نوع مقاله : مقاله پژوهشی
1 دانشجوی کارشناسی ارشد منابع آب، دانشگاه ملایر
2 گروه سنجش از دور و سیستم اطلاعات جغرافیایی دانشکده جغرافیا دانشگاه تهران
3 دانشیار گروه آبیاری، دانشکده کشاورزی، دانشگاه بوعلی سینا.
عنوان مقاله [English]
Snow is one of the huge sources of water around the world, and estimation of the equivalent water of snowmelt is regarded as one of the most crucial activities of the hydrologists. Through snow melting, the soil moisture, underground water reservoirs, lakes and rivers water reservoirs are supplied; and the more readily, the snowmelt runoff is regarded as a main factor for controlling the flow regime in mountains and high basins. Therefore, the estimation of the snow cover and its runoff is very important issue in the mountainous basins. But, this effort is very difficult to be done due to lack of adequate land information in this regard. Using snowmelt hydrological models and satellite imagery are very useful to cope with this problem. In this study, it was tried to simulate and evaluate the daily runoff of snowmelt by the use of a snowmelt runoff model (SRM) and the information extracted from MODIS eight-day images, for Nahavand watershed which is one of the Karkheh river basin’s parts located on western Iran. The model was run and calibrated for the water years from 2003 to 2010; and it was validated for the water years 2011 to 2013. The highest correlation coefficients and volume difference for the model in the calibration period were 0.75 and -3.62, respectively; and 0.79 and 26.67 for the validation period, respectively. A sensitivity analysis was done for degree day, snow runoff coefficient and rain runoff factors and its results shows that a lower sensitivity of model to increased or decreased of rain runoff coefficient among the other parameters. In general, obtained results show a high level of accuracy of this model by the use of satellite imagery as an input for estimating the snowmelt runoff for the studied watershed and the capability of this model for other similar basins as well