Suppr超能文献

河网的几何学。I. 尺度、波动与偏差。

Geometry of river networks. I. Scaling, fluctuations, and deviations.

作者信息

Dodds P S, Rothman D H

机构信息

Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Jan;63(1 Pt 2):016115. doi: 10.1103/PhysRevE.63.016115. Epub 2000 Dec 27.

Abstract

This paper is the first in a series of three papers investigating the detailed geometry of river networks. Branching networks are a universal structure employed in the distribution and collection of material. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary, suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, here we report a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of a subbasin's dominant stream with its area, a characterization of basin shape known as Hack's law. We generalize this relationship to a joint probability density, and provide observations and explanations of deviations from scaling. We show that fluctuations about scaling are substantial, and grow with system size. We find strong deviations from scaling at small scales which can be explained by the existence of a linear network structure. At intermediate scales, we find slow drifts in exponent values, indicating that scaling is only approximately obeyed and that universality remains indeterminate. At large scales, we observe a breakdown in scaling due to decreasing sample space and correlations with overall basin shape. The extent of approximate scaling is significantly restricted by these deviations, and will not be improved by increases in network resolution.

摘要

本文是三篇系列论文中的第一篇,研究河网的详细几何结构。分支网络是一种用于物质分布和收集的通用结构。大型河网是二维分支网络的一个重要类别,不仅具有内在的研究价值,也是一种普遍存在的自然现象。在河网结构的描述中,尺度律是普遍观察到的。报道的尺度指数值各不相同,这表明不存在唯一的一组尺度指数。为了改进目前对河网尺度的理解,并更全面地描述分支网络结构,我们在此报告一项关于尺度波动和偏离尺度的理论与实证研究。我们研究了如密西西比河和亚马逊河等大陆尺度河网的数据,并从一个简单的有向随机网络模型中获得灵感。我们将研究重点放在子流域主河流长度与其面积的尺度关系上,这是一种被称为哈克定律的流域形状特征。我们将这种关系推广到联合概率密度,并对尺度偏离进行观察和解释。我们表明,尺度波动很大,且随系统规模增大。我们发现在小尺度上存在强烈的尺度偏离,这可以由线性网络结构的存在来解释。在中等尺度上,我们发现指数值存在缓慢漂移,这表明尺度只是大致遵循,普遍性仍然不确定。在大尺度上,由于样本空间减小以及与整个流域形状的相关性,我们观察到尺度关系失效。这些偏离显著限制了近似尺度的范围,并且不会因网络分辨率的提高而得到改善。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验