2D numerical simulation of unsteady flows for large scale floods prediction in real time. (December 2019)

• Record Type: Journal Article
• Authors: Echeverribar, I.; Morales-Hernández, M.; Brufau, P.; García-Navarro, P.
• Is Part Of: Advances in water resources. Volume 134(2019)
• Publication Date: 2019-12
• Subjects: Computational mesh -- Shallow water flow -- GPU -- Real time flood prediction; Hydrology -- Periodicals; Hydrodynamics -- Periodicals; Hydraulic engineering -- Periodicals; 551.48
• DOI: 10.1016/j.advwatres.2019.103444
• Languages: English
• ISSNs: 0309-1708

Abstract

Highlights: A sophisticated fully 2D model accelerated with GPU is presented. Details of the numerical scheme and the acceleration technique are given. The necessity of these numerical fixes in real cases is demosntrated. The model is applied to a large stretch of the Ebro River. The results are compared with field measurements. Abstract: The challenge of finding a compromise between computational time and level of accuracy and robustness has traditionally expanded the use simplified models rather than full two-dimensional (2D) models for flood simulation. This work presents a GPU accelerated 2D shallow water model for the simulation of flood events in real time. In particular, an explicit first-order finite volume scheme is detailed to control the numerical instabilities that are likely to appear when used in complex topography. The model is first validated with the benchmark test case of the Toce River (Italy) and numerical fixes are demonstrated to be necessary. The model is next applied to reproduce real events in a reach of the Ebro River (Spain) in order to compare simulation results with field data. The second case deals with a large domain (744 km 2 ) and long flood duration (up to 20 days) allowing an analysis of the performance and speed-up achieved by different GPU devices. The high values of fit between observed and simulated results as well as the computational times achieved are encouraging to propose the use of the model as forecasting system.