Machine Learning-Based Surrogate Modeling for Urban Water Networks: Review and Future Research Directions

Surrogate models replace computationally expensive simulations of physically-based models to obtain accurate results at a fraction of the time. These surrogate models, also known as metamodels, have been employed for analysis, control, and optimization of water distribution and urban drainage systems. With the advent of machine learning (ML),...

Quantifying the true potential of Real Time Control in urban drainage systems

To evaluate the performance of Real Time Control (RTC) of urban drainage systems (UDS) a comparison is made with the pre-RTC situation, making the RTC performance dependent on the functioning of the UDS prior to implementation. To standardise things, a generalised baseline is formulated here as the operation with optimal static settings of the...

Predictive heuristic control: Inferring risks from heterogeneous nowcast accuracy

Urban Drainage Systems can cause ecological and public health issues by releasing untreated contaminated water into the environment. Real-time control (RTC), augmented with rainfall nowcast, can effectively reduce these pollution loads. This research aims to identify key dynamics in the nowcast accuracies and relate those to the performance...

The Impact of Blue-Green Infrastructure and Urban Area Densification on the Performance of Real-Time Control of Sewer Networks

Urban areas are constantly developing and thereby affect the local water cycle. Real-time control (RTC) strategies are used to operate urban drainage systems optimally during these transitions. This paper aims to develop a methodology to study the impacts of common gradual changes occurring in the urban environment (densification of the urban...

HAPPy to Control: A Heuristic And Predictive Policy to Control Large Urban Drainage Systems

Model Predictive Control (MPC) of Urban Drainage Systems (UDS) has been established as a cost-effective method to reduce pollution. However, the operation of large UDS (containing over 20 actuators) can only be optimized by oversimplifying the UDS dynamics, potentially leading to a decrease in performance and reduction in users' trust, thus...