A MATHEMATICAL FRAMEWORK TO CHARACTERIZE COMPLEXITY ASSEMBLY IN FRACTAL RIVER NETWORKS

IF 3.3 3区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
YI JIN, JINGYAN ZHAO, JIABIN DONG, JUNLING ZHENG, QING ZHANG, DANDAN LIU, HUIBO SONG
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引用次数: 0

Abstract

As a multi-scale system featuring fractal hierarchical branching structure, the quantitative characterization of natural river networks is of fundamental significance for the assessment of the hydrological and ecological issues. However, as already evidenced, the fractal behavior cannot be uniquely inverted by fractal dimension, which induces a challenge in accurately describing the arbitrary scale-invariance properties in natural river networks. In this work, as per fractal topography theory, an open mathematical framework for the description of arbitrary fractal river networks is proposed by clarifying the assembly mechanisms of complexity types (i.e. the original and behavioral complexities) in a river network. On this basis, a general algorithm for the characterization of complexities is developed, and the effects of the original and behavioral complexities on the structure of a river network are systematically explored. The results indicate that the original complexity determines the tortuosity and spatial coverage of a river network, and the behavioral complexity dominates the river patterns, heterogeneity, and scale-invariance properties. Our investigation lays a foundation for assessing and predicting accurately the effect on environments, ecology and humans from river networks.
分形河网复杂性装配的数学框架
天然河网作为一个具有分形层次分支结构的多尺度系统,其定量表征对水文生态问题的评价具有基础性意义。然而,由于分形维数不能唯一地反映自然河网的分形行为,这给准确描述河网的任意尺度不变性带来了挑战。本文根据分形地形理论,通过阐明河网中复杂性类型(即原始复杂性和行为复杂性)的组装机制,提出了描述任意分形河网的开放数学框架。在此基础上,提出了一种表征复杂性的通用算法,并系统地探讨了原始复杂性和行为复杂性对河网结构的影响。结果表明:原始复杂性决定了河网的扭曲度和空间覆盖度,行为复杂性决定了河网的格局、异质性和尺度不变性。本研究为准确评估和预测河网对环境、生态和人类的影响奠定了基础。
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来源期刊
CiteScore
7.40
自引率
23.40%
发文量
319
审稿时长
>12 weeks
期刊介绍: The investigation of phenomena involving complex geometry, patterns and scaling has gone through a spectacular development and applications in the past decades. For this relatively short time, geometrical and/or temporal scaling have been shown to represent the common aspects of many processes occurring in an unusually diverse range of fields including physics, mathematics, biology, chemistry, economics, engineering and technology, and human behavior. As a rule, the complex nature of a phenomenon is manifested in the underlying intricate geometry which in most of the cases can be described in terms of objects with non-integer (fractal) dimension. In other cases, the distribution of events in time or various other quantities show specific scaling behavior, thus providing a better understanding of the relevant factors determining the given processes. Using fractal geometry and scaling as a language in the related theoretical, numerical and experimental investigations, it has been possible to get a deeper insight into previously intractable problems. Among many others, a better understanding of growth phenomena, turbulence, iterative functions, colloidal aggregation, biological pattern formation, stock markets and inhomogeneous materials has emerged through the application of such concepts as scale invariance, self-affinity and multifractality. The main challenge of the journal devoted exclusively to the above kinds of phenomena lies in its interdisciplinary nature; it is our commitment to bring together the most recent developments in these fields so that a fruitful interaction of various approaches and scientific views on complex spatial and temporal behaviors in both nature and society could take place.
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