A popular semi-distributed model for watershed hydrological study is the Soil and Water Assessment Tool (SWAT). The SWAT-CUP model's uncertainty analysis capability now has the ability to integrate ParaSol, Sequential Uncertainty Fitting (SUFI-2), Generalized Likelihood Uncertainty Estimation (GLUE), Particle Swarm Optimisation, and Markov Chain Monte Carlo (MCMC) into a single platform. In the current work, the SWAT model was calibrated for the years 1994 to 2005 while using the first three years as a warm-up phase (1990 to 1993) and validated for monthly streamflow simulation from 2006 to 2015. For Bramhani River Basin the SUFI-2 technique was used for the uncertainty analysis was performance. For sensitivity analysis, ten notable parameters were chosen. Nash-Sutcliffe Efficiency (NSE), the coefficient of determination (R2), and Percentage BIAS (PBIAS) were used to evaluate the model's performance on a monthly time scale streamflow simulation. The P and R variables were utilized to determine how much ambiguity there was. During the calibration period, the values of NSE, R2, and PBIAS were determined to be 0.80, 0.81, and -0.08; and for the validation period, they were 0.72, 0.76, and -0.17, respectively. During calibration, the P and R factor values were observed to be 0.77 and 0.89, respectively, and 0.86 and 0.82, respectively, during the validation period. During the calibration and validation periods, the simulated streamflow is also well matched within the 95 percent prediction uncertainty (95PPU) range of the SUFI-2 method, suggesting an acceptable performance of the model under parameter uncertainty.

SWAT, SUFI-2, Streamflow, uncertainty analysis, sensitivity parameter

The current study demonstrates how to utilise the SWAT model to simulate streamflow catchment of the Indian Brahmani River Basin, identify the parameters that are most sensitive, and quantify model parameter uncertainty using the SUFI-2 method. The pre-calibration uncertainty analysis resulted in the identification and ranking of sensitive parameters. The statistics show that nine variables are very sensitive and significantly affect streamflow. The soil conservation service curve number for AMC II factor has been shown to be the most sensitive parameter for the Brahmani river basin. The model's monthly streamflow simulation during the streamflow calibration by SUFI-2 was found to have excellent NSE, R2, and PBIAS values. These numbers were, respectively, 0.80, 0.81, and -0.08. The model performance is reassuringly sufficient, as evidenced by the validation's NSE, R2, and PBIAS values of 0.72, 0.76, and -0.17, respectively. Given the parameter uncertainty, the model performance is rather good, as indicated by P and R factor values of 0.77 and 0.89 during calibration and 0.86 and 0.82 throughout the validation period, respectively. The results of the model simulation indicate that the SWAT model may be successfully applied for streamflow simulation under parameter uncertainty in an ungauged watershed.

Sonali Swagatika, Jagdish Chandra Paul, Ambika Prasad Sahu, Dwarika Mohan Das and Alok Kumar Patra (2022). Streamflow Simulation of Brahmani River Basin using SWAT Model. Biological Forum – An International Journal, 14(3): 1707-1714.