This study describes the application of a semi-distributed model for flow simulation and assessment of sensitive parameters. Semi-distributed model is a trade-off between fully distributed and lumped models. In this study, the Soil and Water Assessment Tool (SWAT) model was applied for modeling the average monthly flow in Roodan watershed, Iran. This watershed has arid and semi-arid areas critical for development as they have the potential to preserve surface waters in spite of water scarcity. The major purposes of this research were (1) to identify sensitive parameters; and (2) to evaluate the monthly flow at arid region (south of Iran) with low precipitation. To formulate a better model, the impacts of three additional parameters, namely revap coefficient (GW_REVAP), reach evaporation adjustment factor (EVRCH) and length of main channel (CH_L(2)) were reviewed critically. To delineate the watershed, the kind of data used were the digital elevation map (DEM), land use map, soil layers properties and meteorological data. Then, the model was calibrated using the Sequential Uncertainty Fitting (SUFI-2) algorithm. This method is a kind of inverse modeling and considers uniqueness. A modeler defines a large limit range values for every parameter and after every iteration every parameter will get small limit range values. Generally, the model gave satisfactory values of Nash- Sutcliffe (NS) and coefficient of determination (R2). Values of R2 and NS were 0.93 and 0.92 respectively for calibration. For validation, both values were reported at 0.83. Usually, calibration and validation of hydrological models have different accuracy. The main reason is that the model validate for different phenomena. In such cases, the calibration of additional parameters, i.e. GW_REVAP, EVRCH and CH_L(2), cannot be substantially improved as well.
SUFI-2 algorithm, Monthly flow, Sensitivity analysis, Semi-auto calibration, SWAT