filter strip
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2021 ◽  
Author(s):  
Kyle R Douglas-Mankin

This Dataset was compiled from cited literature in support of the review article "Douglas-Mankin KR, Helmers MJ, Harmel RD. 2021. Review of filter strip performance and function for improving water quality from agricultural lands. <i>Trans. ASABE</i>, 64(2). https://doi.org/10.13031/trans.14169", which summarizes, analyzes, and interprets data from 74 published studies to assess filter strip effectiveness in reducing sediment, nutrients, pesticides, and pathogens from agricultural lands. Journal article will be online April 2021.


2021 ◽  
Author(s):  
Kyle Douglas-Mankin

This Dataset was compiled from cited literature in support of the review article "Douglas-Mankin KR, Helmers MJ, Harmel RD. 2021. Review of filter strip performance and function for improving water quality from agricultural lands. <i>Trans. ASABE</i>, 64(2). https://doi.org/10.13031/trans.14169", which summarizes, analyzes, and interprets data from 74 published studies to assess filter strip effectiveness in reducing sediment, nutrients, pesticides, and pathogens from agricultural lands. Journal article will be online April 2021.


2021 ◽  
Author(s):  
Kyle R Douglas-Mankin

This Dataset was compiled from cited literature in support of the review article "Douglas-Mankin KR, Helmers MJ, Harmel RD. 2021. Review of filter strip performance and function for improving water quality from agricultural lands. <i>Trans. ASABE</i>, 64(2). https://doi.org/10.13031/trans.14169", which summarizes, analyzes, and interprets data from 74 published studies to assess filter strip effectiveness in reducing sediment, nutrients, pesticides, and pathogens from agricultural lands. Journal article will be online April 2021.


2021 ◽  
Vol 64 (2) ◽  
pp. 659-674
Author(s):  
Kyle R. Douglas-Mankin ◽  
Matthew J. Helmers ◽  
R. Daren Harmel

HighlightsFilter strip processes for water pollutant reductions were quantified from 74 studies with almost 300 data points.Regression was significant versus width (sediment, N, P), area ratio (sediment, atrazine), and Ks (N, P, atrazine, alachlor).This review discusses ten functional factors affecting FS efficiency as well as FS monitoring recommendations.Cost-effectiveness was assessed and varies considerably by influent load and treatment effectiveness.Abstract. Filter strips (FSs) are edge-of-field conservation practices commonly implemented to reduce flux of sediment, nutrients, and other constituents from agricultural fields. While various aspects of FS effectiveness have been reviewed, this study provides a comprehensive summary of FS efficiency data for sediment, nutrients, pesticides, and pathogens as part of a special collection focused on agricultural conservation practices. This analysis also fills an important gap by assessing performance-based FS costs and cost-effectiveness. Data from 74 U.S. and international studies with 294 different treatments and 3,050 replications were compiled and analyzed. Results showed that runoff reduction tended to increase with increasing FS width up to about 15 m and that sediment reduction was significantly related to the ratio of FS area to drainage area and to FS width, with reduction tending to increase with increasing width up to about 20 m. Total P reduction was significantly related to FS soil saturated hydraulic conductivity, and total N reduction was significantly related to both saturated hydraulic conductivity and width. Total P and total N reductions both tended to increase with increasing FS width up to about 20 m and with increasing FS slope up to about 10%. Annualized FS costs were estimated to range from $314 to $865 ha-1 year-1 for different FS implementations. A major component of the cost is the opportunity cost of taking land out of production. Costs per unit of sediment retained by FS systems ranged from $10.3 to $18.6 Mg-1. A comprehensive assessment of FS cost-effectiveness (cost:benefit) is needed. Monitoring equipment, approaches, and recommendations are discussed, acknowledging the challenges of implementing field-scale FS studies. This information is critical to guide on-farm and programmatic FS decisions and to increase the scientific understanding of this commonly used agricultural conservation practice. Keywords: Best management practice, Buffer strip, Nonpoint-source pollution, Riparian buffer, Vegetated filter strip.


2020 ◽  
Vol 13 (1) ◽  
pp. 103
Author(s):  
Olufemi Abimbola ◽  
Aaron Mittelstet ◽  
Tiffany Messer ◽  
Elaine Berry ◽  
Ann van Griensven

Excess nutrients and herbicides remain two major causes of waterbody impairment globally. In an attempt to better understand pollutant sources in the Big Sandy Creek Watershed (BSCW) and the prospects for successful remediation, a program was initiated to assist agricultural producers with the implementation of best management practices (BMPs). The objectives were to (1) simulate BMPs within hotspots to determine reductions in pollutant loads and (2) to determine if water-quality standards are met at the watershed outlet. Regression-based load estimator (LOADEST) was used for determining sediment, nutrient and atrazine loads, while artificial neural networks (ANN) were used for determining E. coli concentrations. With respect to reducing sediment, total nitrogen and total phosphorus loads at hotspots with individual BMPs, implementing grassed waterways resulted in average reductions of 97%, 53% and 65% respectively if implemented all over the hotspots. Although reducing atrazine application rate by 50% in all hotspots was the most effective BMP for reducing atrazine concentrations (21%) at the gauging station 06883940, this reduction was still six times higher than the target concentration. Similarly, with grassed waterways established in all hotspots, the 64% reduction in E. coli concentration was not enough to meet the target at the gauging station. With scaled-down acreage based on the proposed implementation plan, filter strip led to more pollutant reductions at the targeted hotspots. Overall, a combination of filter strip, grassed waterway and atrazine rate reduction will most likely yield measureable improvement both in the hotspots (>20% reduction in sediment, total nitrogen and total phosphorus pollution) and at the gauging station. Despite the model’s uncertainties, the results showed a possibility of using Soil and Water Assessment Tool (SWAT) to assess the effectiveness of various BMPs in agricultural watersheds.


2019 ◽  
Vol 35 (3) ◽  
pp. 271-281 ◽  
Author(s):  
Anand Krishna Gupta ◽  
Ramesh Pal Rudra ◽  
Bahram Gharabaghi ◽  
Pradeep Kumar Goel ◽  
Saleh Sebti ◽  
...  

Abstract. Vegetative filter strips (VFS) are globally recognized as an effective BMP in reducing non-point source pollution. Maximum effectiveness of a VFS at a watershed-level could be achieved by adequately installing and sizing a VFS along the edge of the field. Existing watershed models have limitations in appropriately representing and modeling VFS at the watershed scale. Therefore, in this research, a new modeling approach consisting of the Agricultural Non-Point Source (AGNPS) model, AGNPS_VFS toolkit, and a regression equation is developed to explore the effectiveness of VFS applied along the edge of fields. AGNPS cells are identified as locations where the edge of the field VFS is to be installed. Further, the approach was tested with a case study. The model was calibrated and validated for a flow and sediment load at the watershed outlet. Thereafter, the modeling approach is used to compute sediment reducing efficiency (SRE) for the edge of the field VFS. Objectives of this study were to test the effectiveness of uniform VFS (5 × 18 m) lengths located at several locations (draining an upstream area of 3, 4, 6 ha, and at spatially variable locations) within a watershed to demonstrate the ability of the developed approach to evaluate effectiveness of VFS application in sediment abatement. Maximum SRE was observed for VFS placed at spatially variable locations; the developed approach reduced nearly 23.03% of sediment yield, while VFS placed along cells draining an upstream area of 3, 4, and 6 ha removed 9.59%, 12.39%, and 5.91% of sediment loads respectively. Keywords: Non-point source pollution, Sediment transport, Vegetative filter strip (VFS), VFSMOD.


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