AN ABSTRACT OF THE THESIS OF
Rachelle S. Valverde for the degree of Master of Science in Civil Engineering presented on June
18, 2013
Title: Roughness and Geometry Effects of Engineered Log Jams on 1-D Flow Characteristics
Abstract approved:
________________________________________________________________
Desirée D. Tullos
The re-introduction of large woody debris (LWD) into streams and rivers for stream restoration
purposes is rapidly growing. Engineered log jams (ELJs) are man-made structures intended to
mimic natural LWD structures, designed and installed to protect stream banks from erosion while
increasing habitat diversity. Several studies have evaluated the flow resistance of single cylinder
wooden objects; however, limited information is available on complex ELJs. Design guidelines
recommend using hydraulic models to evaluate the flooding impact of proposed ELJ designs and
one-dimensional (1-D) hydraulic models are often used in the design of ELJs. However, while 1D models have contributed some new knowledge, their application in the design of ELJs is still
underdeveloped. For example, ELJs are often represented in practice as high ground or increased
roughness in one-dimensional hydraulic models, but the accuracy and influence of adjusting
channel geometry or roughness to represent ELJs has not been evaluated. This study thus
evaluates the performance and characterizes the hydraulic impacts of different ELJ
representations in a 1-D hydraulic model. The objective of this study is to investigate how
representation of ELJs in a 1-D hydraulic model influences a) accuracy of WSE predictions, and
b) 1-D flow characteristics of velocity, area, and hydraulic depth. The analysis is conducted for a
case study of an ELJ at which channel geometry and hydraulic flow properties were measured
and calibrated in a 1-D hydraulic model. We also present a sensitivity analysis of roughness and
geometry at high flows. Calibration results demonstrate that geometry has a greater effect on
model accuracy than hydraulic roughness for the evaluated ranges. Results of the sensitivity
analysis indicate that increasing the roughness associated with an ELJ is simulated as a backwater
effect, increasing WSEs upstream of the ELJ. Increasing ELJ roughness also causes a reduced
velocity upstream of and at the ELJ. In contrast, the effect of adding ELJ geometry reduces the
hydraulic depth and increases the velocity at the ELJ cross section. When combined, the effects
of ELJ geometry and roughness combine to lower the WSE and raise velocities at the ELJ and
raise WSE and lower velocities upstream of the ELJ, and geometry appears to dominate effects of
adding roughness. Designers may choose to represent an ELJ as a modified geometry or
increased roughness depending on whether upstream flood risk or localized scour adjacent to the
ELJ is of concern.
©Copyright by Rachelle S. Valverde
June 18, 2013
All Rights Reserved
Roughness and Geometry Effects of Engineered Log Jams on 1-D Flow Characteristics
by
Rachelle S. Valverde
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Presented June 18, 2013
Commencement June 2014
Master of Science thesis of Rachelle S. Valverde presented on June 18, 2013.
APPROVED:
________________________________________________________________
Major Professor, representing Civil Engineering
________________________________________________________________
Head of the School of Civil and Construction Engineering
________________________________________________________________
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader upon
request.
_________________________________________________________________
Rachelle S. Valverde, Author
ACKNOWLEDGEMENTS
I would like to thank my advisor, Desirée Tullos, for her encouragement, knowledge and time. I
would also like to thank all my field assistants: Lisa Thompson, Alexis Mills, Julia Rask, YunJi
Choi, Christopher Gifford-Miears, and Harrison Ko. Thank you to Arne Skaugset for providing
crest gauges for this study. Cara Walter, who was a great resource, maintained the gauging station
and provided invaluable knowledge of surveying, and GPS throughout this entire endeavor.
Background information on the study site and support was provided by The River Design Group.
This study would not have been possible without their cooperation. Lastly, I would like to thank
my friends and family for their support from afar.
TABLE OF CONTENTS
Page
1. Introduction .................................................................................................................................. 1
2. Background .................................................................................................................................. 4
2.1 Geography of the Calapooia River Basin............................................................................... 4
2.2 Jam History, and Location ..................................................................................................... 6
2.2.1 Study Area ...................................................................................................................... 6
3. Methods ....................................................................................................................................... 8
3.1 Field Surveys: Data Collection and Processing ..................................................................... 8
3.2 Model ELJ Representation: Geometry and Roughness ......................................................... 9
3.3 Hydraulic Model .................................................................................................................. 12
3.3.1 Calibration at Low Flows ............................................................................................. 13
3.3.2 Sensitivity Analysis for High Flows ............................................................................. 14
4. Results........................................................................................................................................ 15
4.1 Model Calibration ................................................................................................................ 15
4.1.1 Model Accuracy............................................................................................................ 15
4.1.2 Simulated Water Surface Elevations, Velocities and Flow Areas ................................ 15
4.2 Sensitivity Analysis.............................................................................................................. 17
4.2.1 Effect of Geometry on Simulated Water Surface Elevations, Velocities and Flow Areas
............................................................................................................................................... 17
4.2.2 Effect of Roughness on Simulated Water Surface Elevations, Velocities, and Flow
Areas ...................................................................................................................................... 20
4.2.3 Effect of Geometry and Roughness on Simulated Water Surface Elevations, Velocities
and Flow Areas ...................................................................................................................... 20
5. Discussion .................................................................................................................................. 23
5.1 Calibration of 1-D Hydraulic Model at Low Flow .............................................................. 23
5.2 Effect of Geometry and Roughness in a 1-D Hydraulic Model ........................................... 23
5.3 Relative Roles of Geometry and Roughness in a 1-D Hydraulic Model ............................. 25
5.4 Effect of ELJ on 1-D Flow Characteristics at Varying Stages (High and Low Flow) ......... 25
6. Conclusions ................................................................................................................................ 29
Bibliography .................................................................................................................................. 30
Appendix........................................................................................................................................ 35
LIST OF FIGURES
Figure
Page
1. Location map of study area……………………………………………………...…….…….5
2. Engineered Log Jam on Sodom Ditch, Oregon……………………………..…….….……..6
3. Observed water surface elevations…………………………………………………..……...9
4. Model geometry and roughness configurations for XS2 and XS3…..…………...….……..10
5. Water surface elevations of best fit by discharge…………………...………..…………….16
6. Velocity and area for best fit models of Figure 5 by discharge………………..….….…….17
7. Effect of geometry on water surface elevation and velocity-area……………..….….….….19
8. Effect of roughness on water surface elevation and velocity-area…………………....…….21
9. Effect of geometry and roughness on water surface elevation and velocity-area……….…..22
10. Effect of geometry, roughness and combined geometry and roughness on WSE,
velocity and area……………………………………………………………………..…...27
LIST OF TABLES
Table
Page
1. Cross section 1-D flow characteristics at 9 cms…………………………………………….7
2. Observed flows and associated blockage values..………………….……………………….9
3. Roughness distribution for geometry, roughness and combined geometry and
roughness comparisons……………………………..………………………..………...…..12
4. Sensitivity analysis flood frequency…………………………...…………………………...14
Roughness and Geometry Effects of Engineered Log Jams on 1-D Flow Characteristics
1. Introduction
The re-introduction of large woody debris (LWD) into streams and rivers for restoration
purposes is rapidly growing (Bernhardt et al. 2005; Brummer et al. 2006; Manners and Doyle
2008). The value of LWD as a restoration technique is increasingly recognized, with events such
as the Wood in World Rivers Conference, US Bureau of Reclamation Large Wood Conference;
and special issues of Geomorphology in March 2003, and Earth Surface Processes and
Landforms in July 2007 (Lassettre and Kondolf 2011). Engineered log jams (ELJs) are man-made
structures intended to mimic natural LWD structures, designed and installed to protect stream
banks and increase habitat diversity (Abbe and Montgomery 1996; Herrera Environmental
Consultants 2006; Shields et al. 2004). ELJs have seen a dramatic growth in use over the past two
decades as a sustainable approach to bank protection (Herrera Environmental Consultants 2006).
ELJs increase habitat diversity by altering channel morphology (Abbe and Montgomery 1996;
Manners et al. 2007); pool formation, size and spacing (Manners et al. 2007); channel width and
variability (Smith et al. 1993); and channel roughness (Buffington and Montgomery 1999).
Furthermore, the addition of ELJs is associated with increases in fish species richness (Shields et
al. 1994; Shields et al. 1995), and habitat diversity (Davidson and Eaton 2012; Lassettre and
Kondolf 2011). In addition to geomorphic and ecological impacts, ELJs can be an important
component of flow resistance (Hygelund and Manga 2003), contributing to channel roughness by
influencing channel geometry, bedform, bank irregularities, stream meander, and bed material
(Chow 1959).
Total flow resistance in stream channels can be partitioned into distinct components that
are related to channel features. Variables related to flow resistance can be partitioned such as bed
shear stress, friction slope, Darcy-Weisbach friction factor, Manning’s n and flow depth (Wilcox
et. al. 2006; Einstein and Barbarossa 1952; Rouse 1965). Among the four types of flow resistance
classified by Rouse (1965), the wall surface and form resistance are the main contributors to ELJ
resistance (Wilcox et al. 2006). Wall surface or skin friction resistance is the resistance due to the
boundary layer (Yen 2002). The boundary layer represents the channel bed roughness that causes
energy losses resulting from skin friction and drag from individual grains in the bed (Einstein and
Barbarossa 1952). Form resistance is due to pressure drag on the irregular bed surface (Wilcox et
al. 2006). For channels with ELJs, form resistance can be attributed to woody debris.
2
Due to the important implications for channel velocities, depths, and sediment transport
capacity, several formulae have been developed using physical models and field investigations to
evaluate the contribution of LWD to flow resistance. For example, several studies have attempted
to quantify the hydraulic effect of woody debris by use of the flow resistance equation (Curran
and Wohl 2003; Gippel et al. 1992; Shields and Gippel 1995), which represents debris resistance
by a roughness coefficient or friction factor (Dudley et al. 1998; Gippel 1995; Hygelund and
Manga 2003; Manga and Kirchner 2000; Manners et al. 2007; Shields and Gippel 1995; Wilcox
et al. 2006). Alternately, an equation to determine the Manning’s n of ELJs was derived as a
function of ELJ density, hydraulic radius and drag coefficient (Petryk and Bosmajian 1975).
Similarly, a method for estimating debris resistance through the Darcy-Weisbach friction factor
has also been developed using debris density, channel geometry, and the debris drag coefficient
(Shields and Gippel 1995). These formulae assume that the cumulative effect of an ELJ in a
channel may be treated as boundary roughness uniformly distributed along the reach, thus
neglecting the effect of form resistance.
These formulae are often applied to one-dimensional (1-D) hydraulic models in the
design and evaluation of ELJs. For example, flood defense alternatives using dams made of ELJs
were evaluated in a 1-D hydraulic model to aid in the selection of an effective downstream flood
mitigation alternative (Thomas and Nisbet 2012). Flood risks associated with proposed ELJ
obstruction alternatives, which were modeled as high ground, were evaluated through the use of a
1-D hydraulic model for selection of the alternative with the least flooding risk (Whitman n.d.).
However, two key limitations of existing formulae exist. First, the effects of LWD and
ELJs on flow resistance are known to vary with the architecture of the wood and the channel
hydraulics. For example, field studies that have directly measured the drag coefficient of model
woody debris find that it varies with factors such as log orientation, relative log size, depth of
submergence, branches, leaves (Hygelund and Manga 2003). Single-cylinder flume studies
highlight the relationships between flow, geometry, and log orientation (Gippel et al. 1992;
Wilcox et al. 2006; Young 1991). However, most studies on localized hydraulic effects of wood
have been performed on single cylinder objects (Manners and Doyle 2008). To bridge the gap
between single cylinder woody debris and ELJs, Manners (2007) found that the assumption of
nonporosity resulted in a 10-20% overestimation of ELJ drag coefficients.
3
Second, despite the recommendations from design documents to use hydraulic models in
evaluating potential risk associated with proposed ELJs (Abbe et al. 2003; Herrera Environmental
Consultants 2006; Oregon Department of State Lands 2010), the aforementioned formulae
developed to represent the flow resistance of ELJs have not been thoroughly validated in a
hydraulic numerical model. Guidelines recommend that hydraulic analysis include an evaluation
of flow velocities, water surface elevations, shear stress, and bed deformation, but no guidance is
given regarding how to represent ELJs to evaluate their effect on these hydraulic parameters. For
example, current design methods developed to estimate debris resistance are based on uncertain
empirically-derived coefficients for single cylinder objects (Gippel 1995). Parameterizing the
roughness of an ELJ in a hydraulic model is difficult because models only parameterize
roughness by a single factor, which does not account for the factors noted above that influence
wood’s contribution to flow resistance (Warmink et al. 2013). Finally, while studies (Brummer et
al. 2006; Herrera Environmental Consultants 2006; Whitman n.d.) report water surface elevation
results of using 1-D numerical models to model ELJs as high ground in the channel cross section,
the accuracy of the roughness coefficient and representation of the ELJ as high ground in a 1-D
model has not been evaluated.
Thus, we investigate how representation of ELJs in a 1-D hydraulic model influences a)
accuracy of water surface elevation (WSE) estimates, and b) 1-D flow characteristics of velocity,
area, and hydraulic depth. The primary objectives of this study are to evaluate the contribution of
an ELJ to both boundary and form resistance, evaluate the performance and, characterize the
hydraulic impact of different ELJ representations in a 1-D hydraulic model. In this study, we
represent an ELJ as combinations of different roughness coefficients and channel geometries. The
roughness model configurations are to evaluate the contribution to boundary resistance, while the
geometry models are used to evaluate form resistance. The first component of this study involves
the calibration of a 1-D ELJ hydraulic model using the various representations of the study ELJ’s
geometry and roughness to evaluate the accuracy of different configuration for modeling ELJs at
low flows. A sensitivity analysis is also performed at bank full flows, for which no calibration
data is available, to investigate the hydraulic effect of ELJ roughness and geometry on 1-D flow
characteristics at high flows. The analysis is conducted for a case study of a ELJ located on a
bifurcation of the Calapooia River, Oregon, for which channel geometry and hydraulic conditions
were monitored and simulated in a 1-D hydraulic model.
4
2. Background
2.1 Geography of the Calapooia River Basin
The Sodom Ditch was excavated in the late 19th century as a bifurcation of the Calapooia
River (Figure 1), and was intended to be a high-water diversion to minimize flooding along the
Calapooia River (Calapooia Watershed Council 2013). The Sodom Ditch bifurcation is located
downstream of Brownsville, Oregon on the Calapooia River at river mile 28.3 and rejoins the
Calapooia River at river mile 19.6 (Calapooia Watershed Council 2013). From its headwaters in
the Western Cascades of Oregon the Calapooia River flows north-west where it joins the
Willamette River near Albany, Linn County (Runyon 2004). Elevations within the Calapooia
watershed range from 1,580 meters at the summit of Tidbits Mountain to 61 meters draining an
area of 947 km2. The geology of the headwaters are characterized by deeply eroded volcanoes
comprised of basalt and andesite, which is indicative of the Oregon Western Cascades (Sherrod
and Smith 2000).
The Sodom Dam was located on the Sodom Ditch approximately 427 meters downstream
of the bifurcation between the Calapooia River and the Sodom Ditch (Calapooia Watershed
Council 2013). It was first built as a push-up dam, then a wooden crib dam and then a concrete
structure (Calapooia Watershed Council 2013). The concrete dam was built in 1957 and
integrated a weir and pool fishway (Calapooia Watershed Council 2013). The Sodom Dam was
approximately 3.3 meters in height and 26 meters across, including the crest and the width of the
fishway. Flashboards were installed during the summer to increase the reservoir elevation by 3
meters above the crest of the dam.
The dam was a partial barrier to the fish passage of two federally-listed threatened
species. The dam delayed migration of winter Steelhead moving upstream and presented a
significant obstacle to spring Chinook salmon. The dam was also a safety hazard, with significant
erosion at the outlet apron and concrete deterioration. The dam was removed during the summer
of 2011and replaced with a grade control structures to stabilize the sediment in place and
maintain an established flow split between the historical Calapooia and the Sodom ditch. ELJs
were constructed for bank stabilization and habitat restoration.
5
a)
b)
XS1
XS2
XS3
XS4
Flow
XS5
XS6
Figure1. Location map of study area.
a) Map of the Calapooia watershed with the location of gauging station, b) Extent and layout of
study reach with cross sections and ELJ in shaded gray.
6
2.2 Jam History, and Location
2.2.1 Study Area
The post-removal site plan for the Sodom ditch included eight complex ELJs. For this
analysis, we selected a meander jam located 200 meters downstream of the bifurcation on the
right bank. The study ELJ consists of several key, stacked, and racked members (Figure 2). Key
members are large logs embedded deep into the channel substrate to ensure a solid foundation
during bankfull flows (Abbe et al. 2003). Over the key members, smaller logs are stacked to link
individual members together. The smallest logs are then racked on top of the stacked members to
decrease the permeability of the ELJ to deflect flow around the structure.
Stacked Member
Racked Member
Key Member
Figure 2. Engineered Log Jam on Sodom Ditch, Oregon
The study area consists of a 73 meter reach that encompassed the study ELJ. The reach is
represented by a series of six cross sections (Figure 1b); one upstream of the ELJ, one on each of
the upstream and downstream faces of the ELJ and three downstream of the ELJ (Table 1). The
first 14 meters of the study reach have the highest velocities as flow exits a riffle located directly
upstream of the study reach. The subsequent 21 meters, XS2 and XS3, encompass the ELJ and
are characterized by lower velocities and deeper hydraulic depths relative to XS1. Directly
downstream of the ELJ, XS5, the channel forms a pool where the channel widens and the
hydraulic depth is at its greatest. Flow then enters a riffle located immediately below the pool,
which is the downstream extent of the study reach.
7
Table 1. Cross section 1-D flow characteristics at 9 cms
Cross Section Station Area of
(XS)
(m)
Influence
1
80
US
2
66
ELJ
3
52
ELJ
4
45
DS
5
24
DS
6
7
DS
Hydraulic
Depth (m)
1.69
3.31
3.95
2.96
3.75
1.79
Velocity
(m s-1)
0.56
0.25
0.20
0.25
0.15
0.28
Width
(m)
15
20
20
21
30
27
8
3. Methods
3.1 Field Surveys: Data Collection and Processing
The river channel bathymetry was surveyed in February of 2013 and ground topography
was surveyed in March of 2013. Surveys include six cross sections (Figure 1b) along the 73mlength reach, elevations along top members of the ELJ, ground elevations below the ELJ, and
bathymetric points within the water prism. Topography outside of and within the wadeable
portions of the channel was surveyed using a Topcon GR-3 Real Time Kinematic (RTK) Global
Positioning System (GPS). In-channel bathymetry was surveyed using a raft-mounted Teledyne
WorkHorse Rio Grande Acoustic Doppler Current Profiler (ADCP). Cross sections were
positioned to characterize the regions of flow influenced by the ELJ, including associated changes
in channel geometry, gradient, and roughness. The regions influenced by the ELJ are upstream of
the ELJ (XS1), adjacent to the ELJ (XS2, XS3) and downstream of the ELJ (XS4, XS5, XS6).
From the field surveys a Triangulated Irregular Network (TIN) was developed in
Environmental Systems Research Institute (ESRI)® ArcMap™ 10 in US feet in the Oregon North
State Plane projection, North American Datum 83(ESRI 2010). HEC-GeoRAS, an ArcGIS
extension, was used to prepare the GIS data for import into HEC-RAS. Using the HEC-GeoRAS
toolbar, bank lines and flow paths were digitized by overlaying an aerial photograph on the data.
HEC-GeoRAS produced an export file with river center line and cross sections.
In addition to topographic surveys, WSEs were surveyed during several runoff events
between February and April 2013. WSEs were obtained (Table 2 and Figure 3) from the ADCP,
GPS or from crest gauges (Sauer and Turnipseed 2010) installed on the right and left banks of
each of the six cross sections. The average of the left and right bank WSE was used as the
observed WSE at each cross section. Blockage ratios were calculated as the ratio of the
submerged ELJ area to the submerged area of the channel, including the ELJ, for each of the
observed discharge events.
Photographs of the upstream and downstream faces of the ELJ were collected, which
were calibrated using a survey rod with one foot increments clearly marked. Photographs were
stitched together using Microsoft Image Composite Editor (Figure 2). The composite images
were loaded into Autodesk® AutoCAD® Civil 3D® 2012, scaled, and then used to determine
ELJ area, porosity, and wetted perimeter. The area and wetted perimeter were used to define the
ELJ cross sections for the full frontal area or preserved wetter perimeter representations. The
9
study ELJ was found to be non-porous with a porosity of 0%, as the multiple layers of the ELJ
combine to form a solid object.
Discharge is currently gauged approximately 2.25 km downstream of the study area on
the Sodom Ditch at Linn West Road (Figure 1), with no stream junctions or significant inputs or
diversions between the study area and the downstream gauge. To verify the downstream gauge as
representative of the study site, a Teledyne StreamPro ADCP was used to directly measure the
discharge at the study area using USGS standard methods (Mueller and Wagner 2009). The
StreamPro and Linn West gauge were found to differ by 2.6%.
Table 2. Observed flows and associated blockage ratios
Collection Method
Event Date
Flow (cms)
Blockage Ratio
GPS & ADCP
GPS
GPS Crest Gauge Crest Gauge GPS
2/14/2013 2/22/2013 3/4/2013 3/20/2013 4/7/2013 4/8/2013
9
7
13
33
35
28
0.269
0.270
0.261
0.245
0.244
0.249
90
90
89
89
88
88
Elevation (m)
b) 91
Elevation (m)
a) 91
87
86
85
87
86
85
84
84
83
83
82
82
0
10
20
30 40 50
Station (m)
60
70
0
10
20
30 40 50
Station (m)
60
70
Figure 3. Observed water surface elevations. For 7 cms, 9, cms, 13 cms, 33 cms, and 35 cms. a)
XS2, and b) XS3. Grey line to the right of the cross section represents the estimated bank line
behind the ELJ.
3.2 Model ELJ Representation: Geometry and Roughness
The ELJ is represented at XS2 and XS3 (Figure 1), the upstream and downstream faces
of the ELJ, respectively, for three geometry configurations. The geometry configurations are used
10
to evaluate the form resistance contribution of the ELJ in the model. The first geometry omits the
ELJ by making no modifications to the geometry (Figure 4a, 4b). The second geometry represents
the ELJ by adjusting the vertical position of the channel invert to block out the frontal area of the
ELJ (Figure 4c, 4d). The full frontal area geometry eliminates the entire area occupied by ELJ
from the cross section, delineated by connecting high points along the ELJ, which may cause the
area blocked out to be an over estimation of the actual ELJ area. The last geometry represents the
ELJ by blocking out an area that has preserved the wetted perimeter of the actual ELJ (Figure 4e,
4f). The preserved wetter perimeter geometry preserves the wetted perimeter of the ELJ by using
the AutoCAD scaled photographs of the ELJ. The preserved wetted perimeter geometry increased
the wetted perimeter by 3.3 meters at XS2 and remained the same at XS3 as compared to the full
frontal area cross sections.
nELJ-F
a)
c)
b)
NGSR
nELJ-F
nELJ-F
nELJ-P
NGDR
d)
FGSR
e)
nELJ
nELJ
nELJ-P
FGDR
f)
nELJ
nELJ-P
PGSR
PGDR
Figure 4. Model geometry and roughness configurations for XS2 and XS3. a) No Geometry
Single Roughness (NGSR); b) No Geometry Double Roughness (NGDR); c) Full frontal area
Geometry Single Roughness (FGSR); d) Full frontal area Geometry Double Roughness (FGDR);
e) Preserved wetted perimeter Geometry Single Roughness (PGSR); f) Preserved wetter
perimeter Geometry Double Roughness (PGDR). Remaining cross sections (XS1, XS4, XS5,
XS6) in the model have no geometric changes and have a single roughness distribution, nc.
11
The ELJ is also represented as a roughness element, with roughness distribution in the
ELJ cross-sections configured in two ways: 1) a single roughness coefficient for each cross
section (Figures 4a, 4c, 4e); and 2) two roughness coefficients, horizontally distributed through
the ELJ cross sections (Figures 4b, 4d, 4f). The two roughness configurations are used to evaluate
the contribution of ELJ boundary resistance in the model. A Manning's n of 0.034 was calculated
for the representative unobstructed cross section (XS1) of the Sodom Ditch, based on cross
section and flow measurements surveyed on March 4, 2013. This representative value of
Manning’s n, hereafter referred to as nc, was applied consistently to all model cross sections in
HEC-RAS. For some models (Figure 4b, 4d, 4f), the upstream and downstream faces of the ELJ
(XS2 and XS3) were represented in the model with two different roughness distributions (Table
3). The first roughness model (Figure 4a, 4c, 4e) applies a single Manning’s n (nELJ-F) to the full
cross section (XS2 and XS3). The second model (Figure 4b, 4d, 4f) assigns a higher Manning’s n
(nELJ-P) to the partial area occupied by the ELJ at XS2 and XS3, while the remainder of the cross
section is assigned a Manning’s n of nELJ. In all models the remaining cross sections, XS1, XS4,
XS5, and XS6, are assigned a Manning’s n of nc.
The combinations of channel geometries and roughness coefficients result in six
hydraulic models (Figure 4). First, the No Geometry Single Roughness (NGSR) model (Figure
4a), has no geometric representation of the ELJ and a single roughness coefficient. Second, the
No Geometry Double Roughness (NGDR) model (Figure 4b), has no geometric representation of
the ELJ and two roughness coefficients. Third, the Full Geometry Single Roughness (FGSR)
model (Figure 4c), has the full frontal area geometry of the ELJ and a single roughness
coefficient. Fourth, the Full Geometry Double Roughness (FGDR) model (Figure 4d), has the full
frontal area geometry of the ELJ and two roughness coefficients. Fifth, the Preserved Geometry
Single Roughness (PGSR) model (Figure 4e), has the preserved wetter perimeter geometry of the
ELJ and a single roughness coefficient. Finally, the Preserved Geometry Double Roughness
(PGDR) model (Figure 4f), has the preserved wetter perimeter geometry of the ELJ and two
roughness coefficients.
To evaluate the effects of geometry, roughness, and geometry plus roughness, the models
are compared in the following ways. To evaluate the effect of ELJ geometry on simulated WSE,
velocity and area in the model, NGSR is compared to FGSR, NGDR to FGDR, and FGDR to
PGDR. To evaluate the effect of additional ELJ roughness NGSR is compared to NGDR, FGSR
to FGDR, and FGDR to PGDR. To evaluate the combined effect of geometry and additional ELJ
roughness, NGSR is compared to FGDR. The model configurations for the roughness, geometry
12
and combined roughness and geometry model comparisons are listed in Table 3. The six model
scenarios were compared to a base model to determine the effect of geometry and roughness on
the simulated WSE. The base model for each comparison is the model without geometry for the
geometry comparison, with single roughness for the roughness comparison, and with single
roughness and without geometry for the combined geometry and roughness comparison.
Table 3. Roughness distribution for geometry, roughness and combined geometry & roughness
comparisons
Comparison
Model
NGSR
FGSR
Geometry
NGDR
FGDR
PGDR
NGSR
FGSR
NGDR
Roughness
FGDR
PGSR
PGDR
Geometry
NGSR
& Roughness FGDR
nELJ-F
0.034
0.034
0.034
0.034
0.034
0.034
-
nELJ nELJ-P
0.034 0.04
0.034 0.04
0.034 0.04
0.034 0.06
0.034 0.06
0.034 0.06
0.034 0.06
3.3 Hydraulic Model
HEC-RAS (Hydrologic Engineering Center – River Analysis System) is a hydraulic
model used to simulate WSEs (USACE 2010). In a HEC-RAS steady state simulation, water
surface profiles are computed from the downstream cross section to the next upstream cross
section by using the standard step method (Haestad Methods et al. 2003) to solve the energy
equation. To determine total conveyance and the velocity coefficients for a cross section, HECRAS subdivides flow in the main channel from the over banks. Conveyance is calculated for each
subdivision by applying the Manning’s equation (EQ.1).
Where K is conveyance for the subdivision, n is Manning’s roughness coefficient for the
subdivision, A is flow area of the subdivision, and R is hydraulic radius for each subdivision. The
total conveyance for each subdivision is calculated as the sum of the conveyance from the left
over bank, main channel, and right over bank. Flow in the main channel is subdivided only when
13
the Manning’s roughness coefficient varies across the channel. The composite main channel
Manning’s roughness coefficient is defined as:
Where
is the composite or equivalent coefficient of roughness, P is the wetted perimeter of the
entire main channel,
is the wetted perimeter of subdivision i, and
is the coefficient of
roughness for subdivision i.
Input parameters for the 1-D model include topographic data in the form of a series of
cross sections, a roughness coefficient in the form of Manning’s n values across the cross section,
flow rates, WSEs, and boundary conditions. Separate downstream boundary conditions were
developed for the dual objectives of this study. For the first objective of low flow model
calibration, the downstream boundary conditions at XS6 were defined as the observed WSEs
(Table 2) for each calibration simulation. For the second objective of high flow sensitivity
analysis, a lack of high flows over the study period resulted in no observed WSEs at high flows.
Therefore the downstream boundary condition was specified as normal depth, applying a water
surface slope of 0.000771, which was obtained from a survey performed by RDG during a 156
cms event that occurred on December 30, 2011.
Some of the limitations of the calibration portion of this study include model error,
instrument error, and measurement error. HEC-RAS can calculate WSE to within a user-defined
tolerance, which was set at the maximum of 0.01 m for this study. The observed WSEs were
measured with either RTK GPS or with crest gauges, both of which have an accuracy of 0.01 m.
There is also the error introduced by the surveyor’s definition of the WSE location, which
fluctuates in a natural channel. By repeating measurements at the same location at the same flow
rate the surveyor introduced error was determine to be 0.01 m. The calibrated models cannot be
calibrated to an accuracy of less than 0.01 m.
3.3.1 Calibration and Validation at Low Flows
Manning’s n was used as the calibration parameter in all the low-flow model scenarios,
with the directly calculated value of 0.034 applied at all cross sections for the initial simulation.
Manning’s n was then adjusted in subsequent simulations, starting at the downstream cross
section and working upstream until the best fit of simulated WSE to observed were obtained
using goodness of fit parameters. The model was calibrated using the observed flow rates and
14
WSEs from five flow events. The remaining event of 13 cms was used to validate the calibrated
model. Two goodness-of-fit statistics were calculated: Nash-Sutcliffe Efficiency (NSE), and bias
(BIAS). The NSE is a normalized statistic that compares the residual variance to the measure data
variance such that a value of 1 indicates a perfect fit (Moriasi et al. 2007). BIAS measures the
average tendency of the simulated data to be smaller or larger than the observed, with positive
values indicating model underestimation and negative values indicating model overestimation. A
model was assumed to be calibrated when the goodness of fit statistics converged to a fixed
value.
3.3.2 Sensitivity Analysis for High Flows
A sensitivity analysis was performed to investigate how boundary resistance, represented
by the Manning’s roughness parameter, and form resistance, represented by the geometric
representation of an ELJ, affects model output. The sensitivity of the model was tested through a
series of steady flow model examples. The six models, NGSR, NGDR, FGSR, FGDR, PGDR and
PGDR were evaluated at flood events ranging from a 2 year to a 100 year event (Table 4). The
Linn West gauging station has only been in operation since 2011 and, therefore, could not be used
to determine flood frequencies for periods longer than the gauge has been installed. Therefore,
linear regression equations for ungauged sites developed by the USGS were used to estimate the
runoff events for the Sodom Ditch (Riesley et al. 2005). The USGS peak flow frequency
regression equations are based on drainage area, mean basin elevation and mean annual
precipitation.
Table 4. Sensitivity analysis flood frequency
Flood Frequency (yrs)
Flow (cms)
2
113
5
170
10
226
25
283
50
340
100
396
15
4. Results
4.1 Model Calibration
4.1.1 Model Accuracy
The directed-calculated roughness of 0.034 produced WSEs in the models that greatly
overestimated the WSE compared to the observed. The roughness was therefore lowered until the
best fit was achieved. All the models converged to a best fit with an unreasonably low Manning’s
n of 0.005 for every cross section throughout the study reach (Appendix Table A.1). The fit
parameters converged at this roughness and it was found that any Manning’s n lower than 0.005
produced no change in the model. For the lower calibration flows of 7 cms and 9 cms, the fit
statistics are all identical. Therefore, it cannot be determined which model produces the most
accurate fit to the observed WSEs for the lowest flows. However, for the higher calibration flows
of 28 cms, 33 cms and 35 cms, the addition of ELJ geometry results in an NSE closer to 1 and a
BIAS closer to 0 than when representing ELJ roughness. The better NSE and BIAS at these
higher flows suggest that the addition of ELJ geometry results in a more accurate representation
of the observed WSE than representing ELJ roughness. The 13 cms flow used to validate the
calibrated model resulted in an NSE closer to 1 and a BIAS closer to 0 similar to 28 cms, 33 cms,
and 35 cms.
For the highest flows of 33 and 35 cms, the observed WSE at XS5 are omitted from NSE
and BIAS calculations. At these high flows the crest gauges at XS5 were found to be defective as
they did not meet USGS gauge standards. Therefore, the WSEs for these flows at this location
were not used in the calibration of the model. The omission of these WSEs resulted in the
calculation of modified fit parameters. At 33 cms the modified NSE is 0.972 and a -0.00027 m
BIAS for NGSR, which is a much better fit as compared to 13 cms with an unmodified NSE of
-0.430 and a -0.00013 m BIAS.
4.1.2 Simulated Water Surface Elevations, Velocities and Flow Areas
Observations indicate the ELJ cross sections generate a local increase in the WSE as the
flow encounters the face of ELJ (XS2) and then lowers once it passes the ELJ (XS4) (Figure 5).
This longitudinal trend is roughly simulated by all calibration models, though the accuracy of the
WSE varies with the different geometry and roughness representations.
Calibrated models with ELJ geometry representation produced WSEs that were lower at
XS2 and XS3 than models without ELJ geometry (Figure 5). Comparing NGSR and NGDR to
16
b) 86.39
Water Surface Elevation (m)
Water Surface Elevation (m)
a) 86.35
86.34
86.33
86.32
86.31
86.3
86.29
86.28
86.27
0
20
40
60
80
0
20
40
60
80
0
20
40
60
80
0
20
40
60
Station (m)
80
d) 86.83
Water Surface Elevation (m)
c) 86.51
Water Surface Elevation (m)
86.38
86.37
86.36
86.35
86.34
86.33
86.32
86.31
86.3
86.29
86.28
86.5
86.49
86.48
86.47
86.46
86.45
86.44
40
60
80
e) 86.98
f)
Water Surface Elevation (m)
20
Water Surface Elevation (m)
0
86.82
86.81
86.8
86.79
86.78
86.77
86.76
86.75
86.74
86.73
86.72
86.71
86.96
86.94
86.92
86.9
86.88
86.86
86.84
86.82
87
86.98
86.96
86.94
86.92
86.9
86.88
86.86
0
20
40
60
Station (m)
80
Figure 5. Water surface elevations of best fit by discharge. Solid squares are the observed water
surface elevations with instrument and measurement error bars . NGSR (□), NGDR (*), FGSR
(○), FGDR (◊). Plot c is the validated model. a) 7cms, b) 9 cms, c) 13 cms, d) 28 cms, e) 33 cms,
f) 35 cms. PGSR and PGDR were omitted from the results since their geometry is the same as for
FGSR and FGDR during low flow events.
17
FGSR, and FGDR, the addition of geometry causes a localized drop in the WSE at the location of
the ELJ geometry. For each flow rate (Figure 5) the WSEs for NGSR are identical to NGDR; and
FGSR are identical to FGDR, illustrating that the influence of roughness is negligible relative to
the influence of geometry.
Although the WSEs for NGSR are the same as NGDR and FGSR are the same as FGDR,
the models account for the change in ELJ geometry and roughness with changes in the velocity
and area (Figure 6). For example, at the highest flow, 35 cms, upstream of the ELJ (XS1), a very
small increase in velocity (+0.004 m s-1) is accompanied by a small decrease in area (-0.04 m2).
More notably, at the upsream face of the ELJ (XS2), the velocity increases (+0.178 m s-1) and the
area decreases (-15.78 m2) with the addtion of ELJ geometry. At the downsream face of the ELJ
(XS3), the velocity increases (+0.096 m s-1) and the area decreases (-10.82 m2) with the addtion
of ELJ geometry. For the remaing cross sections (XS1, XS4-6), there is no change in the velocity
and area with or without ELJ geometry.
4.2 Sensitivity Analysis
A sensitivity analysis was performed to determine the effect of form resistance by
geometry and boundary resistance by roughness of ELJs at high flows. NGSR is compared to
FGSR, NGDR is compared to FGDR, and FGDR is compared to PGDR to evaluate the effect of
form resistance by the addition of geometry to a hydraulic model. NGSR is compared to NGDR,
FGSR is compared to FGDR, and PGSR is compared to PGDR to evaluate the effect of boundary
resistance by the addition of roughness to a hydraulic model.
4.2.1 Effect of Geometry on Simulated Water Surface Elevations, Velocities and Flow
Areas
Form resistance through the addition of ELJ geometry has the effect (Figures 7a, 7c) of
locally lowering the WSE at the ELJ cross sections (XS2 and XS3) and raising the WSE upstream
of the ELJ (XS1). The preservation of the wetted perimeter of the ELJ causes the WSE to rise at
XS1, XS2 and XS3 for every flow rate (Figure 7e) as compared to FGDR. The changes in WSEs
for all the geometry comparisons (Figure 7a, c, e) are accompanied by corresponding changes in
velocity and area (Figure 7b, d, f). In general, the addition of ELJ geometry reduces velocity and
increases flow area upstream of the ELJ (XS1), while the velocities increase and the area
decreases at the ELJ (XS2 and XS3) with the addition of ELJ geometry (Figure 7b, d).
18
b) 0.6
70
0.5
60
0.5
60
20
0.1
0
0
20
40
60
20
10
0
80
0
0
20
40
60
80
d) 1.4
80
0.7
60
1.2
70
50
1
Velocity (m/s)
0.5
40
0.4
30
0.3
20
0.2
Velocity (m/s)
70
Area (m2)
c) 0.8
0.6
10
0.1
0
20
40
60
60
50
0.8
40
0.6
30
0.4
20
0.2
0
0
10
0
80
0
0
20
40
60
80
90
1.4
80
1.4
80
1.2
70
1.2
70
60
50
0.8
40
0.6
0.4
0.2
30
0
20
40
60
Station (m)
80
60
1
50
0.8
40
0.6
30
20
0.4
20
10
0.2
10
0
0
Velocity (m/s)
f) 1.6
Area (m2)
90
Velocity (m/s)
e) 1.6
1
Area (m2)
30
0.2
0.1
10
0
40
0.3
Area (m2)
30
0.2
50
0.4
Area (m2)
40
0.3
Area (m2)
50
0.4
Velocity (m/s)
70
Velocity (m/s)
a) 0.6
0
0
0
20
40
60
Station (m)
80
Figure 6. Velocity and area for best fit model of Figure 5 by discharge. NGSR (□), NGDR (*),
RFGSR (○), FGDR (◊). Velocities are solid lines and areas are dashed lines. Plot c is the
validated model. a) 7cms, b) 9 cms, c) 13 cms, d) 28 cms, e) 33 cms, f) 35 cms
19
b)
3.8
ELJ
210
3.5
89.5
89
88.5
150
2.3
130
2
110
20
40
90.5
60
80
40
60
80
215
3.5
89.5
89
88.5
88
190
3.2
165
2.9
2.6
140
2.3
115
2
1.7
20
40
60
80
90
0
f)
90.5
20
40
60
80
3.8
ELJ
215
3.5
Velocity (m/s)
90
89.5
89
88.5
88
190
3.2
165
2.9
2.6
140
2.3
115
2
87.5
1.7
0
20
40
60
Station (m)
Area (m2)
90
0
Water Surface Elevation (m)
20
d) 3.8
ELJ
87.5
e)
90
0
Velocity (m/s)
Water Surface Elevation (m)
2.6
1.7
0
c)
170
2.9
88
87.5
190
3.2
Area (m2)
90
Velocity (m/s)
Water Surface Elevation (m)
90.5
80
Area (m2)
a)
90
0
20
40
60
Station (m)
80
Figure 7. Effect of geometry on water surface elevation and velocity-area. Dashed lines are area,
and solid lines are velocity. a)WSEs, NGSR (black) versus FGSR (grey), b) Velocity-Area,
NGSR (black) versus FGSR (grey), c) WSEs, NGDR (black) versus FGDR (grey), d) VelocityArea, NGDR (black) versus FGDR (grey), e) WSEs, FGDR (black) versus PGDR (grey), f)
Velocity-Area, FGDR (black) versus PGDR (grey). The roughness distributions for the model
comparisons in Figure 7 are listed in Table 3.
20
The WSEs, velocities, and areas at cross sections downstream of the ELJ are not affected by the
addition of ELJ geometry in any model comparison.
4.2.2 Effect of Roughness on Simulated Water Surface Elevations, Velocities, and Flow
Areas
Boundary resistance simulated by increased ELJ roughness causes an overall rise in the
WSE which propagates upstream of the ELJ. For every flow rate, the addition of ELJ roughness
raises the simulated WSE at cross sections containing and upstream of the ELJ (XS1, XS2 and
XS3). Accompanying increases in water depth at the ELJ and at upstream cross-sections, ELJ
roughness reduces velocity and increases area (Figures 8b, 8d, 8f). The magnitude of differences
appears to be relative to each other; smaller increases in area at XS1 are associated with smaller
reductions in velocity, as compared to XS2 and XS3. As with geometry, the WSEs, velocities,
and areas at cross sections downstream of the ELJ are not affected by the addition of ELJ
roughness in any model comparison.
4.2.3 Effect of Geometry and Roughness on Simulated Water Surface Elevations,
Velocities and Flow Areas
When comparing a model representing a single roughness coefficient and no ELJ
geometry (NGSR) to a model with double roughness and full frontal area geometry (FGDR), the
WSE upstream of the ELJ (XS1) increases for every discharge (Figure 9a). For this same
comparison, combining both geometry and roughness, the WSE decreases (Figure 9a) at the ELJ
cross sections (XS2 and XS3). Velocities increase and areas decrease at cross sections with the
ELJ (XS2 and XS3) (Figure 9b). At XS1, upstream of the ELJ, the velocity decreases while the
area increases (Figure 9b).
21
200
3.5
89.5
89
88.5
180
3
160
2.5
140
120
2
88
100
1.5
0
20
40
60
80
80
0
20
40
60
80
d) 3.8
230
ELJ
3.5
89.5
89
88.5
88
87.5
210
3.2
190
2.9
170
2.6
150
2.3
130
2
110
1.7
0
20
40
60
80
e) 90.5
88.5
88
87.5
40
60
80
230
3.5
210
3.2
190
2.9
170
2.6
150
2.3
130
2
110
Velocity (m/s)
89
20
f) 3.8
ELJ
89.5
90
0
90
1.7
0
20
40
60
Station (m)
80
Area (m2)
Velocity (m/s)
90
Area (m2)
c) 90.5
Water Surface Elevation (m)
220
ELJ
90
87.5
Water Surface Elevation (m)
4
Area (m2)
b)
Velocity (m/s)
Water Surface Elevation (m)
a) 90.5
90
0
20
40
60
Station (m)
80
Figure 8. Effect of roughness on water surface elevation and velocity-area. Dashed lines are area,
and solid lines are velocity. a) WSEs, NGSR (black) versus NGDR (grey), b) Velocity-Area,
NGSR (black) versus NGDR (grey), c) WSEs, FGSR (black) versus FGDR (grey), d) VelocityArea, FGSR (black) versus FGDR (grey), e) WSEs, PGSR (black) versus PGDR (grey), f)
Velocity-Area, PGSR (black) versus PGDR (grey). The roughness distributions for the model
comparisons in Figure 7 are listed in Table 3.
22
b) 4
90
220
200
3.5
89.5
89
88.5
180
3
160
2.5
140
120
2
88
87.5
0
20
40
60
Station (m)
80
Area (m2)
ELJ
Velocity (m/s)
Water Surface Elevation (m)
a) 90.5
100
1.5
80
0
20
40
60
Station (m)
80
Figure 9. Effect of geometry and roughness on water surface elevation and velocity-area. NGSR
(black) versus FGDR (grey). a) WSE by discharge; b) Velocity-Area for 396 cms, dashed lines
are area, and solid lines are velocity.
23
5. Discussion
5.1 Calibration of 1-D Hydraulic Model at Low Flow
While the calibrated Manning’s n value is unrealistically low (Chow 1959), the results
from the calibration analysis can still be used to interpret overall effects of geometry on hydraulic
models. The discrepancy between the calculated and calibrated channel roughness may be
attributed to the geometry of the study reach. The entire 72 meter length reach of the study reach
is located in a pool. Riffles are located immediately upstream and downstream of the study pool.
The downstream boundary condition in the model is the upstream portion of a riffle immediately
downstream of the study reach. WSE in riffles are generally used to validate the calibration of a
HEC-RAS model as they and are considered to be locations of hydraulic control. Thus, while the
calibration of Manning’s roughness parameter is unrealistic, we believe the patterns in the effect
of roughness and geometry representations on the simulated WSE, velocity and area are still
valid. Results indicate that the addition of ELJ geometry is more accurate for representing WSEs
than a roughness-based representation when calibrating a hydraulic model at low flows. At low
flows the geometry has a much greater effect on the WSE, velocity and roughness (Figure 5,
Figure 6).
The NSE for 7, 9, 13 and 28 cms indicate unacceptable model performance (Table A.1).
NSE values less than 0 are considered unacceptable and values equal to or close to zero indicate
that the mean observed value is a better predictor that the simulated value (Moriasi et al. 2007).
Therefore, for all calibrated models at flows of 7, 9, 13 and 28 cms the mean of the observed is a
better predictor than those simulated by the model.
BIAS is a good indicator of model over or underestimation; however it is not a good
indicator of model accuracy. For every calibrated model and flow rate BIAS indicates that the
model is overestimating WSE compared to observed WSE (Figure 5). BIAS is calculated by
dividing the difference of the sum of the observed and simulated WSE by the observed WSE. The
WSEs are based on arbitrary datums which can change, thus altering the BIAS. Therefore BIAS
is only a good indicator of model over or underestimation and not accuracy.
5.2 Effect of Geometry and Roughness in a 1-D Hydraulic Model
Consistent with previous studies (Thorne and Furbish 1995; Daniels and Rhoads 2003;
Shields et al. 2004), the flow resistance provided by the increase in ELJ roughness produced a
backwater effect that increased WSEs upstream of the ELJ (Figures 8a, c, e, grey line); and
24
decreased the velocity and increased cross sectional area (Figure 8b, d, f) relative to models with
no geometric or roughness representation of the ELJ (Figures 8a, c, e, black line). The increased
roughness representation of the ELJ depicts the effect of boundary resistance in the model. The
effect of reducing the cross sectional area with representation of ELJ geometry generates
hydraulics similar to a partial dam or weir (Daniels and Rhoads 2003), resulting in higher
velocities and lower cross-sectionally averaged water depths adjacent to the ELJ. This weir effect
is associated with both the obstruction’s size relative to the width of flow, as well as the
impermeable representation of the ELJ obstruction in HEC-RAS. In reality the actual ELJ is not
impermeable, but permeability cannot currently be modeled in HEC-RAS. While the porosity of
the study ELJ was low (0%), representing the effects of an ELJ as a geometric feature may be
exaggerated for highly porous architectures. The geometric representation of the ELJ depicts the
effect of form resistance in the model. For our study ELJ the contribution of form resistance was
found to be greater than that of boundary resistance.
Combining the Bernoulli’s and continuity equations explains the effect of ELJ geometry
and roughness on WSE, velocity and area (Figure 10). In HEC-RAS, the WSE is calculated
beginning at the downstream boundary (WSE1) and then progresses to estimate the WSE at the
next upstream cross section (WSE2). The WSE upstream (WSE2) is calculated by adding the
upstream velocity head (VH2) to the downstream WSE (WSE1), subtracting the downstream
velocity head (VH1) and adding any head losses. Head losses are comprised of friction losses and
contraction and expansion losses. For our study reach the modeled head losses contribute a small
fraction to the calculation of WSE2 when compared to the effect of VH2 and VH1. Therefore we
consider V1 and V2 to evaluate the effect on WSE2.When the velocity downstream (V1) is greater
than the velocity upstream (V2) the WSE upstream (WSE2 = Y2 + Z2) will increase. Conversely,
when the velocity downstream (V1) is less than the velocity upstream (V2) the WSE upstream
(WSE2 = Y2 + Z2) will decrease. The addition of ELJ geometry causes a decrease in area, an
increase in velocity (V1 < V2) and a corresponding decrease in the WSE for the ELJ cross sections
(XS2 and XS3). In contrast, the addition of ELJ roughness causes a decrease in velocity (V1 >
V2), an increase in area and a corresponding increase in the WSE upstream of the ELJ (XS1, XS2,
XS3). The combined effect of geometry and roughness merges the effects of geometry and
roughness such that geometry is the dominant parameter for every flow rate.
25
5.3 Relative Roles of Geometry and Roughness in a 1-D Hydraulic Model
Combining ELJ geometry and roughness in a 1-D hydraulic model has the greatest effect
on the simulated WSE, velocity and area as compared to geometry and roughness alone. The
combination of geometry and roughness results in the greatest increase in WSE at XS1 as
compared to geometry and roughness alone, and is therefore a 100% relative increase. Combined
geometry and roughness also had the greatest effect on the simulated velocity and area at XS2
(Figure 10) as compared to NGSR. The large differences in WSE, velocity and area between
NGSR and FGDR are the basis of comparison for the models compared in Figure 10. Geometry
alone produced the next greatest effect on WSE, velocity and area at XS2 and XS3 when
compared to combined geometry and roughness. The localized drop in WSE caused by the
addition of ELJ geometry is illustrated in Figure 10 with a decrease in WSE of 72%, and 95% at
XS3 and XS2 respectively. Roughness alone had the smallest effect on simulated WSE, velocity
and area at XS2 and XS3. Roughness produced an increase in WSE of 14%, 44%, and 76% at
XS3, XS2, and XS1 respectively (Figure 10). Figure 10 illustrates the effect of roughness on the
WSE which grows in magnitude in the upstream direction. The effect of roughness is overall
lower than the effect of geometry or combined geometry and roughness.
This comparison highlights how the dominant effect of form resistance or geometry and
boundary resistance or roughness representations on 1-D hydraulics varies with location. Whether
representing the ELJ as geometry, roughness, or both, velocities increase and area and depths
decrease upstream of the jam. However, at the ELJ (XS2 and XS3), the combination increases
velocities and reduces flow area and depth, indicating that the effect of geometry dominates the
contrasting roughness effects at the ELJ. The cross sections downstream of the ELJ are not
affected by the addition of ELJ geometry in any model comparison.
5.4 Effect of ELJ on 1-D Flow Characteristics at Varying Stages (High and Low Flow)
Results (Figure 8) are consistent with field studies (Thorne and Furbish 1995; Daniels
and Rhoads 2003) that have observed reductions in velocity upstream of ELJs on meanders.
However, results contradict previous research that demonstrated the effect of woody roughness
elements decreases with increasing stage (Shields and Gippel 1995), rather than increasing with
increasing stage as was simulated in this study (Figure 8). For example, Shields and Gippel
(1995) found that ELJs dissipate energy at low flow through flow-contraction and pool-formation
process, an effect that decreases as the ELJ is inundated (Shields and Gippel 1995). In the Shields
and Gippel study the ELJs became fully submerged with increasing stage. In contrast, for
26
the ELJ analyzed for this study, the woody debris extends from the bed of the channel all the way
up to bank full depth and is never fully submerged for the range of our study flows. Therefore, the
effect of the ELJ is not reduced at higher stages, resulting in approximately equal effects at higher
and lower stages (Figure 8).
27
Figure 10: Effect of geometry, roughness and combined geometry and roughness on WSE,
velocity and area. The reference figure for Geometry is Figure 7c, d, for Roughness it is Figure
8e, f, and for Geometry & Roughness it is Figure 9. Figure 9, which produced the greatest
magnitude difference between all model comparisons, was used as the basis of comparison. The
magnitude of the differences in WSE, velocity, and area for each reference figure was evaluated,
and then compared to Figure 9. The direction of the arrow in Figure 10, up or down, indicates a
corresponding increase or decrease in the associated parameter.
28
WSE
Velocity
Area
XS2
XS1
XS3
XS2
XS1
XS3
XS2
XS1
-72%
-95%
6%
49%
86%
-8%
-51%
-75%
1%
14 %
44%
76%
-8%
-9%
-23%
2%
7%
7%
-61%
-48%
100%
62%
100%
-38%
-65%
-100%
7%
Geometry & Roughness
Roughness
Geometry
XS3
Figure 10: Effect of geometry, roughness and combined geometry and roughness on WSE,
velocity and area.
29
6. Conclusions
An understanding of how to represent the influence of ELJs on stream hydraulics is
important to modeling flow dynamics, flood inundation, and river restoration activities. We
present results of an investigation into how the partitioning of ELJ flow resistance into boundary
and form resistance as geometry and as roughness representations respectively, in a hydraulic
model influences the accuracy and magnitude of calculated flow depths and velocities. A 1-D
hydraulic model was developed for an ELJ on a bifurcation of the Calapooia River, Oregon.
Results indicate that the geometry representation of ELJs is a representation of the form
resistance associated with the ELJ and acts as a constriction, concentrating flow in a smaller area
resulting in higher velocities and lower water depths than when the ELJ is not represented in any
way. Results of adding additional roughness to represent the boundary resistance associated with
the ELJ raises water depths at cross sections containing and upstream of ELJs while also reducing
velocities at these locations. When roughness and geometry are combined, the effects of form
resistance or geometry dominate in ELJ cross sections while boundary resistance or roughness
dominates upstream of the ELJ. At both low and high flows, the model is more sensitive to
representing ELJs as geometry than as roughness.
These results assist designers in selecting how to represent ELJs in hydraulic models. For
example, designers may choose to represent an ELJ as a modified geometry or increased
roughness depending on whether upstream flood risk or localized scour adjacent to the ELJ is of
concern. If potential flooding risks associated with a proposed ELJ is of concern then care should
be taken to accurately represent the increased roughness associated with the ELJ. However, if
local flow characteristics around the proposed ELJ are the main concern then accurate
representation of the channel geometry is more important. Further research is needed to calibrate
a 1-D model at high flows to verify that the geometry is more important than roughness in the
representation of ELJs in hydraulic models.
30
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35
Appendix
36
Table A.1. NSE and BIAS of best fit for each calibrated model
Q (cms)
7
Model
NSE
NGSR
-0.527
NGDR
-0.527
FGSR
-0.527
FGDR
-0.527
9
NGSR
0.044
NGDR
0.044
FGSR
0.044
FGDR
0.044
13
NGSR
-0.430
NGDR
-0.430
FGSR
-0.382
FGDR
-0.382
28
NGSR
-2.128
NGDR
-2.128
FGSR
-1.659
FGDR
-1.659
33*
NGSR
0.972
NGDR
0.972
FGSR
0.977
FGDR
0.977
35*
NGSR
0.961
NGDR
0.961
FGSR
0.972
FGDR
0.972
* Observed WSE omitted at XS5
BIAS (m)
-0.00015
-0.00015
-0.00015
-0.00015
-0.00014
-0.00014
-0.00014
-0.00014
-0.00013
-0.00013
-0.00012
-0.00012
-0.00065
-0.00065
-0.00061
-0.00061
-0.00027
-0.00027
-0.00021
-0.00021
-0.00048
-0.00048
-0.00040
-0.00040