Magnitude and processes of bank erosion at a small stream in Denmark

Veihe, Anita; Jensen, Niels H.; Schiøtz, Iris Gunia; Nielsen, Søren Laurentius

doi:10.1002/hyp.7921

Cited by 27 publications

(22 citation statements)

References 40 publications

(118 reference statements)

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“…The effects of soil type on water quality are potentially challenging to determine, first since concentrations in soil can be a combination of both human activities and natural background concentrations (Sheppard et al 2009), and second due to the complex chemical and physical structure of the soil (Pennanen 2001). The most important characteristics of soil on water quality are soil moisture, grain size and hydraulic conductivity (Veihe et al 2011). In this study, land use was not found to be an important predictor of DO, but instead the models benefitted most from the inclusion of additional watershed variables.…”

Section: Discussionmentioning

confidence: 99%

Spatial modelling of stream water quality along an urban–rural gradient

Taka

Aalto

Luoto

2015

Geografiska Annaler: Series A, Physical Geography

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It is widely known that intensive land use generally decreases stream water quality, but the influence of watershed physiography is relatively poorly understood. Since management planning has to take into account the protection of water quality, the current status of stream water must be identified. The potential effects of land use and watershed physiography variables on water quality were studied in an extensive set of 83 watersheds in the Helsinki region, Finland, covering wide land‐use intensity gradient. The aims of this study were to test if the geographical information of watershed land‐use data can be used to model the stream water quality, and to examine whether the spatial water quality models are improved after including predictors of watershed physiography to the land‐use model. Water quality variables were related to watershed predictors by utilizing generalized additive models and linear mixed models, and the independent effect of the variables was investigated using a hierarchical partitioning approach. While land use turned out to be the most influential factor explaining water quality, all models improved significantly after incorporating the watershed characteristics, such as topography and soil. These results were consistent across three modelling techniques. This study, with its novel approach to examine the impacts of several watershed physiographic characteristics on urban stream water quality in northern Europe, demonstrates that spatial land use and watershed physiography data can be used as cost‐efficient predictors in stream water quality models.

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Section: Discussionmentioning

confidence: 99%

Spatial modelling of stream water quality along an urban–rural gradient

Taka

Aalto

Luoto

2015

Geografiska Annaler: Series A, Physical Geography

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“…In Danish rivers, a study using erosion pin produced values ranging between 25 and 36 mm year −1 (Kronvang, Audet, Baattrup-Pedersen, Jensen, & Larsen, 2012). Similarly, in another study on a 16-km 2 Danish agricultural catchment, Veihe et al (2010) estimated a loss of material of 17.6 to 30.1 mm year −1 . The results obtained for the current bank dynamics along a small stream are, therefore, comparable to the results of previous studies performed on small agricultural catchments.…”

Section: Quantifying Bank Erosion Over One Hydrological Yearmentioning

confidence: 95%

Quantification of bank erosion in a drained agricultural lowland catchment

et al. 2017

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The long‐term and current volumes of sediment exported from stream banks were calculated as potential sources of sediment in a large pond located at the catchment outlet of a small agricultural lowland basin strongly affected by anthropogenic pressure in France. Bank erosion was measured over a short period using a network of erosion pins along a small stream (1400 m long) to quantify the material exported during a single winter (2012–2013). The material exported by this same stream over the last 69 years was quantified using an original approach involving the comparison of a compilation of three‐dimensional historical stream redesign plans that date back to 1944 with the state of the banks in 2013 (differential global positioning system and LiDAR data). The results suggest that a global trend of material loss along the stream banks monitored by erosion pins, with an average erosion rate of 17.7 mm year−1 and an average volume of exported material of 75 t km−1. Over 69 years, this same stream exported an average of 36 t km−1 year−1, and the average loss of material from the banks throughout the whole catchment was estimated to be 14 t km−1 year−1. The contribution of bank material to the filling of the pond over the last 10 years is between 46% and 52% based on an extrapolation of erosion pin dynamics or between 27% and 30% based on the comparison of LiDAR data to the average historical profile extrapolated for the catchment. These results suggest that bank erosion represents a major source of sediment in degraded waters in traditionally understudied agricultural lowland catchments, where anthropogenic pressures are high.

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“…The partitioning of phosphate among its various states determines its bioavailability for uptake by organisms, which is directly tied to its importance as a limiting nutrient. The relative abundance of bioavailable phosphorus in sediment has been shown to vary markedly within single study sites (1-55%; Veihe et al, 2011) and between study areas (averaging 0.5-22% of total phosphorus; Nellesen et al 2011;Thompson and McFarland 2007;Hubbard et al 2003;McDowell and Sharpley 2001;McDowell and Wilcock 2007;Howe et al 2011). …”

Section: Phosphorus Loading and Bank Erosionmentioning

confidence: 99%

“…Sensitivity analysis looks to quantitatively apportion variance in this Study Location Bledsoe et al, 2000 Mississippi, USA Hongthanat, 2010 Iowa, USA Howe et al, 2011 Vermont, USA Hubbard et al, 2003 Mississippi, USA Kerr et al, 2011Australia Merritts et al, 2010 Pennsylvania / Maryland, USA Nellesen et al, 2011 Iowa, USA Peacher, 2011 Missouri, USA Schilling et al, 2009 Iowa, USA Thompson and McFarland, 2007 Texas, USA Tufekcioglu, 2010 Iowa, USA Veihe et al, 2011 Denmark output distribution to each of the input variables. Sensitivity analysis may be local or global.…”

Section: Sensitivity Analysismentioning

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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Magnitude and processes of bank erosion at a small stream in Denmark

Cited by 27 publications

References 40 publications

Spatial modelling of stream water quality along an urban–rural gradient

Spatial modelling of stream water quality along an urban–rural gradient

Quantification of bank erosion in a drained agricultural lowland catchment

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

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