An improved method for the parameterization of sediment trapping in VFSMOD

Author(s):  
Stefan Reichenberger ◽  
Robin Sur ◽  
Stephan Sittig ◽  
Sebastian Multsch ◽  
Rafael Muñoz-Carpena

<p>The most widely implemented mitigation measure to reduce transfer of pesticides to surface water bodies via surface runoff are vegetative filter strips (VFS). To reliably model the reduction of surface runoff, eroded sediment and pesticide load by VFS an event-based model is needed. The most commonly used model for this purpose is VFSMOD. VFSMOD simulates reduction of total inflow (∆Q) and reduction of incoming eroded sediment load (∆E) mechanistically. These variables are subsequently used to calculate the reduction of pesticide load (∆P). While ∆P can be relatively well predicted from ∆Q, ∆E and some other variables, errors in ∆Q and ∆E will propagate to ∆P. Hence, for strongly sorbing compounds, an accurate prediction of ∆E is crucial. The most important parameter characterizing the incoming sediment in VFSMOD is the median particle diameter d50. The objective of this study was to derive a generic d50 parameterization methodology for sediment trapping in VFSMOD that can be readily used for regulatory VFS scenarios.</p><p>Four studies with 16 hydrological events were selected for modelling. A first set of VFSMOD simulations, following the SWAN-VFSMOD sediment parameterization with d50 = 20 µm yielded a general overestimation of ∆E. Consequently, a maximum-likelihood-based calibration and uncertainty analysis with the DREAM-ZS algorithm was performed for the 16 events. The resulting d50 values were all in the low range (1.3-5.4 µm) and did not allow to establish a robust relationship to predict a wider range of d50 from the available explanatory variables. To increase the sample size and the range of d50 values, the comprehensive Kinston dataset for a loamy sand in North Carolina was calibrated with DREAM-ZS. Calibration was performed separately for each hydrological event. Further data points with measured particle size distributions in run-on were assimilated from the literature. The extended test data set of d50 values and explanatory variables was analysed using an extended multiple linear regression (MLR) approach and Classification and Regression Trees (CART).</p><p>A good calibration of event totals and outflow hydrographs could be achieved for most events and VFS treatments of the Kinston site. The calibrated d50 values yielded a wider range (2-16 µm) than the initial 16 events.</p><p>The improved d50 parameterization method derived with MLR/CART will be adopted in the next version of SWAN-VFSMOD to provide more realistic quantitative mitigation within FOCUS STEP4.</p>

2020 ◽  
Author(s):  
Stefan Reichenberger ◽  
Robin Sur ◽  
Carolin Kley ◽  
Stephan Sittig ◽  
Sebastian Multsch

<p>The most widely implemented mitigation measure to reduce transfer of pesticides and other pollutants to surface water bodies via surface runoff are vegetative filter strips (VFS). To reliably model the reduction of surface runoff, eroded sediment and pesticide inputs into surface water by VFS in a risk assessment context, an event-based model is needed. The most commonly used dynamic, event-based model for this purpose is VFSMOD. VFSMOD simulates reduction of total inflow (ΔQ) and reduction of incoming eroded sediment load (ΔE) mechanistically. These variables are subsequently used to calculate the reduction of pesticide load by the VFS (ΔP). There are several options in VFSMOD to calculate ΔP, notably the empirical Sabbagh equation (either with original or revised regression coefficients) and a regression-free, mechanistic mass-balance approach (Reichenberger et al., 2017).</p><p>Four studies with 16 hydrological events were selected from the experimental data compiled by Reichenberger et al. (2019), representing different levels of data availability and uncertainty. A first set of VFSMOD simulations, with parameterization according to the settings in the tool SWAN-VFSMOD, was run with the aim to compare the performance of the different pesticide trapping equations.  The simulations yielded a general overestimation of ΔE, suggesting that the SWAN-VFSMOD parameterization of sediment filtration is too optimistic. However, a reliable prediction of ΔE is important for the reliability of predicted ΔP, in particular for strongly sorbing compounds.</p><p>In a second step, a maximum-likelihood-based calibration and uncertainty analysis with the DREAM-ZS algorithm was performed for each hydrological event and the target variables ΔQ and ΔE. Overall a good match of measured ΔQ and ΔE was achieved, but only a few parameters could be well constrained.</p><p>In a third step, in order to reduce the observed equifinality, the hydraulic parameters were fixed to the best parameter sets obtained during the second phase, and only sediment filtration parameters were calibrated with DREAM-ZS.</p><p>The most important parameter characterizing the incoming sediment in VFSMOD is the median particle diameter DP. A set of empirical equations to predict DP from soil texture (Foster et al., 1985) was used as supporting information in the calibration of DP.         </p><p>The poster will present an improved, generic parameterization methodology for sediment trapping in VFSMOD that can be used for regulatory VFS scenarios.</p>


1997 ◽  
Vol 11 (3) ◽  
pp. 618-622 ◽  
Author(s):  
Wondi Mersie ◽  
Cathy A. Seybold

This paper describes the design, construction, and operation of tilted beds to investigate the effectiveness of vegetative filter strips (VFS) in removing agricultural chemicals from runoff water. The beds are designed to catch surface runoff, leachate, and subsurface lateral flow. Switchgrass was established on beds filled with Cullen clay loam or Emporia sandy loam. Switchgrass establi shed on Cullen clay loam beds reduced surface runoff by 60% and by 11% in sandy loam containing switchgrass compared to respective bare soils. Infiltration was 64, 26, 17, and 8% for clay loam with switchgrass, clay loam without switchgrass, sandy loam with switchgrass, and sandy loam without switchgrass, respectively.


2019 ◽  
Vol 11 (24) ◽  
pp. 7212 ◽  
Author(s):  
Joo Hyun Bae ◽  
Jeongho Han ◽  
Dongjun Lee ◽  
Jae E Yang ◽  
Jonggun Kim ◽  
...  

The South Korean government has recently focused on environmental protection efforts to improve water quality which has been degraded by nonpoint sources of water pollution from runoff. In order to take care of environmental issues, many physically-based models have been used. However, the physically-based models take a large amount of work to carry out site simulations, and there is a need to find faster and more efficient approaches. For an alternative approach for sediment management using the physically-based models, the machine learning-based models were used for estimating sediment trapping efficiency of vegetative filter strips. The seven nonlinear regression algorithms of machine learning models (e.g., decision tree, multilayer perceptron, k-nearest neighbors, support vector machine, random forest, AdaBoost and gradient boosting) were applied to select the model which best estimates the sediment trapping efficiency of vegetative filter strips. The sediment trapping efficiencies calculated by the machine learning models showed similar results as those of vegetative filter strip modeling system (VFSMOD-W) model. As a result of the accuracy evaluation among the seven machine learning models, the multilayer perceptron model-derived the best fit with VFSMOD-W model. It is expected that the sediment trapping efficiency of the vegetative filter strips in various cases in agricultural fields in South Korea can be predicted easier, faster and accurately by the machine learning models developed in this study. Machine learning models can be used to evaluate sediment trapping efficiency without complicated physically-based model design and high computational cost. Therefore, decision makers can maximize the quality of their outputs by minimizing their efforts in the decision-making process.


Soil Research ◽  
1999 ◽  
Vol 37 (5) ◽  
pp. 929 ◽  
Author(s):  
R. J. Loch ◽  
T. Espigares ◽  
A. Costantini ◽  
R. Garthe ◽  
K. Bubb

A field study of sediment movement through vegetative barriers was carried out to assess the sediment-trapping effectiveness of vegetative barrier types typically used in forest forest plantation management in south-east Queensland, Australia, and to develop a simple methodology for predicting sediment movement through these barriers. For sites at the centre of Queensland's 110 000 ha Pinus plantation and 45 000 ha Araucaria plantation program, small field flumes (plots) were established on a range of vegetation types and slope gradients, and sediment-laden flows passed through them. Sediment trapping in the plots was assessed by comparing paired samples taken from the inlet and outlet of the plots at pre-determined sampling times. Measurements included total sediment and equivalent size distributions of sediment particles (the latter measurements being based on settling velocities). For plots that did not erode, the degree of sediment trapping, if based on total sediment only, was quite variable. However, if rates of transport were considered in terms of the various size fractions, results were very consistent. A simple conceptual approach equating the vegetated area to a sedimentation pond allowed deposition to be calculated on the basis of settling velocity, flow depth, and residence time within the vegetated area. Estimated transport rates of sediment through the vegetated areas were in close agreement with measured transport rates, confirming the eciency of this approach. The results highlight a number of issues for management of sediment movement from forest estates.


2014 ◽  
Vol 998-999 ◽  
pp. 1405-1409
Author(s):  
Na Deng ◽  
Huai En Li

Vegetative filter strip (VFS) is be defined as areas of vegetation designed to remove sediment and other pollutants from surface runoff. Many factors affect the effectiveness of VFS. So the quantitative analysis on relation between effectiveness and influencing factors had been conducted based on the plot experiment data in this paper. Result reveals that the order in impact degree of its factors is: inflow rate factor > width factor > vegetation condition > pollutants concentration in inflow > initial soil water content factor, the relation equation of purification effect and VFS width is the form of logarithm, and the relation equation of concentration reduction rate and inflow rate is the form of power function. Furthermore, a simple empirical model had been developed to predict sediment trapping efficiency in allusion to Chinese northwest region, which can provide computational basis for design of VFS in northwest region and other similar areas.


2018 ◽  
Vol 29 (11) ◽  
pp. 3917-3927 ◽  
Author(s):  
Daili Pan ◽  
Xiaodong Gao ◽  
Juan Wang ◽  
Min Yang ◽  
Pute Wu ◽  
...  

2018 ◽  
Vol 22 (1) ◽  
pp. 53-70 ◽  
Author(s):  
Rafael Muñoz-Carpena ◽  
Claire Lauvernet ◽  
Nadia Carluer

Abstract. Vegetation buffers like vegetative filter strips (VFSs) are often used to protect water bodies from surface runoff pollution from disturbed areas. Their typical placement in floodplains often results in the presence of a seasonal shallow water table (WT) that can decrease soil infiltration and increase surface pollutant transport during a rainfall-runoff event. Simple and robust components of hydrological models are needed to analyze the impacts of WT in the landscape. To simulate VFS infiltration under realistic rainfall conditions with WT, we propose a generic infiltration solution (Shallow Water table INfiltration algorithm: SWINGO) based on a combination of approaches by Salvucci and Entekhabi (1995) and Chu (1997) with new integral formulae to calculate singular times (time of ponding, shift time, and time to soil profile saturation). The algorithm was tested successfully on five distinct soils, both against Richards's numerical solution and experimental data in terms of infiltration and soil moisture redistribution predictions, and applied to study the combined effects of varying WT depth, soil type, and rainfall intensity and duration. The results show the robustness of the algorithm and its ability to handle various soil hydraulic functions and initial nonponding conditions under unsteady rainfall. The effect of a WT on infiltration under ponded conditions was found to be effectively decoupled from surface infiltration and excess runoff processes for depths larger than 1.2 to 2 m, being shallower for fine soils and shorter events. For nonponded initial conditions, the influence of WT depth also varies with rainfall intensity. Also, we observed that soils with a marked air entry (bubbling pressure) exhibit a distinct behavior with WT near the surface. The good performance, robustness, and flexibility of SWINGO supports its broader use to study WT effects on surface runoff, infiltration, flooding, transport, ecological, and land use processes. SWINGO is coupled with an existing VFS model in the companion paper (Lauvernet and Muñoz-Carpena, 2018), where the potential effects of seasonal or permanent WTs on VFS sediment and pesticide trapping are studied.


2017 ◽  
Vol 593-594 ◽  
pp. 54-64 ◽  
Author(s):  
Daili Pan ◽  
Xiaodong Gao ◽  
Miles Dyck ◽  
Yaqian Song ◽  
Pute Wu ◽  
...  

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