Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing

• Published in: Natural hazards (Dordrecht) Vol. 91; no. 2; pp. 567 - 586
• Main Authors: Hu, Xiaozhang, Song, Lixiang
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.03.2018; Springer Nature B.V
• Subjects: Accuracy; Banks (topography); Civil Engineering; Computational efficiency; Computer applications; Computer simulation; Computing time; Data; Data processing; Data structures; Earth and Environmental Science; Earth Sciences; Environmental Management; Flash flooding; Flash floods; Flood predictions; Flooding; Floods; Fronts; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Graphics; Graphics processing units; Hydrodynamic models; Hydrodynamics; Hydrogeology; Mathematical models; Model accuracy; Modelling; Natural Hazards; Original Paper; Overland flow; Rain; Rainfall; Resolution; Robustness (mathematics); Runoff; Runoff process; Simulation; Slope; Solutions; Surface runoff; Topography; Topography (geology); Two dimensional models; Watersheds; Hydrodynamic model; Mountain watershed; Numerical simulation; Flash flood; Finite volume; GPU computing
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-017-3141-7

Numerical accuracy and computational efficiency are the two key factors for flash flood simulation. In this paper, a two-dimensional fully hydrodynamic model is presented for the simulation of flash floods in mountain watersheds. A robust finite volume scheme is adopted to accurately simulate the overland flow with wet/dry fronts on highly irregular topography. A graphics processing unit-based parallel method using OpenACC is adopted to realize high-performance computing and then improve the computational efficiency. Since the finite volume scheme is explicit which involves many computationally intensive loop structures without data dependence, the parallel flash flood model can be easily realized by using OpenACC directives in an incremental developing way based on the serial model codes, except that data structure and transportation should be optimized for parallel algorithm. Model accuracy is validated by benchmark cases with exact solutions and experimental data. To further analyze the performance of the model, we considered a real flash flooding-prone area in China using a NVIDIA Tesla K20c card and three grid division schemes with different resolution. Results show that the proposed model can fast simulate the rainfall−runoff process related to the rapid mountain watersheds response, and a higher speedup ratio can be achieved for finer grids resolution. The proposed model can be used for real-time prediction of large-scale flash flood on high-resolution grids and thus has bright application prospects.