Visual Simulation of Eroded Rill Evolution Process on Graphics Processing Unit

Authors

Mansheng Long, 1. School of Electronics and Information Engineering, Jinggangshan University, Ji'an 343009, China; ;2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG, Ji'an 343009, China;

Abstract

Abstract: A slope erosion model based on CA (Cellular Automata) and a corresponding simulation algorithm based on GPU (Graphics Processing Unit) were proposed to visualize rapidly the dynamic process of water erosion and microrelief development on hillslope under rainfall events. The model is composed of processes such as rainfall, infiltration, runoff, erosion, deposition, and sediment transport. At each time step, water and sediment were exchanged among adjacent cells observing sediment mass conservation law and flow continuity equation. All cells update their runoff and sediment simultaneously complying with the above simple rules so as to realize the evolution of hillslope microrelief. Perlin noise was superimposed on the slope surface to model the spatial variation and randomness of erosion factors such as microrelief and rainfall, which enhanced the visual effect of rill development. The experiment results show that the slope erosion model based on CA can effectively characterize the rill development process on hillslope, and GPU can be used to greatly improve the real-time performance of slope erosion visualization.

Recommended Citation

Long, Mansheng (2020) "Visual Simulation of Eroded Rill Evolution Process on Graphics Processing Unit," Journal of System Simulation: Vol. 29: Iss. 3, Article 7.
DOI: 10.16182/j.issn1004731x.joss.201703007
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss3/7

First Page

516

Revised Date

2015-07-21

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201703007

Last Page

523

CLC

TP391.9

Recommended Citation

Long Mansheng. Visual Simulation of Eroded Rill Evolution Process on Graphics Processing Unit[J]. Journal of System Simulation, 2017, 29(3): 516-523.

DOI

10.16182/j.issn1004731x.joss.201703007