ALBERT

Description: Fluvial deposits offer Earth’s best‐preserved geomorphic record of past climate change over geological timescales. However, quantitatively extracting this information remains challenging in part due to the complexity of erosion, sediment transport and deposition processes and how each of them responds to climate. Furthermore, sedimentary basins have the potential to temporarily store sediments, and rivers subsequently rework those sediments. This may introduce time lags into sedimentary signals and obscure any direct correlation with climate forcing. Here, using a numerical model that combines all three processes—and a new analytical solution—we show that the thickness of fluvial deposits at the outlet of a mountain river can be linked to the amplitude and period of rainfall oscillations but is modulated by the mountain uplift rate. For typical uplift rates of a few mm/yr, climate oscillations at Milankovitch periods lead to alluvial sediment thickness of tens of meters as observed in nature. We also explain the time lag of the order of 20%–25% of the forcing period that is commonly observed between the timing of maximum rainfall and erosion. By comparing to field datasets, our predictions for the thickness and time lag of fluvial deposits are broadly consistent with observations despite the simplicity of our modeling approach. These findings provide a new theoretical framework for quantitatively extracting information on past rainfall variations from fluvial deposits.

Description: Plain Language Summary: Climate influences the evolution of terrestrial landscapes through the amount of precipitation, which provides water to erode rocks and transport sediment in rivers. At the outlets of mountain ranges, rivers can deposit part of their sediment load; the shape of the deposits is influenced by the amount of flow in the rivers. If the climate changes such that the precipitation rate increases, rivers can cut into their own previous deposits. The remaining deposits are then abandoned above the riverbed. On the contrary, if precipitation decreases, rivers tend to deposit more sediment, leading to increases in the thickness of sediments at the outlets of mountain rivers. Thus, there is a relationship between the amount of precipitations and the thickness of sediments deposited at river outlets. We study this with a computer model that allows us to relate the variations in precipitation rates to variations in thickness of fluvial terrace deposits. This work can be used to better understand how rivers respond to climatic changes, and also to reconstruct climatic variations of the past from observed river deposits.

Description: Key Points: We use a numerical model and a new analytical solution to quantify a physical link between fluvial deposits and climate oscillations. Our method provides a theoretical framework for extracting information on past climate variations from fluvial terrace deposits. Our results explain time lag of 20%–25% of forcing period commonly observed between the timing of maximum rainfall and erosion.

Description: TOTAL

Description: Marie Sklodowska‐Curie grant

Description: https://doi.org/10.5281/zenodo.3833983

Description: We present a multi‐model analysis for mechanistic hypothesis testing in landscape evolution theory. The study site is a watershed with well constrained initial and boundary conditions in which a river network locally incised 50~m over the last 13 ka. We calibrate and validate a set of 37 landscape evolution models designed to hierarchically test elements of complexity from four categories: hillslope processes, channel processes, surface hydrology, and representation of geologic materials. Comparison of each model to a base model, which uses stream‐power channel incision, uniform lithology, hillslope transport by linear diffusion, and surface‐water discharge proportional to drainage area, serves as a formal test of which elements of complexity improve model performance. Model fit is assessed using an objective function based on a direct difference between observed and simulated modern topography. A hybrid optimization scheme identifies optimal parameters and uncertainty. Multi‐model analysis determines which elements of complexity improve simulation performance. Validation tests which model improvements persist when models are applied to an independent watershed. The three most important model elements are (1) spatial variation in lithology (differentiation between shale and glacial till), (2) a fluvial erosion threshold, and (3) a non‐linear relationship between slope and hillslope sediment flux. Due to nonlinear interactions between model elements, some process representations (e.g., non‐linear hillslopes) only become important when paired with the inclusion of other processes (e.g., erosion thresholds). This emphasizes the need for caution in identifying the minimally sufficient process set. Our approach provides a general framework for hypothesis testing in landscape evolution.

Description: Constraining Earth’s sediment mass balance over geologic time requires a quantitative understanding of how landscapes respond to transient tectonic perturbations. However, the mechanisms by which bedrock lithology governs landscape response remain poorly understood. Rock type influences the size of sediment delivered to river channels, which controls how efficiently rivers respond to tectonic forcing. The Mendocino triple junction region of northern California, USA, is one landscape in which large boulders, delivered by hillslope failures to channels, may alter the pace of landscape response to a pulse of rock uplift. Boulders frequently delivered by earthflows in one lithology, the Franciscan mélange, have been hypothesized to steepen channels and slow river response to rock uplift, helping to preserve high-elevation, low-relief topography. Channels in other units (the Coastal Belt and the Franciscan schist) may experience little or no erosion inhibition due to boulder delivery. Here we investigate spatial patterns in channel steepness, an indicator of erosion resistance, and how it varies between mélange and non-mélange channels. We then ask whether lithologically controlled boulder delivery to rivers is a possible cause of steepness variations. We find that mélange channels are steeper than Coastal Belt channels but not steeper than schist channels. Though channels in all units steepen with increasing proximity to mapped hillslope failures, absolute steepness values near failures are much higher (∼2×) in the mélange and schist than in Coastal Belt units. This could reflect reduced rock erodibility or increased erosion rates in the mélange and schist, or disproportionate steepening due to enhanced boulder delivery by hillslope failures in those units. To investigate the possible influence of lithology-dependent boulder delivery, we map boulders at failure toes in the three units. We find that boulder size, frequency, and concentration are greatest in mélange channels and that Coastal Belt channels have the lowest concentrations. Using our field data to parameterize a mathematical model for channel slope response to boulder delivery, we find that the modeled influence of boulders in the mélange could be strong enough to account for some observed differences in channel steepness between lithologies. At the landscape scale, we lack the data to fully disentangle boulder-induced steepening from that due to spatially varying erosion rates and in situ rock erodibility. However, our boulder mapping and modeling results suggest that lithology-dependent boulder delivery to channels could retard landscape adjustment to tectonic forcing in the mélange and potentially also in the schist. Boulder delivery may modulate landscape response to tectonics and help preserve high-elevation, low-relief topography at the Mendocino triple junction and elsewhere.

Description: Long‐term erosion can threaten infrastructure and buried waste, with consequences for management of natural systems. We develop erosion projections over 10 ky for a 5 km2 watershed in New York, USA. Because there is no single landscape evolution model appropriate for the study site we assess uncertainty in projections associated with model structure by considering a set of alternative models, each with a slightly different governing equation. In addition to model structure uncertainty we consider the following uncertainty sources: selection of a final model set; each model's parameter values estimated through calibration; simulation boundary conditions such as the future incision of downstream rivers and future climate; and initial conditions (e.g., site topography which may undergo near‐term anthropogenic modification). We use an Analysis‐of‐Variance approach to assess and partition uncertainty in projected erosion into the variance attributable to each source. Our results suggest 1/6 of the watershed will experience erosion exceeding 5 m in the next 10 ky. Uncertainty in projected erosion increases with time and the projection uncertainty attributable to each source manifests in a distinct spatial pattern. Model structure uncertainty is relatively low, which reflects our ability to constrain parameter values and reduce the model set through calibration to the recent geologic past. Beyond site‐specific findings, our work demonstrates what information prediction‐under‐uncertainty studies can provide about geomorphic systems. Our results represent the first application of a comprehensive multi‐model uncertainty analysis for long‐term erosion forecasting.

Description: Fluvial deposits offer Earth’s best-preserved geomorphic record of past climate change over geological timescales. Quantitatively extracting this information remains challenging in part due to the complexity of erosion, sediment transport and deposition processes and how each of them responds to climate. Furthermore, sedimentary basins have the potential to temporarily store sediments, and rivers subsequently rework those sediments. This may introduce time lags into sedimentary signals and obscure any direct correlation with climate forcing. Here, using a numerical model that combines all three processes—and a new analytical solution—we show that the thickness of fluvial deposits at the outlet of a mountain river can be linked to the amplitude and period of rainfall oscillations but is modulated by the mountain uplift rate. For typical uplift rates of a few mm/yr, climate oscillations at Milankovitch periods lead to alluvial sediment thickness of tens of meters as observed in nature. We also explain the time lag of the order of 20–25% of the forcing period that is commonly observed between the timing of maximum rainfall and erosion. By comparing to field datasets, our predictions for the thickness and time lag of fluvial deposits are broadly consistent with observations despite the simplicity of our modeling approach. These findings provide a new theoretical framework for quantitatively extracting information on past rainfall variations from fluvial deposits.

Description: Passive margin stratigraphy contains time-integrated records of landscapes that have long since vanished. Quantitatively reading the stratigraphic record using coupled landscape evolution and stratigraphic forward models (SFMs) is a promising approach to extracting information about landscape history. However, there is no consensus about the optimal form of simple SFMs because there has been a lack of direct tests against observed stratigraphy in well constrained test cases. Specifically, the extent to which SFM behavior over geologic space and time scales should be governed by local (downslope sediment flux depends only on local slope) versus nonlocal (sediment flux depends on factors other than local slope, such as the history of slopes experienced along a transport pathway) processes is currently unclear. Here we develop a nonlocal, nonlinear SFM that incorporates slope bypass and long-distance sediment transport, both of which have been previously identified as important model components but not thoroughly tested. Our model collapses to the local, linear model under certain parameterizations such that best-fit parameter values can indicate optimal model structure. Comparing 2-D implementations of both models against seven detailed seismic sections from the Southeast Atlantic Margin, we invert the stratigraphic data for best-fit model parameter values and demonstrate that best-fit parameterizations are not compatible with the local, linear diffusion model. Fitting observed stratigraphy requires parameter values consistent with important contributions from slope bypass and long-distance transport processes. The nonlocal, nonlinear model yields improved fits to the data regardless of whether the model is compared against only the modern bathymetric surface or the full set of seismic reflectors identified in the data. Results suggest that processes of sediment bypass and long-distance transport are required to model realistic passive margin stratigraphy, and are therefore important to consider when inverting the stratigraphic record to infer past perturbations to source regions.