Shabanali Gholami; Masoumeh Nasiri
Abstract
Human life is affected by different hydrological events such as floods, water storage, droughts, water pollutions, avalanche and etc. that the risk range of these events depends on the behavior of hydrological variables and watersheds characteristics. Lack of correct data and information or inadequate ...
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Human life is affected by different hydrological events such as floods, water storage, droughts, water pollutions, avalanche and etc. that the risk range of these events depends on the behavior of hydrological variables and watersheds characteristics. Lack of correct data and information or inadequate correct data is the important factor affects on regognition of the behavior of hydrological variables and watershed charactristics. In this regard, there are different models which could follow watershed characteristics and estimate or simulate runoff and sediment load and other water balance factors in watershed. SWAT model is one of the important hydrological models. In this research, Atrak River monthly runoff was simulated using this model based on collected data in Maraveh Tappeh watershed, Gholestan province, Iran. Required information such as topography, land use, pedologyand also, hydrological and meteorological data such as daily rainfall, temperature, relative humidity and runoff have been collected. To determine important and sensitive parameters, sensitivity analysis has been performed using one parameter at a time (OAT) method. The results indicated that curve number, channel hydraulic conductivity, surface runoff lag coefficient, base flow alpha factor and soil evaporation compensation factor have the most influence on different parts of water balance. Calibration and validation of the model were performed using the SUFI2 algorithm for the periods of 1994 to 1999 and 2000 to 2008, respectively The simulation accuracy using Nash-Sutcliffe and coefficient of determination were 0.54 and 0.54 for the calibration period and 0.46 and 0.46 during the validation period, respectively. So, it can be concluded that the performance of the SWAT model for estimating monthly flow is quite good.
