SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Uncertainty in a lumped and a semi-distributed model for discharge prediction in Ghatchila Catchment 
Authors:Yaduvanshi, A., P. Srivastava, A.W. Worqlul and A.K. Sinha 
Volume (Issue):10(4) 
Article ID:381 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:model comparison 
Secondary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Watershed Description:14,176 km^2 Ghatshila River, a tributary of the Subarnarekha River in northeast India. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Hydrologic simulations of different models have direct impact on the accuracy of discharge prediction because of the diverse model structure. This study is an attempt to comprehend the uncertainty in discharge prediction of two models in the Ghatshila catchment, Subarnarekha Basin in India. A lumped Probability Distribution Model (PDM) and semi-distributed Soil and Water Assessment Tool (SWAT) were applied to simulate the discharge from 24 years of records (1982–2005), using gridded ground based meteorological variables. The results indicate a marginal outperformance of SWAT model with 0.69 Nash-Sutcliffe (NSE) for predicting discharge as compared to PDM with 0.62 NSE value. Extreme high flows are clearly depicted in the flow duration curve of SWAT model simulations. PDM model performed well in capturing low flows. However, with respect to input datasets and model complexity, SWAT requires both static and dynamic inputs for the parameterization of the model. This work is the comprehensive evaluation of discharge prediction in an Indian scenario using the selected models; ground based gridded rainfall and meteorological dataset. Uncertainty in the model prediction is established by means of Generalized Likelihood Uncertainty Estimation (GLUE) technique in both of the models. 
Keywords:SWAT; PDM; GLUE; model structure; discharge