The Kahang Cu-Mo porphyry deposit is located in the central part of the Cenozoic Urumieh-Dokhtar metallogenic belt (UDMB). Quartz monzonite to granodiorite rocks host mineralization as veins and stockworks. Hydrothermal and supergene processes have led to the redistribution of rare elements in the Kahang Cu-Mo porphyry deposit. This paper aims to identify the trend of changes in the concentration of supra-ore elements (Pb, Zn, As, Ag, and Sb), and sub-ore elements (Cu, Au, Ag, and Mo), and highlight their associated geochemical anomalies. For this purpose, 936 geochemical samples were systematically collected from the soil environment in the study area. Then, ordinal trend surface analysis (OTSA) and canonical trend surface analysis (CTSA) methods with first- and second-degree functions were applied to recognize spatial trends and anomalies. The methods decompose geochemical contour maps into trend and residual components. The results of the OTSA method indicate an increasing trend of the sum of supra-ore and sub-ore elements from the southern to the northern part of the study area. The residual contour map generated by this method reveals five geochemical anomalies zones, with the identification of these anomalies improving as the degree of the surface trend function increases. Furthermore, the CTSA method results demonstrate that the increasing trend of supra-ore and sub-ore elements are oriented in the southeast-northwest and southwest-northeast directions, respectively. Therefore, the anomaly in area I is linked to the mineralization of supraore elements, whereas the anomaly in area IV corresponds to the mineralization of sub-ore elements. The residual contour maps obtained from the CTSA method show that, in addition to the degree of the trend surface function, the direction of the trend also plays a significant role in highlighting geochemical anomalies. The results of this paper show that trend surface analysis methods can effectively identify and highlight changes in the concentration of elements with different geochemical properties within an exploration area. The proposed methodologies are robust approaches for enhancing geochemical prospectivity mapping, and they may possess the potential to separate mixed and complex geochemical anomalies linked to mineralization by considering the spatial distribution of these anomalies in analogous mineral systems.
