
Impacts of Using Different Soil Databases on Streamflow Simulation in an Experimental Rural Catchment of the Brazilian Savanna (Impactos do Uso de Diferentes Bases de Dados na Simulação da Vazão em uma Represa Experimental Rural da Savanna Brasileira)
Author(s) -
Leandro de Almeida Salles,
Jorge Enoch Furquim Werneck Lima,
Henrique Marinho Leite Chaves,
Sara Ferrigo,
Heloisa do Espirito Santo Carvalho
Publication year - 2015
Publication title -
revista brasileira de geografia física
Language(s) - English
Resource type - Journals
ISSN - 1984-2295
DOI - 10.26848/rbgf.v8.1.p187-195
Subject(s) - streamflow , baseflow , environmental science , soil and water assessment tool , biome , drainage basin , hydrology (agriculture) , calibration , swat model , database , statistics , computer science , geography , mathematics , geology , cartography , ecology , geotechnical engineering , ecosystem , biology
The purpose of this study was to analyze the soil database influence on streamflow simulation using the SWAT model in the experimental catchment of the Pipiripau river (235 km²), located in Brazilian savanna (Cerrado biome). To achieve this goal, two databases were used, one developed with data collected nearby the Pipiripau region (SDB1), and another one with data from literature (SDB2). The evaluation was performed using a streamflow historical time series of 10 years (1989-1998), on monthly and daily basis. The analysis was made without calibration, using only the results from SWATs first simulation, as it was applied in an ungagged basin. For daily simulations, the Nash & Sutcliffe model efficiency (NSE), the adapted Nash & Sutcliffe model efficiency (ANSE), and the Percent Bias (PBIAS) were respectively -11.88, -11.80, and -23.15% for SDB1, and -9.94, -9.88, and -84.72, for SDB2. For the monthly simulations, the NSE, ANSE, and PBIAS results were, respectively,-1.78, -2.98, and -24.53% for SDB1, and 6.51, 9.88, and -84.72 for SDB2. Even if the PBIAS analysis and the annual water budget results for the SDB1 simulations had better results, the negative values of NSE and ANSE indicates that, without calibration, the simulations failed to represent observed data. It is remarkable that the use of SDB1 visibly improved daily baseflow simulations during the rainy season. The results indicate the importance of developing specific soil databases for different regions, as well as research on other parameters in order to improve SWATs physical basis.