Systematic connectivity in single thread meandering alluvial rivers: statistical generalization of hydraulic geometry

Czapiga, Matthew

Permalink

https://hdl.handle.net/2142/44498 Copy

Description

Title

Systematic connectivity in single thread meandering alluvial rivers: statistical generalization of hydraulic geometry

Author(s)

Czapiga, Matthew

Issue Date

2013-05-24T22:18:19Z

Director of Research (if dissertation) or Advisor (if thesis)

Parker, Gary

Department of Study

Civil & Environmental Eng

Discipline

Civil Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• River Morphodynamics
• Bankfull Hydraulic Geometry
• Connectivity

Abstract

System connectivity is achieved when some intrinsic organization allows inter-medium travel. Depth connectivity is investigated in alluvial meandering streams as a solution to river navigability. These types of rivers are naturally ordered systems, which exhibits self-similarity amongst many scales. Four river sections and four experimental runs were used to investigate patterns in depth connectivity with varied path dimensions. Dimensions of measured depth and connective path were made dimensionless through bankfull hydraulic geometry. As these mean statistics scale with river discharge, connective paths should follow the same trends. Systematic connectivity was computed through a numerical calculation that determines the success rate for every combination of dimensionless depth, path width, and path length. Distributions of depth are presented as hypsometric curves; the standard deviation of these distributions quantifies depth variability. The experimental runs shows larger magnitude depths and more variability in depths larger than bankfull channel depth. Experimental runs also display lower internal connectivity than the rivers. Connectivity results show similarity as a function of dimensionless path dimensions, a dimensionless threshold depth, and the reach-averaged hypsometric standard deviation. A first order model is presented which adequately predicts general patterns, but accuracy decreases through increases to either the width factor or hypsometric standard deviation.

Graduation Semester

2013-05

Permalink

http://hdl.handle.net/2142/44498

Copyright and License Information

Copyright 2013 Matthew Czapiga

Owning Collections