Heavy metals are dangerous for our environment that is due to their toxic and stable behavior in nature. These metals can change the chemical properties of sediments, and move the metal and pollutants to the stream of water over their deposition sites. Thus, they are potential sources of pollution traorting the pollutants into the environment. On the other hand, heavy metals those remained in the contaminated sediments could come together in aquatic organisms and plants and then move to the chain food, which may endager the organisms and the animal life and plant environment. In this regard, minig activites is one of the main sources of heavy metal pollution in environments around the mines. Because mining activities are such that they affect vast areas around them, it is better if the whole mining area is studied through stream sediments data analysis having vast influence area. Therefore, sediments are efficient media for monitoring pollutants in the environment. Various indices and methods have been developed and applied to assess pollution and the impact of human activities on sediment quality. In this study, to evaluate the risk of heavy metals pollution, a dataset of stream sediment geochemical elements was used in the 1:100,000 scale Khoy quadrangle map. In the study area, ultramafic rocks including peridotite, harzburgite and dunite, basaltic lava rocks, orbital-bearing calcareous rocks and metamorphic rocks are predominant lithologies. Due to the fact that the sediment data represent upstream materials of sampling locations, sample catchment basin (SCB) method was applied to portray the pollutions. Subsequently, according to the geological map of the area, element contents of the samples and their positions, catchment basins and the upstream lithologies in the catchments of were extracted. Then uni-element background concentration caused by lithology was calculated by weighted average method, and was applied as reference value for calculation of sediment quality indices such as, Contamination factor, Geoaccumulation index and ecological risk factor. in order to use the Integrated quality indices, the elements with multivariate statistical methods such as Pearson correlation matrix, factor analysis and hierarchical clustering were investigated and the correlation between their changes was analyzed. in previous researches to identify the levels of pollution using the ecological risk factor, the Hakanson standard was used, but in this study because of the use of statistical analysis and limitation of elements to participate in the Integrated index,The assessment range of this index is adjusted to strengthen the results and adapt it to reality based on the new conditions. In this research, study of contaminated basins showed that the sources of contamination were mainly due to the geological features of the area but in some cases mineral and human activities were very effective in spreading the contamination. Next, to prioritize the contaminated areas according to the meteorological station data including mean annual precipitation and temperature coefficient, map of soil erosion intensity coefficient, length, environment, height difference of contaminated basins, by erosion potential method, amount erosion and sediment discharge were calculated for each basin and according to sediment contamination level and sediment discharge of each basin, those contaminated areas were ranked by Volumetric production potential and TOPSIS method.