From standard to data-driven flow-based design of urban drainage and wastewater management systems: integrating variability, open data, and standardization

Flowchart showing the transition from conventional to data-driven urban drainage design, supported by four interconnected themes: peak flow variability, open data sources, modelling strategies, and dataset standardization. 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 nonstationarity 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.