Civil Engineering ETDs

Publication Date

Summer 7-16-2018

Abstract

Riparian vegetation, an indicator of healthy river system, increases the hydraulic roughness and reduces the conveyance capacity of a channel. Vegetation provides dominant drag force influencing the velocity distribution, turbulence intensity and water depth. Thus, the study of hydraulic roughness due to vegetation is essential to determine the characteristics of flow. Traditionally, a constant Manning’s roughness value is assigned based on land cover maps and that does not adequately account for vegetation. The roughness due to vegetation are determined on the basis of its parameters like height, density, LAI and flexibility. Remote sensing data (LiDAR, aerial photos or satellite images) are preferred in determining detailed vegetation parameters to time consuming field data. The objective of this research was to evaluate the performance of remote sensing-based methods to estimate hydraulic roughness of vegetation. A Canopy Height Model (CHM) was used in this study to estimate the height of vegetation and an empirical relation (Beer Lambert law) to determine LAI from LiDAR data for Middle Rio Grande reach located at Albuquerque, New Mexico. The two two-dimensional hydrodynamic models, Sedimentation and River Hydraulics (SRH-2D) model and SRH-2DV, were used in this study. The models were simulated for four different flows (142 m3/s, 198 m3/s, 283 m3/s and 425 m3/s) for two roughness conditions i.e. constant and dynamic roughness. The results showed the minor changes in hydraulic parameters determined due to constant and dynamic roughness. The overall average dynamic roughness value predicted was more by 0.0008 compared to constant roughness for 283 m3/s. Due to increase in dynamic roughness, water depth increased by 4 cm reducing the velocity by 1.7 cm/s for 283 m3/s. Further study is suggested to determine the accuracy of hydraulic roughness estimated due to vegetation parameters derived from LiDAR through calibration of model results.

Keywords

LiDAR, Vegetation parameters, Hydrodynamic modeling, Middle Rio Grande

Document Type

Thesis

Language

English

Degree Name

Civil Engineering

Level of Degree

Masters

Department Name

Civil Engineering

First Committee Member (Chair)

Mark Stone

Second Committee Member

Julie Coonrod

Third Committee Member

Su Zhang

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