A Parallel Computation and Web Visualization Framework for Rapid Large-scale Flood Risk Mapping

Abstract

Abstract For rapid flood risk mapping, a key aspect is transferring the results of flood simulations for web visualization. The challenges here include: (1) large-scale and complicated modelling; (2) the need for fast computation to solve flood numerical models; and (3) effective web visualization. This paper tackles these challenges by introducing a web-based framework that can transfer the results of parallel flood simulation to a web visualization application. Flood depth data, velocity and flood arrival time are calculated using a parallel shallow water model with a predicted input flow. This is automatically transferred into shapefile data using ArcObjects components. Other data relating to the flood risk mapping is managed and served through a REST (Representational State Transfer) interface. The web visualization is performed using the ArcGIS for JavaScript API. We applied the framework to the floodplain of the lower Yellow River in China. The results show basic geo-information about the domain, the flood depth classified by color and economic loss through inundation of villages and farmland. Although the simulated domain was large and the boundary conditions complicated, the whole process from flood risk simulation to web visualization took less than 3 hours, which is enough time to increase flood preparedness.