This study presents a novel Coupled Human And Natural Systems (CHANS) modelling framework that integrates a hydrodynamic model with an agent-based model at the memory level within a multi-GPU computing environment. This two-way coupled model captures real-time interactions between human activities and flood dynamics, with a focus on the deployment of temporary flood defences during the 2015 Desmond flood in Carlisle, UK. The findings reveal that temporary defences can significantly reduce flood inundation by 30% with early warnings and 15% through real-time decision-making, leading to financial savings of £30 million and £15 million, respectively. The study further explores the decision-making process for effective emergency flood management, emphasising the importance of early warnings and resources optimisation. The new CHANS model provides a valuable tool for testing and optimising emergency flood management strategies, highlighting the necessity of directly incorporating human activities into flood risk management.