Real-time control enhanced blue-green infrastructure towards torrential events: A smart predictive solution

Passive Blue Green Infrastructure(BGI) may discharge large overflows at storm peak times, contributing to downstream flooding risks. Assoc. Prof. Liu Hailong’s team proposed an adaptive Real-time Control(RTC) solution to predischarges the BGI and mitigate peak flows. Their study proved that RTC applications are able to increase urban sustainability towards climate change and extreme precipitation.


Climate change-induced storms have posed a threat to current urban stormwater systems. As a critical flood control measure, passive urban blue-green infrastructure (BGI) is incapable of effectively utilizing available storage capacity to mitigate peak flows during cloudburst events. At storm peak times, landscape-based BGI may overflow to the drainage system, contributing to downstream flooding risks. To alleviate the effect, this research investigated an adaptive RTC solution that would predischarge the BGI and initiate runoff detention during the most vulnerable period of peak intensity. A case study of a RTC-enhanced landscape detention basin in Tongzhou, Beijing, was conducted using 2D1D modeling. To minimize peak-time overflow under extreme conditions, the studied smart BGI equipped with sensors and electronically movable gates was actuated by both rule-based control (RBC) and model predictive control (MPC) algorithms. Modeling results indicate that the proposed predictive solutions reduced catchment peak outflow by 7.6% to 45.1% over the passive system during three historical cloudburst events. This proposal proves that similar RTC applications could be scaled up to additional landscape projects to increase urban sustainability towards climate change and extreme precipitation.


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