Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model

Subsurface (or tile) drainage improves land productivity by enhancing soil aeration and preventing water-logged conditions. However, the continuous expansion of drained agricultural lands and reliance on synthetic fertilizer in the Midwestern United States have increasingly facilitated nitrate trans...

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Main Authors: Shailendra Singh, Soonho Hwang, Jeffrey G. Arnold, Rabin Bhattarai
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Agriculture
Subjects:
Online Access:https://www.mdpi.com/2077-0472/13/8/1484
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author Shailendra Singh
Soonho Hwang
Jeffrey G. Arnold
Rabin Bhattarai
author_facet Shailendra Singh
Soonho Hwang
Jeffrey G. Arnold
Rabin Bhattarai
author_sort Shailendra Singh
collection DOAJ
description Subsurface (or tile) drainage improves land productivity by enhancing soil aeration and preventing water-logged conditions. However, the continuous expansion of drained agricultural lands and reliance on synthetic fertilizer in the Midwestern United States have increasingly facilitated nitrate transport from agricultural fields to surface water bodies. Hence, there is a need to implement various agricultural best management practices (BMPs) in order to reduce the adverse water quality impacts resulting from excess nitrate, such as eutrophication and the formation of hypoxic zones. In this study, we used a SWAT+ model to assess the overall impacts on the riverine nitrate load and crop yield in the corn–soybean cropping system based on a combination of different management practices. The corn and soybean yields simulated with the model were found to be in good agreement with the observed yields for both the calibration and validation periods. The long-term simulation over a period of 30 years showed a reduction in the nitrate load of up to 32% without impacting the crop yield. The model results suggest that by reducing the current N application rate by 20% and using a 40:60 split between spring pre-plant and side-dressing N applications combined with cereal rye as a cover crop in corn–soybean rotation, one can potentially reduce nitrate losses without impacting crop yields. This study will help researchers, stakeholders, and farmers to explore and adopt alternative management practices beneficial for offsetting the environmental impacts of agricultural productions on the watershed scale.
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spelling doaj.art-d9017130c6b54a0e8436fc065dc33e902023-11-18T23:50:44ZengMDPI AGAgriculture2077-04722023-07-01138148410.3390/agriculture13081484Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ ModelShailendra Singh0Soonho Hwang1Jeffrey G. Arnold2Rabin Bhattarai3Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USADepartment of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USAAgricultural Research Service, United States Department of Agriculture, Temple, TX 76502, USADepartment of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USASubsurface (or tile) drainage improves land productivity by enhancing soil aeration and preventing water-logged conditions. However, the continuous expansion of drained agricultural lands and reliance on synthetic fertilizer in the Midwestern United States have increasingly facilitated nitrate transport from agricultural fields to surface water bodies. Hence, there is a need to implement various agricultural best management practices (BMPs) in order to reduce the adverse water quality impacts resulting from excess nitrate, such as eutrophication and the formation of hypoxic zones. In this study, we used a SWAT+ model to assess the overall impacts on the riverine nitrate load and crop yield in the corn–soybean cropping system based on a combination of different management practices. The corn and soybean yields simulated with the model were found to be in good agreement with the observed yields for both the calibration and validation periods. The long-term simulation over a period of 30 years showed a reduction in the nitrate load of up to 32% without impacting the crop yield. The model results suggest that by reducing the current N application rate by 20% and using a 40:60 split between spring pre-plant and side-dressing N applications combined with cereal rye as a cover crop in corn–soybean rotation, one can potentially reduce nitrate losses without impacting crop yields. This study will help researchers, stakeholders, and farmers to explore and adopt alternative management practices beneficial for offsetting the environmental impacts of agricultural productions on the watershed scale.https://www.mdpi.com/2077-0472/13/8/1484BMPscover cropfertilizer managementnitratesubsurface drainage
spellingShingle Shailendra Singh
Soonho Hwang
Jeffrey G. Arnold
Rabin Bhattarai
Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
Agriculture
BMPs
cover crop
fertilizer management
nitrate
subsurface drainage
title Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
title_full Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
title_fullStr Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
title_full_unstemmed Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
title_short Evaluation of Agricultural BMPs’ Impact on Water Quality and Crop Production Using SWAT+ Model
title_sort evaluation of agricultural bmps impact on water quality and crop production using swat model
topic BMPs
cover crop
fertilizer management
nitrate
subsurface drainage
url https://www.mdpi.com/2077-0472/13/8/1484
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AT jeffreygarnold evaluationofagriculturalbmpsimpactonwaterqualityandcropproductionusingswatmodel
AT rabinbhattarai evaluationofagriculturalbmpsimpactonwaterqualityandcropproductionusingswatmodel