Author(s): Reinaldo Garcia, Pilar Garcia-Navarro

Linked Author(s): Pilar García-Navarro

Keywords: Water drones; 2D models; GPU; Cloud Computing;

Abstract: Water drone technology are making available huge amount of high-resolution bathymetric data for hydraulic simulation models. However, the application of two-dimensional (2D) models that make use of this data confronts several obstacles, including the model limitation to handle the enormous quantity of elevation points, and very long runtimes, which often make the use of 2D models impractical if not impossible. There have been attempts to use square cell models to large scale applications, but this type of model need to use very small cell size all over the modeling area, leading to excessive number of cell elements. The development of parallelized versions of 2D numerical finite-volume algorithm for Graphic Processing Units (GPUs) on flexible meshes, is radically changing the hydrologic and hydraulic modeling practice. However, until recently, the cost of top-of the line hardware had prevented widespread use of this technology. In this work we discuss a high-resolution application of the RiverFlow2D model running in the Google Cloud to simulate flow around hydraulic structures in the Everglades National Park in the USA. One to 4 million cells were generated using a plugin developed for the QGIS open source Geographic Information System. The model was calibrated with ADCP velocity data. In order to perform simulations remotely and using the most advanced hardware, the model was implemented in Google Cloud VMs (Virtual Machines) with NVIDIA Tesla V100 cards. The GPU Cloud model allowed reducing runtimes from 50 to 600 times costing less than 2 US$ per hour. Results demonstrate that high-resolution applications, that were not feasible until recently can be realistically done using highly detailed bathymetric surveys gathered with water drones and GPU flexible mesh 2D models in the Cloud.

DOI: https://doi.org/10.3850/38WC092019-8882

Year: 2019