Low variability runoff inhibits coupling of climate, tectonics, and topography in the Greater Caucasus

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.epsl.2022.117525. This is version 4 of this Preprint.

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Authors

Adam Matthew Forte , Joel Leonard, Matthew Rossi, Kelin Whipple, Arjun Heimsath, Lasha Sukhishvili, Tea Godoladze, Fakhraddin Kadirov

Abstract

Hypothesized feedbacks between climate and tectonics are mediated by the relationship between topography and long-term erosion rates. While many studies show monotonic relationships between channel steepness and erosion rates, the degree of nonlinearity in this relationship varies by landscape. Mechanistically explaining controls on this relationship in natural settings is critical because highly nonlinear relationships imply low sensitivity between climate and tectonics. To this end, we present a coordinated analysis of cosmogenic 10Be concentrations in river sands paired with topographic, hydroclimatic, and tectonic data for the Greater Caucasus Mountains where topography is invariant along-strike despite large gradients in modern precipitation and convergence rates. We show that spatial patterns in erosion rates largely reflect regional tectonics with little sensitivity to mean precipitation or runoff. The nonlinearity in the erosion rate – steepness relationship may arise from very low runoff variability, which we attribute to the large contribution from snowmelt. Transitioning from rainfall- to snowmelt-driven runoff as mean elevation increases is common to many mid-latitude mountain ranges. The associated decrease in runoff variability may represent important, unrecognized dynamics inhibiting the sensitivity of tectonics to climate more broadly.

DOI

https://doi.org/10.31223/X5V02X

Subjects

Geomorphology, Tectonics and Structure

Keywords

Greater Caucasus, erosion rates, climate-tectonic coupling

Dates

Published: 2021-03-23 20:57

Last Updated: 2022-04-08 04:40

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License

CC BY Attribution 4.0 International