Assessment of Best Management Practices on Hydrology and Sediment Yield at Watershed Scale in Mississippi Using SWAT

Dipesh Nepal and Prem B. Parajuli
Additional contact information
Dipesh Nepal: Department of Agricultural and Biological Engineering, Mississippi State University, Starkville, MS 39762, USA
Prem B. Parajuli: Department of Agricultural and Biological Engineering, Mississippi State University, Starkville, MS 39762, USA

Agriculture, 2022, vol. 12, issue 4, 1-19

Abstract: The selection and execution of appropriate best management practices (BMPs) in critical areas of a watershed can effectively reduce sediment yield. Objectives of this research include developing a watershed-scale Soil and Water Assessment Tool (SWAT) model for the Big Sunflower River Watershed (BSRW), identifying high sediment yield areas using calibrated and validated model, and assessing the effects of various BMPs. The efficiency of three BMPs, grassed waterways (GWW), vegetative filter strips (VFS), and grade stabilization structures (GSS), and their combinations in reducing sediment yield, were investigated. The model performed well for streamflow (P-factor = 0.72–0.87; R-factor = 0.74–1.27; R 2 = 0.60–0.86; NSE = 0.60–0.86) and total suspended solids (TSS) (P-factor = 0.56–0.89; R-factor = 0.43–2.83; R 2 = 0.62–0.91; NSE = 0.38–0.91) during calibration and validation. The simulation of individual BMPs revealed that GWW showed the highest sediment yield reduction (up to 44%), followed by VFS (up to 38%) and GSS (up to 7%). Two BMPs’ combinations showed that GSS and GWW had the largest sediment yield reduction potential (up to 47%) while VFS and GSS had the lowest potential (up to 42%). Similarly, a combination of all three BMPs reduced the sediment yield up to 50%. The findings of this study will aid in sustainable watershed management and will be valuable for watershed managers and planners.

Keywords: best management practices (BMPs); SWAT; flow; model; sediment yield; watershed (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2077-0472/12/4/518/pdf (application/pdf)
https://www.mdpi.com/2077-0472/12/4/518/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:12:y:2022:i:4:p:518-:d:787647

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().