Autogenic vs Subsidence Controls on Fluvial Stratigraphic Grain Size Fining through Multi-Channel Landscape Evolution Modelling

Amanda Wild,Jean Braun, Alex Whittaker,Sebastien Castelltort

crossref(2024)

引用 0|浏览0
暂无评分
摘要
Grain size within the stratigraphic record is often used to interpret changes in tectonics and climate. For example, past work has described the influence of underlying subsidence or flux oscillations due to climate on grain size fining rates within the basin. However, little research has deconstructed the role of internal dynamics in shaping the grain size fining rates preserved within strata under varied basin geometries, precipitation gradients, and bypass states of basin evolution. Through the combination of a landscape evolution model based on the Stream Power Law modified for sedimentation by Yuan et al. (2019) with an extension of the self-similar grain size model of Fedele and Paola (2007) into multiple dimensions (i.e., along dynamically evolving river channels) by Wild et al (in review), we have developed a steady-state framework identifying autogenic vs subsidence dominated grain size fining. When basin accommodation is high relative to incoming flux, or early in the basin evolution, grain size fining is primarily subsidence-dominated regardless of precipitation gradients and basin geometries. Alternatively, under high bypass and low underlying accommodation, grain size fining is autogenically dominated and controlled by relative upstream discharge (or the ratio of the upstream, mountain catchment area vs the downstream, sedimentary system area). Foreland basins (eg: the Alberta foreland basin) with ample downstream area tend to evolve from a high subsidence to autogenic dominated state as they fill over time. Constrained downstream areas (eg: Death Valley fans) display a minimal autogenic impact on grain size fining regardless of their bypass state. We will present our modelled stratigraphic results and compare them to natural systems, such as the Alberta Foreland basin and alluvial fans of Death Valley.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要