Charts showing relationship between catchment-averaged erosion rate and landscape steepness index
Relationship between catchment-averaged erosion rate (or denudation rate – y-axis) and landscape steepness index ksn (x-axis). The greatest erosion rates are typically expected in the steepest landscapes. The left panel shows this relationship does not hold in the Zhuoshui River catchment. However, a good fit can be achieved if the steepness index is adjusted to incorporate changes in rock resistance to erosion (and runoff, to a lesser extent), as shown in the right panel. The best fit between the adjusted steepness index kLrsn and erosion rate is achieved in a scenario where Miocene slates have the lowest strength, which is consistent with their low metamorphic grade and high fracture density compared to the other exposed rock types (Deng et al. [2020]). The three data points in both panels with erosion rates in excess of 5 millimeters/year are from the headwaters dominated by the Miocene slate. Colors in the right panel represent the rock strength index, going from blue (low strength – weak rocks) to yellow (high strength – strong rocks). Square and circles are data obtained from two different methods. Credit: Deng et al. [2020], 5c and 8d
Source: Journal of Geophysical Research: Earth Surface

Quantifying erosion rates across landscapes is a key challenge in geosciences: erosion rate data are crucial to understand how landscapes evolve through time, as well as to assess numerous hazards (e.g., landslides, flooding, earthquakes). For example, sediment (gravel, sand) will be preferentially sourced from areas with the greatest erosion rates; such areas may also represent areas of greatest tectonic activity.

Over the last 20 years, techniques based on the measurement of cosmogenic radionuclides (CRN) concentrations in river sands have been the tool of choice to quantify erosion rates. CRN are rare elements produced as cosmic rays bombard the surface of the Earth and interact with the atoms that make up rocks. Rocks at depth have no CRN. CRN start accumulating into rocks as they reach the surface: the longer a rock stays near the surface, the greater its CRN concentration. If erosion rates are low, rocks spend a long time near the surface: rocks (and the sand produced from their erosion) will therefore have high CRN concentrations. Conversely, rocks and sand will have low CRN concentrations in fast eroding landscapes.

However, the best understood CRN system is the one that leads to the formation of Beryllium-10 (10Be) in quartz crystals: most CRN-derived erosion rates are based on 10Be concentrations in quartz sand, which means we have very few erosion rate datasets from catchments that do not have quartz (e.g., slate, mudstone).

Deng et al. [2020] use meteoric 10Be (delivered to rocks by rain) to derive erosion rates for a range of rock types, including rocks that do not contain quartz. They show that the slate headwaters of the Zhuoshui River catchment in Taiwan are eroding much faster than the other rocks in the rest of the catchment, at around 4 to 8 millimeters per year.

The authors use their new data to test the commonly assumed relationship between landscape steepness and erosion rates. They show that the highest erosion rates are associated with moderate steepness indices (left panel above), but that the datasets can be reconciled by adjusting the steepness index to incorporate variations in rock resistance to erosion: the best fit is achieved with Miocene slates five to ten times weaker than the other rock types exposed in the catchment (right panel above).

This study bridges a significant gap: it demonstrates that meteoric 10Be can be used to quantify erosion rates in catchments with a range of lithologies exposed. It proposes a new framework to quantify differences in rock resistance to erosion and demonstrate their impact on landscape steepness, with implications for retrieving erosional signals from topographic data.

Citation: Deng, K., Yang, S., von Blanckenburg, F., & Wittmann, H. [2020]. Denudation rate changes along a fast‐eroding mountainous river with slate headwaters in Taiwan from 10Be (meteoric)/9Be ratios. Journal of Geophysical Research: Earth Surface, 125, e2019JF005251.

—Mikael Attal, Associate Editor, JGR: Earth Surface

Text © 2020. The authors. CC BY-NC-ND 3.0
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