Effects of Provenance, Transport Processes and Chemical Weathering on Heavy Mineral Composition: A Case Study From the Songhua River Drainage, NE China

Abstract

Understanding the heavy mineral composition of the Songhua River basin in NE China and the influencing factors (e.g., provenance, transport processes and chemical weathering) is crucial for the study of both the source-to-sink processes and the drainage evolution in the region. To this end, a total of 43 samples were collected from the river bars and terraces of the main and tributary streams of the Songhua River, and analyzed for heavy minerals in different grain-size fractions based on the novel automated TESCAN Integrated Mineral Analyzer (TIMA) combined with standard optical method. The results show that the tributaries originating from different mountains have significantly different heavy mineral composition. The locally occurring basic source signal in the tributaries of the Nenjiang River (the largest tributary of the Songhua River) are not well preserved in the Nenjiang River and the Songhua River trunk streams, indicating that the control of sources on heavy mineral composition is influenced by fluvial processes. Additionally, significant differences in the heavy mineral composition of different reaches of the same river also indicate that the heavy mineral composition is significantly influenced by fluvial processes. Influenced by hydraulic sorting during river processes, heavy minerals are enriched in different size fractions with the low-density minerals systematically overestimated in a wide window, suggesting an advantage of multi-window policy over wide window policy. In contrast to modern river sediments, the original heavy mineral composition of river terrace sediments has been severely damaged due to chemical weathering, so the degree of chemical weathering of terrace sediments needs to be evaluated first in provenance tracing and paleo-drainage evolution studies. TIMA has an irreplaceable role in identifying mineral species, additional images and elemental composition, and however, it performs poorly in identifying polycrystalline minerals, thus the combination with traditional methods can obtain more complete and accurate information.