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Statistical Characterization of Morphodynamic Signals Using Wavelet Analysis

Gutierrez, Ronald R. (2013) Statistical Characterization of Morphodynamic Signals Using Wavelet Analysis. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Morphodynamic and hydrodynamic properties are concomitantly part of the entire dynamic of river systems and commonly present both temporal and spatial persistent variability. Therefore, the study of both river morphodynamic signals (e.g. bed forms and meandering and anabranching river morphometrics) and hydrodynamic signals (e.g. velocity fields, sediment concentrations) requires both temporal and spatial multi-scale signal representations. The present research is focused on the former type of signals and it is a first attempt to discriminate such signals and, subsequently, develop the theoretical background to link these processes at different spatial and temporal scales and determine the scales that have more influence on river evolution.
The main contribution of this study are: [1] to design a methodology to discriminate bed form features (e.g. bars, dunes and ripples) via the combined application of robust spline filters and one-dimensional continuous wavelet transforms, allowing the quantitative recognition of bed form hierarchies. The methodology was tested by using synthetic bed form signals and subsequently applied to the analysis of bed form features from the Parana River, Argentina. [2] To develop a methodology for the statistical analysis of the spatial distribution of meandering rivers morphometrics by coupling the capabilities of one-dimensional wavelet transforms, principal component analysis and Frechet distance. A universal river classification method is also proposed. [3] To perform a novel study of the planimetric configuration of confluences in tropical free meandering rivers located in the upper Amazon catchment. River confluences in tropical environments represent areas where biota is concentrated; therefore, a better understanding and characterization of these features has a particular importance for the Amazonian ecosystem. [4] To evaluate the potential of two-dimensional wavelet transforms in the analysis of bed form features.
The broader impact will be an improved understanding of river morphodynamics of the upper Amazon River for practical applications such as navigability. Furthermore, the project will provide an updated statistical analysis of the meandering rivers dynamics for practical applications, including erosion control, river ecology, and habitat restoration. The developed statistical tool will be included as an application of the RVR Meander platform (, which is a broadly used software for river restoration.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Gutierrez, Ronald R.rrg11@pitt.eduRRG11
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorAbad, Jorgejabad@pitt.eduJABAD
Committee MemberLiang, Xuxuliang@pitt.eduXULIANG
Committee MemberBudny, Danielbudny@pitt.eduBUDNY
Committee MemberRizzo, Piervincenzopir3@pitt.eduPIR3
Committee MemberLangendoen, EddyEddy.Langendoen@ARS.USDA.GOV
Date: 25 September 2013
Date Type: Publication
Defense Date: 3 April 2013
Approval Date: 25 September 2013
Submission Date: 27 June 2013
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 160
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Civil and Environmental Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: River morphodynamics, meanders, river confluences, wavelet transforms
Date Deposited: 25 Sep 2013 13:36
Last Modified: 25 Sep 2018 05:15


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