Temporal Variability of Fluvial Sand Composition: An Annual Time Series From Four Rivers in SW Germany

Abstract

The sampling of fluvial sediment is subject to many sources of uncertainty, for example, time and location, and the number of samples collected. It is nevertheless commonly assumed that a sample taken at one time and location provides a somewhat averaged compositional signal. Any spatial or temporal variability of this signal is often neglected. This study investigates how the composition of bed load sand changes over an observation period of 1 year in four river basins with differing bedrock geology in southwestern Germany. Up to 12 bulk sediment samples were taken at the same locations using the same approach and analyzed for their granulometry and geochemistry. The results indicate that (a) different grain sizes yield different compositions due to source rock composition and hydraulic sorting effects, (b) bulk sediment composition changes temporally due to changing grain‐size distribution, and (c) compared to the bulk sample, the composition of narrow grain sizes is temporally more stable but nevertheless has an average variability of 15%. Because heavy mineral‐bound elements such as Zr have the highest variability, we relate a major component of compositional variability to temporally varying heavy mineral concentrations in response to hydrodynamic processes. Mixing modeling demonstrates that the fluvial sand faithfully reflects its catchment geology and that the sediment sources do not change substantially during the observation period, even during a flooding event. We conclude (a) that the causes for compositional variability may be disentangled using chemical and granulometric time series data and (b) that narrow grain sizes yield representative source rock contributions.

How to Quantify Heavy Mineral Fertility From Point‐Counting Data

“…While the geochemistry data of the Ziller sand may scatter depending on the analyzed grain‐size fraction, all fractions are chemically similar to more felsic source rock compositions (Figure 12) measured at different locations in or near the Ziller catchment (Finger et al., 1993; Melcher et al., 1996; Wyss, 1993). This supports the idea that felsic granitoid rocks are the dominant source rock in the catchment and that sediment chemistry reflects source rock chemistry in settings with limited chemical weathering (Stutenbecker et al., 2023; von Eynatten et al., 2012). Mineralogical compositions of rocks in the Ziller catchment (Raith, 1970) show that the dominance of epidote and mica can be explained by source rock composition.…”

Using Convex Optimization to Efficiently Apportion Tracer and Pollutant Sources From Point Concentration Observations

“…Measurements of concentrations are always accompanied by a degree of uncertainty that reflects both analytical noise, and also cases where the modeling assumptions are not fully satisfied, for example, imperfect mixing of the water column, hydrodynamic sorting of sediment, or non‐conservative behavior (e.g., Bouchez et al., 2010; Stutenbecker et al., 2023). To prevent the optimization from over‐fitting this noise we regularize our solution by penalizing relative deviations in c from the mean observed concentration.…”

Inherited Grain‐Size Distributions: Effect on Heavy‐Mineral Assemblages in Modern and Ancient Sediments

“…It is clear from this study how important grain-size fraction selection is, and how much mineral diversity can vary from one fraction to another, in addition to the obvious presence of grain-size inheritance within certain grain-size fractions. This significance was mentioned in Stutenbecker et al (2023) who looked at the temporal compositional variability of four smaller rivers in Germany.…”