Development and evaluation of a GPU-based coupled three-dimensional hydrodynamic and water quality model. (February 2023)

• Record Type: Journal Article
• Authors: Ma, Qiaofeng; Liang, Shuxiu; Sun, Zhaochen; Zhang, Ruijin; Wang, Ping
• Is Part Of: Marine pollution bulletin. Volume 187(2023)
• Publication Date: 2023-02
• Subjects: GPU acceleration -- Three-dimensional -- Coupled hydrodynamic and water quality model -- Marine pollution source; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2022.114494
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: In this study, a graphics processing unit (GPU)-based three-dimensional coupled hydrodynamic and water quality numerical model (GPUOM-WQ) was developed for the first time, which introduces pollution sources of atmospheric deposition, aquaculture wastewater, and oil platform emission to describe marine pollution comprehensively. A test case with analytical solutions and a real case with measured data were used to validate the accuracy of GPUOM-WQ. Simulation results indicate that the maximum error between the numerical and analytical solutions is 0.9 %, and the average relative error between simulated and measured values of 5 water quality variables at 38 stations in spring, summer, fall and winter is 14.63 %. In the real case simulation, GPUOM-WQ accelerates the computation 62.48 times, which is 3.23 times faster than in 64-core central processing unit (CPU) parallel mode. This study makes it possible to accurately simulate the marine water quality variation and spatiotemporal distribution in a high-resolution and efficient way. Highlights: A GPU-based 3D coupled hydrodynamic and water quality numerical model is developed. Atmospheric deposition, aquaculture wastewater and oil platform emission are included. The accuracy of the model is verified by two cases. The model achieves 62.48 times speedup ratio.