Document Type : Research Article
Ph.D student of Irrigation and Drainage, Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran
Professor in Water Resources Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
Professor of Climatology, Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
Associate Professor of Irrigation, Drainage and Water Resources, Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad. mashhad. Iran
Assistant Professor. Department of Geography. Faculty of Letters and Humanities. Ferdowsi University of Mashhad. Mashhad. Iran
Considering the impact of snow studies in managing water resources and preventing the dangers caused by floods, and because the modeling of snow melt runoff is faced with the lack of snow density data in the basin due to many changes in the distribution of snow masses, and creating Snow measurement stations at high altitudes are difficult and expensive work, in this study, an attempt was made to invent a new equation and using remote sensing techniques in a simpler and more physical way to determine the degree-day factor parameter (α) and then the simulation was performed by defining its calculated values using classical and new methods along with the annual and seasonal values of the recession coefficient (k) for the snow- melt runoff model (SRM) and the results It has been evaluated and compared. In order to evaluate the performance of the model and its parameters, simulations were performed for the calibration and validation periods for the water years 2011-2012 and 2012-2013, respectively, and the MODIS snow cover product (MOD10A1) was used to estimate the snow-covered area and to estimate the radiation values. NEO net radiation product (CERES-NETFLUX-E) was used. The results showed that the best method for simulating runoff in the calibration period (2011-2012) was the use of the new degree-day factor calculation method and the use of two values of the seasonal recession coefficient with the coefficient of determination of 0.72 and the volume difference of 4.17. In the validation period (2012-2013), the runoff simulation method with the new degree-day factor method and an annual recession coefficient with a coefficient of determination of 0.51 and the volume difference of 4.38 provided the best results in terms of assessment of the model accuracy criteria.