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The Sediment Transport and Erosion Prediction (STEP) model is methodically described in this paper. The STEP model was implemented at a 3.47 km × 3.47 km grid resolution in the Kalisapi sub-watershed, Central Java, Indonesia. It was calibrated and validated in the period of 2003–2008 and 2010–2014 respectively. The result shows that the STEP model functions satisfactorily at monthly and annual time window in the calibration and validation periods. In both periods, the STEP model is able to produce fruitful annual sediment transport rates with R2 values of 0.71 and 0.9 in the calibration and validation period respectively. Moreover, the STEP model exhibits more equitable spatial variability than that of the widely known USLE model. Correspondingly, it can be surmised that the STEP model is capable of simulating spatial and temporal variability of sediment transport from a watershed at monthly and annual time scales. • STEP model is developed to simulate soil erosion, deposition and sediment transport processes in time and space. • STEP model has been successfully implemented, calibrated and validated in the Kalisapi sub-watershed, Indonesia. • Calibrating STEP model to fit the observation is straightforward as it only needs to modify two model parameters. • STEP model source code and input data for the study area are freely available in the Bitbucket repository service. [ABSTRACT FROM AUTHOR]

Identifying the erosion processes contributing to increased basin fine sediment yield is important for reducing downstream impacts on aquatic ecosystems. However, erosion rates are spatially variable, and much eroded sediment is stored within river basins and not delivered downstream. A spatially distributed sediment budget model is described that assesses the primary sources (hillslope soil erosion, gully and riverbank erosion) and sinks (floodplain and reservoir deposition) of fine sediment for each link in a river network. The model performance is evaluated in a 17,000-km2 basin in south-east Australia using measured suspended sediment yields from eight catchments within the basin, each 100–700km2 in area. Spatial variations within the basin in yield and area-specific yield were reliably predicted. Observed yields and area-specific yields varied by 17-fold and 15-fold respectively between the catchments, while predictions were generally within a factor of 2 of observations. Model efficiency at predicting variations in area-specific yield was good outside forested areas (0.58), and performance was weakly sensitive to parameter values. Yields from forested areas were under-predicted, and reducing the predicted influence of riparian vegetation on bank erosion improved model performance in those areas. The model provided more accurate and higher resolution predictions than catchment area interpolation of measured yields from neighbouring river basins. The model is suitable for guiding the targeting of remediation measures within river basins to reduce downstream sediment yields. [Copyright &y& Elsevier]