SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Modelling the ffects of historical and future land cover changes on the hydrology of an Amazonian Basin 
Authors:Abe, C.A., F. de Lucia Lobo, Y.B. Dibike, M.P. de Farias Costa, V. dos Santos and E.M.L.M. Novo 
Volume (Issue):10(7) 
Article ID:932 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:land use change 
Secondary Application Category:hydrologic assessment 
Watershed Description:5,924 km^2 Upper Crepori River, a tributary of the Tapajós River located in the Amazon River Basin in northwest Brazil. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Land cover changes (LCC) affect the water balance (WB), changing surface runoff (SurfQ), evapotranspiration (ET), groundwater (GW) regimes, and streamflow (Q). The Tapajós Basin (southeastern Amazon) has experienced LCC over the last 40 years, with increasing LCC rates projected for the near future. Several studies have addressed the effects of climate changes on the region’s hydrology, but few have explored the effects of LCC on its hydrological regime. In this study, the Soil and Water Assessment Tool (SWAT) was applied to model the LCC effects on the hydrology of the Upper Crepori River Basin (medium Tapajós Basin), using historical and projected LCC based on conservation policies (GOV_2050) and on the “Business as Usual” trend (BAU_2050). LCC that occurred from 1973 to 2012, increased Q by 2.5%, without noticeably altering the average annual WB. The future GOV_2050 and BAU_2050 scenarios increased SurfQ by 238.87% and 300.90%, and Q by 2.53% and 2.97%, respectively, and reduced GW by 4.00% and 5.21%, and ET by 2.07% and 2.43%, respectively. Results suggest that the increase in deforestation will intensify floods and low-flow events, and that the conservation policies considered in the GOV_2050 scenario may still compromise the region’s hydrology at a comparable level to that of the BAU_2050. 
Keywords:water balance; land cover change; Amazon; hydrological modelling; water resources