Spatial distribution and source identification of heavy metals (As, Cr, Cu and Ni) at sub-watershed scale using geographically weighted regression

Heavy metals are among the most important sources of water and soil pollution. These elements accumulate in the agricultural soil through using contaminated water for irrigation, fertilizers, pesticide and enter to the river systems by water erosion. Therefore, land use plays a serious role in water and sediment pollution. In this regards, geographically weighted regression was used to investigate the spatial correlation between sediment heavy metals and land uses in a highland watershed. The landuse map was used to calculate the area percentage of landuse types in sub-watersheds, followed by geographically weighted regression method to investigate the spatial correlation of As, Cr, Cu and Ni versus three types of land uses. The highest correlation was observed for irrigated plots versus As and Ni in upstream and for rainfed plots versus AS, Ni and Cr in the downstream. The relationship between heavy metals and developed lands was more complicated and the highest correlation was found for Ni and As at outlet (R-2 = 0.52-0.89), for Cr in the upstream (R-2 = 0.50-0.76), and for Cu in the upstream and downstream (R-2 = 0.36-0.60). The results indicated that there is a positive correlation between heavy metals and land uses which varies with the level of agricultural and urbanization development at sub watershed. Based on the findings, appropriate policies and decisions should be taken on agricultural land to prevent the transfer of heavy metals by sediment to aquatic environments. (C) 2019 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. Production and Hosting by Elsevier B.V.