Please use this identifier to cite or link to this item:
|Title:||RAINFALL-RUNOFF MODELING OF A WATERSHED USING SWAT MODEL|
Nash and Sutcliffe Efficiency (NSE)
|Abstract:||The present study was undertaken with an aim to test the performance of SWAT model on Sher River at Belkheri in Narsimhpur District of Madhya Pradesh, India. Sher River is fairly big tributary of Narmada River joining from left side. For model application, the watershed area was divided into 11 sub-watersheds. The watershed comprises mainly of 6 land use (with more than 60% agriculture area coverage), slope mostly ranges from 0-10 (more than 80%). Available hydrological data (i.e. from 1995-2008) was split into two groups for calibrating and validating parameter of the model (1995 and 1996 was taken as warm up periods). The model was calibrated at Belkheri gauging site both on daily and monthly basis time scale. The model was auto-calibrated and validated using SWAT cup SUFI-2 software. Model performance was analyzed based on quantitative statistical analysis and visual comparison between observed and simulated flows. Nash and Sutcliffe Efficiency (NSE) was taken as the main objective function during calibration and validation. The average daily calibration and validation showed good model response with NSE of 0.724 and 0.765 respectively. Also the monthly calibration and validation showed good model fit with NSE of 0.87 and 0.88 respectively. The study was also carried out to perform the sensitivity analysis of different parameters responsible for streamflow generation. Based on the analysis, OV_N and SLSUBBSN followed by GW_DELAY, CN2, GWQMN, GW_REVAP and SOL_AWC were found to be the most sensitive parameters. Overall, the performance of the model in simulating streamflow at Belkheri gauging site can be rated as very good and the calibrated model could be used for runoff simulation for this agriculture dominating watershed|
|Appears in Collections:||DOCTORAL THESES (Hydrology)|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.