Theses and Dissertations

Issuing Body

Mississippi State University


Parajuli, Prem B.

Committee Member

Linhoss, Anna C.

Committee Member

Schmitz, Darrel W.

Committee Member

Ouyang, Ying

Date of Degree


Document Type

Dissertation - Open Access


Biological Engineering

Degree Name

Doctor of Philosophy


James Worth Bagley College of Engineering


Department of Agricultural and Biological Engineering


This study used the Soil and Water Assessment Tool (SWAT) to model 2 watersheds in Mississippi, which are the Lower Pearl River Watershed (LPRW) and the Big Sunflower River Watershed (BSRW), to simulate streamflow, groundwater storage and recharge, sediments, nutrients, and bacteria transport. The LPRW model was calibrated and validated for daily streamflow at 4 locations with R2 ranging from 0.49 to .90 and Nash-Sutcliffe Efficiency (NSE) ranging from 0.49 to 0.84. In the BSRW, the model showed good to very good performance for daily streamflow simulation (R2 = 0.53-0.75 and NSE = 0.49-0.72) and seasonal groundwater table depth fluctuations (R2 = 0.76 to 0.86 and NSE = 0.71-0.79). The BSRW model was also calibrated and validated for total sediment (TS) load (R2 = 0.50-0.72, NSE = 0.47-0.66), total phosphorus (TP) load (R2 = 0.79-0.82, NSE = 0.73-0.77), and fecal coliform bacteria concentrations (R2 = 0.56-0.60 and NSE = 0.23-0.40). In the LPRW, the effectiveness of grassed waterways, detention ponds, and parallel terraces Best Management Practices (BMPs) to attenuate peak streamflow decreases significantly under increased rainfall and under increased CO2 concentration climate change scenarios; however, under increased temperature or decreased rainfall, the effectiveness of BMPs to reduce peak streamflows did not significantly change. In the BSRW, implementing crop rotations practices with rice resulted in the lowest groundwater storage (-10.7%), but it also led to the highest increases in monthly groundwater recharge (up to +60.1%). The crop rotations with corn and cotton usually resulted in the largest increases in groundwater storage (up to +27.2%). The BSRW was modeled to assess the sensitivity of bacteria concentrations to climate change, and this study determined that bacteria concentrations were most sensitive to rainfall, followed by temperature, solar radiation, and CO2 concentrations. The BSRW model also showed significant parameter uncertainty in the streamflow, TS load, TP load, and total nitrogen (TN) load simulations, and that equifinal parameter sets exist in the model. Moreover, the SWAT parameters that were sensitive to streamflow were also found to be sensitive to sediment and nutrient transport.