Application of the CONCEPTS Channel Evolution Model in Stream Restoration Strategies

Transcription

1 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. CON- CEPTS 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 /2010GM 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

2 488 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 CON- CEPTS 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 restoration 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] 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 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 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)

3 LANGENDOEN 489 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 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 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 Hydrology. Water movement and storage is characterized by processes of interception, evapotranspiration (ET), infiltration, vertical drainage, surface runoff, subsurface lateral 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 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 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

4 490 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 CONCEPTS 3. INPUT DATA REQUIREMENTS 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 REMM REMM s input data are related to model execution, the physical description of the riparian buffer, and boundary

5 LANGENDOEN 491 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 ( 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. CON- CEPTS 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. 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 CON- CEPTS. 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 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 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.

6 492 APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL 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 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 Kalamazoo River Dam Removal 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 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 The Plainwell- Otsego (POC) reach extends from the upstream end of the Otsego City Dam to the Plainwell Dam at rkm The Plainwell reach extends from the Plainwell Dam to the upstream boundary of the study reach at rkm 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 ( ). 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 km 2 ) was estimated using a drainage area comparison with the flow record from the Kalamazoo River at Comstock ( ; 2740 km 2 ). 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

7 LANGENDOEN 493 Figure 2. Map of Kalamazoo River study reach (85 40 W, N) showing modeled cross sections and locations of the Plainwell and Otsego City Dams.

8 494 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 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] 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] 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(112tyr 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

9 LANGENDOEN 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 <63 μm <2 mm Total Dams in (DI) Dams out (DO) Dams out (DO, year 1 3) Dams out (DO, year 4 38) Design (D)

10 496 APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL 5.2. Shades Creek Bank Stabilization 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) 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, N), with photos indicating the degree of stream bank erosion 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

11 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 Load a (t yr 1 r) ΔT b (cm yr 1 ) LANGENDOEN 497 Δz c b (cm yr 1 ) 2001 land use , LURP , LUFU , a Numbers are given at the mouth of Shades Creek with the Cahaba River. b Average annual change in top width along the modeling reach. c Average annual change in bed elevation along the modeling reach. 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 Uplands (%) Stream Banks (%) Total (t yr 1 ) Scenario Fines Sands Fines Sands Fines Sands 2001 land use ,700 8, LURP ,500 7, LUFU ,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 Evaluation of Vegetative Bank Stabilization Treatments 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

12 498 APPLICATION OF CONCEPTS CHANNEL EVOLUTION MODEL Figure 6. Goodwin Creek Bendway study site (89 52 W, 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 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 The riparian buffer in both scenarios had a width of 15 m (three

13 LANGENDOEN 499 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 ( m) to the observed tensiometer data at a depth of 1.0 m. Figures 7c and 7f compare the simulated PWP in layer 3 ( m) to the observed tensiometer data at a depth of 2.7 m.

14 500 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 km.