高抒. 海洋沉积地质过程模拟:性质与问题及前景[J]. 海洋地质与第四纪地质, 2011, 31(5): 1-7. DOI: 10.3724/SP.J.1140.2011.05001
引用本文: 高抒. 海洋沉积地质过程模拟:性质与问题及前景[J]. 海洋地质与第四纪地质, 2011, 31(5): 1-7. DOI: 10.3724/SP.J.1140.2011.05001
GAO Shu. NUMERICAL MODELING OF MARINE SEDIMENTARY PROCESSES: THE NATURE, SCIENTIFIC PROBLEMS, AND PROSPECT[J]. Marine Geology & Quaternary Geology, 2011, 31(5): 1-7. DOI: 10.3724/SP.J.1140.2011.05001
Citation: GAO Shu. NUMERICAL MODELING OF MARINE SEDIMENTARY PROCESSES: THE NATURE, SCIENTIFIC PROBLEMS, AND PROSPECT[J]. Marine Geology & Quaternary Geology, 2011, 31(5): 1-7. DOI: 10.3724/SP.J.1140.2011.05001

海洋沉积地质过程模拟:性质与问题及前景

NUMERICAL MODELING OF MARINE SEDIMENTARY PROCESSES: THE NATURE, SCIENTIFIC PROBLEMS, AND PROSPECT

  • 摘要: 探讨了海洋沉积地质数值模拟的功能问题。地球科学研究以正演方法(以数值模拟为代表)和反演方法(以地层记录分析为代表)的结合为特征。数值模拟作为一种重要的研究工具,具有获得过程和机理分析结果、形成工作假说、指导现场观测和采样的作用。与此同时,在正反演交融中模型本身也得到了提高和完善。在海洋沉积地质领域,数值模拟在沉积物输运和堆积过程、地貌演化过程、全新世陆架与海岸沉积层序形成、沉积记录形成过程、极端事件过程以及环境动力和生态系统过程的研究中具有很大潜力。但是,进一步的发展取决于能否克服自然系统和模型自身复杂性的制约,为此需要以"学术共同体模型"方式来加以推进。

     

    Abstract: In the present contribution the functions of numerical models in marine sedimentary geology are analyzed. The basic research in earth sciences is characterized by a combination of forward modeling and inverse (i.e. core analysis) methods. Numerical modeling represents an important tool for the research, which can play a key role in the understanding of processes and mechanisms associated with a geological system, the formulation of working hypotheses for further studies, and the design of field measurements and sampling schemes. At the same time, with the interaction between the numerical experiments and the analysis of ground truth data, the models themselves may be improved, approaching a sophisticated status. In the field of marine sedimentary geology, numerical modeling will contribute significantly to the studies of sediment transport and accumulation processes, morphodynamic processes, the formation of Holocene costal and shelf sedimentary sequences and stratigraphic records, deposits of extreme events, as well as environmental dynamics and ecosystem dynamics, in the near future. At the present stage, the models have to be able to deal with complex natural systems and, therefore, they are becoming increasingly complicated in structure and functioning. In order to cope with such a situation, a "community modeling" approach should be adopted to improve the modeling techniques.

     

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