Improving the Computational Performance of an Operational Two-Dimensional Real-Time Flooding Forecasting System by Active-Cell and Multi-Grid Methods in Taichung City, Taiwan

An operational two-dimensional real-time flood forecasting system has been developed in Taiwan to prevent urban inundation. This system takes an hour to come up with forecasts for the next three hours, and the resolution of the forecasts is 40 × 40 m. This study used a large urban area of 126 km2 in downtown Taichung City for the case study and adopted the active-cell and multi-grid methods to meet the target by computing from data of a 12-h rainfall within one hour at 20 m × 20 m spatial resolution to provide faster forecasting and more hours for flood preparation. With the active-cell method, the Central Processing Unit (CPU) time was reduced by 65.04% from 659 m 29 s to 230 m 33 s under the 200-year return period storm. Further, with multi-grid methods, the CUP time was reduced by 73.98% from 230 m 33 s to 60 m 0 s. In general, the computing time of this model has been reduced 11-fold. The error validation coefficients of inundation areas were between 89.39~97.45% with an average error of depth between 1.06~3.22 cm.