Urban drainage model calibration requires coordinating data preparation, parameter screening, simulation, validation and interpretation, and remains slow and expertise-intensive. AI agents, which use large language models to plan and execute multi-step tasks, could automate it, yet how an agent should be organised is...
Jian Wang, Shu-Ming Liu, Guang-Tao Fu et al.· npj Clean Water· 0 citations
Urban stormwater modelling plays a critical role in assessing interventions for flood risk and water quality management in response to ageing infrastructure and future uncertainties. However, modelling workflows in practice remain highly manual, and key steps in model configuration, execution, and interpretation often...
Jian Wang, Chenyue Sun, Dragan A. Savić et al.· Journal of Environmental Man...· 0 citations
Biofilm development in drinking water distribution systems (DWDS) affects water quality, hydraulic performance, and microbial risk, yet its spatial distribution and structural properties remain poorly characterized. Existing assessment methods rely on microbiological or bulk water indicators that are difficult to int...
Konstantinos Glynis, M. Blokker, Z. Kapelan et al.· ACS ES&T Water· 0 citations
Urban water systems are increasingly challenged by climate extremes, aging infrastructure, and rising flood risks. Conventional water management practices remain fragmented across data, operations, and assets, limiting coordinated decision-making and scalable engineering deployment. Digital twins (DT) show great promis...
Hao-Zheng Wang, Jin-Kuo Li, Xu-Hui Dang et al.· Water Research· 0 citations
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