The Soil and Water Assessment Tool (SWAT) was used to model runoff and sediment in the Beheshtabad (3860 km 2 ) and Vanak (3198 km 2 ) watersheds in the northern Karun catchment in central Iran. Model calibration and uncertainty analysis were performed with sequential uncertainty fitting (SUFI-2), which is one of the programs interfaced with SWAT, in the package SWAT-CUP (SWAT Calibration Uncertainty Programs). Two measures were used to assess the goodness of calibration and uncertainty analysis: (a) the percentage of data bracketed by the 95% prediction uncertainty (95PPU) (P factor), and (b) the ratio of average thickness of the 95PPU band to the standard deviation of the corresponding measured variable (D factor). Ideally, the P factor should tend towards 1 with a D factor close to zero. These measures together indicate the strength of the calibration-uncertainty analysis. Runoff and sediment data from four hydrometric stations in each basin were used for calibration and validation. The P factor for Beheshtabad stations ranged from 0.31 to 0.86, while those for Vanak stations were between 0.71 and 0.80. The D factor for Beheshtabad ranged from 0.3 to 1.1, and for Vanak it was 0.77-1.16. These measures indicate a fair model calibration and accounting of uncertainties. The predicted runoff values were quite similar to those for discharge.

Soil depth generally varies in mountainous regions in rather complex ways. Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time, effort and consequently relatively large budget to perform. This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran. For this, one hundred sampling points were selected using randomly stratified methodology, and considering all geomorphic surfaces including summit, shoulder, backslope, footslope and toeslope; and soil depth was actually measured. Eleven primary and secondary topographic attributes were derived from the digital elevation model (DEM) at the study area. The result of multiple linear regression indicated that slope, wetness index, catchment area and sediment transport index, which were included in the model, could explain about 76 % of total variability in soil depth at the selected site. This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale.

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