Source to tap urban water cycle modelling

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.

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[English]

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.

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Our works referenced by this work:

1. I. Nalbantis, and D. Koutsoyiannis, A parametric rule for planning and management of multiple reservoir systems, Water Resources Research, 33 (9), 2165–2177, doi:10.1029/97WR01034, 1997.
2. D. Koutsoyiannis, Coupling stochastic models of different time scales, Water Resources Research, 37 (2), 379–391, doi:10.1029/2000WR900200, 2001.
3. D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Journal of the American Water Resources Association, 38 (4), 945–958, doi:10.1111/j.1752-1688.2002.tb05536.x, 2002.
4. A. Efstratiadis, D. Koutsoyiannis, and D. Xenos, Minimizing water cost in the water resource management of Athens, Urban Water Journal, 1 (1), 3–15, doi:10.1080/15730620410001732099, 2004.
5. 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.
6. 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.
7. N. Mamassis, A. Efstratiadis, G. Karavokiros, S. Kozanis, and A. Koukouvinos, Final report, Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system, Contractors: , Report 2, 84 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, November 2011.
8. 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.

Our works that reference this work:

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.
2. 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.
3. 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.
4. 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.
5. 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.
6. D. Nikolopoulos, H. J. van Alphen, D. Vries, L. Palmen, S. Koop, P. van Thienen, G. Medema, and C. Makropoulos, Tackling the “new normal”: A resilience assessment method applied to real-world urban water systems, Water, 11 (2), 330, doi:10.3390/w11020330, 2019.

Tagged under: Water and energy