Quantitative Provenance Analysis of Sediment Routing Systems Across Temporal Scales: Challenges and Future Directions

Integrating geomorphology, sedimentology, sedimentary petrology, and provenance analysis has significantly advanced our understanding of sedimentary processes. Depositional dynamics—particularly sediment partitioning, landscape evolution, and signal propagation—are now closely linked to tectonic and climatic forcing within the Sediment Routing System (SRS) framework. Quantitative provenance analysis (QPA) contributes a compositional dimension that enhances sediment budget estimates and enables the quantification of anthropogenic impacts. Nevertheless, a fully integrated, multidisciplinary approach remains underdeveloped.

This study addresses these gaps through three objectives: refining Sediment Generation Models (SGM) by coupling lithology, relief, and climate; developing a streamlined QPA–SRS workflow for sand and silt apportionment; and assessing the resolution of sedimentary signal reconstruction at historic (10² yr), intermediate (10²–10⁶ yr), and deep-time (≥10⁷ yr) scales.

At historic timescales, compositional and morphotectonic analyses capture the impact of human activity on sediment generation, while QPA integrated with OSL and sedimentological data successfully traces drainage responses to Holocene climatic variability. In deep-time systems, the combination of high-resolution provenance techniques and detailed sedimentology underscores a key limitation: the need for precise, coeval dating of climatic, tectonic, and depositional events.

While identifying natural controls in modern settings is relatively straightforward, transient landscapes often obscure the geological record. Focusing on sfirst-cycle SRS, this study develops an integrated framework with SGM providing essential baseline data. Systematic application of these models across diverse lithological, tectonic, and climatic settings will promote greater unification of sedimentary geology sub-disciplines, offering more accurate reconstructions of ancient systems and refined predictions of future landscape and climate evolution.