SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Sensitivity analysis of the parameters of the SWAT model and simulation of the hydrosedimentological processes in a watershed in the northeastern region of Brazil 
Authors:de Aragão, r., M.A.S. Cruz, J.R.A. de Amorim, L.C. Mendonça, E.E. de Figueiredo and V.S. Srinivasan 
Journal:Revista Brasileira de Ciência do Solo 
Article ID: 
URL (non-DOI journals):http://www.scielo.br/scielo.php?script=sci_abstract&pid=S0100-06832013000400026&lng=en&nrm=iso&tlng=en 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:sediment loss and transport 
Secondary Application Category:hydrologic assessment 
Watershed Description:173.3 km^2 and 277.8 km^2 subwatersheds of the Japaratura River, in the state of Sergipe, in northeast Brazil 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Erosion has been recognized as the main cause of soil degradation and is accelerated by human intervention in watersheds, causing losses to the agricultural sector and damaging the environment. To estimate the impacts caused by land use or climate changes on hydrosedimentological processes, physically-based distributed models have been shown to be quite effective. In this study, the SWAT model was calibrated and validated for two subwatersheds of the Japaratuba Mirim river watershed, one located upstream of the Fazenda Pão de Açúcar - PA (137.3 km2), and another located upstream of Fazenda Cajueiro - CJ (277.8 km2) in the state of Sergipe, to simulate runoff and soil erosion. To test the sensitivity of the calibrated parameters, the runoff was also simulated by a cross application of the 12 most sensitive parameters in the two watersheds, from 1985 to 2000. The results showed that the model was able to simulate the runoff and forecast, in a consistent way, the sediment yield. However, while the cross application of the parameters from the bigger (CJ) to the smaller watershed (PA) resulted in satisfactory Nash-Sutcliffe efficiency (NSE) and percent bias (PBIAS), the opposite was not true. 
Keywords:water erosion, sediment yield, hydrologic modeling