SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Improving streamflow prediction using uncertainty analysis and bayesian model averaging 
Authors:Neto, A.A.M., P.T.S. Oliveira, D.B.B. Rodrigues and E. Wendland 
Year:2018 
Journal:Journal of Hydrologic Engineering 
Volume:23(5) 
Pages: 
Article ID:05018004 
DOI:10.1061/(ASCE)HE.1943-5584.0001639 
URL (non-DOI journals):https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0001639 
Model:SWAT 
Broad Application Category:hydrologic only 
Primary Application Category:uncertainty analysis 
Secondary Application Category:hydrologic assessment 
Watershed Description:65 km^2 Ribeir˜ao da Onça drainage area, located in the municipality of Brotas in the central part of S˜ao Paulo State in southeast Brazil. 
Calibration Summary: 
Validation Summary: 
General Comments:As of April 9, 2018 the DOI for this article does not work but the URL does. 
Abstract:Hydrological modeling has been used worldwide as an important tool to evaluate the consequences of land cover and land use change on hydrological processes. However, the lack of spatial-temporal rainfall and runoff data have compromised the reliability of the results in several regions of Brazil. In this study, the authors investigated the use of uncertainty analysis and Bayesian model averaging (BMA) as a tool for improving streamflow estimates in the Ribeir˜ao da Onça Basin (ROB), located in southeastern Brazil. They used a set of two precipitation data sources (ground and remote sensing data) and different spatial interpolation schemes as input data for the Soil and Water Assessment Tool (SWAT) model, resulting in five model configurations. These models were submitted to automatic calibration and uncertainty analysis through the sequential uncertainty fitting ver-2 (SUFI-2) method. Then, the BMA method was used to merge those different model configuration results into a single probabilistic prediction, thereafter compared among themselves. An analysis of the accuracy and precision of all simulations produced by the precipitation ensemble members against the BMA simulation supports the use of the latter as a suitable framework for streamflow simulations at the ROB. Furthermore, the approaches evaluated in this study may be used to improve streamflow predictions in ungauged or data-scarce basins. 
Language:English 
Keywords:Bayesian model averaging; Hydrological modeling; Soil and Water Assessment Tool (SWAT) model; Uncertainty analysis.