No abstract

Hydro-sedimentological models make it possible to understand the dynamics of water and sediment production in watersheds, if properly calibrated. The objective of this study is to analyze the effect of Curve Number (CN) and Green & Ampt (GA) methods and of seasonal calibration of the Soil and Water Assessment Tool (SWAT) model for estimating flow and sediment production in an agricultural basin. This research presented an original application with hourly suspended sediment concentration (SSC) generated by Artificial Neural Networks (ANNs) for using to the SWAT model calibration. The study was applied in the Taboão basin (77.5 km²), with data from 2008 to 2018. The best Nash–Sutcliffe (NS) coefficients were obtained using the combination of wet years for calibration and the GA method, both for daily flow (NScalibration 0.74 and NSvalidation 0.68) and for daily sediment production (NScalibration 0.83 and NSvalidation 0.77). The CN method did not result in satisfactory values already in the calibration for daily flow (NScalibration 0.39). The results showed that it is possible to apply the SWAT model for hydrosedimentological prediction in the Taboão basin, with good efficiency, using the GA method and calibration with wet periods.