Exploring the effects of alternative water demand management strategies using an agent-based model

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.

[doc_id=2004]

[English]

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.

PDF Full text (1665 KB)

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

Our works referenced by this work:

1. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Hydronomeas: A system for supporting water resources management, 8 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.
2. A. Efstratiadis, G. Karavokiros, and N. Mamassis, Master plan of the Athens water resource system - Year 2009, Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system, Contractors: , Report 1, 116 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, April 2009.
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. 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.
5. 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.
6. A. Efstratiadis, Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017, 2014.
7. 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.
8. C. Makropoulos, D. Nikolopoulos, L. Palmen, S. Kools, A. Segrave, D. Vries, S. Koop, H. J. van Alphen, E. Vonk, P. van Thienen, E. Rozos, and G. Medema, A resilience assessment method for urban water systems, Urban Water Journal, 15 (4), 316–328, doi:10.1080/1573062X.2018.1457166, 2018.

Tagged under: Hydroinformatics, Urban water