%0 Journal Article %A Edrisi, Terife %A Habibnejad Roshan, Mahmoud %A Jafari Gorzin, Behnoush %T Simulation of Zaremrod river flow in different time scales using soil moisture accounting model(SMA) %J journal of watershed management research %V 11 %N 21 %U http://jwmr.sanru.ac.ir/article-1-805-en.html %R 10.52547/jwmr.11.21.198 %D 2020 %K Rainfall and runoff, Zaremrod Watershed, Simulation, HEC-HMS and SMA, %X River flow simulation has particular importance to be aware of the river flow and determining flood discharges in the future periods. Different hydrologic processes such as interception, surface depression storage, infiltration, soil storage, percolation, and groundwater storage would be considered in continuous hydrologic modeling. Considering the different methods of hydrological simulation, continuous simulation has a best prediction because of the dry and wet conditions modeling during the long-term period. HEC-HMS model uses Soil Moisture Accounting (SMA) algorithm to simulate the long-term relationship between rainfall, runoff, storage, evapotranspiration, and soil losses. In this study, soil moisture accounting model (HMS SMA) was applied to determine the effect of soil moisture on runoff generation, evaluating of flows simulated, in the Zaremrod watershed, Mazandaran province. Daily R-R data (4 years, from 2006 to 2010) and monthly evapotranspiration data, Digital Elevation Model (DEM-25m) and the drainage network map were used for the calibration and validation of model. The results of simulation revealed that monthly scale with maximum value of the determination coefficient and Nash–Sutcliffe efficiency and minimum mean absolute error and root-mean-square error manifested the most accurate simulation in the calibration and validation. Generally Results of the research showed capability of HEC-HMS model with new model for losses calculation (SMA) for river flow simulation in the Zaremrod watershed. %> http://jwmr.sanru.ac.ir/article-1-805-en.pdf %P 198-207 %& 198 %! %9 Research %L A-10-1029-1 %+ Sari Agricultural Science and Natural Resources University %G eng %@ 2251-6174 %[ 2020