Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

Midgley, Taber L.; Fox, Garey A.; Heeren, Derek M.

doi:10.1016/j.geomorph.2011.12.044

Cited by 134 publications

(107 citation statements)

References 35 publications

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“…Hydrodynamic, morphodynamic, bank-erosion, and channel-migration models of river environments also benefit from information on vegetation cover because they require estimations of channel roughness and bank strength that are caused by channel material and vegetation [37][38][39]. These models can be used to determine flood inundation areas, flood risk management, river management, and river rehabilitation [38,[40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

et al. 2013

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Vegetation plays an important role in stabilizing the soil and decreasing fluvial erosion. In certain cases, vegetation increases the accumulation of fine sediments. Efficient and accurate methods are required for mapping and monitoring changes in the fluvial environment. Here, we develop an area-based approach for mapping and monitoring the vegetation structure along a river channel. First, a 2 × 2 m grid was placed over the study area. Metrics describing vegetation density and height were derived from mobile laser-scanning (MLS) data and used to predict the variables in the nearest-neighbor (NN) estimations. The training data were obtained from aerial images. The vegetation cover type was classified into the following four classes: bare ground, field layer, shrub layer, and canopy layer. Multi-temporal MLS data sets were applied to the change detection of riverine vegetation. This approach successfully classified vegetation cover with an overall classification accuracy of 72.6%; classification accuracies for bare ground, field layer, OPEN ACCESSRemote Sens. 2013, 5 5286 shrub layer, and canopy layer were 79.5%, 35.0%, 45.2% and 100.0%, respectively. Vegetation changes were detected primarily in outer river bends. These results proved that our approach was suitable for mapping riverine vegetation.

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Section: Introductionmentioning

confidence: 99%

Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

et al. 2013

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“…Many have been designated scenic rivers and have created a recreational and tourism industry for the area [36,37]. Streambanks in the watershed are comprised of a cohesive silty loam top layer above an unconsolidated gravel layer [8,13].…”

Section: Watershed Descriptionmentioning

confidence: 99%

“…The two erodibility parameters, τ c and k d , are soil dependent. Models such as the Bank Stability and Toe Erosion Model (BSTEM), Conservational Channel Evolution and Pollutant Transport System (CONCEPTS), and HEC-RAS with BSTEM use the linear excess shear-stress equation to predict fluvial erosion and require τ c and k d as input [7][8][9]. The Soil and Water Assessment Tool (SWAT) either allows the user to input τ c and k d , or calculates the parameters based on soil characteristics and empirical relationships [10].…”

Section: Introductionmentioning

confidence: 99%

Watershed Variability in Streambank Erodibility and Implications for Erosion Prediction

Enlow

Fox

Guertault

2017

Water

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Abstract:Two fluvial erosion models are commonly used to simulate the erosion rate of cohesive soils: the empirical excess shear stress model and the mechanistic Wilson model. Both models include two soil parameters, the critical shear stress (τ c ) and the erodibility coefficient (k d ) for the excess shear stress model and b 0 and b 1 for the Wilson model. Jet erosion tests (JETs) allow for in-situ determination of these parameters. JETs were completed at numerous sites along two streams in each the Illinois River and Fort Cobb Reservoir watersheds. The objectives were to use JET results from these streambank tests to investigate variability of erodibility parameters on the watershed scale and investigate longitudinal trends in streambank erodibility. The research also determined the impact of this variability on lateral retreat predicted by a process-based model using both the excess shear stress model and the Wilson model. Parameters derived from JETs were incorporated into a one-dimensional process-based model to simulate bank retreat for one stream in each watershed. Erodibility parameters varied by two to five and one to two orders of magnitude in the Illinois River watershed and Fort Cobb Reservoir watershed, respectively. Less variation was observed in predicted retreat by a process-based model compared to the input erodibility parameters. Uncalibrated erodibility parameters and simplified applied shear stress estimates failed to match observed lateral retreats suggesting the need for model calibration and/or advanced flow modeling.

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“…These results suggest that bank failure and toe erosion contribute similar magnitudes of sediment and phosphorus to watersheds; however, the relative importance of these processes varies between studies. Previous research has shown that fluvial parameters have a greater influence on BSTEM modeling than stability inputs (McQueen, 2011;Midgley et al, 2012) and that fluvial erosion may account for a larger proportion of total watershed sediment budgets than mass wasting (Laubel et al, 2000;Pizzuto, 2009), although this is likely dependent on site specific conditions.…”

Section: Comparison With Field Datamentioning

confidence: 99%

Uncertainty and sensitivity in a bank stability model: implications for estimating phosphorus loading

Lammers

Bledsoe

Langendoen

2016

Earth Surf Processes Landf

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UNCERTAINTY AND SENSITIVITY IN A BANK STABILITY MODEL: IMPLICATIONS FOR ESTIMATING PHOSPHORUS LOADINGEutrophication of aquatic ecosystems is one of the most pressing water quality concerns in the U.S. and around the world. Bank erosion has been largely overlooked as a source of nutrient loading, despite field studies demonstrating that this source can account for the majority of the total phosphorus budget of a watershed. Substantial effort has been made to develop mechanistic models to predict bank erosion and instability in stream systems; however, these models do not account for inherent natural variability in input values. Providing only single output values with no quantification of associated uncertainty can complicate management decisions focused on reducing bank erosion and nutrient loading to streams. To address this issue, uncertainty and sensitivity analyses were performed on the Bank Stability and Toe Erosion Model (BSTEM), a mechanistic model developed by the USDA-ARS that simulates both mass wasting (stability) and fluvial erosion of streambanks. Sensitivity analysis results indicate that variable influence on model output can vary depending on assumed input distributions.Generally, bank height, soil cohesion, and plant species were found to be most influential in determining stability of clay (cohesive) banks. In addition to these three inputs, groundwater elevation, stream stage, and bank angle were also identified as important in sand (non-cohesive) banks. Slope and bank height are the dominant variables in fluvial erosion modeling, while erodibility and critical shear stress are relatively unimportant. However, the threshold effect of critical shear stress (determining whether erosion occurs) was not explicitly accounted for, ii possibly explaining the relatively low sensitivity indices for this variable. Model output distributions of sediment and phosphorus loading rates corresponded well to ranges published in the literature, helping validate both model performance and selected ranges of input values. In addition, a probabilistic modeling approach was applied to data from a watershed-scale sediment and phosphorus loading study on the Missisquoi River, Vermont to quantify uncertainty associated with these published results. While our estimates indicated that bank erosion was likely a significant source of sediment and phosphorus to the watershed in question, the uncertainty associated with these predictions indicates that they should probably be considered order of magnitude estimates only.iii ACKNOWLEDGEMENTS

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Evaluation of the bank stability and toe erosion model (BSTEM) for predicting lateral retreat on composite streambanks

Cited by 134 publications

References 35 publications

Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

Watershed Variability in Streambank Erodibility and Implications for Erosion Prediction

Uncertainty and sensitivity in a bank stability model: implications for estimating phosphorus loading

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