Isolating climatic, tectonic, and lithologic controls on mountain landscape evolution

Abstract

Establishing that climate exerts an important general influence on topography in tectonically active settings has proven an elusive goal. Here, we show that climates ranging from arid to humid consistently influence fluvial erosional efficiency and thus topography, and this effect is captured by a simple metric that combines channel steepness and mean annual rainfall, k snQ . Accounting for spatial rainfall variability additionally increases the sensitivity of channel steepness to lithologic and tectonic controls on topography, enhancing predictions of erosion and rock uplift rates, and supports the common assumption of a reference concavity near 0.5. In contrast, the standard channel steepness metric, k sn , intrinsically assumes that climate is uniform. Consequently, its use where rainfall varies spatially undermines efforts to distinguish climate from tectonic and lithologic effects, can bias reference concavity estimates, and may ultimately lead to false impressions about rock uplift patterns and other environmental influences. Capturing climate is therefore a precondition to understanding mountain landscape evolution.

Stochastic in Space and Time: 2. Effects of Simulating Orographic Gradients in Daily Runoff Variability on Bedrock River Incision

“…As such, we consider best‐fit concavities both using drainage area (Figure 8c) and precipitation‐weighted drainage area (Figure 8d). For each model run, we determine the best‐fit concavity by using the linear relationship between χ ‐elevation or χ Q ‐elevation (sensu Leonard et al., 2023b). All model runs use a ratio of the area exponent, m , to the slope exponent, n , of 0.5.…”

“…One barrier to field verification is uncertainty in how well suited stream power predictions are for isolating relationships among climate, erosion, and bedrock river morphology. Given the proliferation of carefully curated data sets attempting to constrain how climate is embedded in the erodibility coefficient (e.g., Adams et al., 2020; Ferrier et al., 2013; Forte et al., 2022; Leonard et al., 2023b), the time is ripe to re‐visit assumptions implied by conventional applications of stream power to landscape evolution studies, especially in the context of the complexities that result from spatial gradients in orographic precipitation (e.g., Anders et al., 2006, 2007; Bookhagen & Burbank, 2006; Bookhagen & Strecker, 2008; Roe, 2005; Roe et al., 2003).…”

The Uplift of an Early Stage Collisional Plateau Unraveled by Fluvial Network Analysis and River Longitudinal Profile Inversion: The Case of the Eastern Anatolian Plateau

“…This normalization is needed because the two indices co‐vary and to allow the comparison of longitudinal profiles with different drainage areas (Wobus et al., 2006). Here we chose θ ref = 0.45 since it appears to be most selected value in tectonically active areas (Kirby & Whipple, 2012; Leonard et al., 2023; Wobus et al., 2006) and falls within our θ estimates.…”

Alluvial development during climate fluctuations depicted with spectral decomposition of the Middle Triassic to Lower Jurassic post‐rift succession in the Horda Platform (Norway) and the impact on reservoir properties

“…Climatic fluctuations have been increasingly acknowledged as a strong driving force on deposition, by controlling run‐off rates and affecting weathering patterns in the catchment (e.g. Blair, 1987; Cesta & Ward, 2016; Gao et al, 2020; Leonard et al, 2023; Terrizzano et al, 2017; Würtzen et al, 2021, 2022). Fan growth thus happens in response to an interplay between tectonic uplift and event‐based pulses of intense precipitation that results in high transport‐ and sedimentation rates, causing rapid sediment build‐up and frequent fluvial avulsions (Clevis et al, 2003; Cesta & Ward, 2016; Würtzen et al, 2022).…”