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Statistical self-similarity of width function maxima with implications to floods

Advances in Water Resources

By:
,
DOI: 10.1016/S0309-1708(01)00030-6

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Abstract

Recently a new theory of random self-similar river networks, called the RSN model, was introduced to explain empirical observations regarding the scaling properties of distributions of various topologic and geometric variables in natural basins. The RSN model predicts that such variables exhibit statistical simple scaling, when indexed by Horton-Strahler order. The average side tributary structure of RSN networks also exhibits Tokunaga-type self-similarity which is widely observed in nature. We examine the scaling structure of distributions of the maximum of the width function for RSNs for nested, complete Strahler basins by performing ensemble simulations. The maximum of the width function exhibits distributional simple scaling, when indexed by Horton-Strahler order, for both RSNs and natural river networks extracted from digital elevation models (DEMs). We also test a powerlaw relationship between Horton ratios for the maximum of the width function and drainage areas. These results represent first steps in formulating a comprehensive physical statistical theory of floods at multiple space-time scales for RSNs as discrete hierarchical branching structures. ?? 2001 Published by Elsevier Science Ltd.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Statistical self-similarity of width function maxima with implications to floods
Series title:
Advances in Water Resources
DOI:
10.1016/S0309-1708(01)00030-6
Volume
24
Issue:
9-10
Year Published:
2001
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
955
Last page:
965
Number of Pages:
11