ALBERT

Description: Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

Description: Boulder bars are a common form of riverbed morphology that could be affected by landslide dams. However, few studies have focused on the formation and geometry characteristics of boulder bars due to outburst floods triggered by landslide dam failure. In such a way, eight group landslide dam failure experiments with a movable bed length of 4 to 7 times the dam length with 25 boulder bars were carried out. In addition, 38 boulder bars formed in the field triggered by four landslide dam failures were investigated. The aim of this paper is to study the formation and geometry characteristics of boulder bars along the riverbeds. The results show that boulder bars are formed after peak discharge of outburst flow. The number of boulder bars is 0.4 to 1.0 times the ratio of riverbed length to dam bottom length. Besides, boulder bars have the characteristic of lengthening upstream during the failure process. A boulder bar's upstream edge has a more extensive development than a boulder bar's downstream edge. The length of a boulder bar along the channel changes faster than the boulder bar's width and height. After the dam failure, the boulder bar's length is about 8 to 14 times its width. The relationship between the ratio of boulder bar length to width and the boulder bar's dimensionless length could be described with a hyperbolic equation. The dimensionless area of the boulder bar increases linearly with the dimensionless area of the river section, and the linear ratio is about 0.5. With the field data, this demonstrates that the formation and geometry characteristics of boulder bars in tests are consistent with the field boulder bars. Therefore, the results in this paper are credible and can be applied to the riverbed's geomorphological characteristics analysis triggered by overtopped landslide dam failure. The plentiful experimental and field data could contribute to the community boulder bar research.

Description: Estimation of erosion rate is an important component of landscape evolution studies, particularly in settings where transience or spatial variability in uplift or erosion generates diverse landform morphologies. While bedrock rivers are often used to constrain the timing and magnitude of changes in baselevel lowering, hilltop curvature (or convexity), CHT, provides an additional opportunity to map variations in erosion rate given that average slope angle becomes insensitive to erosion rate owing to threshold slope processes. CHT measurement techniques applied in prior studies (e.g., polynomial functions), however, tend to be computationally expensive when they rely on high-resolution topographic data such as lidar, limiting the spatial extent of hillslope geomorphic studies to small study regions. Alternative techniques such as spectral tools like continuous wavelet transforms present an opportunity to rapidly document trends in hilltop convexity across expansive areas. Here, we demonstrate how continuous wavelet transforms (CWTs) can be used to calculate the Laplacian of elevation, which we utilize to estimate erosion rate in three catchments of the Oregon Coast Range that exhibit varying slope angle, slope length, and hilltop convexity, implying differential erosion. We observe that CHT values calculated with the CWT are similar to those obtained from 2D polynomial functions. Consistent with recent studies, we find that erosion rates estimated with CHT from both CWTs and 2D polynomial functions are consistent with erosion rates constrained with cosmogenic radionuclides from stream sediments. Importantly, our CWT approach calculates curvature at least 103 times more quickly than 2D polynomials. This efficiency advantage of the CWT increases with domain size. As such, continuous wavelet transforms provide a compelling approach to rapidly quantify regional variations in erosion rate as well as lithology, structure, and hillslope sediment transport processes, which are encoded in hillslope morphology. Finally, we test the accuracy of CWT and 2D polynomial techniques by constructing a series of synthetic hillslopes generated by a theoretical nonlinear transport model that exhibit a range of erosion rates and topographic noise characteristics. Notably, we find that neither CWTs nor 2D polynomials reproduce the theoretically prescribed CHT value for hillslopes experiencing moderate to fast erosion rates, even when no topographic noise is added. Rather, CHT is systematically underestimated, producing a power law relationship between erosion rate and CHT that can be attributed to the increasing prominence of planar hillslopes that narrow the zone of hilltop convexity as erosion rate increases. As such, we recommend careful consideration of measurement length scale when applying CHT to estimate erosion rate in moderate to fast-eroding landscapes, where curvature measurement techniques may be prone to systematic underestimation.

Description: Dune height is an important predictor of impact during a storm event given that taller dunes have a lower likelihood of being overtopped than shorter dunes. However, the temporal dominance of the wave collision regime, wherein volume loss (erosion) from the dune occurs through dune retreat without overtopping, suggests that dune width must also be considered when evaluating the vulnerability of dunes to erosion. We use XBeach, a numerical model that simulates hydrodynamic processes, sediment transport, and morphologic change, to analyze storm-induced dune erosion as a function of dune aspect ratio (i.e., dune height versus dune width) for storms of varying intensity and duration. We find that low aspect ratio (low and wide) dunes lose less volume than high aspect ratio (tall and narrow) dunes during longer and more intense storms when the beach width is controlled for. In managed dune scenarios, where sand fences are used to construct a “fenced” dune seaward of the existing “natural” dune, we find that fenced dunes effectively prevent the natural dune behind them from experiencing any volume loss until the fenced dune is sufficiently eroded, reducing the magnitude of erosion of the natural dune by up to 50 %. We then control for dune morphology to assess volume loss as a function of beach width and confirm that beach width exerts a significant influence on dune erosion; a wide beach offers the greatest protection from erosion in all circumstances while the width of the dune determines how long the dune will last under persistent scarping. These findings suggest that efforts to maintain a wide beach may be effective at protecting coastal communities from dune loss. However, a trade-off may exist in maintaining wide beaches and dunes in that the protection offered in the short-term must be considered in concert with potentially long-term detrimental effects of limiting overwash, a process which is critical to maintaining island elevation as sea level rises.

Description: Thermochronometry provides one of few methods to quantify rock exhumation rate and history, including potential changes in exhumation rate. Thermochronometric ages can resolve rates, accelerations, and complex histories by exploiting different closure temperatures and path lengths using data distributed in elevation. We investigate how the resolution of an exhumation history is determined by the distribution of ages and their closure temperatures through an error analysis of the exhumation history problem. We define the sources of error, defined in terms of resolution, model error and methodological bias in the inverse method used by Herman et al. (2013) which combines data with different closure temperatures and elevations. The error analysis provides a series of tests addressing the various types of bias, including addressing criticism that there is a tendency of thermochronometric data to produce a false inference of faster erosion rates towards the present day because of a spatial correlation bias. Tests based on synthetic data demonstrate that the inverse method used by Herman et al. (2013) has no methodological or model bias towards increasing erosion rates. We do find significant resolution errors with sparse data, but these errors are not systematic, tending rather to leave inferred erosion rates at or near a Bayesian prior. To explain the difference in conclusions between our analysis and that of other work, we examine other approaches and find that previously published model tests contained an error in the geotherm calculation, resulting in an incorrect age prediction. Our reanalysis and interpretation show that the original results of Herman et al. (2013) are correctly calculated and presented, with no evidence for a systematic bias.

Description: Over the last 2 decades, permafrost degradation has been observed to be a major driver of enhanced rock slope instability and associated hazards in high mountains. While the thermal regime of permafrost degradation in high mountains has been addressed in several modelling approaches, no mechanical models that thoroughly explain rock slope destabilisation controls in degrading permafrost have been developed. Meanwhile, recent laboratory studies have shown that degrading permafrost affects both, rock and ice mechanical strength parameters as well as the strength of rock–ice interfaces. This study presents a first general approach for a temperature-dependent numerical stability model that simulates the mechanical response of a warming and thawing permafrost rock slope. The proposed procedure is exemplified using a rockslide at the permafrost-affected Zugspitze summit crest. Laboratory tests on frozen and unfrozen rock joint and intact rock properties provide material parameters for discontinuum models developed with the Universal Distinct Element Code (UDEC). Geophysical and geotechnical field surveys reveal information on permafrost distribution and the fracture network. This model can demonstrate how warming decreases rock slope stability to a critical level and why thawing initiates failure. A generalised sensitivity analysis of the model with a simplified geometry and warming trajectory below 0 ∘C shows that progressive warming close to the melting point initiates instability above a critical slope angle of 50–62∘, depending on the orientation of the fracture network. The increase in displacements intensifies for warming steps closer to 0 ∘C. The simplified and generalised model can be applied to permafrost rock slopes (i) which warm above −4 ∘C, (ii) with ice-filled joints, (iii) with fractured limestone or probably most of the rock types relevant for permafrost rock slope failure, and (iv) with a wide range of slope angles (30–70∘) and orientations of the fracture network (consisting of three joint sets). Here, we present a benchmark model capable of assessing the future destabilisation of degrading permafrost rock slopes.

Description: Although in situ measurements in modern frequently occurring turbidity currents have been performed, the flow characteristics of turbidity currents that occur only once every 100 years and deposit turbidites over a large area have not yet been elucidated. In this study, we propose a method for estimating the paleo-hydraulic conditions of turbidity currents from ancient turbidites by using machine learning. In this method, we hypothesize that turbidity currents result from suspended sediment clouds that flow down a steep slope in a submarine canyon and into a gently sloping basin plain. Using inverse modeling, we reconstruct seven model input parameters including the initial flow depth, the sediment concentration, and the basin slope. A reasonable number (3500) of repetitions of numerical simulations using a one-dimensional layer-averaged model under various input parameters generates a dataset of the characteristic features of turbidites. This artificial dataset is then used for supervised training of a deep-learning neural network (NN) to produce an inverse model capable of estimating paleo-hydraulic conditions from data on the ancient turbidites. The performance of the inverse model is tested using independently generated datasets. Consequently, the NN successfully reconstructs the flow conditions of the test datasets. In addition, the proposed inverse model is quite robust to random errors in the input data. Judging from the results of subsampling tests, inversion of turbidity currents can be conducted if an individual turbidite can be correlated over 10 km at approximately 1 km intervals. These results suggest that the proposed method can sufficiently analyze field-scale turbidity currents.

Description: The detachment of rock fragments from fractured bedrock on hillslopes creates sediment with an initial size distribution that sets the upper limits on particle size for all subsequent stages in the evolution of sediment in landscapes. We hypothesize that the initial size distribution should depend on the size distribution of latent sediment (i.e., fracture-bound blocks in unweathered bedrock) and weathering of blocks both before and during detachment (e.g., disintegration along crystal grain boundaries). However, the initial size distribution is difficult to measure because the interface across which sediment is produced is often shielded from view by overlying soil. Here we overcome this limitation by comparing fracture spacings measured from exposed bedrock on cliff faces with particle size distributions in adjacent talus deposits at 15 talus–cliff pairs spanning a wide range of climates and lithologies in California. Median fracture spacing and particle size vary by more than 10-fold and correlate strongly with lithology. Fracture spacing and talus size distributions are also closely correlated in central tendency, spread, and shape, with b-axis diameters showing the closest correspondence with fracture spacing at most sites. This suggests that weathering has not modified latent sediment either before or during detachment from the cliff face. In addition, talus at our sites has not undergone much weathering after deposition and is slightly coarser than the latent sizes because it contains unexploited fractures inherited from bedrock. We introduce a new conceptual framework for understanding the relative importance of latent size and weathering in setting initial sediment size distributions in mountain landscapes. In this framework, hillslopes exist on a spectrum defined by the ratio of two characteristic timescales: the residence time in saprolite and weathered bedrock and the time required to detach a particle of a characteristic size. At one end of the spectrum, where weathering residence times are negligible, the latent size distribution can be used to predict the initial size distribution. At the other end of the spectrum, where weathering residence times are long, the latent size distribution can be erased by weathering in the critical zone.

Description: Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes, and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made to develop landslide mapping methods, based on 2D satellite or aerial images, and to constrain the empirical volume–area (V–A) relationship which, in turn, would allow for the provision of indirect estimates of landslide volume. Despite these efforts, major issues remain, including the uncertainty in the V–A scaling, landslide amalgamation and the underdetection of landslides. To address these issues, we propose a new semiautomatic 3D point cloud differencing method to detect geomorphic changes, filter out false landslide detections due to lidar elevation errors, obtain robust landslide inventories with an uncertainty metric, and directly measure the volume and geometric properties of landslides. This method is based on the multiscale model-to-model cloud comparison (M3C2) algorithm and was applied to a multitemporal airborne lidar dataset of the Kaikōura region, New Zealand, following the Mw 7.8 earthquake of 14 November 2016. In a 5 km2 area, the 3D point cloud differencing method detects 1118 potential sources. Manual labeling of 739 potential sources shows the prevalence of false detections in forest-free areas (24.4 %), due to spatially correlated elevation errors, and in forested areas (80 %), related to ground classification errors in the pre-earthquake (pre-EQ) dataset. Combining the distance to the closest deposit and signal-to-noise ratio metrics, the filtering step of our workflow reduces the prevalence of false source detections to below 1 % in terms of total area and volume of the labeled inventory. The final predicted inventory contains 433 landslide sources and 399 deposits with a lower limit of detection size of 20 m2 and a total volume of 724 297 ± 141 087 m3 for sources and 954 029 ± 159 188 m3 for deposits. Geometric properties of the 3D source inventory, including the V–A relationship, are consistent with previous results, except for the lack of the classically observed rollover of the distribution of source area. A manually mapped 2D inventory from aerial image comparison has a better lower limit of detection (6 m2) but only identifies 258 landslide scars, exhibits a rollover in the distribution of source area of around 20 m2, and underestimates the total area and volume of 3D-detected sources by 72 % and 58 %, respectively. Detection and delimitation errors in the 2D inventory occur in areas with limited texture change (bare-rock surfaces, forests) and at the transition between sources and deposits that the 3D method accurately captures. Large rotational/translational landslides and retrogressive scars can be detected using the 3D method irrespective of area's vegetation cover, but they are missed in the 2D inventory owing to the dominant vertical topographic change. The 3D inventory misses shallow (

Description: On the list of challenges facing the world largest deltas, increased saline water intrusion (SWI) in the surface water system and its role in jeopardizing freshwater supply are often ranked very high. Yet, detailed process-based studies of SWI at the whole delta scale are limited, and the trends are regularly associated with global sea level rise. Here, using field measurements and a sophisticated 3D model that integrates the riverine, rural, estuarine, and coastal dynamics within one numerical domain, we study SWI at the scale of the Mekong Delta in extensive detail. While many studies downscale the SWI problem to a topic within an estuary, we show that the physical processes on the continental shelf, such as monsoon-driven ocean surge, directly influence salinity dynamics within the delta. Typical values of 20–40 cm surge over the continental shelf contribute to up to 10 km of further SWI. The delta's estuarine system is also more sensitive than many other systems to variations of river discharge. Furthermore, spring–neap variability plays a key role in SWI in the delta. The estuarine variability from a stratified to a mixed system between neap and spring tides develops 3D processes such as estuarine circulation and tidal straining that become the main upstream salt transport mechanisms. The 3D nature of salinity dynamics, and the role of upstream and downstream processes, suggests that compromising on dimension or extent of the numerical domain can limit the accuracy of predictions of SWI in the delta. The study also showcases the fact that riverbed incision in response to anthropogenic sediment starvation in the last 2 decades has increased stratification and activated or magnified 3D salt transport subprocesses that amplify upstream salt transport. With all the external forces on the delta, namely climate change and an altered hydrological regime by the upstream dams, due to deeper estuarine channels (driven by sand mining and upstream impoundments) compared to its near past, the delta itself has become far more vulnerable to even mild natural events. This exemplifies the fundamental importance of preserving the sediment budget and riverbed levels in protecting the world's deltas against SWI.