Calibration and validation of Soil and Water Assessment Tool (SWAT) model in the Bheri River Basin of Nepal | |
| Author | Nay Lin Htet |
| Call Number | AIT Caps. Proj. no.CIE-18-28 |
| Subject(s) | Runoff--Nepal--Bheri River Basin Hydrology--Nepal--Bheri River Basin |
| Note | A capstone project report submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Engineering Civil and Infrastructure Engineering |
| Publisher | Asian Institute of Technology |
| Series Statement | Caps. Proj. ; no. CIE-18-28 |
| Abstract | 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. |
| Year | 2018 |
| Corresponding Series Added Entry | Asian Institute of Technology. Caps. Proj. ; no. CIE-18-28 |
| Type | Capstone Project |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Civil and Infrastructure Engineering (CIE) |
| Chairperson(s) | Shrestha, Sangam; |
| Examination Committee(s) | Duc Hoang Nguyen; |
| Degree | Capstone Project (B.Sc.)-Asian Institute of Technology, 2018 |