TY  - SER
AU  - Nay Lin Htet 
AU  - Shrestha,Sangam
AU  - Duc Hoang Nguyen,
TI  - Calibration and validation of Soil and Water Assessment Tool (SWAT) model in the Bheri River Basin of Nepal
T2  - Caps. Proj.
PY  - 2018///
CY  - Pathum Thani
PB  - Asian Institute of Technology
KW  - Runoff
KW  - Nepal
KW  - Bheri River Basin
KW  - Hydrology
N1  - A capstone project report submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Engineering Civil and Infrastructure Engineering; Capstone Project (B.Sc.)-Asian Institute of Technology, 2018
N2  - Integration of hydrological models in management of watersheds resources are gaining pop-  ularity among researchers in the recent years. The Soil and Water Assessment Tool (SWAT)  is a model developed by the United State Department of Agriculture to predict the impact  of land management practices on hydrology, sediment and contaminant transport in large,  complex catchment. Many researchers around the globe have already applied SWAT in hy-  drological simulation at different time scales to investigate watershed quality.  In this research, SWAT model is applied in the simulation of Bheri River Basin, Nepal.  SWAT Calibration and Uncertainty Program (SWAT-CUP) is used for calibration, validation  and sensitivity analysis. The simulation is done for both daily and monthly time steps to  evaluate the SWAT effectiveness. The calibration period is from 1999 to 2006 with 4-year  skip period (1995-1998) and the validation is done from 2007 to 2013.  The statistical results show that the performance of the SWAT model for Bheri River Basin is  quite good, having the NSE value of 0.77 and R2 value of 0.87 for daily calibration and 0.62  and 0.67 for daily validation respectively. Monthly values are better (NS=0.86, R2=0.87)  for calibration and (NS=0.71, R2-0.71) for validation respectively. Comparing the daily and  monthly values reveals that SWAT is better at long term simulations with large watershed  areas.  Baseflow alpha factor for bank storage (ALPHA~NK) is found to be the most sensitive  parameter while the deep aquifer percolation factor (RCHRGJ)P) was the least sensitive.  The annual precipitation is 756.1 mm and the basins highest water yield rate is found to be during the period between June and September.
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B13626
ER  -