Abstract
Computation cost and sensitivity of the simulated results to the input parameters are the essential targets in this study. The impact of different DEMs with various sources and cell -sizes are studied on the output accuracy of the hydrological model. Evaluation of the most influential input parameters is conducted by employing Sequential Uncertainties Fitting Ver. 2 algorithms on the performance of the SWAT model. The simulation time is calculated in each case, and the trade-off between the output accuracy and the computation time is discussed. Zarrineh River watershed in Iran has been studied as a case study. The outcomes indicate that the reach lengths, reach slopes, the number of sub-basins and the amount of HRUs are the most influential parameter in runoff simulation by the SWAT model, and they differ by changing the DEM source and resolution. Simulated results over-predict the runoff during low precipitation periods and under-predict it during high precipitation seasons. The accuracy of simulated results decreases by reducing the DEM resolution, and ten times reduction of the DEM resolution generally leads to a 50% increase of error while decreasing the simulation time by eight times. The results show that the fine resolution of the input data enhances the performance of the SWAT model in the prediction of a few parameters such as the runoff yield, the hydrological response, and estimating the terrain morphology. The SWAT model has the best performance while using the DEM generated from the TOPO1:25000 as the input with 0.79, 0.79, −13.57 for the NSE, R2, PBIAS, respectively. The results can be employed to estimate the impact of low-resolution input data on the simulated result and reduce the computation time by decreasing the input DEM resolution with only a minor reduction of accuracy.
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