Thor: a rock strength database for investigating lithologic controls in landscape evolution
•Extensive rock strength database compiles over 6100 rock strength measurements.•Facies variations cause rock strength changes up to two orders of magnitude.•Globally, river steepness is controlled by lithology.•Lithology reconciles predicted and measured erosion rates at basin scale. Topographic in...
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Published in | Earth and planetary science letters Vol. 660; p. 119364 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
15.06.2025
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Subjects | |
Online Access | Get full text |
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Summary: | •Extensive rock strength database compiles over 6100 rock strength measurements.•Facies variations cause rock strength changes up to two orders of magnitude.•Globally, river steepness is controlled by lithology.•Lithology reconciles predicted and measured erosion rates at basin scale.
Topographic information has been widely used to provide insights into tectonics and climate. However, these metrics are subject to lithologic effects that limit our understanding of how landscapes grow, evolve, and decay. To address this, we compile over 6100 Schmidt hammer-based rock strength measurements from 264 published studies to create an extensive rock strength database that we call Thor. We use this database to perform a meta-analysis that enables us to quantify, on a global scale, the impact of lithology on fluvial metrics. Our findings reveal a strong correlation between topographic metrics and rock strength, particularly the normalized steepness index (ksn) and the fluvial erodibility coefficient (K). Additionally, using four case studies worldwide we identify that incorporating rock strength data improves the correlation between measured and predicted erosion rates for all sites, regardless of tectonic activity and climate setting. While we acknowledge the roles of climate and tectonics in shaping Earth's surface, our findings reveal a notable influence of lithology in landscape evolution, both globally and locally. These findings underscore the potential bias introduced by spatially variable lithology on commonly used topographic metrics for inferring drainage reorganization, incision, tectonics, and climate forcing. |
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ISSN: | 0012-821X |
DOI: | 10.1016/j.epsl.2025.119364 |