Next Article in Journal
Introduction to Special Issue on “The System of Rice Intensification (SRI)—Contributions to Agricultural Sustainability”
Next Article in Special Issue
Impacts of High-Frequency Chicken Manure Biochar Application on N2O and CH4 Emissions from Vegetable Field in Subtropical China
Previous Article in Journal
Compatibility of Native Strains of Beauveria peruviensis and Metarhizium sp. as Strategy for Biological Control of Coffee Berry Borer (Hypothenemus hampei, Ferrari)
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions

1
School of Environment and Energy Engineering, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagi-ro, Gwangju 61005, Republic of Korea
2
Department of Civil and Environmental Engineering, Konkuk University-Seoul, 120, Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(5), 906; https://doi.org/10.3390/agronomy14050906
Submission received: 3 April 2024 / Revised: 22 April 2024 / Accepted: 23 April 2024 / Published: 26 April 2024

Abstract

Effective management of water quality in watersheds is crucial because it is directly linked to the sustainability of aquatic ecosystems. In conventional watershed management, best management practices (BMPs) have been instrumental in addressing deteriorating water quality issues caused by non-point source pollution. Greenhouse gas (GHG) emissions have emerged as a global concern, necessitating immediate and diverse environmental actions to mitigate their impacts. This study aims to explore BMPs that maximize total phosphorus (TP) load removal efficiencies, while minimizing costs and GHG emissions within watersheds, using the Soil and Water Assessment Tool (SWAT) and non-dominated sorting genetic algorithm III (NSGA-III). The Yeongsan River Watershed between 2012 and 2021 was selected as the study area. Hydrological and BMP data were analyzed. Applying identical BMPs to the watershed showed that the BMPs with high TP removal efficiency may not be effective in terms of cost and GHG emissions. Therefore, the optimal combination of BMPs for the Yeongsan River Watershed was determined using NSGA-III considering TP removal efficiency, cost, and GHG emissions. This study is the first to consider GHG emissions at the watershed level when applying BMPs and is expected to contribute to the development of BMP implementation incorporating GHG emissions.
Keywords: greenhouse gas emissions; best management practices; Soil and Water Assessment Tool; non-dominated sorting genetic algorithm III greenhouse gas emissions; best management practices; Soil and Water Assessment Tool; non-dominated sorting genetic algorithm III

Share and Cite

MDPI and ACS Style

Jeong, D.S.; Kim, J.H.; Kim, J.H.; Park, Y. Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions. Agronomy 2024, 14, 906. https://doi.org/10.3390/agronomy14050906

AMA Style

Jeong DS, Kim JH, Kim JH, Park Y. Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions. Agronomy. 2024; 14(5):906. https://doi.org/10.3390/agronomy14050906

Chicago/Turabian Style

Jeong, Dae Seong, Joon Ha Kim, Jin Hwi Kim, and Yongeun Park. 2024. "Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions" Agronomy 14, no. 5: 906. https://doi.org/10.3390/agronomy14050906

APA Style

Jeong, D. S., Kim, J. H., Kim, J. H., & Park, Y. (2024). Evaluation of the Best Management Practices for Reducing Phosphorus Load in a Watershed in Terms of Cost and Greenhouse Gas Emissions. Agronomy, 14(5), 906. https://doi.org/10.3390/agronomy14050906

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop