Modeling and prioritizing interventions using pollution hotspots for reducing nutrients, atrazine and e. Coli concentrations in a watershed

Olufemi Abimbola; Aaron Mittelstet; Tiffany Messer; Elaine Berry; Ann van Griensven

doi:10.3390/su13010103

Modeling and prioritizing interventions using pollution hotspots for reducing nutrients, atrazine and e. Coli concentrations in a watershed

Olufemi Abimbola, Aaron Mittelstet, Tiffany Messer, Elaine Berry, Ann van Griensven

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

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.

Original language	English
Article number	103
Pages (from-to)	1-22
Number of pages	22
Journal	Sustainability (Switzerland)
Volume	13
Issue number	1
DOIs	https://doi.org/10.3390/su13010103
State	Published - Jan 1 2021

Bibliographical note

Funding Information:
This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

Funding Information:
Funding: This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

Publisher Copyright:
© 2020 by the authors. Li-censee MDPI, Basel, Switzerland.

Keywords

Atrazine
Best management practices
Big Sandy Creek Watershed (BSCW)
E. coli
Nutrients
Soil and Water Assessment Tool (SWAT)

ASJC Scopus subject areas

Geography, Planning and Development
Renewable Energy, Sustainability and the Environment
Environmental Science (miscellaneous)
Energy Engineering and Power Technology
Management, Monitoring, Policy and Law

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3390/su13010103

Cite this

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title = "Modeling and prioritizing interventions using pollution hotspots for reducing nutrients, atrazine and e. Coli concentrations in a watershed",

abstract = "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{\textquoteright}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.",

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author = "Olufemi Abimbola and Aaron Mittelstet and Tiffany Messer and Elaine Berry and {van Griensven}, Ann",

note = "Funding Information: This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Funding Information: Funding: This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Publisher Copyright: {\textcopyright} 2020 by the authors. Li-censee MDPI, Basel, Switzerland.",

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AU - Berry, Elaine

AU - van Griensven, Ann

N1 - Funding Information: This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Funding Information: Funding: This research was funded by the U.S. Department of Agriculture—National Institute of Food and Agriculture (Hatch project NEB-21-177). The authors also thank the Nebraska Department of Environment and Energy (NDEE) for the support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. Publisher Copyright: © 2020 by the authors. Li-censee MDPI, Basel, Switzerland.

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AB - 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.

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KW - E. coli

KW - Nutrients

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Modeling and prioritizing interventions using pollution hotspots for reducing nutrients, atrazine and e. Coli concentrations in a watershed

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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