Is a climate signal detectable using cosmogenic data and coarse‐resolution digital topography in fluvially dominated landscapes?

Abstract While the influence of climate on landscapes is conceptually intuitive, quantifying it remains challenging due to the myriad of ways earth surface processes respond to climate. In this study, we investigate if and how climate impacts fluvial relief and hillslope morphology by examining the relationship between basin average cosmogenic 10 Be‐derived erosion rates and basin average topographic metrics across climatic gradients in the Bhutan Himalaya. We selected this region because it is an ideal natural laboratory for assessing climate controls on landscapes, with large precipitation variations, minimal lithologic differences and extensive existing datasets. Our findings suggest that increasing precipitation may drive several trends: (1) nonlinearity between erosion rate and fluvial metrics (k snQ ) increases, (2) the threshold hillslope gradient declines and (3) the characteristic hillslope length increases. Although these trends are weak and subject to considerable uncertainty, the subtle variations still conform with a conceptual model where wetter climates promote mass movement, extend hillslope length and reduce mountain relief as indicated by elevated nonlinearity between fluvial relief and erosion rate in wetter regions. This consistency suggests that more carefully crafted data or experimental designs offer the hope of quantifying climate's role in landscape form. Our study provides valuable insights for future research on sampling strategies and data analysis aimed at extracting climatic signals from observational datasets.

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Publication Details

Journal
Earth Surface Processes and Landforms
Published
2025-09-18
DOI
https://doi.org/10.1002/esp.70164
Primary Topic
Geology and Paleoclimatology Research
Type
article
Field-Weighted Citation Impact
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article

Is a climate signal detectable using cosmogenic data and coarse‐resolution digital topography in fluvially dominated landscapes?

Rong Yang, Sean F. Gallen, Congli Xu
Earth Surface Processes and Landforms
Geology and Paleoclimatology Research
article

Is a climate signal detectable using cosmogenic data and coarse‐resolution digital topography in fluvially dominated landscapes?

Rong Yang, Sean F. Gallen, Congli Xu
article en

Abstract

Abstract While the influence of climate on landscapes is conceptually intuitive, quantifying it remains challenging due to the myriad of ways earth surface processes respond to climate. In this study, we investigate if and how climate impacts fluvial relief and hillslope morphology by examining the relationship between basin average cosmogenic 10 Be‐derived erosion rates and basin average topographic metrics across climatic gradients in the Bhutan Himalaya. We selected this region because it is an ideal natural laboratory for assessing climate controls on landscapes, with large precipitation variations, minimal lithologic differences and extensive existing datasets. Our findings suggest that increasing precipitation may drive several trends: (1) nonlinearity between erosion rate and fluvial metrics (k snQ ) increases, (2) the threshold hillslope gradient declines and (3) the characteristic hillslope length increases. Although these trends are weak and subject to considerable uncertainty, the subtle variations still conform with a conceptual model where wetter climates promote mass movement, extend hillslope length and reduce mountain relief as indicated by elevated nonlinearity between fluvial relief and erosion rate in wetter regions. This consistency suggests that more carefully crafted data or experimental designs offer the hope of quantifying climate's role in landscape form. Our study provides valuable insights for future research on sampling strategies and data analysis aimed at extracting climatic signals from observational datasets.

Earth Surface Processes and LandformsVol. 50(12)
GFZ Helmholtz Centre for Geosciences (DE), Zhejiang University (CN), Colorado State University (US)
Openalex Percentile: Top 70%
Geology and Paleoclimatology Research
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