Complex systems in aeolian geomorphology
Complex systems in aeolian geomorphology
复制标题
DOI：
10.1016/j.geomorph.2007.04.012
复制
发表时间：
2007-11-01
期刊：
影响因子：
3.9
通讯作者：
Baas, Andreas C. W.
中科院分区：
文献类型：
--
作者：
Baas, Andreas C. W.
风成地貌学为研究地球表面过程和地貌复杂系统提供了丰富的基础。风沙运动是一个典型的耗散非线性动力学过程，而沙丘场演化是一个典型的自组织现象。这两个广泛领域的风成地貌的复杂性和系统的方法进行了讨论和分析。基于当代物理模型的风成边界层流/沉积物输运/床型相互作用的反馈回路分析表明，该系统从根本上是不稳定的（或至多是亚稳定的），并可能表现出混沌行为。最近的现场实验研究风成流光和时空运输模式，但是，表明，沙运输风可能完全控制的自相似湍流级联的边界层流，和运输事件时间序列的关键方面可以完全再现（自组织）1/fforcing，运动阈值和跃移惯性的组合。各种类型的裸沙丘和沙丘场模式的演变已经成功地模拟与自组织细胞自动机，只包括简化的物理为基础的相互作用（规则）。然而，由于它们的物理规模不确定，不清楚它们实际上是模拟涟漪（底形）还是沙丘（地貌），这就提出了关于风成沙丘、撞击涟漪和水下（水流）涟漪和沙丘之间区别的基本交叉问题。一个扩展的元胞自动机（CA）模型，目前正在开发中，纳入了植被在风沙环境中的影响，并能够模拟nebkhas，井喷，抛物线海岸沙丘的发展。初步结果表明，建立相图和吸引子轨迹植被风成沙丘的潜力。然而，进展是有限的，严重缺乏适当的概念量化有意义的状态变量在景观尺度。目前在裸沙模型中使用的状态变量远不能捕捉到丰富的3D地形和模式，并且没有足够的判别力来区分不同的吸引子。扩展模型中的植被成分，以及实际上一般的生态地貌系统，对建立适当的状态变量提出了更严峻的挑战。重新审视旧的概念，如景观熵，也许补充信息理论的最新发展，可能是一个潜在的富有成效的研究途径，虽然这样的实施纲要仍然相当模糊。(C)2007 Elsevier B. V.保留所有权利。
Aeolian geomorphology provides a rich ground for investigating Earth surface processes and landforms as complex systems. Sand transport by wind is a classic dissipative process with non-linear dynamics, while dune field evolution is a prototypical self-organisation phenomenon. Both of these broad areas of aeolian geomorphology are discussed and analysed in the context of complexity and a systems approach. A feedback loop analysis of the aeolian boundary-layer-flow/sediment-transport/bedform interactions, based on contemporary physical models, reveals that the system is fundamentally unstable (or at most meta-stable) and likely to exhibit chaotic behaviour. Recent field-experimental research on aeolian streamers and spatio-temporal transport patterns, however, indicates that sand transport by wind may be wholly controlled by a self-similar turbulence cascade in the boundary layer flow, and that key aspects of transport event time-series can be fully reproduced from a combination of (self-organised) 1/fforcing, motion threshold, and saltation inertia. The evolution of various types of bare-sand dunes and dune field patterns have been simulated successfully with self-organising cellular automata that incorporate only simplified physically-based interactions (rules). Because of their undefined physical scale, however, it not clear whether they in fact simulate ripples (bedforms) or dunes (landforms), raising fundamental cross-cutting questions regarding the difference between aeolian dunes, impact ripples, and subaqueous (current) ripples and dunes. An extended cellular automaton (CA) model, currently under development, incorporates the effects of vegetation in the aeolian environment and is capable of simulating the development of nebkhas, blow-outs, and parabolic coastal dunes. Preliminary results indicate the potential for establishing phase diagrams and attractor trajectories for vegetated aeolian dunescapes. Progress is limited, however, by a serious lack of appropriate concepts for quantifying meaningful state variables at the landscape scale. State variables currently used in the bare-sand models are far from capturing the rich 3D topography and patterns and are not sufficiently discriminative to distinguish different attractors. The vegetation component in the extended model, and indeed ecogeomorphic systems in general, pose even graver challenges to establishing appropriate state variables. A re-examination of older concepts, such as landscape entropy, perhaps complemented by recent developments in information theory, may be a potentially fruitful avenue for research, although the outlines of such an implementation are still rather vague. (C) 2007 Elsevier B.V. All rights reserved.