Application of the CONCEPTS Channel Evolution Model
in Stream Restoration Strategies
Eddy J. Langendoen
National Sedimentation Laboratory, Agricultural Research Service, USDA, Oxford, Mississippi, USA
The series of biennial U.S. National Water Quality Inventory surveys show no
reduction in the percentage of degraded miles of streams since the early 1990s
despite an exponential increase in river restoration projects to improve water
quality, enhance in-stream habitat, and manage the riparian zone. This may suggest
that many river restoration projects fail to achieve their objectives and could
therefore benefit from using proven models of stream and riparian processes to
guide restoration design and to evaluate indicators of ecological integrity. The U.S.
Department of Agriculture has developed two such models: the channel evolution
computer model CONCEPTS and the riparian ecosystem model REMM. CONCEPTS is a robust computational model for simulating the long-term evolution of
incised and restored or rehabilitated stream corridors. REMM is a computational
model for evaluating management decisions to control nonpoint source pollution in
the riparian zone. These models have been integrated to evaluate the impact of
in-stream, edge-of-field, and riparian conservation measures on stream morphology
and water quality. This chapter presents how in-stream restoration measures are
represented in CONCEPTS. Further, the capabilities of CONCEPTS and REMM
are demonstrated through model applications that evaluate the long-term stability
of newly constructed channels, the impact of bank protection on downstream
sediment loads and streambed composition, and the effectiveness of woody and
herbaceous riparian buffers in controlling stream bank erosion of an incised stream.
1. INTRODUCTION
The rapid increase in number of stream restoration projects
in the United States over the last two decades [Bernhardt et
al., 2005] has not led to a reduction in miles of streams
impaired by sediment [U.S. Environmental Protection Agency,
1994, 1995, 1997, 2000, 2002, 2007]. Because only 564,000
(16%) of total U.S. stream miles are assessed, it is likely that
the impact of the documented restoration projects on the
Stream Restoration in Dynamic Fluvial Systems: Scientific
Approaches, Analyses, and Tools
Geophysical Monograph Series 194
This paper is not subject to U.S. copyright.
Published in 2011 by the American Geophysical Union.
10.1029/2010GM000986
assessment is limited. Nevertheless, many restoration projects
fail to achieve their objectives. According to Palmer and Allan
[2006], this is due to the lack of policies to support restoration
standards, to promote proven methods, and to provide basic
data needed for planning and implementation.
A common reason of restoration project failure is to only
focus on the reach to be restored and thereby ignoring its
location within the watershed [Palmer and Allan, 2006]. As
a consequence, projects often are exposed to flow and sediment regimes different from those used in the design phase
resulting in possible flooding, bank collapse, or excessive
scour and fill of the stream bed. Palmer et al. [2005] recommend the use of proven models of in-stream and riparian
processes not only to guide the design of restoration projects
but also to assess, both pre- and postproject, indicators of
ecological integrity. The U.S. Department of Agriculture
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
(USDA) has developed various computer models to evaluate
the effects of hillslope (upland) and in-stream restoration
measures on stream morphology, downstream sediment
loads, and to predict key attributes of stream corridors known
to control physical habitat quality, such as base flow statistics, water temperature, bed material composition, and large
wood density [Shields et al., 2006]. Two of these models,
CONCEPTS [Langendoen and Alonso, 2008; Langendoen
and Simon, 2008] and REMM [Altier et al., 2002], simulate
in-stream and riparian physical processes at the streamcorridor scale. CONCEPTS and REMM have been shown to
successfully simulate the effects of conservation measures
on the transport of water and sediment within a stream and
riparian zone [e.g., Lowrance et al., 2000; Wells et al., 2007;
Langendoen et al., 2009b] and therefore form a proven
method to assess the impact of stream restoration strategies
on channel morphology. A third model, BSTEM, simulates
the effects of restoration measures on sediment loadings
from stream banks at individual cross sections and is discussed elsewhere in this book [Simon et al., this volume].
This chapter presents: (1) an overview of the CONCEPTS
and REMM models, (2) guidelines for evaluating stream
restoration measures using CONCEPTS, and (3) a range of
applications to demonstrate the capabilities of the CONCEPTS and REMM models.
2. SIMULATION OF STREAM CORRIDOR
PHYSICAL PROCESSES
2.1. Simulated Processes
Restoration of the functions of a stream is needed when a
natural reequilibration either is not physically possible or is
very slow. The complex dynamics of physical and ecological
processes and their interactions make designing effective
restoration practices difficult. Computer models that can
properly simulate these processes can guide professionals in
the planning and design phases of restoration practices. The
discussion below of the CONCEPTS and REMM models is
limited to the simulation of physical processes that affect
stream morphology. However, these models can be used to
calculate indicators that assist in ecological restoration
[Shields et al., 2006].
The forces acting on the stream boundary and the resistance
to erosion of the boundary materials govern stream morphology. In general, the force exerted by the flowing water on the
channel boundary depends on flow velocity distribution and
boundary roughness. The resistance to erosion is a function
of boundary material properties such as texture, density, erodibility, and shear strength. These properties are significantly
affected by the presence of riparian vegetation. Stream resto-
ration measures are designed to affect both the forces exerted
by the flow (e.g., lowering near bank velocities) and the
resistance to erosion of the channel boundary (e.g., reducing
its erodibility). The CONCEPTS and REMM computer
models simulate these processes and their controls. The
following sections very briefly discuss the science included
in the models and their integration. More details are given by
Altier et al. [2002], Langendoen and Alonso [2008], Langendoen and Simon [2008], and Langendoen et al. [2009a].
2.2. CONCEPTS: Computer Model of In-Stream Processes
The CONCEPTS computer model has been developed to
simulate the evolution of incised streams and to evaluate the
long-term impact of rehabilitation measures to stabilize
stream systems and reduce sediment yield [Langendoen and
Alonso, 2008; Langendoen and Simon, 2008]. CONCEPTS
simulates unsteady, one-dimensional (1-D) flow, graded sediment transport, and bank erosion processes in stream corridors. It can predict the dynamic response of flow and
sediment transport to in-stream structures.
2.2.1. Hydraulics. CONCEPTS models streamflow as 1-D
along the channel’s centerline. Hence, it is limited to fairly
straight channels; it cannot predict bar formation and channel
migration. CONCEPTS simulates gradually varying flow
(described by the Saint-Venant equations) as a function of
time along a series of cross sections representing stream and
floodplain geometry. The governing system of equations are
solved using the generalized Preissmann scheme, allowing a
variable spacing between cross sections and large time steps
conducive to long-term simulations of channel evolution.
The implementation of the solution method contains various
enhancements to improve the robustness of the model, particularly for flashy runoff events.
2.2.2. Sediment transport and bed adjustment. Alluvial
stream banks are typically composed of fine-grained deposits
containing clays, silts, and fine sands (hereafter referred to as
fines), which may overlay coarser relic point bars. Streambeds are more commonly composed of sands and gravels,
resistant clay layers, or bed rock. Therefore, the range in
particle sizes being transported in alluvial streams may be
quite large, and the composition of the sediment mixture in
transport may be quite different from that of the bed material
if a majority of the sediments are fines transported in suspension. CONCEPTS therefore calculates sediment transport
rates by size fraction for 14 predefined sediment size classes
ranging from 10 μm to 64 mm.
CONCEPTS uses a total-load evaluation of bed material
transport and treats movement of clays and fine silts (<10 μm)
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as pass-through background wash load. The differences in
transport mechanics of suspended and bed load movement
are accounted for through nonequilibrium effects. The composition of bed surface and substrate is tracked, enabling the
simulation of vertical and longitudinal fining or coarsening
of the bed material.
2.2.3. Stream bank erosion. CONCEPTS simulates channel width adjustment by incorporating the two fundamental
physical processes responsible for bank retreat: fluvial erosion or entrainment of bank material particles by flow and
bank mass failure due to gravity. Bank material may be
cohesive or noncohesive and may comprise numerous soil
layers.
The detachment of cohesive soils is calculated following
an excess shear-stress approach. An average shear stress on
each soil layer is computed. If the critical shear stress of the
material is exceeded, entrainment occurs. CONCEPTS is
able to simulate the development of overhanging banks.
Stream bank failure occurs when gravitational forces that
tend to move soil downslope exceed the forces of friction and
cohesion that resist movement. The risk of failure is expressed by a factor of safety, defined as the ratio of resisting
to driving forces or moments. CONCEPTS performs stability
analyses of wedge-type failures and cantilever failures of
overhanging banks. The effects of pore water pressure and
confining pressure exerted by the water in the stream are
accounted for.
2.3. REMM: Computer Model of Riparian Processes
REMM has been developed as a tool to aid natural resource agencies and others in making decisions regarding
management of riparian buffers to control nonpoint source
pollution [Altier et al., 2002]. The structure of REMM is
consistent with buffer system specifications recommended
by the U.S. Forest Service and the USDA Natural Resources
Conservation Service as national standards [Welsch, 1991].
The specified riparian buffer system consists of three zones
parallel to the stream, representing increasing levels of management away from the stream. Although REMM is designed to simulate this type of buffer system, the model can
be used with different types of vegetation within each zone.
Processes simulated in REMM include storage and movement of surface and subsurface water, sediment transport and
deposition, transport, sequestration, and cycling of nutrients,
and vegetative growth.
2.3.1. Hydrology. Water movement and storage is characterized by processes of interception, evapotranspiration (ET),
infiltration, vertical drainage, surface runoff, subsurface lat-
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eral flow, upward flux from the water table in response to ET,
and seepage. The storage and movement of water between
the zones is based on a combination of mass balance and
rate-controlled approaches. Vertical drainage from a soil
layer occurs when soil water content exceeds the field capacity. The amount drained from a soil layer also depends on
the capacity of the receiving layer and is set equal to the
lesser of the hydraulic conductivities of the draining and
receiving layers. When a shallow groundwater table is present, soil water content above the groundwater table is assumed to be in equilibrium with the water table. The matric
potential or pressure head is approximated by the height
above the water table. Soil water content is related to pressure head using Campbell’s equations [Campbell, 1974].
Subsurface lateral movement is assumed to occur when a
water table builds up over the restricting soil layer. The
lateral water movement is simulated using Darcy’s equation.
Rates of lateral subsurface movement between zones are
constrained by the lesser of the respective hydraulic conductivities of the soil layers in each zone. If rates of soil water
movement for the upslope zone exceed the transmission rates
for the downslope zone, the soil water excess is accumulated
in the upslope zone until it is saturated. A seep will then occur
to the surface of the downslope zone.
2.3.2. Plant growth. REMM simulates the growth of several types of herbaceous and woody vegetation in two canopy layers for even-aged forest stands. Individual species
present in a particular buffer system may be characterized
through the parameterization of various variables, which
represent values for the initial sizes of the plants, rates of
photosynthesis, respiration requirements, rates of growth and
mortality, sensitivity to light and temperature, response to
nutrients, and timing of phenostages.
2.4. CONCEPTS-REMM Integration
The physical process modules of CONCEPTS and REMM
have been integrated to study the interactions between
in-stream and riparian processes. A daily feedback of several
parameters has been established to calculate: (1) daily stream
loadings of water, sediments, and nutrients emanating from
the riparian buffer; (2) effects of water surface elevation
on soil water in the riparian zone (seepage and recharge);
(3) effects of pore water pressure and root biomass on
stream bank stability; and (4) in case of bank failure, stream
loadings of sediments, nutrients, and plant/tree biomass
contained by the failure block.
The bank stability analysis performed by CONCEPTS
accounts for soil water content and root biomass in the bank.
The groundwater table and vertical distribution of soil water
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
computed by REMM in the zone nearest to the channel are
used to calculate pore water pressure. The pore water pressure is assumed hydrostatic below the groundwater table.
Soil water content above the groundwater table is converted
to suction values using Campbell’s [1974] equation. The
mechanical effect of roots is to enhance the confining stress
and resistance to sliding and increase the shear strength of the
soil/root mass through the binding action of roots in the fiber/
soil composite [e.g., Coppin and Richards, 1990; Gray and
Sottir, 1996]. The vertical distribution of root biomass concentration calculated by REMM is converted to a root-arearatio (RAR) and used to modify soil shear-strength using Wu
et al.’s [1979] equation.
3. INPUT DATA REQUIREMENTS
3.1. CONCEPTS
CONCEPTS uses two types of input data: (1) input data
that control the execution of the model (e.g., simulation start
and end dates, simulated processes, and requested output)
and (2) input data that characterize the modeled stream
corridor. Different data are required to perform hydraulic
routing, sediment routing, and stream bank erosion
calculations.
To perform hydraulic routing the channel and floodplain
geometry are required and are represented by a series of cross
sections. These data are typically obtained through channel
surveys using standard methods such as level or total station.
Flow resistance is parameterized using the Manning n friction factor. The user can input different Manning n values for
streambed, left and right banks, and left and right floodplains. Manning n values are reported in literature and can
be calibrated using observed water surface profiles or flow
depths. Discharge has to be specified at the inlet of the study
reach and at tributary inflow points. Time series of discharges
can be obtained through measurements or generated using
hydrologic computer models. A boundary condition at the
model outlet is optional. The model calculates a looped
rating curve internally based on local flow conditions. However, if water level at the downstream boundary is controlled
externally, the user can specify a rating curve or a time series
of water level elevation.
To simulate sediment transport and bed adjustment initial
bed material stratigraphy with grain size distribution and
porosity for each stratigraphic layer is required. Bed material
can vary along the stream but is assumed homogeneous
across the stream. Bed material gradation can be determined
by sampling the bed material. Entrainment of cohesive, finegrained bed material is calculated using an excess shear-stress
approach that requires the specification of a critical shear
stress below which no erosion takes place and an erosion rate
or erodibility coefficient that represents the rate at which the
cohesive bed material is eroded once the critical shear stress is
exceeded. The resistance to erosion can be measured in situ
using portable flumes or jet testers, or samples can be collected
and tested in laboratory settings using annular flumes or
flumes such as the Erosion Function Apparatus [Briaud et al.,
2001]. At inflow locations, fractional sediment transport rates
have to be specified, which can be either measured or calculated using sediment transport relations.
Stream bank erosion calculations require the specification
of bank material stratigraphy, with its associated grain-size
distributions, bulk density, resistance to erosion (critical
shear stress and erosion-rate coefficient) values, and shearstrength (cohesion and friction angle) values. Most properties can be measured by collecting samples and consequent
laboratory analysis. Resistance to erosion and shear strength
properties can also be measured in situ using jet test and
borehole shear test devices, respectively.
Validation and applications of CONCEPTS [e.g., Wells
et al., 2007; Langendoen and Alonso, 2008; Langendoen
and Simon, 2008; Langendoen et al., 2009a, 2009b] showed
that it can satisfactorily predict and quantify (a) the temporal
progression of an incised stream through the different stages
of channel evolution, (b) changes in thalweg elevation,
(c) changes in channel top width, and (d) bed material grain
size distribution. However, bed and bank material properties
representing resistance to erosion and failure must be adequately characterized. It is highly recommended to perform a
geomorphic analysis of the stream system to determine channel conditions and variations in sediments and soils along the
stream. Such an analysis could be performed using the Rapid
Geomorphic Assessment technique [e.g., Simon et al., 2002].
Differences between observed and simulated evolution are
commonly largest along reaches where either model assumptions regarding flow and sediment transport (e.g., 1-D
assumption) are inappropriate, as is the case in the late stages
of channel adjustment, or assumptions regarding input data
(e.g., channel geometry, water inflows, or bed and bank
material properties) are required. The use of median and
average values of critical shear stresses and effective cohesion generally provide good results. Because critical shear
stresses typically vary greatly both between different soils
and within a soil, users of the model should measure an
adequate number of critical shear stress values for each soil
in the bed and banks.
3.2. REMM
REMM’s input data are related to model execution, the
physical description of the riparian buffer, and boundary
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conditions such as weather and upland inputs. The buffer
characteristics comprise its physical dimensions (length,
width, slope, etc.), the fraction of the area covered by vegetation, and physical descriptors of litter and soil layers (such
as initial carbon and nutrient levels, and hydrologic properties). Vegetation data includes information on the plant,
factors related to photosynthesis, transpiration characteristics, nutrient content of plant part pools, and the initial size of
the plants. Regional databases are available that describe
typical plant characteristics for various species.
Daily weather input consists of rainfall amount and duration, minimum and maximum air temperature, incoming
solar radiation, and wind velocity. Gridded data sets, such
as VEMAP (http://www.cgd.ucar.edu/vemap/V2.html), are
available that cover the United States if these data are not
available from nearby weather stations. Daily field inputs
include surface runoff and subsurface drainage volumes and
associated eroded soil material, inorganic and organic materials, and plant nutrients.
Calibration and testing procedures of the REMM submodels are reported in the works of Altier et al. [1998], Bosch et
al. [1998], and Inamdar et al. [1998a, 1998b].
4. IMPLEMENTATION OF RESTORATION MEASURES
This section describes how in-stream and riparian restoration measures can be represented in CONCEPTS. CONCEPTS is capable of evaluating restoration measures at
individual cross sections and along entire reaches. This
allows, for example, the determination of restoration measure placement or the length of protection needed. It should
be noted that because CONCEPTS is a 1-D model, it cannot
simulate the complex 3-D flow near in-stream structures and
the resulting local channel morphology. The 3-D effects are
averaged over the distance between two consecutive cross
sections. However, a 1-D approach can adequately assess
the long-term impact of restoration measures on channel
stability.
491
elevation can be set to the level of the bed surface at the
cross section with the grade control structure. This will
prevent erosion below this elevation. Deposition is possible,
and the deposited material can be eroded in the future, but the
extent of erosion is then limited to the top of the grade
control structure.
The second method uses a drop structure element in CONCEPTS. This method should be used if the drop in bed
elevation at the structure is significant. In this case, free-fall
conditions cause a significant energy head loss that may not
be simulated adequately by the above method. This method
simulates both free fall and drowned conditions at drop
structures. Bed load will be captured by the structure as long
as its invert exceeds the upstream bed elevation. Once bed
elevation exceeds structure invert, all sediment will pass the
structure and no further deposition will occur upstream of the
structure. The drop structure geometry is limited to a symmetrical trapezoidal cross section with a horizontal bottom.
4.2. Stream Bank Restoration Measures
Stream bank restoration practices can be placed anywhere
on the bank by introducing layers that represent the erodibility of the stabilization measure (Figure 1). Hence, these bank
protection measures could cover the toe only or protect the
entire bank face. Similarly, the effects of riparian vegetation
on top of the bank on stream bank erosion can be evaluated
using different soil layers.
4.1. Streambed Restoration Measures
Streambed restoration measures are typically employed to
stabilize the streambed and control channel grade. Common
grade control measures are sills or drop structures that can be
constructed of large stones, logs, or sheet pile weirs.
There are two methods to evaluate grade control measures
using CONCEPTS. Both methods assume that the grade
control measures are stable under the full range of imposed
flow conditions. First, if the designed drop in bed elevation at
the structure is rather small, such that the flow drowns the
structure for medium to large runoff events, the bedrock
Figure 1. Use of soil layers to characterize stream bank protection
and stabilization measures in CONCEPTS. The shown stream bank
comprises four soil layers and three soils. The top layer is the
unmodified soil with an increased cohesion value representing the
added reinforcement provided by the tree roots and a reduced
erodibility coefficient. The third layer is the unmodified soil with
an increased critical shear stress value and reduced erodibility
coefficient representing the resistance to fluvial erosion provided
by the rock serving as toe protection.
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
4.2.1. Protection against fluvial erosion. A bank material
must be introduced to represent the protected portion of the
bank. The critical shear stress and erodibility coefficient for
this bank material layer should characterize the resistance to
erosion of the stream bank protection measure. For example,
the critical shear stress could be set to the allowable shear
stress used in tractive channel design. The Natural Resources
Conservation Service [2007, Chapter 8] tabulates allowable
shear stress values for many bank protection measures.
A number of protection measures, for example, vegetation, root wads, or vanes, deflect the flow away from the
bank thereby reducing shear stresses exerted by the flow,
which cannot be simulated accurately by a 1-D model such
as CONCEPTS. However, this could be represented by an
equivalent increase in critical shear stress of the affected
bank soils.
4.2.2. Bank stabilization measures. Bank stabilization
measures typically enhance soil shear strength. This could
be done, for example, by improving drainage or by mechanical reinforcement provided by roots of riparian vegetation.
The vertical distribution of root biomass of riparian vegetation is represented by introducing bank material layers with
varying cohesion values. The Riproot model of Pollen-Bankhead and Simon [2009] can be used to calculate the added
cohesion due to plant roots.
5. MODEL APPLICATION
This section presents three sample applications in which
the CONCEPTS model was used to assess the performance
of stream restoration measures at the stream corridor scale.
The first application evaluates the long-term stability of a
channel constructed within a reservoir deposit to minimize
bank erosion and downstream sediment load. In the second
example, CONCEPTS is used to assess the impact of urbanization on channel morphology and the potential benefits of
stream bank protection measures. The last example presents
the capabilities of the combined CONCEPTS and REMM
model to evaluate vegetative riparian management strategies.
5.1. Kalamazoo River Dam Removal
5.1.1. History. Between the mid-1800s and the early
1900s, four dams were constructed on the Kalamazoo River
between Plainwell and Allegan, Michigan. The impoundments have been the depositories of upstream sediment and
industrial waste materials containing polychlorinated biphenyl (PCB) and kaolinite clays. During the 1960s, water levels
behind the decommissioned hydroelectric dams were lowered, exposing the previously inundated material. In response
to the lowering of water levels, the river began to erode the
sediments and transport them downstream, but much of this
waste clay remains impounded behind the dams mainly as
floodplain deposits [Rheaume et al., 2002, 2004]. The state
of Michigan is interested in removing the dams while minimizing impacts locally and to downstream reaches, and to
provide for improved fisheries. CONCEPTS was used to
simulate sediment loadings from PCB-contaminated stream
banks and channel changes for a section between Plainwell
and Otsego, which contains the Plainwell and Otsego City
Dams, under three different scenarios: (1) dams in (DI) or
baseline, (2) dams out (DO), and (3) design (D). The design
scenario evaluates a redesigned stream-riparian corridor to
minimize the adverse local and downstream impacts of the
dam removal.
5.1.2. Study reach. The study reach of the Kalamazoo
River is 8.8 km long, from river kilometer (rkm) 82.4
(cross-section OC8), to cross-section P3, at rkm 91.2 (Figure 2). The model of the study reach is composed of 52 cross
sections and contains both Plainwell and Otsego City Dams.
The Plainwell Dam is 172 ft (52.4 m) wide and 14 ft (4.3 m)
high. The Otsego City Dam is 151 ft (46.0 m) wide and 13 ft
(4.0 m) high. The study reach can be separated into three
distinct subreaches based on location relative to the Plainwell
and Otsego City Dams. The Otsego (OC) reach extends from
rkm 82.4 to the Otsego City Dam at rkm 85.3. The PlainwellOtsego (POC) reach extends from the upstream end of the
Otsego City Dam to the Plainwell Dam at rkm 88.3. The
Plainwell reach extends from the Plainwell Dam to the upstream boundary of the study reach at rkm 91.2.
5.1.3. Input data. Flows for all three simulation scenarios
are based on a 17.7 year discharge record (October 1984 to
June 2002) from the USGS gauge on the Kalamazoo River at
Comstock, Michigan (04106000). The 17.7 year flow record
was created using daily data from 1984 to 1989 and hourly
data from 1989 to June 2002 to account for changing hydraulic conditions and instantaneous peaks. The Gunn River
flows into the POC section of the study reach from the north
between cross-sections G5 and G6 (Figure 2). Because there
is no flow data for this tributary, the flow from the Gunn
River (296 km2) was estimated using a drainage area comparison with the flow record from the Kalamazoo River at
Comstock (04106000; 2740 km2). Given the respective
drainage areas, the Gunn River discharge record was 17%
of the Kalamazoo River at Comstock discharge record.
A sediment rating curve for fines (clays, silts, and very fine
sands) was derived from 51 suspended-sediment samples
collected by the USGS at the Plainwell gauge. For coarse
sediment particles transported as bed load, the sediment
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Figure 2. Map of Kalamazoo River study reach (85°40′W, 42°28′N) showing modeled cross sections and locations of the
Plainwell and Otsego City Dams.
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
transport rates at the inlet are assumed to equal the local
sediment-transport capacity of the flow.
The simulation period is August 2000 through November
2037. The start date coincides with the first cross-section
surveys by the USGS [Rheaume et al., 2002]. The inflow
record of water and sediment consists of the observed flow
through June 2002 followed by two sequences of the 17.7
year flow record discussed above. The simulation period is
long enough for channel adjustments to reach equilibrium for
the DO and D scenarios.
Bed material stratigraphy and composition were determined at 101 transects covering the study reach [Rheaume
et al., 2002, 2004] and were directly used in the model
simulations. Data on bank material stratigraphy, composition, and properties were collected at 27 locations. Regions
with similar bank material were identified, and data collected in these regions were aggregated. Critical shear
stress of the bank material ranges from a minimum of
1.3 Pa along the POC reach to a maximum of 70 Pa along
the left bank immediately upstream of the Plainwell Dam.
Effective cohesion ranges from a minimum of 0 Pa for
sandy bank material to a maximum of 6.8 kPa for the right
bank of the most upstream cross sections. A comprehensive
report of the measured values and those assigned to each
model cross section is provided in the work of Wells et al.
[2004].
5.1.4. Modeling scenarios. The DI scenario assumes current channel geometries and boundary sediments as initial
conditions. This simulation is used as a baseline by which to
compare the two alternative scenarios in terms of gross
amounts of channel change, the mass of material eroded from
channel banks, and fine-grained sediment transport. The DO
scenario also assumes current channel geometries as initial
conditions but with the Plainwell and Otsego City Dams no
longer in place, leaving 3–4 m high knickpoints. Finally, the
design scenario also assumes that the two dams are no longer
in place; however, design channel geometry is used instead
of the current channel geometry for initial conditions [Rachol
et al., 2005].
For the D scenario, channel geometry, channel location,
floodplain area, and channel elevation were modified between the Otsego City Dam (rkm 85.3) and cross-section
P15 (rkm 89.0) to minimize potential flooding, erosion, or
sedimentation problems after removal of the dams [Rachol et
al., 2005]. Cross sections in the impounded area upstream of
the Plainwell Dam were mainly modified by lowering the
channel to its predam elevation and removing impounded
sediment to increase floodplain area. The slope through this
reach is similar to that for predam conditions. In the POC
reach, the slope of the designed channel is steeper than that
for predam conditions. In the anastomosing part of the reach,
valley cross sections were modified by simplifying the multiple channel system into one or two main channels. Downstream of the multichannel reach, the channel elevation was
lowered below its predam elevation to provide a smooth
transition to the incised reach downstream of the Otsego City
Dam and impounded sediment removed to create a floodplain area. Streambeds of excavated cross sections were
assigned material composition and properties found at the
level of excavation [Rheaume et al., 2002, 2004].
5.1.5. Results and discussion. The DI modeling scenario
represents a baseline condition with existing channel geometries (including the low-head dams) and boundary characteristics. In general, the simulation predicted aggradation in
the Plainwell reach with sediment deposited in the backwaters caused by U.S. Highway 131 bridge and the Plainwell
Dam (Figure 3a). The main branch of the POC reach is
slightly erosional, whereas the OC reach is mainly a transport
reach. Results show that over the entire study reach, there is a
net annual deposition of material (4100 t yr 1). However,
silts and clays are eroded primarily from the bed at an
average annual rate of 1990 t yr 1.
For the DO scenario, large-scale erosion of the deposits
upstream of the dams occurred very quickly as the finegrained particles were unable to resist the increased shear
(Figure 3b). The channel incises down to its parent bed
material (predam elevations), limiting the extent of erosion
to the depth of the reservoir deposits. In the Plainwell reach,
bed deposition of 6400 t yr 1 for the baseline (DI) scenario
turned to erosion of 289 t yr 1 for the DO scenario. Net bed
erosion in the POC reach increased 1346% to 6580 t yr 1 for
the DO scenario compared with the DI scenario (455 t yr 1).
Bank erosion also increased greatly (1645%) in the POC
reach from about 157 to 2740 t yr 1 on average, due to
higher shear stresses exerted by the flow caused by the initial
steepening of the channel, especially upstream of the Otsego
City Dam location.
Figure 3c shows the differences between the current thalweg profile and that of the design channel for the D scenario.
Simulation shows the POC and OC reaches are fairly stable
because of the coarse-grained bed material. Channel deposition (2570 t yr 1) simulated under this scenario is 37% lower
than the DI scenario (4100 t yr 1). Erosion of stream bank
materials <63 μm (112 t yr 1) is 28% greater than that for the
DI scenario (87.7 t yr 1).
Over the simulation period, the DI/baseline scenario provides the smallest load passing the outlet (Figure 4 and
Table 1). The total load is the largest for the DO scenario;
however, the silt and clay fraction is smallest for the DO and
D scenario. The increase in sand-sized sediment transport
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495
Figure 4. Sediment loadings at the outlet of the study reach for the
(a) dams in, (b) dams out, and (c) design scenarios.
Figure 3. Initial and final thalweg profiles for the (a) dams in,
(b) dams out, and (c) design scenarios.
appears to limit the amount of fines being transported. Sediments eroded from the channel boundary and downstream
sediment load are similar and fairly low for the DI and
D scenarios, indicating a stable stream system. Removal of
the low-head dams induces severe channel bed and stream
bank erosion upstream of the former dam locations, significantly increasing sediment load. However, most of these
sediments are eroded in the first 3 years (Table 1). The
quantities of fine-grained material (<63 μm) transported past
the downstream boundary over the last 35 years of the
simulation are similar to those of the DI and D scenarios.
Therefore, most of the channel adjustment due to dam
removal occurs in the first 3 years of the simulation.
Although the DI (baseline) case clearly provides the smallest loads for total sediment transport, in order to improve
navigation and fisheries within this reach of the Kalamazoo
River, the removal of the low-head dams and implementation
of the design proposed by the USGS provides reduced loadings in materials less than 63 μm, and total loads passing
OC8 are comparable with the existing DI loadings.
Table 1. Simulated Average Annual Sediment Load Passing the
Downstream Boundary of the Kalamazoo River Study Reach
Sediment Yield in Kilotons per Year
Scenario
Dams in (DI)
Dams out (DO)
Dams out (DO, year 1–3)
Dams out (DO, year 4–38)
Design (D)
<63 μm
<2 mm
Total
10.4
8.9
43.7
6.5
8.4
10.5
25.9
114
20.0
13.9
10.5
30.1
127
23.6
14.2
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
5.2. Shades Creek Bank Stabilization
5.2.1. Overview. The Shades Creek watershed is located
near Birmingham, Alabama, in an area experiencing rapid
urbanization (Figure 5). Nearly the entire length of Shades
Creek is listed as impaired due to sediments. Surveys conducted between 1990 and 1993, and again in 1997, indicated
impairment caused by collection system failure, road and
bridge construction, land development, urban runoff, removal
of riparian vegetation, and bank/shoreline modification.
Simon et al. [2004] carried out a study to determine bed
material composition, sediment yields, and sources in the
Shades Creek watershed and to compare these to “reference”
sediment yields for unimpaired streams in the region.
As part of the study, CONCEPTS was used in combination
with the watershed model AnnAGNPS [Bingner and
Theurer, 2001] to evaluate, among others, (1) the effects of
urbanization on channel erosion and bed material gradation
and (2) the potential reduction in fine-grained sediment yield
provided by stream bank stabilization measures. AnnAGNPS provides peak flow discharge, runoff volume, and
clay, silt, and sand mass for each runoff event for reaches and
cells draining into the modeling reach. These data are then
converted into triangular-shaped hydrographs. The presented
results below describe three simulation scenarios using
(1) current (2001) land use (70% forest, 16% pasture, 11%
urban, and 3% water), (2) current land use with selected
stream bank protection (hereafter referred to as 2001LURP),
and (3) land use change from forest to urban, that is, 81%
urban and 0% forest (2001LUFU).
5.2.2. Study reach. The Shades Creek modeling reach
extends from approximately 10.0 km above the confluence
with the Cahaba River to approximately 86.5 km above the
confluence with the Cahaba River. The modeling reach is
composed of 156 cross sections. Bed and bank material
composition and geotechnical properties at each cross section were obtained from sediment samples and in situ testing.
Stream bank materials have an average silt/clay content of
15%, an average sand content of 81%, and an average gravel
content of 4%. Bank toe materials have an average silt/clay
content of 13%, an average sand content of 67%, an average
gravel content of 5%, and an average boulder/cobble content
of 15%. The streambed materials have an average silt/clay
content of 1%, an average sand content of 24%, an average
gravel content of 28%, and an average boulder/cobble content of 47%. Measured effective cohesion values were adjusted for root reinforcement by riparian vegetation by
adding 2 to 4 kPa to the top 1 m of the bank soils depending
on riparian vegetation density and species. Measured critical
shear stresses were adjusted for shielding of bank face material by riparian vegetation.
Figure 5. Map of Shades Creek, Alabama (86°51′W, 33°22′N), with
photos indicating the degree of stream bank erosion.
5.2.3. Results. A summary of the simulation results are
listed in Table 2. Both runoff and average annual suspendedsediment load showed a discernible increase for the modeling scenario where all forest land was changed to urban
(2001LUFU). Increases in sediment load are a direct result
of greater runoff rates. This is manifest in the number of
cross sections experiencing width adjustment greater than
2.0 m, which increased from 11 for the 2001 land use
scenario to 23 for the 2001LUFU scenario. Stream banks are
the greatest source of sediments to suspended load, except
for the 2001LURP scenario, which simulated protected
banks (see Table 3). Uplands were the main source of fines
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497
Table 2. Simulated Annual Runoff, Suspended Sediment Load, Average Widening, and Average Change in Bed Elevation for Shades
Creek, Alabama
Scenario
Average Annual
Runoff a (mm yr 1)
Average Annual
Sediment Loada (t yr 1r)
¯b
ΔT
(cm yr 1)
¯c
Δz
b
(cm yr 1)
457
457
702
19,700
19,500
29,200
2.83
1.62
4.20
0.172
0.117
0.276
2001 land use
2001LURP
2001LUFU
a
Numbers are given at the mouth of Shades Creek with the Cahaba River.
Average annual change in top width along the modeling reach.
c
Average annual change in bed elevation along the modeling reach.
b
for the 2001LURP scenario because of the 10,200 t yr 1 or
40% reduction in contributions from the banks. This 40%
reduction was the result of protecting 11% of the stream length.
The 46% (12,300 t yr 1) increase in loads for the 2001LUFU
originated mainly from the stream banks (8950 t yr 1) as
opposed to uplands (3460 t yr 1).
CONCEPTS was also used to determine the change in bed
material composition caused by land use changes. Embeddedness is used to characterize bed material composition.
Embeddedness is defined as the percentage of bed material
finer than 2 mm (sand, silt, and clay) in gravel or gravel/
cobble-dominated streambeds. Shades Creek is located in the
Ridge and Valley ecoregions, which reference median embeddedness value is 4% and the reference third quantile
embeddedness value is 13.4% [Simon et al., 2004]. Along
Shades Creek, there are 53 sections with a coarse-grained
streambed, 42 of which are located within stable reaches.
The embeddedness of 10 cross sections is smaller than 4%,
and the streambed of 26 cross sections has an embeddedness
value smaller than 13.4%.
For the 2001 land use scenario, the number of coarsegrained cross sections has reduced to 24 due to aggradation.
Only three sites have an embeddedness value smaller than
4%. There are seven sites with an embeddedness value
smaller than 13.4%. The number of sites with coarse-grained
streambeds between rkm 45 and 55 has reduced from ten to
only one, indicating significant deposition of fines.
For the 2001LURP scenario, the number of coarse-grained
cross sections has reduced to 29; however, this is five more
than for the 2001 land use scenario. Only three sites have an
Table 3. Relative Source Contributions of Uplands and Stream
Banks to Suspended Sediment for Shades Creek, Alabama
Scenario
Uplands (%) Stream Banks (%)
Total (t yr 1)
Fines Sands
Fines
2001 land use 40.3
2001LURP
88.7
2001LUFU
37.2
31.2
33.8
27.6
Fines
Sands
59.7
11.3
62.8
68.8
66.2
72.4
Sands
18,700 8,000
8,500 7,390
27,200 11,800
embeddedness value smaller than the reference median of
4%. There are eight sites with an embeddedness value smaller than the reference third quartile of 13.4%. The average
embeddedness is slightly smaller for the 2001LURP scenario
than that for the 2001 land use scenario.
For the 2001LUFU scenario, the number of coarse-grained
cross sections has reduced to 26, two more than for the 2001
land use scenario. Only one site has an embeddedness value
smaller than the reference median of 4%. There are nine sites
with an embeddedness value smaller than the reference third
quartile of 13.4%.
The above modeling scenarios show that targeted bank
protection is needed to prevent the fining of coarse-grained
beds caused by ongoing urbanization of the watershed. For
example, a 40% reduction in fine-grained sediment loadings
from stream banks can be realized by protecting 11% of the
stream length.
5.3. Evaluation of Vegetative Bank Stabilization Treatments
5.3.1. Overview. The integrated CONCEPTS and REMM
models were used to study the effectiveness of woody and
herbaceous riparian buffers in controlling stream bank erosion along an incised reach of the Goodwin Creek, Mississippi (Figure 6). Between 1996 and 2006, extensive research
on stream bank failure mechanics was conducted along this
reach. The following data were collected at the study site:
cross-section geometry, water surface elevations, bank material properties, pore water pressures in the bank, precipitation, root mapping and tensile strength, canopy interception,
and plant stem flow. Two flow measuring flumes in upstream
tributaries provide continuous discharge and fine sediment
data. A NOAA SURFRAD station located in the watershed
collects the following weather and climate input data for
REMM: incoming solar radiation, air temperature, relative
humidity, wind speed and wind direction.
Major failure episodes have occurred, resulting in up to
5.5 m of top bank retreat along the right bank between March
1996 to March 2001, which increased channel top width
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APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
Figure 6. Goodwin Creek Bendway study site (89°52′W, 34°15′N): (a) location map and (b) plan view showing surveyed
cross-section locations.
from 26 to 32 m approximately. Planar and cantilever failures
were relatively common along the steepest section of the
4.7 m high banks. Cantilevers were formed by (1) preferential erosion of sands and silts by fluvial undercutting about 3.0
to 3.5 m below the top bank and (2) by sapping and small popout failures in the region of contrasting permeabilities of the
stream bank material about 1.6 to 2 m below the top bank. It
was observed that the loss of matric suction from infiltrating
precipitation and subsequent seepage significantly contributes to mass bank instability [Simon et al., 2000].
Bank material consists of about 2 m of moderately cohesive, brown clayey-silt of late Holocene (LH) age overlying
1.5 m of early Holocene (EH) gray, blocky silt of considerable
cohesion and lower permeability, which perches water. These
units are separated by a thin (0.1 to 0.2 m) layer containing
manganese nodules. These materials overlie 1 m of sand and
1.5 m of packed (often weakly cemented) sandy gravel.
Cohesion and friction angle were measured in situ with
effective cohesion values ranging from 0 to 6.3 kPa. Core
samples were also analyzed for bulk density, porosity, and
particle size distribution.
Pore water pressure data were collected using tensiometers
along the right bank of the bendway at (1) an open plot (short
cropped turf/bare) since December 1996; (2) a mature riparian tree stand (a mixture of sycamore (Platanus occidentalis), river birch (Betula nigra), and sweetgum (Liquidambar
styroflora)) since July 1999; and (3) an eastern gamagrass
(Tripsacum dactyloides) buffer since December 1999 [Simon
and Collison, 2002]. Data were recorded every 10 min at
depths of 30, 100, 148, 200, and 270 cm (corresponding to
different layers within the bank profile). For model comparison, these data were time-averaged over a 24 hour (daily)
interval.
5.3.2. Simulation results. The effect of the riparian tree
stand and gamagrass buffer on stream bank erosion was simulated for the period of January 1996 to September 2003. The
riparian buffer in both scenarios had a width of 15 m (three
LANGENDOEN
Figure 7. Comparison of simulated and observed pore water pressures (PWP) within the right bank of the Goodwin Creek
Bendway study site for (a–c) a deciduous tree stand and (d–f ) an eastern gamagrass buffer. Figures 7a and 7d compare
the simulated PWP in layer 1 (0–0.5 m) to the observed tensiometer data at a depth of 0.3 m. Figures 7b and 7e compare the
simulated PWP in layer 2 (0.5–1.7 m) to the observed tensiometer data at a depth of 1.0 m. Figures 7c and 7f compare the
simulated PWP in layer 3 (1.7–3.2 m) to the observed tensiometer data at a depth of 2.7 m.
499
500
APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL
zones of 5 m) and four layers (two layers spanning the LH
unit, one layer spanning the EH unit, and a fourth layer
representing the sand unit). The properties of the trees at the
start of the simulation were height of 21 m, root depth of
1.0 m, a biomass of coarse roots of 48,000 kg ha 1, and a
biomass of fine roots of 15,500 kg ha 1 (mean RAR ≈ 1%).
The properties of the grass at the start of the simulation were
height of 0.1 m, root depth of 1.0 m, and biomass of fine roots
of 4000 kg ha 1 (mean RAR ≈ 0.1%). The biomass values of
fine roots are suitable values for woody and herbaceous riparian buffers along Goodwin Creek.
The temporal and spatial distributions of pore water pressure reflect the effects of infiltrating rainfall and evapotranspiration (Figure 7). For the grass buffer, the simulated pore
water pressures agree well with those observed in the LH and
EH layers (Figure 7d, 7e, and 7f ). Peak suction values in the
fall and the temporal variation of pore water pressure are
accurately simulated, except for the fall of 2000 where suction values are overpredicted in the LH unit (Figure 7d and
7e). For this time period, the planted grasses were in their
first year of development, whereas they were already well
established in the model simulation. For the riparian tree
stand, the simulated pore water pressure distribution agrees
well in the LH unit (Figure 7a and 7b) but does not compare
well in the EH unit (Figure 7c).
Figure 8a compares the simulated increase in channel top
width for the two riparian buffer scenarios to that observed.
The woody buffer greatly reduced stream bank erosion by
preventing any planar failures. The anchoring effects of
coarse roots in the upper 1 m of the stream bank significantly
increased factor of safety, though undercutting of the stream
bank produced some cantilever failures along the central part
of the bendway, leading to near vertical stream banks at the
end of the simulation (Figure 8b). With progressive undercutting, the bank will eventually fail in case of the riparian
tree stand.
Simulated top-bank retreat for the gamagrass buffer is similar to that observed. The added cohesion due to the grass roots
did not noticeably contribute to total shear strength due to the
height of the stream bank with respect to rooting depth. That is,
only the soil shear-strength along the top 1 m of the failure
plane is affected by the grass roots. Further, the grass buffer
does not have a coarse root system that can act as anchors.
To summarize, the deciduous tree stand significantly reduces stream bank erosion rates. However, the simulation
period is too short to accurately calculate the reduction percentage. The effect of the eastern gamagrass buffer on the rate
of stream bank erosion is negligible. The ratio of the rooting
depth to bank height (<0.5) in combination with the absence of
a coarse root system minimizes any contributions of the gamagrass buffer to the stability of the stream bank. This modeling
exercise shows that for the Goodwin Creek Bendway, a coarse
rooting system, e.g., as provided by trees, may significantly
reduce bank erosion rates. The failure of the gamagrass buffer
to reduce erosion rates shows that the hydrologic benefits, that
is a reduction in pore water pressure provided by vegetation, is
of secondary importance to the long-term rate of stream bank
retreat for the studied incised stream.
Figure 8. Comparison of simulated bank retreat at the Goodwin Creek Bendway study site between January 1996 and
September 2003 for the two vegetative treatment scenarios against those observed: (a) change in channel top width and
(b) stream bank erosion at the cross section located at river distance 0.058 km.
LANGENDOEN
6. SUMMARY
The channel evolution model CONCEPTS and the riparian
zone management model REMM were developed to (1)
simulate the long-term evolution of incised channel systems,
(2) evaluate the effectiveness of stream restoration designs,
and (3) assess management decisions to control nonpoint
source pollution in the riparian zone. The models simulate
the processes and controlling factors that shape streams:
hydraulics, sediment transport and bed adjustment, stream
bank erosion, and riparian zone hydrology and plant growth.
Restoration measures to control streambed and stream
bank erosion are represented by adjusting bed and bank
material properties. Three example applications of the model
at the stream corridor scale demonstrated its capabilities to
evaluate stream restoration measures that stabilize streambeds and stream banks or the evolution of newly constructed
channels to replace highly disturbed existing channels.
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