From standard to data-driven flow-based design of urban drainage and wastewater management systems: integrating variability, open data, and standardization
Abstract
Urban drainage and wastewater systems face mounting pressures from climate change, urbanization, and evolving regulations. Conventional design approaches based on static standards and conservative safety factors may no longer adequately address the variability, uncertainty, and non-stationarity characterizing current conditions. This review synthesizes Workshop 4 -'Influent flowrate generators for system design in urban drainage modelling using open data sources' -at the 2025 International Conference on Urban Drainage Modelling (UDM2025), examining opportunities to transition toward data-informed, probabilistic models for more accurate flow prediction and system design. Four interconnected themes are explored: (1) accurately representing peak flow variability rather than treating it as noise; (2) the potential of open environmental data sources (satellite observations, global digital elevation models, population datasets) for modelling in data-scarce contexts;(3) the comparative strengths of data-driven, mechanistic, and hybrid modelling approaches, and the conditions governing their appropriate application; and (4) the need for standardized datasets and metadata schemas, drawing lessons from hydrology's CAMELS initiative, to enable reproducible research and large-sample studies. Key conclusions advocate pragmatic hybridization of modelling paradigms, rigorous validation and uncertainty quantification of open data sources, and coordinated international efforts toward a 'CAMELS for Urban Drainage' dataset; promising more resilient, efficient, and equitable urban water infrastructure.
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BibTeX
@article{serrao2026from,
title = {{From standard to data-driven flow-based design of urban drainage and wastewater management systems: integrating variability, open data, and standardization}},
author = {Marcello Serrao and Natalia Duque Villarreal and Thibaud Maruejouls and Simon Delmas and Tijana Jovanovic and Robin Maes-Prior and Feiyi Li and Dirk Muschalla and Jean-Luc Bertrand-Krajewski and Peter A Vanrolleghem and Wolfgang Rauch},
journal = {Water Science and Technology},
year = {2026},
month = oct,
doi = {10.2166/wst.2026.360},
url = {https://hal.science/hal-05802429v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - From standard to data-driven flow-based design of urban drainage and wastewater management systems: integrating variability, open data, and standardization
AU - Marcello Serrao
AU - Natalia Duque Villarreal
AU - Thibaud Maruejouls
AU - Simon Delmas
AU - Tijana Jovanovic
AU - Robin Maes-Prior
AU - Feiyi Li
AU - Dirk Muschalla
AU - Jean-Luc Bertrand-Krajewski
AU - Peter A Vanrolleghem
AU - Wolfgang Rauch
PY - 2026
DA - 2026/10/14
JO - Water Science and Technology
DO - 10.2166/wst.2026.360
UR - https://hal.science/hal-05802429v1
AB - Urban drainage and wastewater systems face mounting pressures from climate change, urbanization, and evolving regulations. Conventional design approaches based on static standards and conservative safety factors may no longer adequately address the variability, uncertainty, and non-stationarity characterizing current conditions. This review synthesizes Workshop 4 -'Influent flowrate generators for system design in urban drainage modelling using open data sources' -at the 2025 International Conference on Urban Drainage Modelling (UDM2025), examining opportunities to transition toward data-informed, probabilistic models for more accurate flow prediction and system design. Four interconnected themes are explored: (1) accurately representing peak flow variability rather than treating it as noise; (2) the potential of open environmental data sources (satellite observations, global digital elevation models, population datasets) for modelling in data-scarce contexts;(3) the comparative strengths of data-driven, mechanistic, and hybrid modelling approaches, and the conditions governing their appropriate application; and (4) the need for standardized datasets and metadata schemas, drawing lessons from hydrology's CAMELS initiative, to enable reproducible research and large-sample studies. Key conclusions advocate pragmatic hybridization of modelling paradigms, rigorous validation and uncertainty quantification of open data sources, and coordinated international efforts toward a 'CAMELS for Urban Drainage' dataset; promising more resilient, efficient, and equitable urban water infrastructure.
SN - 0273-1223
SN - 1996-9732
ER -