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; R² = 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; R² = 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.

Harmful algal blooms (HABs) are increasingly a global concern and the issue of all fifty states in the U.S as it poses a threat to human health and aquatic ecosystem. This study aimed to investigate the relationship of HABs with streamflow and water quality parameters and assess the hydrology-based potential future HABs in the Ohio River Basin at Ironton (ORBI) using the Soil and Water Assessment Tool (SWAT). SWAT was calibrated and validated against potential HABs indicators including streamflow, total suspended solids (TSS), and dissolved oxygen (DO) with acceptable accuracies. Twenty-one years (2002-2022) of model simulated data were analyzed to relate the 2015 HABs occurrence in the Ohio River with unique temperature, streamflow, TSS, and DO conditions. Additionally, a future climate model was developed to project these variables for the next two decades (2023-2043) using data from the Canadian Regional Climate Model (CRCM5) for Representative Concentration Pathway (RCP) 4.5. The 2015 HABs formation was found to be associated with a series of high flows contributing to high nutrient transport followed by an extended period of low flows balancing nutrients flushing rate. The projections of average temperature, streamflow, and TSS concentration showed increments of 5%, 15%, and 28%; whereas DO concentration showed a decrement of 8%. Flood frequency analysis was conducted to better understand the HABs probability related to peak flow conditions. For the base condition, results showed 3% probability of peak flow (4550 m³/s) associated with 2015 HABs formation at the Ironton gauge station and 20% probability of the same flow in the next two decades demonstrating an increased risk of HABs and highlighting the necessity of mitigation measure implementations.

Change in land use and land cover (LULC) is crucial to freshwater ecosystems as it affects surface runoff, groundwater storage, and sediment and nutrient transport within watershed areas. Ecosystem components such as wetlands, which can contribute to the reduction of water pollution and the enhancement of groundwater recharge, are altered by LULC modifications. This study evaluates how wetlands in the Big Sunflower River Watershed (BSRW) have changed in recent years and quantified their impacts on streamflow, water quality, and groundwater storage using the Soil and Water Assessment Tool (SWAT). The model was well calibrated and validated prior to its application. Our study showed that the maximum increase in wetland areas within the sub-watersheds of interest was 26% from 2008 to 2020. The maximum changes in reduction due to the increase in wetland areas were determined by 2% for streamflow, 37% for total suspended solids, 13% for total phosphorus (TP), 4% for total nitrogen (TN), and the maximum increase in shallow groundwater storage by 90 mm from 2008 to 2020 only in the selected sub-basins. However, the central part of the watershed experienced average declines of groundwater levels up to 176 mm per year due to water withdrawal for irrigation or other uses. This study also found that restoration of 460 to 550 ha of wetlands could increase the reduction of discharge by 20%, sediment by 25%, TN by 18%, and TP by 12%. This study highlights the importance of wetland conservation for water quality improvement and management of groundwater resources.

Best management practices (BMPs) are management operations that reduce pollution and improve water quality. This study assessed the spatial variability of BMPs effectiveness within the Yazoo River Watershed (YRW) using Soil and Water Assessment Tool (SWAT). Two field-scale watersheds, Merigold Watershed (MW) from the Delta and Skuna River Watershed (SRW) in the Bluff Hills, were selected within the YRW. The SWAT model was calibrated and validated for monthly streamflow, and daily total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Monthly evaluated streamflow Nash–Sutcliffe efficiency indices were in the range from 0.60 to 0.86; daily evaluated TSS indices were in the range from 0.11 to 0.15, TN from 0.11 to 0.12, and TP from 0.05 to 0.26 during model calibration and validation periods. BMPs were implemented in MW and SRW to analyze the spatial variability effect on water quality. Cover crops (CC), vegetative filter strips (VFS), and a combination of VFS and CC were applied as BMP scenarios. Overall, a larger reduction in streamflow was about 15%, sediment about 26%, and nutrient loads, which was about 39% (TN) and 50% (TP), was determined in the MW, whereas in the large watershed (YRW) the reductions in streamflow, sediment, TN, and TP loads were about 4%, 5%, 30%, and 24%, respectively. Therefore, the novelty of this research is to compare the efficiency of a BMP in pollutant reduction at two different geographic scales. The results from this study could help farmers, scientific researchers, precision management planning, and implementing agencies select appropriate BMP for field-scale water resources management in minimizing sediment and nutrient quantities in surface water.

Implementing best management practices (BMPs) has proven to be an efficient method for reducing non-point source (NPS) pollutants. Agricultural NPS pollution is considered to be a major contributor to water quality impairment. This study aims to assess the variation in hydrologic and water quality outputs at field and watershed scales when BMPs are implemented using modeling approaches. The Yazoo River Watershed (YRW) is the largest watershed basin in the state of Mississippi with approximately 50% agricultural land. Runoff generated from agricultural areas carries sediments and nutrients. The Merigold watershed (MW) is a sub-basin of the YRW and a field-scale watershed with most of the land use being agriculture. It is essential to quantify the streamflow, sediment, total nitrogen (TN), and total phosphorus (TP) when BMPs are implemented. BMPs such as vegetative filter strips (VFS) and cover crops (CC) were tested in this study. The Soil and Water Assessment Tool (SWAT) model was applied to quantify the watershed’s hydrologic and water quality outputs. SWAT model accuracy assessment was performed by calibration and validation process using the Nash and Sutcliffe Efficiency Index (NSE). Model performance was satisfactory for monthly streamflow, with NSE values in the range of 0.62 to 0.81, and for daily sediments, TN, and TP load estimation, with NSE values of 0.21, 0.20, and 0.47, respectively. CC was planted after harvesting the main crop. Therefore, it is essential to quantify the seasonal reduction in pollutants. Water quality was improved after BMP implementation, and an overall decrease in streamflow, sediment, TN, and TP loads was observed for both MW and YRW during dry and wet seasons. Previous studies regarding seasonal assessments with CC implementation in the MW and YRW were limited. Therefore, the results from this study could be a unique addition to the scientific literature.