An Empirical Model of Sediment Trapping Efficiency by Vegetative Filter Strips in Chinese Northwest

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.

Download Full-text

Evaluation of Sediment Trapping Efficiency of Vegetative Filter Strips Using Machine Learning Models

Sustainability ◽

10.3390/su11247212 ◽

2019 ◽

Vol 11 (24) ◽

pp. 7212 ◽

Cited By ~ 1

Author(s):

Joo Hyun Bae ◽

Jeongho Han ◽

Dongjun Lee ◽

Jae E Yang ◽

Jonggun Kim ◽

...

Keyword(s):

Machine Learning ◽

Multilayer Perceptron ◽

Trapping Efficiency ◽

Learning Models ◽

Sediment Trapping ◽

Vegetative Filter Strips ◽

Filter Strips ◽

Physically Based ◽

Physically Based Models ◽

Machine Learning Models

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.

Download Full-text

Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides

Al-Khwarizmi Engineering Journal ◽

10.22153/kej.2017.01.005 ◽

2017 ◽

Vol 13 (2) ◽

Author(s):

Hayat Kareem Shukur ◽

Dawood E. Sachit

Keyword(s):

Trapping Efficiency ◽

Silty Clay ◽

Infiltration Capacity ◽

Vegetative Filter Strips ◽

Filter Strips ◽

Filter Length ◽

Filter Strip ◽

Vegetative Filter Strip ◽

Receiving Stream ◽

Strip Length

Abstract The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one has a Koc of 2070 L/kg which is less moveable than XXXX) are presented, where the goal is to prevent 95% of incoming sediment and 85% of the incoming pesticide to reach a receiving stream in still water, Oklahoma from a cultivated field (1250 m²),for 2 hour storm with 5 years return period. Several VFS lengths were simulated including1, 3, 5, 6, 9, 11, 12, and 13 m. The results showed that the percent of reduction of sediment, pesticide, and water mainly depends on VFS lengths. Moreover, considering the design storms range, the simulation illustrated that the optimal filter length was13m for silty clay loam. When the value of was increased from 147 L/kg to 6070 L/kg, the filter length decreased from 13 to 9.5 because of the increase in trapping efficiency. In addition, the results revealed that the trapping efficiency was for sediment but not for water orpesticide which was highly impacted by the narrow filter strips. The amount of the rainfall and runoff of the designated field was larger than the infiltration capacity of filter strips, which resulted in low trapping efficiency for pesticide and water. Keywords: Models ,runoff, sediment, vegetative filter strip, , water quality, watershed planning.

Download Full-text

GDVFS: A New Toolkit for Analysis and Design of Vegetative Filter Strips Using VFSMOD

Water Quality Research Journal ◽

10.2166/wqrj.2010.007 ◽

2010 ◽

Vol 45 (1) ◽

pp. 59-68 ◽

Cited By ~ 1

Author(s):

Ramesh P. Rudra ◽

Bahram Gharabaghi ◽

Saleh Sebti ◽

Neelam Gupta ◽

Ashwini Moharir

Keyword(s):

Phosphorus Removal ◽

Design Tool ◽

Vegetative Filter Strips ◽

Bacteria Transport ◽

Filter Strips ◽

Analysis And Design ◽

Vegetative Filter Strip ◽

Removal Efficiencies ◽

Computational Procedures ◽

Main Components

Abstract The Guelph design tool for vegetative filter strips, GDVFS, is a toolkit for the analysis and design of vegetative filter strips (VFSs). The upland hydrology model UH and the vegetative filter strip model VFSMOD (the two main components of GDVFS) were adopted from an existing interface (VFSMOD-W), and new nutrient and bacteria transport add-ons for UH and VFSMOD were incorporated into GDVFS. Other utilities and tools were also included in GDVFS to provide a capable toolkit for the analysis and design of VFSs. The published evaluation of computational procedures used in GDVFS indicates that these procedures perform very well in the estimation of VFS sediment and phosphorus removal efficiencies. According to these results, comparison of the predicted and observed values for sediment and phosphorus removal efficiencies indicates 10 and 20% error, respectively. This paper provides descriptions on the capabilities and methodology followed in the GDVFS toolkit.

Download Full-text

Modeling study on the time-varying process of sediment trapping in vegetative filter strips

The Science of The Total Environment ◽

10.1016/j.scitotenv.2020.138361 ◽

2020 ◽

Vol 725 ◽

pp. 138361 ◽

Cited By ~ 1

Author(s):

Mingjie Luo ◽

Chengzhong Pan ◽

Chunlei Liu

Keyword(s):

Time Varying ◽

Sediment Trapping ◽

Vegetative Filter Strips ◽

Filter Strips ◽

Modeling Study

Download Full-text

Trapping efficiency with rainfall and seasonal changes in vegetative filter strips over a course of three years

Desalination and Water Treatment ◽

10.1080/19443994.2012.671270 ◽

2012 ◽

Vol 40 (1-3) ◽

pp. 319-325

Author(s):

Kyungik Gil ◽

Ji-Woong Shin

Keyword(s):

Seasonal Changes ◽

Trapping Efficiency ◽

Vegetative Filter Strips ◽

Filter Strips

Download Full-text

Vegetative filter strips to control sediment movement in forest plantations: validation of a simple model using field data

Soil Research ◽

10.1071/sr98089 ◽

1999 ◽

Vol 37 (5) ◽

pp. 929 ◽

Cited By ~ 13

Author(s):

R. J. Loch ◽

T. Espigares ◽

A. Costantini ◽

R. Garthe ◽

K. Bubb

Keyword(s):

Conceptual Approach ◽

Sediment Trapping ◽

Vegetative Filter Strips ◽

Filter Strips ◽

Sediment Movement ◽

Paired Samples ◽

Vegetative Barrier ◽

Velocity Flow ◽

Total Sediment ◽

Sampling Times

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.

Download Full-text

An improved method for the parameterization of sediment trapping in VFSMOD

10.5194/egusphere-egu21-117 ◽

2021 ◽

Author(s):

Stefan Reichenberger ◽

Robin Sur ◽

Stephan Sittig ◽

Sebastian Multsch ◽

Rafael Muñoz-Carpena

Keyword(s):

Surface Runoff ◽

Particle Diameter ◽

Sediment Trapping ◽

Vegetative Filter Strips ◽

Data Set ◽

Filter Strips ◽

Explanatory Variables ◽

Data Points ◽

Pesticide Load ◽

Event Based

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 (&#8710;Q) and reduction of incoming eroded sediment load (&#8710;E) mechanistically. These variables are subsequently used to calculate the reduction of pesticide load (&#8710;P). While &#8710;P can be relatively well predicted from &#8710;Q, &#8710;E and some other variables, errors in &#8710;Q and &#8710;E will propagate to &#8710;P. Hence, for strongly sorbing compounds, an accurate prediction of &#8710;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.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 &#181;m yielded a general overestimation of &#8710;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 &#181;m) 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).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 &#181;m) than the initial 16 events.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.

Download Full-text