Climate change-induced extreme precipitation causes coastal flooding. A streamflow simulation in coastal watersheds, Wolf River Watershed (WRW) and Jourdan River Watershed (JRW), was conducted using the Soil and Water Assessment Tool (SWAT) to compare variation in flow at different climates and to analyze the flood frequency. Baseline models were auto-calibrated with SWAT calibration and uncertainty programs (SWAT-CUP). Kling–Gupta efficiency (KGE), defined as the objective function in SWAT-CUP, ranged from 0.8 to 0.7 in WRW and from 0.55 to 0.68 in JRW during the calibration–validation process. Results indicated reliability of the model performances. Monthly averaged baseline flow was 1% greater than historical and 8.9% lower than future climate in WRW. In JRW, monthly averaged baseline flow was 11% greater than historical and 5.7% lower than future climate. Flood frequency analysis showed the highest 1% exceedance probability in annual maximum series (AMS) of baseline model in WRW, whereas AMS of projected model was estimated the highest in JRW. This study aids in preparing for future flood management.

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.

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.

Sediment deposition in river channels from various topographic conditions has been one of the major contributors to water quality impairment through non-point sources. Soil is one of the key components in sediment loadings, during runoff. Yazoo River Watershed (YRW) is the largest watershed in Mississippi. Topography in the watershed has been classified into two types based on land-use and slope conditions: Delta region with a slope ranging from 0% to 3% and Bluff hills with a slope exceeding 10%. YRW spans over 50,000 km²; the Soil and Water Assessment Tool (SWAT) was used to estimate soil-specific sediment loss in the watershed. Soil predominance was based on spatial coverage; a total of 14 soil types were identified, and the sediment contributed by those soils was quantified. The SWAT model was calibrated and validated for streamflow, sediment, Total Nitrogen (TN), Total Phosphorus (TP), and Crop yield for soybeans. Model performance was evaluated using the Coefficient of determination (R²), Nash and Sutcliffe Efficiency index (NSE), and Mean Absolute Percentage Error (MAPE). The performance was good for streamflow, ranging between 0.34 and 0.83, and 0.33 and 0.81, for both R² and NSE, respectively. Model performance for sediment and nutrient was low-satisfactory as R² and NSE ranged between 0.14 and 0.40, and 0.14 and 0.35, respectively. In the case of crop yield, model performance was satisfactory during calibration and good for validation with an R² of 0.56 and 0.76 and with a MAPE of 11.21% and 10.79%, respectively. Throughout YRW, soil type Smithdale predicted the highest sediment loads with 115.45 tons/ha/year. Sediment loss in agricultural fields with a soybean crop was also analyzed, where soil type Alligator predicted the highest with 8.37 tons/ha/year. Results from this study demonstrate a novel addition to the scientific community in understanding sediment loads based on soil types, which can help stakeholders in decision-making toward soil conservation and improving the environment.

This study investigates the neurophysiological and biomechanical factors contributing to successful basketball throw performance in novice athletes, utilizing electroencephalography (EEG) and motion capture (MoCap) to analyze joint angles, ground reaction forces (GRFs), and brain activity. Sixteen participants performed basketball throws while EEG and MoCap systems recorded data on movement mechanics and neural activity. Biomechanical findings revealed that successful trials were characterized by refined movements, reduced wrist extension, increased elbow flexion, and more stable foot positioning compared to unsuccessful trials (all p > 0.05), contributing to greater shot accuracy. Reduced movement variability in successful trials further indicated improved motor consistency, reflective of skill development. EEG results showed higher beta and gamma power in the temporal lobe during successful compared to unsuccessful trials (p < 0.05), suggesting increased engagement in visuomotor integration and neural efficiency. Notably, our novice participants demonstrated limited neural efficiency in frontal regions (p > 0.05), potentially due to cognitive interference and self-monitoring. These findings highlight the importance of coordinated biomechanical execution and neural efficiency in optimizing basketball performance. The insights gained have practical implications for designing training interventions that improve motor performance, particularly for novice athletes.