The simulation speed of two‐dimensional hydrodynamic flood models is a limiting factor when catchments are large, a considerable number of simulations is required (e.g., exploratory modeling, Monte‐Carlo flood simulations, or predicting probabilistic flood maps), or when there is a need for real‐time flood emergency management. Rapid Flood Models (RFMs) that rely only on topographic depressions and the water balance equation have been successfully implemented to predict maximum urban flood inundation depths within seconds to a few minutes. However, the preprocessing step (identification of depressions and their attributes) and the postprocessing step (marking up possible flow paths of flood water in between flooded depressions) of RFMs is time consuming. In this study, we developed a new fast flood inundation model based on the cellular automata (CA) approach. The new model does not require the preprocessing and postprocessing steps of RFMs and therefore can provide more simulation speed. The performance of our new model, referred to as Cellular Automata fast flood evaluation (CA‐ffé), was compared to two well‐known hydrodynamic flood models (HEC‐RAS and TUFLOW) in 20 simulation experiments conducted in five different urban subcatchments. CA‐ffé predicted maximum inundation depth with reasonable accuracy in a matter of seconds to a few minutes for a single rainfall event simulation. The CA‐ffé model performed exceptionally well in areas with low‐lying depressions. However, in areas where floodwaters had higher momentum and velocity, the model usually was not able to estimate inundation depths calculated by HEC‐RAS or TUFLOW. CA‐ffé's key drawback is also its inability to represent the temporal evolution of flooding and flow velocities. Nevertheless, its ability to provide spatial flood extents and depths in a fraction of the time compared to its hydrodynamic counterparts is a significant advancement toward exploratory approaches for water systems planning, model‐based predictive control, and real‐time flood management.

Water Sensitive Urban Design (WSUD) has attracted growing attention as a sustainable approach for mitigating pluvial flooding (also known as flash flooding), which is expected to increase in frequency and intensity under the impacts of climate change and urbanisation. However, spatial planning of WSUD is not an easy task, not only due to the complex urban environment, but also the fact that not all locations in the catchment are equally effective for flood mitigation. In this study, we developed a new WSUD spatial prioritisation framework that applies global sensitivity analysis (GSA) to identify priority subcatchments where WSUD implementation will be most effective for flood mitigation. For the first time, the complex impact of WSUD locations on catchment flood volume can be assessed, and the GSA in hydrological modelling is adopted for applications in WSUD spatial planning. The framework uses a spatial WSUD planning model, the Urban Biophysical Environments and Technologies Simulator (UrbanBEATS), to generate a grid-based spatial representation of catchment, and an urban drainage model, the U.S. EPA Storm Water Management Model (SWMM), to simulate catchment flooding. The effective imperviousness of all subcatchments was varied simultaneously in the GSA to mimic the effect of WSUD implementation and future developments. Priority subcatchments were identified based on their influence on catchment flooding computed through the GSA. The method was tested for an urbanised catchment in Sydney, Australia. We found that high priority subcatchments were clustering in the upstream and midstream of the main drainage network, with a few distributed close to the catchment outlets. Rainfall frequency, subcatchment characteristics, and pipe network configuration were found to be important factors determining the influence of changes in different subcatchments on catchment flooding. The effectiveness of the framework in identifying influential subcatchments was validated by comparing the effect of removing 6% of the Sydney catchment's effective impervious area under four WSUD spatial distribution scenarios. Our results showed that WSUD implementation in high priority subcatchments consistently achieved the largest flood volume reduction (3.5-31.3% for 1% AEP to 50% AEP storms), followed by medium priority subcatchments (3.1-21.3%) and catchment-wide implementation (2.9-22.1%) under most design storms. Overall, we have demonstrated that the proposed method can be useful for maximising WSUD flood mitigation potential through identifying and targeting the most effective locations.

Rapid urbanisation, population growth and the effects of climate change drive the need for sustainable urban water management (SUWM) in Asian cities. The complexity of this challenge calls for the integration of knowledge from different disciplines and collaborative approaches. This paper identifies key issues and sets the stage for interdisciplinary research on SUWM in Asia. It reports on the initial stages of a SUWM research programme being undertaken at Monash University, Australia, and proposes a framework to guide the process of interdisciplinary research in urban water management. Three key themes are identified: (1) Technology and Innovation, (2) Urban Planning and Design, and (3) Governance and Society. Within these themes 12 research projects are being undertaken across Indonesia, China, India and Bangladesh. This outward-looking, interdisciplinary approach guides our research in an effort to transgress single-discipline solutions and contribute on-ground impact to SUWM practices in Asia.