplified conceptual approach to a quasi-physically based one. Despite the large complexity of the natural system, the models gave good fits to existing flow data with the most simplified model providing the closest agreement to historical flows. Calibrated models were used to study the possible effects of the intervention under a range of operational scenarios and identify the sources of the associated uncertainties. The results of the work suggest that the system of tunnels in question has a favourable effect in reducing flood hazard in the area, thus liberating scarce land resources for agriculture, and in reducing flows in the Bregava River (especially high flows). It is also suggested that a significant reduction in the uncertainty of modelling the karstic environment can be achieved by an appropriate, complementary combination of modelling approaches viewed as a multi-model ensemble.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2007.10.011

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Epting, J., D. Romanov, P. Huggenberger, and G. Kaufmann, Integrating field and numerical modeling methods for applied urban karst hydrogeology, Hydrol. Earth Syst. Sci., 13, 1163-1184, 2009.
    2. Gattinoni, P., and V. Francani, Depletion risk assessment of the Nossana Spring (Bergamo, Italy) based on the stochastic modeling of recharge, Hydrogeology Journal, 18 (2), 325-337, 2010.
    3. #Makropoulos, C., E. Safiolea, S. Baki, E. Douka, A. Stamou and M. Mimikou, An integrated, multi-modelling approach for the assessment of water quality: lessons from the Pinios River case in Greece, International Environmental Modelling and Software Society (iEMSs), 2010 International Congress on Environmental Modelling and Software, Modelling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada, D. A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.), 2010.
    4. Bauwens, A., C. Sohier and A. Degré, Hydrological response to climate change in the Lesse and the Vesdre catchments: contribution of a physically based model (Wallonia, Belgium), Hydrol. Earth Syst. Sci., 15, 1745-1756, doi: 10.5194/hess-15-1745-2011, 2011.
    5. #Kukuric, N., van der Gun, J., Vasak, S., Bonacci, O., Polshkova, I., Tujchneider, O., Perez, M., Paris, M., D'elia, M., Ngatcha, B. N., Mudry, J., Chadha, D. K., Wendland, F., Berthold, G., Blum, A., Fritsche, H.-G., Kunkel, R., Wolter, R., Drobot, R., Szucs, P., Brouyere, S., Minciuna, M.-N., Lenart, L., Dassargues, A., Stevanović, Z., Kozák, P., Lazić, M., Szanyi, J., Polomčić, D., Kovács, B., Török, J., Milanović, S., Hajdin, B., Papic, P., Meglič, P. and Prestor, J., Transboundary Aquifers, in Transboundary Water Resources Management: A Multidisciplinary Approach (eds J. Ganoulis, A. Aureli and J. Fried), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, doi: 10.1002/9783527636655.ch4, 2011.
    6. Long, Y. Q., W. Li, W. X. Lu and T. T. Cui, Modeling the recovery of the spring flow and groundwater level in a depleted karst aquifer - a case study of the Jinci Spring, Applied Mechanics and Materials, 448-453, 989-994, 2013.
    7. Long, Y., T. Cui, Z. Yang, W. Li and Y. Guo, A coupled karst-porous groundwater model based on the adapted general head boundary, Environmental Engineering and Management Journal, 12 (9), 1757-1762, 2013.
    8. #Bonacci, O., Poljes, ponors and their catchments, Treatise on Geomorphology, 6, 112-120, 2013.
    9. Raynaud, F., V. Borrell-Estupina, S. Pistre, S. Van-Exter, N. Bourgeois, A. Dezetter and E. Servat, Combining hydraulic model, hydrogeomorphological observations and chemical analyses of surface waters to improve knowledge on karst flash floods genesis, Proc. IAHS, 369, 55-60, 10.5194/piahs-369-55-2015, 2015.
    10. Merheb, M., R. Moussa, C. Abdallah, F. Colin, C. Perrin, and N. Baghdadi, Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis, Hydrological Sciences Journal, doi:10.1080/02626667.2016.1140174, 2016.

Book chapters and fully evaluated conference publications

  1. V. Bellos, P. Kossieris, A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, P. Dimas, and C. Makropoulos, Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system, Proceedings of 7th IAHR Europe Congress "Innovative Water Management in a Changing Climate”, Athens, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.

    In this work, we investigate whether the parameters of physics-based hydraulic models, omnipresent in every relevant engineering handbook, can be used in blind trust in a real-world complex system. Here, we focus on the discharge coefficient for flows through a sluice gate and the Manning’s coefficient for steady flows, and we compare their typical literature values (experimentally derived) against the ones obtained via a “grey-box” calibration approach using real flow data from the complex raw-water conveyance system of Athens, Greece.

  1. G.-K. Sakki, A. Efstratiadis, and C. Makropoulos, Stress-testing for water-energy systems by coupling agent-based models, Proceedings of 7th IAHR Europe Congress "Innovative Water Management in a Changing Climate”, Athens, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.

    Full text:

  1. P. Dimas, D. Nikolopoulos, and C. Makropoulos, Simulation framework for pipe failure detection and replacement scheduling optimization, e-Proceedings of the 5th EWaS International Conference, Naples, 556–563, 2022.

    Identification of water network pipes susceptible to failure is a demanding task, which requires a coherent and extensive dataset that contains both their physical characteristics (i.e., pipe inner diameter, construction material, length, etc.) and a snapshot of their current state, including their age and failure history. As water networks are critical for human prosperity, the need to adequately forecast failure is immediate. A huge number of Machine Learning (ML) and AI models have been applied, furthermore, only a few of them have been coupled with algorithms that translate the failure probability into asset management decision support strategies. The latter should include pipe rehabilitation planning and/or replacement scheduling under monetary/time unit constraints. Additionally, the assessment of each decision is seldomly performed by developing performance indices stemming from simulation. Hence, in this work, the outline of a framework, able to incorporate pipe failure detection techniques utilizing statistical, ML and AI models with pipe replacement scheduling optimization and assessment of state-of-the-art resilience indices via simulation scenarios, is presented. The framework is demonstrated on a real world-based case study.

    Full text:

  1. V. Bellos, P. Kossieris, A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, P. Dimas, and C. Makropoulos, Fiware-enabled tool for real-time control of the raw-water conveyance system of Athens, Proceedings of the 39th IAHR World Congress, Granada, 2859–2865, doi:10.3850/IAHR-39WC2521716X20221468, International Association for Hydro-Environment Engineering and Research (IAHR), 2022.

    The raw water network system of Athens (Greece) is a complex infrastructure comprising around 500 km of aqueducts, conveying water from four reservoirs to four water treatment plants, while serving several other local users. In this work, we focus on the most important part of this system, namely the open-channel aqueduct of Mornos. This extends over 200 km and has a dual operation, namely water conveyance and flow regulation through temporary storage along the channel. This is achieved by a series of Λ-type structures, each one comprising sluice gates for flow control and a lateral ogee spillway. Currently, the regulation across the channel is performed through empirical rules, and according to target volumes requested by the operators of the downstream water treatment plants, on a daily basis. However, this management policy, which is strongly based on expert’s knowledge, is neither sustainable nor safe, from a resilience perspective. Furthermore, the system is subject to occasional failures, due to undesirable overflows resulting to non-negligible water losses. In order to establish an optimal control policy, we developed an operational tool for the real- time scheduling of the sluice gate settings. Core of the tool is a conceptual model that incorporates the following assumptions: a) the operation of a Λ-type structure does not affect the operation of the other relevant structures; b) the Λ-type structure has two flow components, namely through the sluice gate and over the lateral spillway, which can be described by theoretical and semi-empirical hydraulic formulas, considering as unknown parameters the discharge coefficients of all sluice gates. On the other hand, the known model inputs are the geometrical characteristics of Λ-type structures and the real-time data for discharge, water level and gate opening, which are obtained from the telemetric monitoring system of the channel. In this respect, the key challenge is the determination of the discharge coefficients. This is employed through a grey-box approach, in which the model parameters are calibrated in continuous mode, using real-time data. To check the plausibility of the discharge coefficients, as derived by the real-time calibration phase, a comparison is made with the corresponding coefficients derived by historical data (off-line calibration). The tool, along with other analytics and algorithms developed, has been seamlessly integrated with the existing legacy system (e.g., SCADA, databases) of the system’s operator (Athens Water Supply and Sewerage Company - EYDAP), using the FIWARE standardization protocol.

    Full text: http://www.itia.ntua.gr/en/getfile/2226/1/documents/04-07-014-1468.pdf (10700 KB)

  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.

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  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. I. Tsoukalas, C. Makropoulos, and A. Efstratiadis, Stochastic simulation of periodic processes with arbitrary marginal distributions, 15th International Conference on Environmental Science and Technology (CEST2017), Rhodes, Global Network on Environmental Science and Technology, 2017.

    Stochastic simulation of hydrological processes has a key role in water resources planning and management due to its ability to incorporate hydrological uncertainty within decision-making. Due to seasonality, the statistical characteristics of such processes are considered periodic functions, thus implying the use of cyclostationary stochastic models, typically using a common statistical distribution. Yet, this may not be representative of the statistical structure of such processes across all seasons. In this context, we introduce a novel model suitable for the simulation of periodic processes with arbitrary marginal distributions, called Stochastic Periodic AutoRegressive To Anything (SPARTA). Apart from capturing the periodic correlation structure of the underlying processes, its major advantages are a) the accurate preservation of seasonally-varying marginal distributions; b) the explicit generation of non-negative values; and c) the parsimonious model structure. Finally, the performance of the model is demonstrated through a theoretical (artificial) case study.

    Full text: http://www.itia.ntua.gr/en/getfile/1731/1/documents/cest2017_00797_oral_paper_V2.pdf (655 KB)

    Additional material:

    See also: http://cest.gnest.org/sites/default/files/presentation_file_list/cest2017_00797_oral_paper.pdf

  1. E. Rozos, I. Tsoukalas, K. Ripis, E. Smeti, and C. Makropoulos, Turning black into green: ecosystem services from treated wastewater, 13th IWA Specialized Conference on Small Water and Wastewater Systems, Athens, Greece, National Technical University of Athens, 2016, (in press).

    In order to reduce the impact of the urban effluents on the environment, modern societies have imposed restrictions regarding the quality of the disposals. For this reason, in the majority of the western world cities, the wastewater is treated before disposal. However, on the other side of the urban water cycle, water abstractions keep putting an increasing pressure on the water resources. As a countermeasure, treated wastewater is used occasionally as an alternative resource by employing large scale infrastructure to treat and supply water for either irrigation or industrial uses. Despite the existence of numerous successful applications, this practice is not very common mainly because of the increased capital and operational costs, usually exceeding the cost of fresh water. The response of the market to this drawback was to introduce in-situ small scale treatment units to cover local water needs. In this study, we assess the benefits of a compact wastewater treatment unit that is used to provide water for irrigating a green area. Apart from the aesthetic improvement, benefits are expected because of the evaporative cooling (latent heat), which reduce the air temperature. A pilot scheme was set up in KEREFYT, the research centre of Athens water supply company. This scheme was simulated with UWOT model to estimate the heat fluxes and the results were fed into Energy2D (a model that simulates heat transfer) to estimate the expected temperature drop.

    Full text: http://www.itia.ntua.gr/en/getfile/1600/1/documents/Manuscript_QiNArbH.pdf (509 KB)

  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)

  1. I. Tsoukalas, P. Dimas, and C. Makropoulos, Hydrosystem optimization on a budget: Investigating the potential of surrogate based optimization techniques, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, 2015.

    Development of uncertainty-aware operational rules for multi-reservoir systems is a demanding and challenging task due to the complexity of the system dynamics, the number of decision variables and the hydrological uncertainty. In order to overcome this issue the parsimonious parameterization-simulation-optimization (PSO) framework is employed coupled with stochastically generated hydrological time-series. However, when the simulation model requires long computational time this coupling imposes a computational barrier to the framework. The purpose of this paper is threefold: a) Investigate the potential of Efficient Global Optimization (EGO) algorithm (and its variants) which is capable of reaching global optima within a few simulation model evaluations (~500 or less). b) Extend the capabilities of WEAP21 water resources management model by using it within PSO framework (named WEAP21-PSO) and c) Validate and compare the results of WEAP21-PSO using the well-known hydrosystem management model Hydronomeas coupled with Evolutionary Annealing Simplex (EAS) optimization algorithm. Results confirm that EGO has the potential and the capabilities to handle computationally demanding problems and furthermore is capable of locating the optimal solution within few simulation model evaluations and that the WEAP21-PSO framework performs well at the task at hand.

    Full text: http://www.itia.ntua.gr/en/getfile/1574/1/documents/cest2015_00162_oral_paper.pdf (475 KB)

    See also: http://cest.gnest.org/cest15proceedings/public_html/papers/cest2015_00162_oral_paper.pdf

  1. E. Rozos, and C. Makropoulos, Preparing appropriate water policies for sd analysis: a broad-brush review on water conservation practices, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.

    Water scarcity is one of the most serious modern-day problems with a continuously growing list of affected regions. In response, both international organizations and local governments have officially acknowledged this problem and have acted accordingly either by funding related research programs (the scientific community has been studying water scarcity for the last few decades) or by directly taking water demand management measures or by appropriate subsidies. As a result, there are nowadays examples of good practices/techniques that achieve considerable reduction of water demand. The scientific community, apart from suggesting new ideas, provides also feedbacks on these practices/techniques through scientific publications (e.g Zhang et al., 2009; March et al. 2004; Brewer et al. 2001; Surendran and Wheatley, 1998), which are usually thorough assessments of case studies based on some specific strategy, applied at a specific scale and serving a single sector. These reviews are valuable sources for further specialized studies and can serve as guidelines for the implementation of similar technical applications. However, the objective of these reviews is not to provide a broad-perspective picture of the available options suitable for each part of the urban water cycle. In this study, it is attempted to give a rough idea of this “broad picture” by providing an index of the representative best practices. To compile this index, first, the successful applications of water management practices/techniques found in literature were classified using three category types: the sector, the application scale and the employed water reduction strategy. Then, the basic characteristics of the representative best practices were assembled and presented in a compact and organized manner. These indicated best water management practices could be used to appropriately formulate representative water policies resulting from a system dynamics (SD) analysis that will take into account various socio-economic parameters. This will hopefully facilitate a quick uptake of the most promising options for each type of application.

    Full text: http://www.itia.ntua.gr/en/getfile/1573/1/documents/CEST2015_00131_Presentation.pdf (612 KB)

    Additional material:

  1. E. Rozos, and C. Makropoulos, Urban regeneration and optimal water demand management, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.

    Increasing water scarcity has drawn attention to the management of urban water demand, which can be achieved through the re-engineering of the urban water cycle in order to implement water reuse practices. Examples of these new practices include the use of locally treated water for a variety of non-potable uses at household or neighbour scales. However, the successful design and implementation of these new practices is not straightforward. The efficiency of a rainwater harvesting scheme, for example, can be greatly reduced if the local tank is under-dimensioned, whereas the maximum efficiency is achieved with the tank capacity exceeding a threshold, which depends on the statistical profile of both the demand and supply (rainfall). The identification of this threshold requires modelling of the rainwater recycling scheme using long historical timeseries (or synthetically generated with a stochastic model) to capture the statistics of the supply/demand. It should be noted that the tanks per se are relatively cheap, but the space to install them and the preparations required (e.g. excavations in case of underground installation) can have significant costs. Therefore, it is imperative to correctly identify the optimum capacity of a tank. Another costly installation required for a rainwater recycle scheme is the dual reticulation, which, in case of retrofitting, translates into expensive plumbing interventions of which the payback period (if any) is very long. However, dual reticulation can be easily implemented during the construction of a building. Such an opportunity is offered in the region of Eleonas, Athens, Greece. Recently, this area has attracted the attention of many urban planners, who have suggested alternative regeneration scenarios: the Agrarian (the area as a green reservoir for the surrounding city), the Urban-Agrarian (extensive green areas along with residential areas and transportation services) and the Metropolitan (transformation of Eleonas into the new Central Business District for Athens). In this study, these three alternative regeneration scenarios were assessed with UWOT. UWOT is a bottom-up urban water model that simulates the generation, aggregation and routing of demand signals (potable water demand, runoff discharge demand, and wastewater discharge demand). First, UWOT was used to 'scan' the water networks of the three scenarios (assuming conventional water network) to identify the most intense water consumers. Afterwards, a local rainwater harvesting scheme was introduced in the networks of the major water consumers to reduce the water demand on-the-spot. Then, UWOT along with an optimization algorithm were used to properly dimension this rainwater harvesting scheme. The results of the optimization indicated that the runoff volume could be considerably reduced, which will further improve the ecological footprint of the planned regeneration.

    Full text: http://www.itia.ntua.gr/en/getfile/1572/1/documents/CEST2015_00129_RozosEtAl.pdf (230 KB)

    Additional material:

  1. E. Rozos, Y. Photis, and C. Makropoulos, Water demand management in the expanding urban areas of south Attica, 14th International Conference on Environmental Science and Technology (CEST2015), Global Network on Environmental Science and Technology, University of the Aegean, Rhodes, Greece, 2015.

    Modern decentralized water-aware technologies (including for example grey water recycling and rainwater harvesting) enable water reuse at the scale of household or neighbourhood. Such options reduce the pressure on the infrastructure and alleviate the need for upgrading the centralized infrastructure, hence reducing the cost of urban growth. To study the benefits of the water-aware technologies on expanding urban areas, an urban water cycle and a land use model were coupled. The former, UWOT, is a bottom-up urban water model that simulates the generation, aggregation and routing of demand signals (potable water demand, runoff discharge demand, and wastewater discharge demand). The latter, SLEUTH, is a cellular automaton model of urban land use change (see project GIGALOPOLIS). The coupling of UWOT and SLEUTH was tested in South Attica. Cellular automaton models use a group of discrete units to simulate the land use evolution of the studied area. For this reason, classes of land uses should be formed based on a set of predefined criteria. The criteria of the classification of the South Attica were the population per cell, the total built area per cell and the population per building. SLEUTH was calibrated using the 2001-2011 census data. Then, SLEUTH was used to simulate the urban expansion and intensification. The simulation period spanned from 2011 to 2031. Afterwards, the results of SLEUTH were fed into UWOT, which simulated the conventional network of this area to estimate the evolution of the water demand, the runoff and the wastewater generation. Finally, a sequence of simulations were performed assuming that the network of all new buildings (those built between 2011 and 2031) incorporated water-saving schemes and that water-saving schemes were being installed in the existing buildings (those built before 2011) with a constant penetration rate. The only difference among the simulations of this sequence was the time of the initiation of the water-saving schemes installation. This provided a nomograph with a group of lines corresponding to potable water demand for different intervention timings and various penetration rates. This nomograph could be used in supporting either the planning of the expansion of the water services to newly urbanized areas and/or the decisions regarding the maintenance and capacity increase of the existing infrastructure.

    Full text: http://www.itia.ntua.gr/en/getfile/1571/1/documents/CEST2015_00128_RozosEtAl.pdf (268 KB)

    Additional material:

  1. S. Baki, I. Koutiva, and C. Makropoulos, A hybrid artificial intelligence modelling framework for the simulation of the complete, socio-technical, urban water system, 2012 International Congress on Environmental Modelling and Software, Managing Resources of a Limited Planet, Leipzig, International Environmental Modelling and Software Society, 2012.

    A (truly) integrated approach to the management of urban water should take into account, further to the characteristics of the technical system, a range of socio-economic processes and interactions – combined into what has been termed the “socio-technical system”. This is by no means an easy endeavour: conventional simulation tools often fail to capture socio-economic processes and their interactions with the technical urban water system. Variables depicting the socioeconomic environment are usually static and estimated from literature and/or expert opinion. To address this issue, new socio-technical modelling approaches are emerging aiming to explicitly account for the feedback loops between the socioeconomic environment and the urban water system. In this paper we develop a hybrid artificial intelligence (AI) conceptual model using System Dynamics (SD), Agent Based Modelling (ABM) and urban water modelling tools to investigate the urban water system’s response to different policies. The SD model simulates the broader socio-economic, natural and technical context and links to more specialised tools for the social and technical sub-systems: For the social subsystem, ABM is used to model preferences and decisions of water users, whereas for the technical system, the Urban Water Optioneering Tool (UWOT) is used to provide a detailed representation of the urban water cycle, affected by the endusers’ decisions. The proposed modelling framework allows for the dynamic nature of the socio-economic variables to be explicitly included in the assessment in order to test the effectiveness of different policies, such as awareness raising campaigns, and dynamically simulate the subsequent response of the urban water system in time. The paper discusses the integration of urban water and social simulation models at a higher modelling level via a System Dynamics platform and the suitability of such a framework for the assessment of the performance and pressures on urban water systems under varying conditions and scenarios.

    Full text: http://www.itia.ntua.gr/en/getfile/1312/1/documents/I5_0781_Baki_et_al.pdf (1543 KB)

    See also: http://www.iemss.org/society/index.php/iemss-2012-proceedings

  1. I. Koutiva, and C. Makropoulos, Towards adaptive water resources management: simulating the complete socio-technical system through computational intelligence, Proceedings of the 12th International Conference on Environmental Science and Technology, A998–A1006, Rhodes, 2011.

    Full text: http://www.itia.ntua.gr/en/getfile/1180/1/documents/CEST2011AdaptiveManagemet.pdf (77 KB)

  1. E. Rozos, S. Baki, D. Bouziotas, and C. Makropoulos, Exploring the link between urban development and water demand: The impact of water-aware technologies and options, Computing and Control for the Water Industry (CCWI) 2011, Exeter, UK, CCWI2011-311, University of Exeter, 2011.

    In conventional urban planning, water demand is covered exclusively by potable water supply and wastewater is directly conducted to the sewers. One of the disadvantages of this practice is that the expansion of an urban area puts additional pressure on existing water infrastructure (both water supply and wastewater networks), which may result in capacity exceedance. In such cases, the required upgrades of existing infrastructure are slow and potentially very costly. On the other hand, modern decentralized water-aware technologies (including for example grey water recycling and rainwater harvesting) enable water reuse at the scale of a household or a neighbourhood. Such options reduce the pressure on the infrastructure and alleviate the need for upgrading centralized infrastructure, hence reducing the cost of urban growth. In an attempt to quantify the potential benefits of these technologies we coupled an urban water management model with a land-use model based on Cellular Automata (CA). The land-use model produces scenarios of urban growth/transformation, which are then assessed through the use of an urban water management model. The assessment is based on indicators including potable water demand, peak runoff discharge and volume of produced waste water. The final result is a representation of the evolution of these indicators as a function of urban growth contrasting conventional and innovative practices.

    Full text: http://www.itia.ntua.gr/en/getfile/1152/1/documents/CCWI2011_311.pdf (476 KB)

    Additional material:

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

    1. Tong Thi Hoang Duong, Avner Adin, David Jackman, Peter van der Steen, Kala Vairavamoorthy, Urban water management strategies based on a total urban water cycle model and energy aspects – Case study for Tel Aviv, Urban Water Journal, Vol. 8, Iss. 2, 2011.

  1. C. Makropoulos, E. Rozos, and D. Butler, Urban water modelling and the daily time step: issues for a realistic representation, 8th International Conference on Hydroinformatics 2009, Concepcion, Chile, Curran Associates, Inc., 57 Morehouse Lane Red Hook, NY 12571 USA, 2011.

    Interest in modelling the total Urban Water Cycle is increasing, due to the realisation of the need for (high-level) flow integration to address issues of recycling, re-use and ultimately sustainability. Urban Water Cycle models are generally operating on a daily time step due to the inherent strategic/planning nature of such work. However, the choice of time step implies (more or less hidden) assumptions which may influence significantly the model’s performance. One such assumption – the way in which water tanks (e.g. rainwater, greywater, greenwater etc) are operated in terms of the sequence between tank overflow (spill) and water extracted from the tank for use (yield) is investigated in this paper. The two alternative sequences are termed here Yield After Spill (YAS) and Yield Before Spill (YBS). The Urban Water Optioneering Tool was used and advantages and disadvantages of these sequences were examined. The paper reviews the differences under a series of technological configurations and draws recommendations for modelling practice. It is suggested that YAS/YBS schemes have different impacts depending on the technological configuration of the case study under investigation, but that under normal operating conditions, daily time step simulations with YBS schemes tend to result in tank sizes that are (marginally) closer to sizes obtained by hourly time-steps. It is however suggested that YAS schemes should be preferred when the parameter of interest is runoff.

    Full text: http://www.itia.ntua.gr/en/getfile/917/1/documents/conf188a275_Fin2.pdf (114 KB)

  1. N. Evelpidou, N. Mamassis, A. Vassilopoulos, C. Makropoulos, and D. Koutsoyiannis, Flooding in Athens: The Kephisos River flood event of 21-22/10/1994, International Conference on Urban Flood Management, Paris, doi:10.13140/RG.2.1.4065.5601, UNESCO, 2009.

    During the night of the 20th of October 1994, a cold front passed over Greece, provoking heavy precipitation and consequently catastrophic floods in many areas of Greece. In some of the affected areas, the precipitation height was equivalent to 140 mm, while in the center of Athens the respective quantity was more than 140 mm. The Greater Athens area experienced one of the most devastating flood events in years, during which nine deaths were reported along with severe damages in the transportation, telecommunication and energy infrastructures. Dozens of homes and stores flooded, cars totally damaged, three buildings collapsed and hundreds of people trapped in cars and buildings give the outline of the disastrous impacts.

    Full text: http://www.itia.ntua.gr/en/getfile/1163/1/documents/Kifissos_Chapter_COST22_v3.pdf (2115 KB)

    See also: http://dx.doi.org/10.13140/RG.2.1.4065.5601

    Works that cite this document: View on Google Scholar or ResearchGate

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

    1. Kandilioti, G. and C. Makropoulos, Preliminary flood risk assessment: the case of Athens, Nat. Hazards, DOI: 10.1007/s11069-011-9930-5, 2011.
    2. #Hildén, M., R. Dankers, T. Kjeldsen, J. Hannaford, C. Kuhlicke, E. Kuusisto, C. Makropoulos, A. te Linde, F. Ludwig, J. Luther and H. Wolters, Floods – vulnerability, risks and management, A joint report of ETC CCA and ICM, European Environment Agency, 2012.
    3. #Vanneuville, W., B. Werner, R. Uhel, et al., Water Resources in Europe in the Context of Vulnerability, EEA 2012 State of Water Assessment, European Environment Agency, 2012.
    4. Evrenoglou, L. S. A. Partsinevelou, P. Stamatis, A. Lazaris, E. Patsouris, C. Kotampasi and P. Nicolopoulou-Stamati, Children exposure to trace levels of heavy metals at the north zone of Kifissos River, Science of The Total Environment, 443, 650-661, 10.1016/j.scitotenv.2012.11.041, 2013.
    5. Diakakis, M., An inventory of flood events in Athens, Greece, during the last 130 years: Seasonality and spatial distribution, Journal of Flood Risk Management, 10.1111/jfr3.12053, 2013.
    6. Diakakis, M., A. Pallikarakis and K. Katsetsiadou, Using a spatio-temporal GIS database to monitor the spatial evolution of urban flooding phenomena: the case of Athens Metropolitan Area in Greece, ISPRS International Journal of Geo-Information, 3 (1), 96-109, 2014.

  1. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, V. Kaffes, C. Papathanasiou, and M. Mimikou, Multi-reservoir management with Open-MI, Proceedings of the 11th International Conference on Environmental Science and Technology, Chania, A, 788–795, Department of Environmental Studies, University of the Aegean, 2009.

    The paper applies advanced integrated modeling techniques supported by the Open Modeling Interface (OpenMI) standard to optimize water resources allocation for a rapidly growing rural area in Greece. Water uses in a rural basin are significantly affected by urban growth, changes in agricultural practices and industrial needs. This results in a complex water system, whose optimal configuration requires the combination of structural and non-structural approaches. Furthermore, the reliable operation of the water system may be placed under significant stress due to increasing trends of extreme events associated with potential climatic changes which affect freshwater availability. To evaluate and improve the system’s operation, a series of specialized models need to be linked and exchange data at runtime. The approach presented in this paper, used OpenMI (an open source, royalty free standard) to facilitate the direct, timestep-by-timestep, communication of models from different providers, written in different coding languages, with different spatial and temporal resolutions. The models were “migrated” to OpenMI and were run simultaneously, linked (exchanging data) at nodes specified by the modeler. The resulting integrated modeling system is tested in the Thessaly Water District, Greece, where growing water demand has often become an issue of conflict between stakeholders. As an example of the type of problems typically faced in the region, a system of two reservoirs receiving flows from different subbassins is designed to satisfy the water demand of the study area. The principal reservoir, the Smokovo reservoir, is a real reservoir, currently in operation, situated on the confluence of two streams, tributaries of the Pinios river. Downstream of Smokovo reservoir, the river flow has to satisfy a series of needs such as ecological flows, increasing irrigation needs, increasing potable water demand of the local municipalities, and production of electricity. The second reservoir introduced in this study is the potential rehabilitation of the Lake Xyniada, as a means to improve the overall resilience of the water system to extreme events and possibly decrease the costs (ecological-economic) of water consumption in the area. The integrated modeling system comprises of three OpenMI-compliant model components: a reservoir model (RMM), a hydraulic model with supporting rainfall-runoff modules (MIKE-11) and a multi-reservoir operational rule component. The models were set-up, calibrated, and linked to exchange data at runtime using data provided by the Public Power Corporation and the Ministry of Environment. The modeling system was run under different operating rules to assess the reliability of the combined reservoir system and compare it with the one-reservoir existing solution against different stakeholder objectives. The paper suggests indicative solutions from the preliminary analysis and concludes with the identification of key future challenges and ideas for further development.

    Full text: http://www.itia.ntua.gr/en/getfile/932/1/documents/openMI_chania.pdf (451 KB)

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

    1. Fotopoulos, F., C. Makropoulos C., and M.A Mimikou, Flood forecasting in transboundary catchments using the Open Modeling Interface, Environmental Modelling and Software, 25(12), 1640-1649, 2010.
    2. #Moe, S. J., L. J. Barkved, M. Blind, C.. Makropoulos, M. Vurro, S. Ekstrand, J. Rocha, M. Mimikou, and M. J. Ulstein, How can climate change be incorporated in river basin management plans under the WFD? Report from the EurAqua Conference 2008, 27 p., Norwegian Institute for Water Research, 2010.

  1. C. Makropoulos, E. Rozos, and C. Maksimovic, Developing An Integrated Modelling System For Blue-Green Solutions, HIC 2014 – 11th International Conference on Hydroinformatics, New York City, USA, HIC2014-216, August 2014.

    Blue-green interventions represent the next level of integration for sustainable cities: that of an integrated urban water and urban green design, operation and management. The key concept is that a more holistic infrastructure design approach would present a win-win scenario, in which urban green would be utilized as infrastructure for water services (e.g. mitigating urban floods) while urban water infrastructure would be used as a source of irrigation for urban green, increasing their performance in a range of services including amenities, reducing heat island effects and increasing ecosystem services. However, this focus on integration brings into sharp relief another need: that of developing models and tools able to investigate the interactions between different green and blue system elements and processes. This “ecosystem” of models and tools presents a challenge due to its scope, in terms of development, but also the challenge of model integration. This paper discusses these challenges and proposes a three level approach to building an integrated modelling system for this case, which is able to: (a) support in the choice of appropriate models; (b) facilitate their linking in runtime and (c) enable the homogenization of results from the different models into common views supporting decision making. The use of standards, in this case OpenMI, are discussed in the light of the proposed approach. The concept is illustrated using a limited set of simple models developed for blue-green solutions design and the preliminary results are presented and discussed.

    Full text: http://www.itia.ntua.gr/en/getfile/1489/1/documents/HIC2014-216.pdf (369 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. 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.

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    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. 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.

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  1. G. Tzortzakis, E. Katsiri, G. Karavokiros, C. Makropoulos, and A. Delis, Tethys: sensor-based aquatic quality monitoring in waterways, 17th IEEE International Conference on Mobile Data Management (MDM), 329–332, doi:10.1109/MDM.2016.56, Porto, 2016.

    It is imperative that water is delivered clean to urban centers and towns despite its channelling through waterways, ponds and city aqueducts. Waterways are occasionally polluted by micro-organisms, landslides, pesticides, as well as by human activity and waste. In coordinated efforts to address such problems, water authorities and local governments resort to cleaning facilities whose main task is to filter the water in a timely fashion. In this regard, authorities must be forewarned of imminent or developing pollution issues, so that immediate corrective action can be taken. The installation of sensors that continuously monitor the quality of water passing through specific points in waterways, proves to be an effective way to implement legislative mandates for clean water. We use submerged sensors to gather measurements that can help characterize the quality of water in canals using parameters including temperature, conductivity, turbidity, PH, and pressure. Raw sensor-generated measurements turn out to be of limited help when it comes to monitor the overall water quality and by themselves, can be even misleading occasionally. In this paper, we discuss the main features of Tethys, a real-time water quality monitoring tool, whose aim is to help the Athens water authorities in their ongoing assessment of water quality. Tethys receives as input streams of measurements from stations in the field, detects unexpected events, visualizes the flow of information, and automatically alerts supervisors about potential dangers appearing in waterways. We outline our design choices, filtering mechanisms, and implementation effort in realizing Tethys and demonstrate its real-time use.

    Full text: http://www.itia.ntua.gr/en/getfile/1765/1/documents/Tethys.pdf (653 KB)

  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. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Handling time-expensive global optimization problems through the surrogate-enhanced evolutionary annealing-simplex algorithm, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5923, European Geosciences Union, 2015.

    In water resources optimization problems, the calculation of the objective function usually presumes to first run a simulation model and then evaluate its outputs. In several cases, however, long simulation times may pose significant barriers to the optimization procedure. Often, to obtain a solution within a reasonable time, the user has to substantially restrict the allowable number of function evaluations, thus terminating the search much earlier than required by the problem’s complexity. A promising novel strategy to address these shortcomings is the use of surrogate modelling techniques within global optimization algorithms. Here we introduce the Surrogate-Enhanced Evolutionary Annealing-Simplex (SE-EAS) algorithm that couples the strengths of surrogate modelling with the effectiveness and efficiency of the EAS method. The algorithm combines three different optimization approaches (evolutionary search, simulated annealing and the downhill simplex search scheme), in which key decisions are partially guided by numerical approximations of the objective function. The performance of the proposed algorithm is benchmarked against other surrogate-assisted algorithms, in both theoretical and practical applications (i.e. test functions and hydrological calibration problems, respectively), within a limited budget of trials (from 100 to 1000). Results reveal the significant potential of using SE-EAS in challenging optimization problems, involving time-consuming simulations.

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  1. C. Makropoulos, and E. Rozos, Managing the complete Urban Water Cycle: the Urban Water Optioneering Tool, SWITCH, Paris, France, 2011.

    Conventional urban water management practices aim to meet water demands while conveying wastewater and stormwater away from urban settings. However, increasing water scarcity, caused by either changes in climatic conditions, increasing consumption, or both, has drawn attention to the possibility of re-engineering the urban water cycle to implement water recycling and reuse practices (Makropoulos et al., 2006). Examples of these new practices are the use of treated greywater (or “greenwater”) or harvested rainwater for a variety of non-potable water uses in the household. The successful design of water recycling schemes should attempt to minimize (simultaneously) the demands for potable water, the energy and cost, and perform adequately in the longer term – possibly even under changing climatic conditions. This paper describes the Urban Water Optioneering Tool (UWOT; Makropoulos et al., 2008), which is a decision support tool that supports the design of the complete (integrated) urban water cycle and helps to achieve sustainable water management for new and existing urban areas and explores both past applications and future developments within the context of new challenges for water in Europe.

    Full text: http://www.itia.ntua.gr/en/getfile/1597/1/documents/Abstract_SWITCH.pdf (114 KB)

  1. E. Rozos, and C. Makropoulos, Ensuring water availability with complete urban water modelling, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, European Geosciences Union, 2011.

    Increasing water scarcity, caused by either climate change or increasing consumption or both, has drawn attention to climate-sensitive adaptive strategies. These strategies include the possibility of re-engineering the urban water cycle to implement water recycling and reuse practices. For this reason a new generation of decision support tools capable of coping with these challenges is needed. UWOT (Urban Water Optioneering Tool) answers to this request by modelling the total urban water cycle and assessing its sustainability through a set of indicators. UWOT can support the planning of adaptive strategies for existing or new developments. Existing developments, for example, may include the installation of retrofit technologies (e.g. low flush toilets, in house water treatment units etc). In this case, UWOT can be used along with optimization algorithms to identify the optimum trade-off between the potable water demand reduction and the required cost (including energy). For new developments, more radical solutions (like central grey/rain water treatment units) can be adopted to manage the available water resources more efficiently. In this case, UWOT can help in the preliminary study of the required investment providing a rough dimensioning and an estimation of the pay-back period. Another issue that UWOT can help with is the investigation of the influence of climatic trends on the efficiency of water saving technologies. Rainwater harvesting, for example, directly depends on climatic conditions. UWOT can be used along with a stochastic model to provide a probabilistic approach for studying this uncertainty. Furthermore, UWOT can be used to examine a health issue related with the prolonged storage of harvested rainwater. Long periods of storage may result in significant degradation of the water quality rendering imperative the implementation of measures to maintain quality standards. UWOT can be used to investigate the necessity of such measures by calculating the Residence Time Index that characterizes the operation of a tank.

    Full text: http://www.itia.ntua.gr/en/getfile/1121/1/documents/UWOT_EGU_2.pdf (3209 KB)

  1. E. Rozos, and C. Makropoulos, Assessing the combined benefits of water recycling technologies by modelling the total urban water cycle, International Precipitation Conference (IPC10), Coimbra, Portugal, 2010.

    Urbanisation is one of the most significant sources responsible for additional pressures (both qualitative and quantitative) on the environment. Typical quantitative pressures are the temporal changes of the hydrosystem's water flow pattern (due to alterations of the terrain) and the water abstractions (due to the water demand increase). Sustainable, water-aware technologies, like Sustainable Urban Drainage Systems (SUDS) and rainwater harvesting schemes, can be implemented to reduce these pressures. These technologies introduce interactions between the components of the urban water cycle. Rainwater harvesting for example, apart from the potable water demand reduction, has significant influence on the generated runoff. Consequently, integrated modelling of the urban water cycle is necessary for the simulation of the modern water technologies and the identification of their combined benefits. In this study, two hypothetical developments, referred hereafter as development H and development L, that implement rainwater harvesting scheme and SUDS are simulated using the Urban Water Optioneering Tool (UWOT). The characteristics of the developments H and L correspond to high and low urbanisation density. The study is organised into three stages. The first stage includes the calibration of UWOT's rainfall-runoff module. The second stage includes the identification of the optimum configurations of the developments that minimise the environmental pressures. The final stage includes a sensitivity analysis aiming to investigate the influence of the characteristics of the water appliances and technologies on the generated runoff. This study indicated that: (a) the localised measures are more efficient than the centralised technologies for mitigating the runoff peak; (b) the cost to minimise the pressures of new developments on the environment increases significantly with the urbanisation density both because of the increased population and the increased sensitivity of the runoff's maximum on the development characteristics; (c) if localised rainwater harvesting is implemented then the efficiency of the water appliances influences considerably the generated runoff.

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Presentations and publications in workshops

  1. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, and V. Kaffes, Multi-reservoir management with OpenMI, OpenMI-LIFE Pinios Workshop, Volos, 2009.

    Full text: http://www.itia.ntua.gr/en/getfile/919/1/documents/openMI_pinios_2009_evi.pdf (719 KB)

    See also: http://www.openmi-life.org/events/pinios-workshop.php?lang=0

  1. C. Makropoulos, D. Koutsoyiannis, and A. Efstratiadis, Challenges and perspectives in urban water management, Local Govenance Conference: The Green Technology in the Cities, Athens, Ecocity, Central Association of Greek Municipalities, 2009.

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Various publications

  1. E. Rozos, S. Kozanis, and C. Makropoulos, Integrated Modelling System, BGD internal project report, 31 January 2014.

    Guidelines on the implementation of OpenMI standard at the BGD models.

    Full text: http://www.itia.ntua.gr/en/getfile/1435/1/documents/BGD_IMS.pdf (649 KB)

  1. H. Perlman, C. Makropoulos, and D. Koutsoyiannis, The water cycle, http://ga.water.usgs.gov/edu/watercyclegreek.html, 19 pages, doi:10.13140/RG.2.2.11182.92480, United States Geological Survey, 2005.

    Full text: http://www.itia.ntua.gr/en/getfile/660/1/documents/2005watercyclegreek.pdf (1516 KB)

    See also: http://ga.water.usgs.gov/edu/watercyclegreek.html

Educational notes

  1. C. Makropoulos, A. Efstratiadis, and P. Kossieris, Lecture notes on Hydraulics and Hydraulic Works: Water Supply, 80 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, December 2019.

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    Additional material:

  1. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource Systems Optimzation - Hydroinformatics, 151 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2018.

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  1. E. Rozos, and C. Makropoulos, Programming in Matlab for optimization problems, Athens, Greece, February 2011.

    Introduction to Matlab programming, notes and exercises.

    Full text: http://www.itia.ntua.gr/en/getfile/1122/1/documents/Matlab.pdf (240 KB)

  1. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource System Optimization and Hydroinformatics, 307 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, April 2011.

    Remarks:

    Lecture notes for the postgraduate course: Water resource systems optimization - Hydroinformatics.

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Academic works

  1. C. Makropoulos, Spatial decision support for urban water management, 321 pages, Department of Civil and Environmental Engineering – Imperial College, London, London, 2003.

    The research describes the development of a Spatial Decision Support System for Urban Water Management and its application in the particular domain of Water Demand Management. The primary hypothesis stated and discussed is that the development of decision support systems with a distinct spatial character (i.e. spatial decision support systems (SDSS)) based on soft computing can assist the decision maker within the urban environment and result in more informed decisions. The thesis investigates the use, within an integrated decisional platform, of different tools (including mathematical modelling, geographic information systems, decision support techniques, spatial analysis, fuzzy inference systems and evolutionary programming). It develops new soft computing techniques, adapts techniques that are available in other domains and combines them in an innovative way to facilitate urban water planning and management. The prototype Spatial Decision Support System developed is tested under a variety of different user inputs and assumptions and is used to discuss alternative water demand management strategies. It is concluded that the prototype developed is a flexible tool that can be adapted to the characteristics of the problem at hand while its transparent nature greatly enhances the inclusion and handling of uncertainty and risk throughout the decision making process. Although the work presented here is open to further development, improvement and testing, it is felt that it is a promising research direction and could be of great potential benefit to the decision making process within the water industry.

Research reports

  1. A. Efstratiadis, N. Mamassis, and C. Makropoulos, Synoptic report on the estimation of the capacity of water supply system of Athens, 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, 30 pages, October 2019.

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

  1. C. Makropoulos, D. Damigos, A. Efstratiadis, A. Koukouvinos, and A. Benardos, Synoptic report and final conclusions, Cost of raw water of the water supply of Athens, 32 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.

    Related project: Cost of raw water of the water supply of Athens

    Full text: http://www.itia.ntua.gr/en/getfile/1099/1/documents/Kostos_Nerou_EYDAP_Teuxos_5.pdf (418 KB)

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

    1. #Makropoulos, C., and E. Papatriantafyllou, Developing roadmaps for the sustainable management of the urban water cycle: The case of WW reuse in Athens, Proceedings of the 13th International Conference of Environmental Science and Technology, Athens, 2013.

  1. C. Makropoulos, A. Efstratiadis, and A. Koukouvinos, Appraisal of financial cost and proposals for a rational management of the hydrosystem, Cost of raw water of the water supply of Athens, 73 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.

    Related project: Cost of raw water of the water supply of Athens

    Full text: http://www.itia.ntua.gr/en/getfile/1097/1/documents/Kostos_Nerou_EYDAP_Teuxos_3.pdf (1053 KB)

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

    1. Baki, S., and C. Makropoulos, Tools for energy footprint assessment in urban water systems, Procedia Engineering, 89, 548-556, doi:10.1016/j.proeng.2014.11.477, 2014.
    2. #Di Federico, V., C. Makropoulos, A. Monteiro, T. Liserra, S. Baki, and A. Galvão, The TRUST approach for the Transition to Sustainability of Urban Water Services: the water scarcity cluster, Water IDEAS 2014 - Intelligent Distribution for Efficient and Affordable Supplies, International Water Association (IWA), Bologna, Italy, 2014.
    3. Frijns, J., E. Cabrera Marchet, N. Carriço, D. Covas, A. J. Monteiro, H. M. Ramos, A. Bolognesi, C. Bragalli, S. Baki, and C. Makropoulos, Management tools for hydro energy interventions in water supply systems, Water Practice and Technology, 10(2), 214-228, doi:10.2166/wpt.2015.024, 2015.

  1. C. Makropoulos, A. Koukouvinos, A. Efstratiadis, and N. Chalkias, Mehodology for estimation of the financial cost , Cost of raw water of the water supply of Athens, 40 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2010.

    Related project: Cost of raw water of the water supply of Athens

    Full text: http://www.itia.ntua.gr/en/getfile/1008/1/documents/Kostos_Nerou_EYDAP_Teuxos_1__.pdf (732 KB)

Engineering reports

  1. C. Maksimovic, H. S. Wheater, D. Koutsoyiannis, S. Prohaska, D. Peach, S. Djordevic, D. Prodanovic, C. Makropoulos, P. Docx, T. Dasic, M. Stanic, D. Spasova, and D. Brnjos, Final Report, Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina, Commissioner: Energy Financing Team, Switzerland, Contractors: CUW-UK, ICCI Limited, London, 2004.

    The possible effects of water transfer through the tunnel Fatnicko Polje - Bileca Reservoir on the hydrologic regime of the Bregava River located in Eastern Herzegovina, in an area characterised by a predominantly karstic terrain, are studied. Three different simulation models of the area were developed and their predictions compared under a range of current and future hydrological and operational management conditions. These are based on a range of modelling approaches from a simplified conceptual approach to a quasi-physically based one. Despite the large complexity of the natural system, the models gave good fits to existing flow data with the most simplified model providing the closest agreement to historical flows. Calibrated models were used to study the possible effects of the intervention under a range of operational scenarios and identify the sources of the associated uncertainties. The results of the work suggest that the system of tunnels in question has a favourable effect in reducing flood hazard in the area, thus liberating scarce land resources for agriculture, and in reduction of flows in the Bregava River, especially the high flows. It is also suggested that a significant reduction in the uncertainty of modelling the karstic environment can be achieved by an appropriate, complementary combination of modelling approaches viewed as a multi-model ensemble.

    Related works:

    • [48] Summary of the study (journal publication).

    Related project: Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina

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