Grant: Idea to Innovation

Increasing city resilience to floods under climate change has become one of the major challenges for decision-makers, urban planners, and engineering practitioners around the world. Accurate prediction of urban floods under heavy precipitation is critically important to address such a challenge as it can help understand the vulnerability of a city to future climate change and simulate the effectiveness of various sustainable engineering techniques in reducing urban flooding risks in real urban settings. It has been observed that the financial sectors are investing significantly in flood prediction efforts with the increase in flood events nationally and globally. Several conventional hydrological models are available, but they cannot be applied directly for flood simulation because they are incapable of estimating flood extent and depth. We proposed a new model named 'FloodMapper' for accurate urban flooding under heavy precipitation events. In our model, we divide the study area into many grid cells, involving both horizontal and vertical flow together in each step of the modelling. We use both the surface height and instantaneous surface water depth to determine the directions of horizontal inflow and outflow for each grid cell during each time step of modelling; this enables us to capture the reverse-flow phenomenon. Although our model is comparatively new, we tested and released its free version in the market already in 2018. We used the model successfully to reproduce the 2016 flood in Lafayette Parish in Louisiana to demonstrate its effectiveness in predicting both flood extent and depth during real-world flooding events. With the cutting-edge market training by L2M program, we hope to achieve a better understanding of our market and the preparations needed for the future steps.