Large wood (LW) addition is often part of fish habitat
restoration projects. However, there is limited information about the
spatial–temporal variability in hydraulic changes after LW additions. We
investigated reach-scale hydraulic changes triggered after the addition of
LW that are relevant to juvenile coho salmon survival. We used Nays2DH, an
unsteady two-dimensional flow model, to quantify the patterns and magnitudes of
changes of stream velocity and shear stress in three alluvial gravel
reaches. The study sites are located in low-gradient reaches draining 5 to
16 km2 in the Oregon Coast Range. Survivable habitat was characterized
in terms of critical swim speed for juvenile coho and bed stability
considering the critical shear stress required to mobilize the median bed
particle size. Model predictions indicated that survivable habitat during
bankfull conditions, measured as the area with velocity below the critical
swim speed for juvenile coho, increased by 95 %–113 % after the LW
restoration. Bed stability also increased between 86 % and 128 % considering
the shear stress required to mobilize the median bed particle size. Model
predictions indicated more habitat created in the larger site; however,
considering that wood would move more frequently in this site there appears
to be a trade-off between the timing and the resilience of restoration
benefits. Overall, this study quantifies how the addition of LW potentially
changes stream hydraulics to provide a net benefit to juvenile salmonid
habitat. Our findings are applicable to stream restoration efforts
throughout the Pacific Northwest.
Introduction
Large wood (LW) is a fundamental component of many temperate streams given
its influence on flow resistance, stream morphology, sediment transport,
nutrient cycling, and stream habitat (e.g., Triska and Cromack, 1980;
Harmon et al., 1986; Montgomery et al., 1995; Kail, 2003). LW structures
increase heterogeneity in the flow field by promoting local scour and
sediment retention, reducing average flow velocity, influencing bed
texture (Buffington and Montgomery, 1999a), and promoting
increased interaction of the flow with the floodplain (Beschta, 1979;
Harmon et al., 1986; Lisle, 1986; Bisson et al., 1987; Wipfli et al., 2007;
Seo et al., 2008). LW jams are often associated with forced pool–riffle
morphologies in reaches that would otherwise exhibit plane-bed
characteristics (Montgomery and Buffington, 1997). Thus,
channels with abundant LW have relatively higher complexity (e.g., high
frequency of pools, channel bars, and riffles), offering a wide range of
habitat for aquatic species including invertebrates and fish (Fausch and
Northcote, 1992; Gerhard and Reich, 2000; Roni and Quinn, 2001; Dolloff and
Warren, 2003; Jahnig and Lorenz, 2008; Benke and Wallace, 2010; Pess et al.,
2012). Historically, abundant LW in Pacific Northwest streams provided
habitat for a variety of fish species (Bisson et al., 1988; Connolly and
Hall, 1999) including anadromous fish such as coho salmon (Oncorhynchus kisutch) and steelhead
(Oncorhynchus mykiss) (Nickelson et al., 1992a; Quinn and Peterson, 1996; Beechie and
Sibley, 1997; Johnson et al., 2005; Gallagher et al., 2014; Jones et al.,
2014). Prior to the recognition of the role of LW pieces in habitats, forest
management operations allowed harvesting to the edge of streams and the
removal of in-channel LW. This removal resulted in the reduction of stream
complexity (Bisson et al., 1987; Sedell et al., 1988; Stednick, 2008),
which has reduced habitat and contributed to fish population declines
(Dolloff, 1986; House and Boehne, 1986; Fausch and Northcote, 1992; Smith
et al., 1993a, b; Brown et al., 1994).
For coho salmon, which generally spend at least 1 year rearing in
freshwater prior to out-migration to the ocean, overwinter survival has been
identified as a critical factor influencing population abundance and
productivity (Tschaplinski and Hartman, 1983; Nickelson et al., 1992a, b; Quinn and Peterson, 1996; Huusko et al., 2007;
Gallagher et al., 2012; Suring et al., 2012). Coho salmon overwinter
survival is strongly linked to the availability of complex, low-velocity
habitats that have been reduced in many areas due to land use and
development (Tschaplinski and Hartman, 1983; McMahon and Hartman, 1989;
Quinn and Peterson, 1996; Johnson et al., 2005). Thus, the restoration of winter
refuge habitat for coho salmon can be crucial for population viability and
species recovery (Nickelson and Lawson, 1998; NMFS, 2016).
The rationale behind LW restoration projects is that the introduced pieces
would create larger and deeper pools, stabilize stream substrate, and
facilitate the interaction of the flow with the floodplain. This ultimately
provides low-velocity refuge where juvenile salmonids can shelter both in
the stream channel and in adjacent, newly connected floodplains (Bustard
and Narver, 1975b; McMahon and Hartman, 1989; Bradford et al., 1995; Cunjak,
1996). However, there is still controversy about the effectiveness of adding
LW as a restoration strategy (Roni et al., 2008, 2014; Whiteway et al., 2010). Studies have reported improvements in fish abundance
after LW introductions in relatively short reaches (75–500 m) (e.g.,
House and Boehne, 1986; Cederholm et al., 1997; Roni and Quinn, 2001), while
others working over larger scales (500–1000 m) have observed positive
changes to stream morphology relevant to fish habitat (Anlauf et al.,
2011; Jones et al., 2014). The survey approaches used in these studies
provided a static perspective on stream habitat and often occurred under low-flow conditions. We currently lack an understanding of how LW structures affect
flow hydraulics and fish habitat at the reach scale under a range of flows,
which is relevant to those looking to address both geomorphic change and
natural habitat limitations.
Previous efforts have used computational fluid dynamics models to simulate
field conditions around obstacles such as wood and boulders in theoretical
domains (Allen and Smith, 2012) and experiment flumes (Xu and Liu,
2016, 2017; Lai et al., 2017), in some cases using flow
deflectors to mimic the effects of wood in channels (Biron et al.,
2009). These studies have provided detailed descriptions of the turbulent
flow around these structures, highlighting the effects of simplifying the
geometry of the obstacles in the prediction of flow velocity (Allen and Smith, 2012; Xu and Liu, 2017) and the effects of the
assumed obstacle shape and orientation on the velocity field and sediment
transport (Biron et al., 2009, 2012).
However, these models are computationally intensive and not yet feasible at
the reach scale.
Two-dimensional (2-D) computational hydraulic modeling offers a relatively
time- and cost-effective strategy to analyze the flow field of a stream reach
without the need for high-resolution field measurements at every discharge
level of interest. These 2-D models have been used to quantify fish habitat
based on flow velocity and depth indicators in streams in a variety of
conditions (e.g., Nagaya et al., 2008; Branco et al., 2013; Cienciala and
Hassan, 2013; Hatten et al., 2013; Laliberte et al., 2014; Fukuda et al.,
2015; Carnie et al., 2016) including the effects of boulders in straight
urban sections (Lee et al., 2010) and the effects of large wood
using non-calibrated models (Hafs et al., 2014; Wall et al., 2016). The
2-D estimates of velocity and channel bed stability at scales of ecological
significance – individual boulders and LW pieces (Crowder and
Diplas, 2000) – can be used to estimate habitat improvements after the
addition of LW. Flow velocity can limit the ability of fish to maintain
position and result in excessive energetic costs (Huusko et
al., 2007), while unstable sediment limits the ability of juveniles to find
shelter within substrate rocks during high flows.
Despite the mentioned applications of 2-D hydraulic modeling, there are
limited examples of calibrated efforts that have evaluated winter habitat
for salmonids at the reach scale. Our objective was to use a calibrated 2-D
model to quantify the change in survivable habitat area for juvenile coho
salmon after the addition of LW by examining changes in water velocity and
substrate stability during a bankfull event in three gravel-bed reaches. In
doing so, we developed field-calibrated before and after models to describe
flow hydraulics in three individual sites. To our knowledge, this was the
first time a calibrated model has been used to estimate the effects of LW in
natural conditions.
Location of the Mill Creek watershed, OR, and the study
sites: 1, 2, and 3.
MethodsStudy area
This study was conducted in three alluvial stream reaches in Mill Creek, a
tributary of the Siletz River in the Oregon Coast Range (Fig. 1). The
watershed is dominated by intensively managed Douglas fir (Pseudotsuga menziesii) forest, and
riparian areas are mostly vegetated with the deciduous species vine maple
(Acer circinatum), bigleaf maple (Acer macrophyllum), and red alder (Alnus rubra). Watershed elevations range from 60 to 730 m (Fig. 1) and the basin is primarily underlain by the Tyee formation
composed of sandstone and siltstone. The climate is marine temperate,
influenced by moisture from the Pacific Ocean, and annual precipitation of
2300 mm in the nearby town of Siletz is mainly received as rain during fall
and winter (November–March). The selected low-gradient fish-bearing reaches
had minimal (LW) pieces present and were located in different tributaries:
Site 1 is located in the main stem of Mill Creek, Site 2 is located in
Cerine Creek, and Site 3 is located in the South Fork (Table 1). All sites
display low to moderately developed pool–riffle sequences with bankfull
discharge (Qbf) between 2.4 and 8.7 m3 s-1 (Table 1).
Characteristics of the three study sites. Values in
parenthesis correspond to the standard errors.
During July 2015, a detailed topographic survey was conducted in each of
the three study reaches including 20–28 cross sections (XS) per site spaced
∼12 bankfull width apart and 1700–2000
additional survey points to characterize abrupt topographic changes. The raw
topography was smoothed and interpolated to a dense point cloud using a
natural neighbor scheme under ArcGIS and used in the model framework (see
Sect. 3.2). We estimated the grain size distribution (GSD) in each reach
based on particle counts (Wolman, 1954) conducted in 11–25 visually
identified patches of relatively uniform sediment size per site (Buffington
and Montgomery, 1999b; Rosenberger and Dunham, 2005; Smith and Prestegaard,
2005; Cienciala and Hassan, 2013). We instrumented the study reaches with
pressure transducers at a relatively stable and uniform XS (Fig. 2).
Discharge was measured using the velocity–area method (Dingman,
2002) with a Hack FH950 portable velocity meter, and depth–discharge rating
curves were developed based on 9–10 discharge measurements per site
covering a wide range in discharge levels: 5 %–100 % of Qbf in Site 1, 5 %–63 % of Qbf in Site 2, and 5 %–89 % of Qbf in Site 3.
In August 2015, 39 pieces of LW were added to the three sites by the
Oregon Department of Fish and Wildlife. The wood was arranged into two jams
per site with three to eight wood pieces each (Fig. 2). The wood pieces added were all
over 6 m long with diameters between 0.5 m and 1.6 m. The logs were oriented
lengthwise in the stream to mimic wood pieces that have been rafted into a
location and provide the most contact with the bed and a stable but natural
configuration to drive geomorphic change. The jams were located in bends in
the stream reaches where possible, and additional logs were placed on top of
jams and braced by existing trees to increase stability, but no other means
of permanently fixing the jam locations was used. The entire process of
building the six jams across sites took less than 2 d.
Topography (derived 0.2 m contours) and location of
introduced large wood (LW), water surface elevation (WSE) monitoring rulers
(circles), water level loggers (triangle), and location of velocity
measurements (dash line). Flow direction is from top to bottom in all three
sites.
Flow modeling
In order to describe flow field changes triggered by the addition of LW, we
used the 2-D unsteady Nays2DH model (Takebayashi et al., 2003; Jang and
Shimizu, 2005; Nelson et al., 2016). This
model was selected for its ability to simulate unsteady conditions
experienced during rapidly varying discharge and rapidly varying shear
stress around obstacles. We first simulated steady intermediate (20 %–50 %
of Qbf) and large (Qbf) flow levels for calibration purposes and
35–45 h long Qbf flow events (unsteady) before and after the LW
additions. These unsteady models were used to characterize the distributions
of depth, velocity, and shear stress pre- and post-LW addition (Table 2) and
include a wide range of flows between 0.1 Qbf and Qbf. The model uses
a free-surface, finite-differenced, and depth-integrated version of the
Navier–Stokes equations (NSEs) assuming a logarithmic velocity profile in the
boundary layer near the bed and a parabolic velocity profile away from it.
Nays2DH uses the cubic-interpolated pseudo-particle (CIP) method for finite
differencing, which gives high-accuracy flow predictions, particularly in
instances of flow separating shear layers. The model calculates present and
future 2-D velocity for a given time step using a cubic profile to determine
its spatial derivative under the assumption that both time steps follow the
governing NSE flow equation (Yabe et al., 1990). This method
requires the use of a short modeling time step to ensure model stability,
thereby limiting the length of model runs given computational cost (Nelson et al., 2016).
Model input data were channel topography, discharge, roughness, downstream
flow stage, and a characterization of the initial upstream water surface elevation (WSE) condition.
Given the large size of the LW pieces with diameters 0.8–2.3 times the
Qbf depth in all three sites, they were represented in the model as
fully penetrating the water depth protruding into the channel and located
based on detailed topographic surveys. Based on time-lapse photography and
flow level observations, the LW pieces were never overtopped by the flow. In
cases in which LW pieces were angled relative to the slope of the streambed or
in which lateral topography in the bed left large gaps under LW pieces, the
shape of the flow-restricting obstacles was adjusted to allow for a
significant amount of flow to pass around the structures.
Nays2DH model parameters and calibration results for pre-
and post-large-wood (LW) models for different discharge (Qi) levels.
Fractional bankfull discharge (Qi/Qbf), average model depth
(Hmean), number of water surface elevation (WSE) and velocity (v)
observations taken, root mean square error (RMSE), R2 for WSE, and time-averaged v are indicated for calibration runs when available along with
observed and modeled WSE slopes.
aAssuming a constant downstream water surface elevationas the
initial boundary condition. bUniform flow assumption as the initial upstream and downstream
boundary condition.
The model parameters were adjusted based on 1000 s constant discharge
calibration simulations with 0.01 s time steps averaged over 10
iterations. We assumed a constant downstream WSE measured in the field for
all calibration runs except for the high flows modeled after LW addition
when wading was hazardous. For these runs, and for the hydrograph
simulations, we employed the uniform flow assumption as the initial upstream
and downstream boundary condition (Table 2). The model equations for
downstream (u) and cross-stream (w) velocity components are solved over an
orthogonal, curvilinear grid (Nelson et
al., 2016) and used to estimate the shear stress (τ) via a unitless coefficient of bed shear force (Cf):
τ=ρCfu2+w2,
where ρ is water density and Cf is estimated based on a spatially
variable unitless Manning roughness coefficient (n) calculated for the
identified sediment patches based on the grain size (D), gravitational
acceleration (g), flow depth (h), and a unitless α parameter that can
vary from 1 to 3.
2n=αD1/67.66g3Cf=n2gh1/3
Roughness values for vegetated areas outside the channel were set to be
10 % higher than the maximum patch n value in each model. The best fits for
all three sites were found with α=3 and D=D84 (size of a
particle equivalent to the 84th percentile in a cumulative frequency
distribution). We chose to model turbulence using the zero-equation option
in the model, which assumes smooth changes in lateral topography, and
thus τ and h dominate the momentum transport. A spatially varying eddy
viscosity is calculated in the model as a ratio of the depth and velocity.
We calibrated the models by comparing observed and predicted WSE through
each reach, with and without LW, and iteratively adjusting Cf by
changing n. The root mean square error for the WSE, computed based on 6–26
observations per flow, was below 0.045 m for all pre-wood scenarios and no
more than 0.21 m for all post-wood models (Table 2). Abrupt changes to
streambed morphology after the addition of LW contributed to model error, as
these changes could alter the observed WSE but were not reflected in our
models. For example, on the downstream end of Site 1 we observed significant
sediment deposition on the right side of the channel and scour on the left
side. Aside from this, the model was able to accurately capture the large
changes in WSE across logjams and the general water surface slope (Table 2). Velocity observations were used as an additional check after calibration
for two to three flow conditions per site when wading was possible. The RMSE of
velocity varied between 0.11 and 0.36 m s-1 (Table 2) based on 13–24
observations taken across the streams (Fig. 2). These values are similar to
other reported values of model RMSE for WSE and velocity for efforts that
did not include wood, indicating overall strong performance of the model
(Cienciala and Hassan, 2013; Mueller and Pitlick, 2014; Segura and
Pitlick, 2015; Katz et al., 2018).
Data analysis
We evaluated the changes in velocity and shear stress triggered by the
addition of LW in the three study reaches during a Qbf flow event with
emphasis on the peak discharge. Then we quantified the differences in the
spatial extent of suitable habitat for juvenile coho salmon during bankfull
flow and during the duration of a complete hydrograph in which discharge
varied between 0.1 Qbf and Qbf. For both velocity and shear stress
distributions, only areas where depth >0.1 m and velocity or
shear stress >0.01 units were included to limit the study to the
active channel, depths at which model assumptions were not likely to be
violated, and areas of the channel in which juvenile fish were likely to
be found (Bustard and Narver, 1975b). We estimated the area with
acceptable fish habitat within the modeled domains using a critical
swimming velocity (vcrit) of 0.5 m s-1 and a burst swim velocity
(vburst) of 1 m s-1 for wintertime juvenile coho salmon (Glova
and McInerney, 1977; Taylor and McPhail, 1985). The vcrit corresponds to
the maximum velocity at which a fish can maintain position in the flow field
for extended periods at a specific temperature, and vburst represents a
maximum instantaneous swim velocity.
Since juvenile salmonids are often shelter in substrate during harsh
environmental conditions (Hartman, 1965; Rimmer et al., 1983; Bradford et
al., 1995; Cunjak, 1996; Bradford and Higgins, 2001), we used the predicted
shear stress values to estimate the proportion of the bed area in which the
entrainment of the D50 is likely. Indeed, the D50 values in the
study sites range from 16 to 39 mm, which is similar to the particle size in
which sheltering juvenile Atlantic salmon have been observed (Cunjak, 1988). Our assumption is that transport of the D50 is a
reasonable threshold to represent conditions in which dislodging fish is
possible because the substrate would fail to provide shelter. The critical
shear stress (τc) associated with the movement of the D50 was
estimated based on slope (s) (Mueller et al., 2005):
4τc*=2.18s+0.021,5τc*=τcρs-ρgD50,
where τc* is the dimensionless critical Shield's stress
and ρs is sediment density (i.e., 2500 kg m-3 for
sandstone). We assumed that channel bed locations with τ>2τc
are likely to experience full transport mobility (Wilcock and
McArdell, 1993) and therefore offer no fish sheltering given that most of
the available particles sizes would likely be mobilized. In sections of the
bed experiencing partial transport (τc<τ<2τc) we assumed that sheltering would be difficult but
not impossible as larger particles are likely to remain stable.
ResultsComparison of velocity before and after the addition of LW
According to model predictions the mean bankfull flow velocity (v) before LW
additions ranged between 0.7 and 1.2 m s-1, while after the addition of LW
pieces velocity ranged between 0.53 and 0.92 m s-1 (Table 3),
corresponding to 23.2 %–36.3 % decreases. The distributions of velocity
values at wetted points throughout the model domain were narrower before LW
was added than the distributions after the LW (Fig. 3). Before the
restoration, all velocity distributions were relatively homogenous with a high
density of observations around the mean values (Fig. 4) and relatively small
standard deviations (0.3 to 0.5 m s-1; Table 3). After the LW additions,
the flow fields became more heterogeneous (standard deviations between 0.4 and 0.7 m s-1; Table 3), with lower clustering of velocity values around
the mean and a greater proportion of areas in the channel bed that
experienced extreme (low and high) velocity conditions (Figs. 3 and 4). The
increased heterogeneity of flow conditions after the LW additions was
associated with a greater proportion of flow interacting with the
floodplains upstream of the LW jams and the flow passing through the
decreased cross-sectional area of the LW jams themselves. The decrease flow
area around the wood is consistent with the increase in the mean WSE slope
between pre- and post-LW in all sites (Table 2).
Mean and standard deviation (SD) of velocity (v) and shear
stress (τ) at bankfull flow (Qbf) pre- and post-LW at the three
study sites; Qbf modeling results for habitat metrics v and τ
expressed as a percentage of the channel bed pre- and post-LW; and
percentage change in available fish habitat.
Site 1 Site 2 Site 3 MetricPre-LWPost-LWPre-LWPost-LWPre-LWPost-LWMean v (SD)1.23 (0.5)0.92 (0.7)0.69 (0.3)0.53 (0.4)1.02 (0.5)0.65 (0.5)Mean τ (SD)23.41 (14.7)18.99 (29.7)12.24 (8)9.14 (11.8)22.27 (18.2)11.35 (16.8)Percent of bed v≤vcrita15.332.526.752.223.847.3vcrit≤v≤vbursta13.932.760.234.517.028.3v>vbursta70.834.813.113.359.224.4τ<τcb30.269.029.159.941.076.4τc<τ<2τcb43.912.623.417.935.314.8τ<2τcb25.818.447.522.223.78.9Percent change in available habitat v≤vcrita+112.8 % +95 % +99.3 % vcrit≤v≤vbursta+134.5 % -42.6 % +66.1 % v>vbursta-50.8 % +1.4 % -58.8 % τ<τcb+128.3 % +105.9 % +86.3 % τc<τ<2τcb-71.4 % -23.5 % -58.2 % τ<2τcb-28.8 % -53.3 % -62.6 %
avcrit is 0.5 m s-1 and vburst=1 m s-1. bτc is the critical shear stress for the movement
of the median grain size (Table 1).
Mean flow velocity at bankfull discharge before (a, c, e) and after (b, d, f) the addition of large wood (LW) in Sites 1,
2, and 3. The colors correspond to thresholds of velocity relevant to the
ability of juvenile coho salmon to maintain position in the stream: dark
blue means v<vcrit where vcrit=0.5 m s-1, light blue means
vcrit<v<vburst where vburst=1 m s-1, and red means v>vburst. The location of the installed water surface rulers is included to
facilitate visual comparison of the increased extent of floodplain inundation
in each site during bankfull conditions.
Velocity distributions at bankfull flow at Sites 1 (a, d), 2 (b, e), and 3 (c, f) before (a–c) and after (d–f) the addition of large
wood (LW). The colors correspond to thresholds of velocity relevant to the
ability of juvenile coho salmon to maintain position in the stream: dark
blue means v<vcrit where vcrit=0.5 m s-1, light blue means
vcrit<v<vburst where vburst=1 m s-1, and red means v>vburst.
The predicted reduced velocity in the stream channels after the addition of
LW indicated increased fish habitat in all sites. The proportion of the
wetted channel area with velocity values below the critical value (v≤vcrit) increased over 95 % in all sites (Table 3, Fig. 3), being
highest in Site 1. The absolute increases in the total area where v≤vcrit were even greater at 186.1 %, 141.2 %, and 169.5 % for Sites
1–3, respectively. These values may be more relevant to restoration success
in the context of density-dependent habitat limitations faced by juvenile
coho salmon. The LW pieces backed up flow, increasing the wetted width,
which resulted in additional low-velocity habitat created beyond the
original channel margins (Fig. 3). Hence, the wetted areas of Sites 1, 2, and
3 increased by 34 %, 22 %, and 35 %, respectively (Fig. 3). The areas
with temporarily acceptable habitat (vcirt≤v≤vburst) also
increased by 134.5 % in Site 1 and by 66.1 % in Site 3 of their wetted
channel area (Table 3). Conversely, temporarily acceptable habitat decreased
from 60.2 % to 34.5 % of the wetted bed in Site 2 (Table 3). This site
had proportionally more areas with v<vburst prior to the LW
introductions (light blue in Fig. 3) and therefore less potential for an
increase in that category. These predictions clearly indicate that the LW
additions increased the area of habitat acceptable for juvenile salmon at
Qbf.
As mentioned above, the velocity distributions changed in shape, with the
highest-frequency values shifting away from the value of vburst to below
or near the value of vcrit, and hence the skewness of the distributions
shifted from negative to positive values in all sites. This shift provides
assurance of the robustness of our results. If the thresholds used to
determine habitat acceptability were shifted slightly, to account for
variations in other habitat parameters such as water temperature or fish
size, the benefits predicted by our model results would remain consistent.
Comparison of shear stress before and after the addition of LW
Model predictions indicated that the reach-average Qbf values of shear
stress (τ) before the LW additions were 23.41 N m-2 in Site 1,
12.24 N m-2 in Site 2, and 22.27 N m-2 in Site 3 (Table 3).
Modeling results indicated 18 %–49 % reductions in shear stress after the
LW pieces were added, which resulted in a substantial increase in fish habitat
in terms of substrate stability. Considering the critical Shields value for
the median grain size (Table 1), the proportions of the wetted bed with
stable conditions (τ<τc) increased from 29 %–41 % before LW
to 59.9 %–76.4 % after wood was added – an overall increase in fish habitat
of 86 %–128 % (Table 3). Further, the total increases in absolute area
where τ<τc were 205.8 % for Site 1, 151.4 % for Site 2, and
151.6 % for Site 3 (Fig. 5). The spatial changes in the distributions of
shear stress were associated with consistent decreases in flow velocity near
the channel margins and additional stream connectivity with available
floodplains (Fig. 5). Additionally, increased WSE slope through the reaches
after the addition of LW helped drive the variation in shear stress through
the formation of deeper pools upstream of LW jams.
Spatial distributions of shear stress (τ) at
bankfull discharge before (a, c, e) and after (b, d, f) the addition
of large wood (LW). Dark blue corresponds to τ<τc, light blue corresponds to τc<τ<2τc, and red corresponds to τ>2τc.
The location of the installed water surface rulers is included to facilitate
visual comparison of the increased extent of floodplain inundation in each
site during bankfull conditions.
The shape of the distributions of shear stress changed from having a
distinct peak near the mean in addition to a high frequency of observations
near zero to a distribution characterized by a constant decay (Fig. 6). We
fitted the mean normalized distributions of shear stress before and after the
LW additions to a gamma function (Segura and Pitlick, 2015) and found
that the shape parameter (α) of the distributions decreased for all
sites. While this parameter before LW varied between 2.2 and 5.4, it varied
between 0.6 and 1.0 after the LW additions. These changes illustrate
increases in complexity in the flow field after the restoration project.
Shear stress (τ) distributions at bankfull flow at
Sites 1 (a, d), 2 (b, e), and 3 (c, f) before (a–c) and after (d–f) the
addition of large wood (LW). Alpha (α) parameters of the a gamma fit
are provided. Dark blue corresponds to τ<τc,
light blue corresponds to τc<τ<2τc, and red corresponds to τ>2τc.
Temporal variability in available habitat during full bankfull flow
events
Modeled results before LW additions during the hydrographs indicate
that the reach area with acceptable habitat in terms of velocity (v<vcrit) varied between 15 % and 36 % in Site 1, 27 %
and 74 % in Site 2, and 23 % and 38 % in Site 3 (Table 4,
Fig. 7a–c). These percentages of reach area with acceptable habitat increased
after the addition of LW to 31 %–74 % in Site 1, 48 %–85 % in Site 2, and
42 %–72 % in Site 3 (Fig. 7a–c), indicating average increases between 23 % and 29 % (Table 4 and Fig. 7a–c). The temporal variability in the
percentage of the channel with acceptable habitat (v<vcrit)
reflects differences in floodplain connectivity among sites. For instance,
the consistent increase in acceptable habitat (v<vcrit) area
in Sites 2 and 3 over the duration of the entire hydrograph (Fig. 7e–f) is
likely a result of their large available floodplain area (Fig. 2).
Conversely, Site 1 experienced a wider range of increases in acceptable area
after LW addition, with the smallest differences occurring around the peak
discharge (Fig. 7d). This is likely the result of water completely
inundating the site's relatively smaller available floodplain area (Fig. 2)
during the rising limb of the hydrograph.
Hydrograph modeling results for habitat metrics of
velocity (v<vcrita) and shear stress (τ<τcb) expressed as the range of the percentage of the channel
bed pre- and post-LW; change in percentage available as fish habitat
pre- and post-LW.
Site 1 Site 2 Site 3 % of BedPre-LWPost-LWPre-LWPost-LWPre-LWPost-LWv≤vcrita15–3631–7427–7448–8523–3842–72change in %16–42 (29) 12–27 (23) 24–35 (29) τ<τcb30–9268–9328–7057–8241–7976–94change in %-2–42 (28) 13–32 (27) 16–36 (30)
avcrit is 0.5 m s-1. bτc is the critical shear stress for the movement
of the median grain size (Table 1).
(a–c) Fraction of the flow domain with v<vcrit or
τ<τc during simulated 40–35 h bankfull flow events in the
three study sites pre- and post-LW; (d–f) differences between after and before
LW additions in the fraction of the reach area with v<vcrit or τ<τc.
Similar to the modeling results for velocity, the proportion of the wetted
channel with acceptable habitat for fish to shelter within channel bed
sediment increased for all flow levels during all hydrograph
simulations in all study sites (Fig. 7a–c). The percentage of the channel
bed with stable substrate (τ<τc) before LW varied
between 30 % and 92 % in Site 1, between 28 % and 70 % in Site 2, and
between 41 % and 79 % in Site 3. These ranges increase on average
27 %–30 % to 68 %–93 % in Site 1, 57 %–82 % in Site 2, and
76 %–94 % in
Site 3 (Fig. 7a–c). Unlike what was observed for velocity, there were
significant temporal variations in the proportion of the wetted channel with
stable substrate (τ<τc), especially at Site 1
(Fig. 7d), which experienced the widest range of change between -2 % and
42 % (Table 3). In this site, the greatest increase in relative habitat
area occurred at the peak of the hydrograph when conditions would
presumably be the harshest for juvenile coho salmon (Fig. 7d). In other words, the
greatest increases in proportional area with stable substrate after LW
addition coincided with high discharge, while there were smaller differences at the initial low discharge values. In addition, larger immobile
substrate areas were evident during the falling limb of the hydrograph
compared to the rising limbs in all sites (Fig. 7d–f). This is likely
associated with the temporary storage of water in the floodplain after the
addition of LW and a related decreased transport capacity (decreased shear
stress) available to mobilize bed material.
Discussion
The goal of this study was to model the hydraulic effects of the
introduction of LW on components of fish habitat in three gravel-bed
streams. Two-dimensional (2-D) modeling predicted significant changes in the
flow field pre- and post-LW additions that resulted in approximately twice
as much simulated winter rearing habitat in all sites. To our knowledge,
this study is the first to simulate the impact of the addition of LW on fish
habitat at the reach scale using a field-calibrated, unsteady 2-D hydraulic
model calibrated to pre- and post-LW flow events. Our findings concur with
uncalibrated and steady-state simulations that have documented increases in
the heterogeneity in the flow field at high discharges after the addition of
LW, thereby increasing fish habitat (He et al., 2009; Hafs et al., 2014;
Wall et al., 2016). The use of water surface elevation and velocity
calibration data in pre- and post-LW models provided a robust framework to
estimate mean depth-averaged flow velocity and shear stress, variables
likely to fully represent realistic winter sheltering opportunities for
juvenile fish in terms of flow velocity and substrate stability.
The addition of LW in the study reaches modified river hydraulics, resulting
in significantly wider wetted areas. At bankfull flow, the increased
floodplain connectivity was associated with more heterogeneous flow fields
characterized by wider distributions of velocity and shear stress with
overall lower mean values. The shapes of pre-LW velocity distributions for
all sites were similar to those observed in small mountain streams with
large frequency at both intermediate and low velocity values (Cienciala and Hassan, 2016). The shape of the velocity
distributions changed dramatically, with post-LW being characterized by a higher
proportion of low-velocity areas in all three sites. Other field modeling
efforts have documented similar effects of LW on the velocity distribution
in the flow field (Wall et al., 2016). Flume experiments as
well as field simulations have also reported reductions in flow velocity
with increasing large wood obstacles (He et al., 2009; Davidson and
Eaton, 2013; Hafs et al., 2014). The distributions of shear stress also
changed dramatically from closely resembling those observed in single-thread
streams pre-LW (Lisle et al., 2000; Mueller and Pitlick, 2014; Segura and
Pitlick, 2015; Cienciala and Hassan,
2016) to resembling complex braided channels (Paola, 1996; Nicholas, 2003;
Mueller and Pitlick, 2014; Tamminga et al., 2015) post-LW. The shift towards
a greater frequency of low shear stress is likely attributed to shear stress partition
by the channel banks and LW form drag (Kean and Smith, 2006; Yager et
al., 2007; Ferguson, 2012; Scheingross et al., 2013). The changes in the
velocity and shear stress distributions occurred as the flow encroached into
the floodplain, and although stream margins have been associated with the
creation of off-channel habitat for juvenile coho salmon in previous studies (Swales and Levings, 1989; Bell et al., 2001), no quantification of the
actual changes in the flow field in terms of velocity or shear stress had
been conducted before. The post-LW distributions of shear stress and velocity indicated
increased hydraulic and habitat heterogeneity (Gerhard and Reich, 2000;
Brooks et al., 2006), which has been reported as a key flow field
characteristic associated with habitat suitability for salmonids (McMahon
and Hartman, 1989; Roni and Quinn, 2001; Venter et al., 2008; Anlauf-Dunn et
al., 2014). The suggested benefits of flow heterogeneity include velocity
refuges in close proximity to feeding locations and cover from predators
(Nickelson et al., 1992a; Nickelson and Lawson, 1998; Gustafsson et al.,
2012). The increased availability of low-velocity areas during bankfull
discharge is relevant for winter fish habitat given the high mortality that
can occur during this season (Quinn and Peterson, 1996). Although we did not measure sediment transport, the overall reduction of
velocity and shear stress likely contributes to increased pool depth and
area (Montgomery et al., 1995; Beechie and Sibley, 1997; Collins et al.,
2002) and decreased overall bed load transport capacity (Thompson and
Fixler, 2017; Wohl and Scott, 2017).
Although we were able to model velocity and shear stress, there are
components of the flow and temporal changes to the bed that we were unable
to account for. While the sharp topography in our model domains around LW
pieces allowed us to predict local areas of elevated shear stress, the 2-D
model is not capable of capturing the strong vertical currents that are
likely to develop in proximity to the LW and deform the streambed with
important impacts on the assessment of available habitat (Mutz et
al., 2007). While it has been observed that 3-D models outperform 2-D models
in predicting flow structures in close proximity to obstacles (Shen and Diplas, 2008), our results are promising. The full
depth penetrating size and downstream orientation of the LW pieces in our
reaches resulted in predictions of fragmented flow, increased maximum local
shear values, deflection of maximum velocities, shear stress away from
the outside of bends, and low-velocity habitat regions in the wake of
longitudinally oriented logs, which aligns with observations made in other
studies using 3-D modeling (Daniels and Rhoads, 2003, 2004a, b; Xu and
Liu, 2017). Despite these promising observations, there still remains
uncertainty around the 3-D nature of the flow, which is likely greater in
areas with denser LW loading and greater stream curvature as well as during periods
of increased discharge (Daniels and Rhoads, 2004a). A comparison
of observed and modeled velocity values near LW structures would provide
further understanding of the uncertainty of our 2-D modeling approach and
insight into the accuracy of the predictions. A comprehensive set of
measurements could show a potential envelope around complex LW structures
for which model predictions are less accurate. However, this was not possible in
our case given logistical constraints to collecting such data. A 3-D version of
the NAYS2DH model, known as NaysCUBE, could potentially address some of
these issues. However, this approach would require substantially more time,
computational power, and calibration to ensure model stability. As the bed
deforms, we would expect to see a feedback of changing velocity and shear
stress values, particularly where we predicted the highest values. Another
limitation of our approach is the inability to account for LW mobility.
Field observations during high flows and the length of LW pieces relative to
stream widths indicate that pieces were unlikely to mobilize downstream (Merten et al., 2010; Ruiz-Villanueva et al., 2016); however, we did
observe some floating and minor adjustment of some LW pieces (particularly
in Site 1) during the highest-flow events. Thus localized stream hydraulics
could be subject to variations (Daniels and Rhoads, 2004a),
including potential flow underneath LW pieces, via both scour and hyporheic
flow through sediment (Ruiz Villanueva et al., 2014) that we did
not account for in the model. As the LW jams continue to develop over many
flow events, in addition to some movement of logs, smaller wood pieces,
sticks, and leaves from the upper watersheds will also collect and have been
shown to meaningfully alter flow through LW jams (Manners et
al., 2007).
Despite these uncertainties, the strong agreement between observed and
predicted water surface elevation and velocity before and after the LW
additions provided evidence that the predictions are robust. This implies
that this unsteady model, which has traditionally been used in larger
systems (Kafle and Shakya, 2018), can be implemented in
significantly smaller systems even in the presence of large obstacles.
Though it is key that sufficient detail on channel morphology in the regions
where LW blocks flow is available to allow for conveyance through the model
domain in such small streams.
The reach scale of this study should also be considered in viewing the
results. Fully loading the watershed with LW at a similar density to our
study sites may reduce the increase in WSE slope we observed after the
addition of LW by backwatering areas where our downstream boundary
conditions were located. This may lead to less heterogeneity of velocity and
shear stress in the flow field, particularly fewer values in the medium to
high range. However, the changes in the flow field we documented clearly
show that the addition of LW created more of the slow-water habitat
preferred by juvenile coho salmon during the winter. The observed shift in
velocity distribution toward very low water velocities, particularly evident
at Sites 2 and 3, may be especially important due to the energetic
challenges faced by coho salmon in winter when food resources and
assimilation capabilities are limited (Cunjak, 1996; Huusko et al.,
2007). Juvenile coho salmon are generally found in microhabitats with water
velocities far below vcr in the winter (Bustard and Narver, 1975a;
McMahon and Hartman, 1989), and the availability of such habitats,
especially during high flows, may be a critical factor in increasing
overwinter survival. The spatial arrangement of these low-velocity habitats
relative to water depth and cover in the form of woody debris and
overhanging banks is also important, as these factors affect the risk of
displacement and predation for juvenile coho salmon (Bustard and Narver,
1975b; Tschaplinski and Hartman, 1983; McMahon and Hartman, 1989). Given the
importance of multiple factors in winter habitat selection by coho salmon,
incorporating velocity, depth, and cover into the habitat modeling process
would be a useful future direction for predicting the effects of LW addition
on habitat suitability.
Considering that after the restoration project the flow field in the study
reaches adjusts to the new condition, the model predictions will
progressively lose accuracy as channel scouring and aggradation occur around
and behind the new LW additions. The period over which the predictions would
be robust is uncertain and would depend on how fast the streams adjust to
the new conditions and how stable the LW additions are. Both the stability
of individual LW pieces and its function in the flow field depend on the
size of the LW piece relative to the size of the stream. Modeling
predictions indicated more habitat created in the large reach (Site 1)
compared to the smaller reaches (Sites 2 and 3) both in terms of velocity
and shear stress (Table 3). However, the introduced LW would likely be more
stable in the smaller sites than in larger sites (Gurnell et al., 2002;
Hassan et al., 2005; Wohl and Jaeger, 2009; Merten et al., 2010;
Ruiz-Villanueva et al., 2016) given not only difference in size (e.g.,
smaller sites being more narrow) but also differences in discharge.
Therefore, we anticipate that the model predictions will lose accuracy
sooner in the larger site and that there may be a trade-off between the
timing and the resilience of restoration benefits. That is, the addition of
LW would likely increase the amount of suitable habitat sooner in the larger
site, but the LW pieces in this site also have the highest potential to leave
the system. In order to test this expectation the model could be run again
with updated topography to explore how the predicted distributions of shear
stress and velocity presented in this study compare to new estimations after
the bed has adjusted. This would provide not only a way to contrast model
predictions but also to understand which site changes faster after the
restoration and what habitat benefits are likely to persist in the longer
term (Wall et al.,
2016). The trade-off relative to
stream size and potential for LW export also highlight the importance of
considering restoration in a basin-wide context.
Although we focused on juvenile coho salmon in our analysis, the modeling
results are highly relevant to other salmonid species in these streams, as
well as to other life history stages. For example, the critical swimming
speed of juvenile steelhead trout falls between the vcrit and
vburst values for coho salmon used in our analysis (Hawkins and Quinn, 1996), so the amount of suitable
habitat for juvenile steelhead following LW addition would also be expected
to increase significantly. Furthermore, juvenile steelhead are more oriented
to the stream bottom in winter than coho salmon, with age 0 steelhead often
using substrate as cover (Bustard and Narver, 1975a). As a
result, the increased bed stability we observed post-LW would likely have an
even stronger effect on habitat suitability for juvenile steelhead than for
coho salmon. Changes in shear stress and bed stability can also have
important effects on the survival of salmonid embryos incubating in the
substrate (Lisle and Lewis, 1992), and our sites are located in
important spawning areas for adult coho salmon and steelhead in the study
basin. A more detailed examination of spawning sites, sediment transport, and
scour depths would be needed to fully investigate the effects of LW on salmonid
embryo survival, but the modeling approach used here could provide valuable
insight into the spatial distribution of shear stress in a study of this
kind.
Conclusions
In this study, we used an unsteady two-dimensional hydraulic model to
investigate the effects of the introduction of large wood (LW) on fish
habitat in three gravel-bed streams. The models predicted habitat increases
in terms of suitable flow velocity and area of stable substrate of over
80 % in all streams. Our study is the first to use a field-calibrated
model to estimate river hydraulics pre- and post-LW at the reach scale. The
distributions of velocity and shear stress changed dramatically from bimodal
to exponential decay, indicating increased flow complexity in the presence
of LW and resembling a change from single-thread to multithread channels. We
observed larger changes in the largest site; however, we anticipate a
trade-off between the timing and the resilience of restoration benefits
given the higher likelihood for wood transport in the larger site. The
methodology presented here can be used in the future as a tool to predict
changes triggered by restoration efforts, evaluate long-term responses to
restoration, and assess the changes in the flow field of different LW
scenarios to improve our understanding of LW dynamics in streams outside of
flume experiments. Finally, although the primary fish species of interest in
Mill Creek is coho salmon, our results are relevant to other salmonids and
non-salmonids that also benefit from reduced velocity and increased channel
bed stability.
Data availability
Nays2D-predicted distributions of velocity and
shear stress are available at the ScholarsArchive@OSU
(https://ir.library.oregonstate.edu/concern/datasets/br86b895f).
Author contributions
CS and CL defined the project and acquired the funding. CS led the organization of the study. Both RB and CS contributed to the determination of the field data collection strategy. RB conducted the flow modeling under the supervision of CS. RB, CS, and CL contributed to the interpretation of results and to the writing.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We are grateful to the Fish and Wildlife Habitat in Managed Forests Research
Program, the Oregon Watershed Enhancement Board (OWEB), and the Spirit
Mountain Community Fund for providing financial support for this research.
The authors thank Weyerhaeuser for providing logistical support. We would
also like to express gratitude to Jeff Light, Scott Katz, Rich McDonald,
Sharon Baywter-Reyes, Desiree Tullos, John Pitlick, and Jason Dunham for
many valuable discussions.
Review statement
This paper was edited by Heather Viles and reviewed by two anonymous referees.
References
Allen, J. and Smith, D.: Characterizing the Impact of Geometric
Simplification on Large Woody Debris Using CFD,
International J. Hydraul. Eng., 1, 1–14, 2012.
Anlauf, K. J., Gaeuman, W., and Jones, K. K.: Detection of Regional Trends
in Salmonid Habitat in Coastal Streams, Oregon,
T. Am. Fish. Soc., 140, 52–66, 2011.
Anlauf-Dunn, K. J., Ward, E. J., Strickland, M., and Jones, K.: Habitat
connectivity, complexity, and quality: predicting adult coho salmon
occupancy and abundance, Can. J. Fish. Aquat. Sci.,
71, 1864–1876, 2014.
Beechie, T. J. and Sibley, T. H.: Relationships between channel
characteristics, woody debris, and fish habitat in northwestern Washington
streams, T. Am. Fish. Soc., 126, 217–229, 1997.
Bell, E., Duffy, W. G., and Roelofs, T. D.: Fidelity and Survival of
Juvenile Coho Salmon in Response to a Flood, T. Am. Fish. Soc., 130, 450–458, 2001.
Benke, A. C. and Wallace, J. B.: Influence of wood on invertebrate
communities in streams and rivers, in: The ecology and management of wood in world rivers, edited by: Gregory, S. V., Boyer, K. L, Gurnell, A. M., American
Fisheries Society, Symposium 37, Bethesda, Maryland, 37,
149–177, 2010.
Beschta, R. L.: Debris removal and its effects on sedimentation in an Oregon
Coast Range stream, Northwest Sci., 53, 71–77, 1979.
Biron, P. M., Carrè, D. M., and Gaskin, S. J.: Hydraulics Of Stream Deflectors Used In Fish-habitat Restoration Schemes, WIT Trans. Ecol. Envir., 124, 305–314, 2009.
Biron, P. M., Carver, R. B., and Carré, D. M.: Sediment transport and
flow dynamics around a restored pool in a fish habitat rehabilitation
project: field and 3-D numerical modelling experiments,
River Res. Appl., 28, 926–939, 2012.
Bisson, P. A., Bilby, R. E., Bryant, M. D., Dolloff, C. A., Grette, G. B.,
House, R. A., Murphy, M. L., Koski, K. V., and Sedell, J. R.: Large woody
debris in forested streams in the Pacific Northwest: past, present, and
future, in: Streamside management, forestry and fishery interactions. Institute of Forest Research, University of Washington, Seattle, 1987.
Bisson, P. A., Sullivan, K., and Nielsen, J. L.: Channel hydraulics, habitat
use, and body form of juvenile coho salmon, steelhead, and cutthroat trout
in streams, T. Am. Fish. Soc., 117, 262–273,
1988.
Bradford, M. J. and Higgins, P. S.: Habitat-, season-, and size-specific
variation in diel activity patterns of juvenile chinook salmon (Oncorhynchus
tshawytscha) and steelhead trout (Oncorhynchus mykiss), Can. J. Fish. Aquat. Sci., 58, 365–374, 2001.
Bradford, M. J., Taylor, G. C., Allan, J. A., and Higgins, P. S.: An
Experimental Study of the Stranding of Juvenile Coho Salmon and Rainbow
Trout during Rapid Flow Decreases under Winter Conditions,
N. Am. J. Fish. Manage., 15, 473–479, 1995.
Branco, P., Boavida, I., Santos, J. M., Pinheiro, A., and Ferreira, M. T.:
Boulders as building blocks: improving habitat and river connectivity for
stream fish, Ecohydrology, 6, 627–634, 2013.
Brooks, A. P., Howell, T., Abbe, T. B., and Arthington, A. H.: Confronting
hysteresis: Wood based river rehabilitation in highly altered riverine
landscapes of south-eastern Australia, Geomorphology, 79, 395–422, 2006.
Brown, L. R., Moyle, P. B., and Yoshiyama, R. M.: Historical Decline and
Current Status of Coho Salmon in California, N. Am. J. Fish. Manage., 14, 237–261, 1994.
Buffington, J. M. and Montgomery, D. R.: Effects of hydraulic roughness on
surface textures of gravel-bed rivers, Water Resour. Res., 35, 3507–3521,
1999a.
Buffington, J. M. and Montgomery, D. R.: A procedure for classifying
textural facies in gravel-bed rivers, Water Resour. Res., 35, 1903–1914,
1999b.
Bustard, D. R. and Narver, D. W.: Aspects of the Winter Ecology of Juvenile
Coho Salmon (Oncorhynchus kisutch) and Steelhead Trout (Salmo gairdneri),
J. Fish. Res. Board Can., 32, 667–680, 1975a.Bustard, D. R. and Narver, D. W.: Preferences of juvenile coho salmon (Oncorhynchus-kisutch) and cutthroat trout (Salmo-clarki) relative to simulated alteration of winter habitat, J. Fish. Res. Board Can., 32, 681–687,
1975b.
Carnie, R., Tonina, D., McKean, J. A., and Isaak, D.: Habitat connectivity
as a metric for aquatic microhabitat quality: application to Chinook salmon
spawning habitat, Ecohydrology, 9, 982–994, 2016.
Cederholm, C. J., Bilby, R. E., Bisson, P. A., Bumstead, T. W., Fransen, B.
R., Scarlett, W. J., and Ward, J. W.: Response of Juvenile Coho Salmon and
Steelhead to Placement of Large Woody Debris in a Coastal Washington Stream,
N. Am. J. Fish. Manage., 17, 947–963, 1997.
Cienciala, P. and Hassan, M. A.: Linking spatial patterns of bed surface
texture, bed mobility, and channel hydraulics in a mountain stream to
potential spawning substrate for small resident trout, Geomorphology, 197,
96–107, 2013.
Cienciala, P. and Hassan, M. A.: Sampling variability in estimates of flow
characteristics in coarse-bed channels: Effects of sample size, Water
Resour. Res., 52, 1899–1922, 2016.
Collins, B. D., Montgomery, D. R., and Haas, A. D.: Historical changes in
the distribution and functions of large wood in Puget Lowland rivers,
Can. J. Fish. Aquat. Sci., 59, 66–76, 2002.
Connolly, P. J. and Hall, J. D.: Biomass of coastal cutthroat trout in
unlogged and previously clear-cut basins in the central coast range of
Oregon, T. Am. Fish. Soc., 128, 890–899, 1999.
Crowder, D. W. and Diplas, P.: Using two-dimensional hydrodynamic models at
scales of ecological importance, J. Hydrol., 230, 172–191, 2000.
Cunjak, R. A.: Behavior and microhabitat of young atlantic salmon
(salmo-salar) during winter, Can. J. Fish. Aquat. Sci., 45, 2156–2160, 1988.
Cunjak, R. A.: Winter habitat of selected stream fishes and potential
impacts from land-use activity, Can. J. Fish. Aquat. Sci., 53, 267–282, 1996.
Daniels, M. D. and Rhoads, B. L.: Influence of a large woody debris
obstruction on three-dimensional flow structure in a meander bend,
Geomorphology, 51, 159–173, 2003.Daniels, M. D. and Rhoads, B. L.: Effect of large woody debris configuration
on three-dimensional flow structure in two low-energy meander bends at
varying stages, Water Resour. Res., 40, W11302, 10.1029/2004WR003181, 2004a.Daniels, M. D. and Rhoads, B. L.: Spatial Pattern of Turbulence Kinetic
Energy and Shear Stress in a Meander Bend with Large Woody Debris,
Water Sci. Appl., 87–97, 10.1029/008WSA07, 2004b.
Davidson, S. L. and Eaton, B. C.: Modeling channel morphodynamic response to
variations in large wood: Implications for stream rehabilitation in degraded
watersheds, Geomorphology, 202, 59–73, 2013.
Dingman, S. L.: Physical hydrology, Prentice Hall, Upper Saddle River, N.J.,
2002.
Dolloff, C. and Warren Jr., M. L.: Fish relationships with large wood in
small streams, Am. Fish. S. S., 37, 179–193, 2003.
Dolloff, C. A.: Effects of stream cleaning on juvenile coho salmon and dolly
varden in Southeast Alaska, T. Am. Fish. Soc.,
115, 743–755, 1986.
Fausch, K. D. and Northcote, T. G.: Large Woody Debris and Salmonid Habitat
in a Small Coastal British Columbia Stream, Can. J. Fish. Aquat. Sci., 49, 682–693, 1992.Ferguson, R. I.: River channel slope, flow resistance, and gravel
entrainment thresholds, Water Resour. Res., 48, W05517, 10.1029/2011wr010850, 2012.
Fukuda, S., Tanakura, T., Hiramatsu, K., and Harada, M.: Assessment of
spatial habitat heterogeneity by coupling data-driven habitat suitability
models with a 2-D hydrodynamic model in small-scale streams,
Ecol. Inform., 29, 147–155, 2015.
Gallagher, S. P., Thompson, S., and Wright, D. W.: Identifying factors
limiting coho salmon to inform stream restoration in coastal Northern
California, Calif. Fish Game, 98, 185–201, 2012.
Gallagher, S. P., Ferreira, J., Lang, E., Holloway, W., and Wright, D. W.:
Investigation of the relationship between physical habitat and salmonid
abundance in two coastal northern California streams,
Calif. Fish Game, 100, 683–702, 2014.
Gerhard, M. and Reich, M.: Restoration of streams with large wood: Effects
of accumulated and built-in wood on channel morphology, habitat diversity
and aquatic fauna, Int. Rev. Hydrobiol., 85, 123–137, 2000.
Glova, G. J. and McInerney, J. E.: Critical Swimming Speeds of Coho Salmon
(Oncorhynchus kisutch) Fry to Smolt Stages in Relation to Salinity and
Temperature, J. Fish. Res. Board Can., 34, 151–154,
1977.
Gurnell, A. M., Piegay, H., Swanson, F. J., and Gregory, S. V.: Large wood
and fluvial processes, Freshwater Biol., 47, 601–619, 2002.
Gustafsson, P., Greenberg, L. A., and Bergman, E. V. A.: The influence of
large wood on brown trout (Salmo trutta) behaviour and surface foraging,
Freshwater Biol., 57, 1050–1059, 2012.
Hafs, A. W., Harrison, L. R., Utz, R. M., and Dunne, T.: Quantifying the
role of woody debris in providing bioenergetically favorable habitat for
juvenile salmon, Ecol. Model., 285, 30–38, 2014.
Harmon, M. E., Franklin, J. F., Swanson, F. J., Sollins, P., Gregory, S. V.,
Lattin, J. D., Anderson, N. H., Cline, S. P., Aumen, N. G., Sedell, J. R.,
Lienkaemper, G. W., Cromack, K., and Cummins, K. W.: Ecology of Coarse Woody
Debris in Temperate Ecosystems, Adv. Ecol. Res., 15,
133–302, 1986.
Hartman, G. F.: The Role of Behavior in the Ecology and Interaction of
Underyearling Coho Salmon (Oncorhynchus kisutch) and Steelhead Trout (Salmo
gairdneri), J. Fish. Res. Board Can., 22,
1035–1081, 1965.
Hassan, M. A., Church, M., Lisle, T. E., Brardinoni, F., Benda, L., and
Grant, G. E.: Sediment transport and channel morphology of small, forested
streams, J. Am. Water Resour. Assoc., 41, 853–876, 2005.Hatten, J. R., Batt, T. R., Scoppettone, G. G., and Dixon, C. J.: An
Ecohydraulic Model to Identify and Monitor Moapa Dace Habitat, PLOS ONE, 8,
e55551, 10.1371/journal.pone.0055551, 2013.
Hawkins, D. K. and Quinn, T. P.: Critical swimming velocity and associated
morphology of juvenile coastal cutthroat trout (Oncorhynchus clarki clarki),
steelhead trout (Oncorhynchus mykiss), and their hybrids, Can. J. Fish. Aquat. Sci., 53, 1487–1496, 1996.
He, Z., Wu, W., and Shields Jr., F. D.: Numerical analysis of effects of
large wood structures on channel morphology and fish habitat suitability in
a Southern US sandy creek, Ecohydrology, 2, 370–380, 2009.
House, R. A. and Boehne, P. L.: Effects of Instream Structures on Salmonid
Habitat and Populations in Tobe Creek, Oregon,
N. Am. J. Fish. Manage., 6, 38–46, 1986.
Huusko, A., Greenberg, L., Stickler, M., Linnansaari, T., Nykanen, M.,
Vehanen, T., Koljonen, S., Louhi, P., and Alfredsen, K.: Life in the ice
lane: The winter ecology of stream salmonids,
River Res. Appl., 23, 469–491, 2007.
Jahnig, S. C. and Lorenz, A. W.: Substrate-specific macroinvertebrate
diversity patterns following stream restoration, Aquat. Sci., 70,
292–303, 2008.
Jang, C.-L. and Shimizu, Y.: Numerical Simulation of Relatively Wide,
Shallow Channels with Erodible Banks, J. Hydraul. Eng., 131,
565–575, 2005.
Johnson, S. L., Rodgers, J. D., Solazzi, M. F., and Nickelson, T. E.:
Effects of an increase in large wood on abundance and survival of juvenile
salmonids (Oncorhynchus spp.) in an Oregon coastal stream, Can. J. Fish. Aquat. Sci., 62, 412–424, 2005.
Jones, K. K., Anlauf-Dunn, K., Jacobsen, P. S., Strickland, M., Tennant, L.,
and Tippery, S. E.: Effectiveness of Instream Wood Treatments to Restore
Stream Complexity and Winter Rearing Habitat for Juvenile Coho Salmon,
T. Am. Fish. Soc., 143, 334–345, 2014.Kafle, M. and Shakya, N.: Two-Dimensional Hydrodynamic Modelling of Koshi
River and Prediction of Inundation Parameters, Hydrology: Current
Research, 9, 298, 10.4172/2157-7587.1000298, 2018.
Kail, J.: Influence of large woody debris on the morphology of six central
European streams, Geomorphology, 51, 207–223, 2003.
Katz, S. B., Segura, C., and Warren, D. R.: The influence of channel bed
disturbance on benthic Chlorophyll a: A high resolution perspective,
Geomorphology, 305, 141–153, 2018.Kean, J. W. and Smith, J. D.: Form drag in rivers due to small-scale natural
topographic features: 1. Regular sequences, J. Geophys. Res.-Earth, 111, F04009, 10.1029/2006JF000467, 2006.
Lai, Y., Smith, D., Bandrowski, D., Liu, X., and Wu, K.: Three Dimensional
Computational Modeling of Flows through an Engineered Log Jam, World
Environmental and Water Resources Congress 2017, Sacramento, California, 16–23, 2017.
Laliberte, J. J., Post, J. R., and Rosenfeld, J. S.: Hydraulic geometry and
longitudinal patterns of habitat quantity and quality for rainbow trout
(Oncorhynchus mykiss), River Res. Appl., 30, 593–601, 2014.
Lee, J. H., Kil, J. T., and Jeong, S.: Evaluation of physical fish habitat
quality enhancement designs in urban streams using a 2-D hydrodynamic model,
Ecol. Eng., 36, 1251–1259, 2010.
Lisle, T. E.: Stabilization of a gravel channel by large streamside
obstructions and bedrock bends, Jacoby Creek, northwestern California, GSA
Bulletin, 97, 999–1011, 1986.
Lisle, T. E. and Lewis, J.: Effects of sediment transport on survival of
salmonid embryos in a natural stream – A simulation approach, Can. J. Fish. Aquat. Sci., 49, 2337–2344, 1992.
Lisle, T. E., Nelson, J. M., Pitlick, J., Madej, M. A., and Barkett, B. L.:
Variability of bed mobility in natural, gravel-bed channels and adjustments
to sediment load at local and reach scales, Water Resour. Res., 36,
3743–3755, 2000.Manners, R. B., Doyle, M. W., and Small, M. J.: Structure and hydraulics of
natural woody debris jams, Water Resour. Res., 43, W06432, 10.1029/2006WR004910, 2007.
McMahon, T. E. and Hartman, G. F.: Influence of Cover Complexity and Current
Velocity on Winter Habitat Use by Juvenile Coho Salmon (Oncorhynchus
kisutch), Can. J. Fish. Aquat. Sci., 46, 1551–1557,
1989.Merten, E., Finlay, J., Johnson, L., Newman, R., Stefan, H., and Vondracek,
B.: Factors influencing wood mobilization in streams, Water Resour. Res.,
46, W10514, 10.1029/2009WR008772, 2010.
Montgomery, D. R. and Buffington, J. M.: Channel-reach morphology in
mountain drainage basins, Geol. Soc. Am. Bull., 109,
596–611, 1997.
Montgomery, D. R., Buffington, J. M., Smith, R. D., Schmidt, K. M., and
Pess, G.: Pool Spacing in Forest Channels, Water Resour. Res., 31,
1097–1105, 1995.
Mueller, E. R. and Pitlick, J.: Sediment supply and channel morphology in
mountain river systems: 2. Single thread to braided transitions, J. Geophys. Res.-Earth, 119, 1516–1541, 2014.Mueller, E. R., Pitlick, J., and Nelson, J. M.: Variation in the reference
shields stress for bed load transport in gravel-bed streams and rivers,
Water Resour. Res., 41, W04006, 10.1029/2004WR003692, 2005.Mutz, M., Kalbus, E., and Meinecke, S.: Effect of instream wood on vertical
water flux in low-energy sand bed flume experiments, Water Resour. Res., 43, W10424, 10.1029/2006WR005676, 2007.
Nagaya, T., Shiraishi, Y., Onitsuka, K., Higashino, M., Takami, T., Otsuka,
N., Akiyama, J., and Ozeki, H.: Evaluation of suitable hydraulic conditions
for spawning of ayu with horizontal 2-D numerical simulation and PHABSIM,
Ecol. Model., 215, 133–143, 2008.
Nelson, J. M., Shimizu, Y., Abe, T., Asahi, K., Gamou, M., Inoue, T.,
Iwasaki, T., Kakinuma, T., Kawamura, S., Kimura, I., Kyuka, T., McDonald, R.
R., Nabi, M., Nakatsugawa, M., Simões, F. R., Takebayashi, H., and
Watanabe, Y.: The international river interface cooperative: Public domain
flow and morphodynamics software for education and applications, Adv. Water Res., 93, 62–74, 2016.
Nicholas, A. P.: Investigation of spatially distributed braided river flows
using a two-dimensional hydraulic model, Earth Surf. Proc. Land., 28, 655–674, 2003.
Nickelson, T. E. and Lawson, P. W.: Population viability of coho salmon,
Oncorhynchus kisutch, in Oregon coastal basins: application of a
habitat-based life cycle model, Can. J. Fish. Aquat. Sci., 55, 2383–2392, 1998.
Nickelson, T. E., Rodgers, J. D., Johnson, S. L., and Solazzi, M. F.:
Seasonal-changes in habitat use by juvenile coho salmon
(Oncorhynchus-kisutch) in Oregon Coastal Streams, Can. J. Fish. Aquat. Sci., 49, 783–789, 1992a.
Nickelson, T. E., Solazzi, M. F., Johnson, S. L., and Rodgers, J. D.:
Effectiveness of Selected Stream Improvement Techniques to Create Suitable
Summer and Winter Rearing Habitat for Juvenile Coho Salmon (Oncorhynchus
kisutch) in Oregon Coastal Streams, Can. J. Fish. Aquat. Sci., 49, 790–794, 1992b.
NMFS: (National Marine Fisheries Service) Recovery Plan for Oregon Coast
CohoSalmon Evolutionarily Significant Unit, National Marine Fisheries
Service, West Coast Region, Portland, Oregon, 2016.
Paola, C.: Incoherent structures: turbulence as a metaphor for stream
braiding, in: Coherent Flow Structures in Open Channels, edited by: Ashworth, P. J., Bennett, S. J., Best, J. L., and McLelland, S. J., John Wiley & Sons, Ltd, Chichester, 1996.
Pess, G. R., Liermann, M. C., McHenry, M. L., Peters, R. J., and Bennett, T.
R.: Juvenile salmon response to the placement of engineered log jams (eljs)
in the Elwha River,Washington State, USA, River Res. Appl.,
28, 872–881, 2012.
Quinn, T. P. and Peterson, N. P.: The influence of habitat complexity and
fish sire on over-winter survival and growth of individually marked juvenile
coho salmon (Oncorhynchus kisutch) in Big Beef creek, Washington, Can. J. Fish. Aquat. Sci., 53, 1555–1564, 1996.
Rimmer, D. M., Paim, U., and Saunders, R. L.: Autumnal Habitat Shift of
Juvenile Atlantic Salmon (Salmo salar) in a Small River, Can. J. Fish. Aquat. Sci., 40, 671–680, 1983.
Roni, P. and Quinn, T. P.: Density and size of juvenile salmonids in
response to placement of large woody debris in western Oregon and Washington
streams, Can. J. Fish. Aquat. Sci., 58, 282–292,
2001.
Roni, P., Hanson, K., and Beechie, T.: Global review of the physical and
biological effectiveness of stream habitat rehabilitation techniques, N. Am. J. Fish. Manage., 28, 856–890, 2008.
Roni, P., Beechie, T., Pess, G., and Hanson, K.: Wood placement in river
restoration: fact, fiction, and future direction, Can. J. Fish. Aquat. Sci., 72, 466–478, 2014.
Rosenberger, A. E. and Dunham, J. B.: Validation of Abundance Estimates from
Mark–Recapture and Removal Techniques for Rainbow Trout Captured by
Electrofishing in Small Streams, N. Am. J. Fish. Manage., 25, 1395–1410, 2005.
Ruiz Villanueva, V., Bladé Castellet, E., Díez-Herrero, A.,
Bodoque, J. M., and Sánchez-Juny, M.: Two-dimensional modelling of large
wood transport during flash floods, Earth Surf. Proc. Land.,
39, 438–449, 2014.
Ruiz-Villanueva, V., Wyżga, B., Zawiejska, J., Hajdukiewicz, M., and
Stoffel, M.: Factors controlling large-wood transport in a mountain river,
Geomorphology, 272, 21–31, 2016.
Scheingross, J. S., Winchell, E. W., Lamb, M. P., and Dietrich, W. E.:
Influence of bed patchiness, slope, grain hiding, and form drag on gravel
mobilization in very steep streams, J. Geophys. Res.-Earth, 118, 982–1001, 2013.
Sedell, J. R., Bisson, P. A., Swanson, F. J., and Gregory, S. V.: What we
know about large trees that fall into streams and rivers, in: From the
forest to the sea: a story of fallen trees, edited by: Maser, C., Tarrant, R. F.,
Trappe, J. M., and Franklin, J. F., U.S. Department of Agriculture,
Forest Service, Pacific Northwest Research Station, U.S. Department of the
Interior, Bureau of Land Management, Portland, OR, 1988.Segura, C. and Pitlick, J.: Coupling fluvial-hydraulic models to predict
gravel transport in spatially variable flows, J. Geophys. Res.-Earth,
120, 834–855, 10.1002/2014JF003302, 2015.Seo, J. I., Nakamura, F., Nakano, D., Ichiyanagi, H., and Chun, K. W.:
Factors controlling the fluvial export of large woody debris, and its
contribution to organic carbon budgets at watershed scales, Water Resour.
Res., 44, W04428, 10.1029/2007WR006453, 2008.
Shen, Y. and Diplas, P.: Application of two- and three-dimensional
computational fluid dynamics models to complex ecological stream flows,
J. Hydrol., 348, 195–214, 2008.Shimizu, Y., Takebayashi, H., Inoue, T., Hamaki, M., Iwasaki, T.,
and Nabi, M.: Nays2DH solver manual, available at: http://i-ric.org/en (last access: August 2019), 2014.
Smith, R. D., Sidle, R. C., and Porter, P. E.: Effects on bedload transport
of experimental removal of woody debris from a forest gravel-bed stream,
Earth Surf. Proc. Land., 18, 455–468, 1993a.
Smith, R. D., Sidle, R. C., Porter, P. E., and Noel, J. R.: Effects of
experimental removal of woody debris on the channel morphology of a forest,
gravel-bed stream, J. Hydrol., 152, 153–178, 1993b.Smith, S. M. and Prestegaard, K. L.: Hydraulic performance of a
morphology-based stream channel design, Water Resour. Res., 41, W11413, 10.1029/2004WR003926, 2005.
Stednick, J. D.: Hydrological and biological responses to forest practices:
the Alsea Watershed study, Springer, New York, 2008.
Suring, E., Constable Jr., R. J., Lorion, C. M., Miller, B. A., and Wiley, D. J.: Salmonid life cycle monitoring in western Oregon streams, 2009–2011,
Monitoring Program Report Number OPSW-ODFW-2012-2, Oregon Department of Fish and Wildlife, Salem, OR, 2012.
Swales, S. and Levings, C. D.: Role of Off-Channel Ponds in the Life Cycle
of Coho Salmon (Oncorhynchus kisutch) and Other Juvenile Salmonids in the
Coldwater River, British Columbia, Can. J. Fish. Aquat. Sci., 46, 232–242, 1989.
Takebayashi, H., Egashira, S., and Okabe, T.: Numerical analysis of braided
streams formed on beds with non-uniform sediment,
Proceedings of hydraulic engineering, 47, 631–636, 2003.
Tamminga, A. D., Eaton, B. C., and Hugenholtz, C. H.: UAS-based remote
sensing of fluvial change following an extreme flood event, Earth Surf. Proc. Land., 40, 1464–1476, 2015.
Taylor, E. B. and McPhail, J. D.: Variation in Burst and Prolonged Swimming
Performance Among British Columbia Populations of Coho Salmon, Oncorhynchus
kisutch, Can. J. Fish. Aquat. Sci., 42, 2029–2033,
1985.
Thompson, D. M. and Fixler, S. A.: Formation and maintenance of a forced
pool-riffle couplet following loading of large wood, Geomorphology, 296,
74–90, 2017.
Triska, F. J. and Cromack Jr., K.: The role of wood debris in forests and
streams, in: Forests: fresh perspectives from ecosystem analysis,
Proceedings of the 40th Annual Biology Colloquium, Press, edited by: Waring, R. H., Oregon State University Press, Corvallis, OR, 1980.
Tschaplinski, P. J. and Hartman, G. F.: Winter Distribution of Juvenile Coho
Salmon (Oncorhynchus kisutch) Before and After Logging in Carnation Creek,
British Columbia, and Some Implications for Overwinter Survival, Can. J. Fish. Aquat. Sci., 40, 452–461, 1983.
Venter, O., Grant, J. W. A., Noël, M. V., and Kim, J.-W.: Mechanisms
underlying the increase in young-of-the-year Atlantic salmon (Salmo salar)
density with habitat complexity, Can. J. Fish. Aquat. Sci., 65, 1956–1964, 2008.
Wall, C. E., Bouwes, N., Wheaton, J. M., Bennett, S. N., Saunders, W. C.,
McHugh, P. A., and Jordan, C. E.: Design and monitoring of woody structures
and their benefits to juvenile steelhead (Oncorhynchus mykiss) using a net
rate of energy intake model, Can. J. Fish. Aquat. Sci., 74, 727–738, 2016.
Whiteway, S. L., Biron, P. M., Zimmermann, A., Venter, O., and Grant, W. A.:
Do in-stream restoration structures enhance salmonid abundance? A
meta-analysis, Can. J. Fish. Aquat. Sci., 67,
831–841, 2010.
Wilcock, P. R. and McArdell, B. W.: Surface-based fractional transport rates
– mobilization thresholds and partial transport of a sand-gravel sediment,
Water Resour. Res., 29, 1297–1312, 1993.
Wipfli, M. S., Richardson, J. S., and Naiman, R. J.: Ecological linkages
between headwaters and downstream ecosystems: Transport of organic matter,
invertebrates, and wood down headwater channels, J. Am. Water Resour.
Assoc., 43, 72–85, 2007.Wohl, E. and Jaeger, K.: A conceptual model for the longitudinal
distribution of wood in mountain streams, Earth Surf. Proc. Land., 34, 329–344, 2009.
Wohl, E. and Scott, D. N.: Wood and sediment storage and dynamics in river
corridors, Earth Surf. Proc. Land., 42, 5–23, 2017.
Wolman, M. G.: A method of sampling coarse river bed material, Transactions
of the American Geophysical Union, 35, 951–956, 1954.
Xu, Y. and Liu, X.: 3D computational modeling of stream flow resistance due
to large woody debris, in: River Flow – Proceedings of the International Conference on Fluvial Hydraulics, RIVER FLOW 2016, CRC Press/Balkema, 2346–2353, 2016.
Xu, Y. and Liu, X.: Effects of Different In-Stream Structure Representations
in Computational Fluid Dynamics Models – Taking Engineered Log Jams (ELJ) as
an Example, Water, 9, 110, 2017.
Yabe, T., Ishikawa, T., Kadota, Y., and Ikeda, F.: A Multidimensional
Cubic-Interpolated Pseudoparticle (CIP) Method without Time Splitting
Technique for Hyperbolic Equations, J. Phys. Soc. Jpn., 59, 2301–2304, 1990.Yager, E. M., Kirchner, J. W., and Dietrich, W. E.: Calculating bed load
transport in steep boulder bed channels, Water Resour. Res., 43, W07418, 10.1029/2006WR005432, 2007.