Urban hydroinformatics: past, present and future

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

[doc_id=1989]

[English]

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.

PDF Full text (662 KB)

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

Our works referenced by this work:

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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. C. Makropoulos, D. Nikolopoulos, L. Palmen, S. Kools, A. Segrave, D. Vries, S. Koop, H. J. van Alphen, E. Vonk, P. van Thienen, E. Rozos, and G. Medema, A resilience assessment method for urban water systems, Urban Water Journal, 15 (4), 316–328, doi:10.1080/1573062X.2018.1457166, 2018.
9. 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.
10. 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.
11. 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.

Tagged under: Hydroinformatics, Urban water