Journal of Geophysical Research: Earth Surface最新文献

Salt marshes sequester large amounts of carbon, mainly within their deep soils. Several nationwide assessments have indicated that spatial variability of marsh soil carbon is minimal, however there's a need to further reduce carbon stock uncertainties by exploring finer-scale variation using a process-based modeling approach. Marsh soil properties vary spatially with several parameters, including marsh platform elevation, which controls inundation depth, and proximity to the marsh edge and tidal creek network, which control variability in relative sediment supply. We used lidar to extract these morphometric parameters from salt marshes to map soil organic carbon across a marsh at the meter scale. Soil samples were collected in 2021 from four northeast U.S. salts marshes with distinctive geomorphologies. Tidal creeks were delineated from 1-m resolution topobathy lidar data using a semi-automated workflow in GIS. Log-linear multivariate regression models were developed to predict soil organic matter, bulk density, and carbon density as a function of predictive metrics at each site and across sites. Distance from tidal creeks was the most significant model predictor. Modeling marsh soil characteristics worked best in marshes with single channel hydrology. Addition of distance to the inlet and tidal range as regional metrics significantly improved cross-site modeling. Our mechanistic approach reveals important meter-level variation in soil characteristics across a marsh and provides motivation to continue rigorous mapping of soil carbon at fine spatial resolutions. Furthermore, carbon density values used to calculate total marsh carbon stocks should be carefully selected depending on project scale, marsh geomorphology, and desired accuracy.

Rock-ice avalanches in cold-high mountainous regions exhibit remarkably high mobility, frequently resulting in catastrophic consequences. However, the systematic influence of ice on the mobility of rock-ice avalanches remains poorly understood. This paper addresses this gap by conducting a comprehensive flume experiment in a temperature-controlled room at −10°C, simulating rock-ice avalanches and considering variations in rock-ice particle size ratios and ice contents. Overall mobility and segregation patterns are quantified by analyzing deposition characteristics, while high-speed cameras capture velocity and segregation features during motion. Our investigation reveals a notable rock-ice segregation phenomenon that significantly impacts the mobility of the mixture. Building on insights from prior numerical experiments conducted under nearly-no-base-slip conditions (Feng et al., 2023, https://doi.org/10.1029/2023jf007115), our results underscore that the particle segregation simultaneously influences both internal (bulk) and basal frictions, thereby producing different nonlinear impacts on the mobility of the rock-ice flow. Additionally, an empirical formula is proposed to describe the evolution of the friction coefficient in cases with different rock-ice particle size ratios and ice contents. These findings have significant implications for predicting runout and assessing the risk of rock-ice avalanches.

Landscape scale bedrock erosion is the integration of bedrock erosion at the reach scale, which is driven by particle impacts from sediment transport caused by near-bed hydraulics. Plunging flow hydraulics have been identified in bedrock canyons and cause velocity profile inversions, which enhance near-bed velocities, sediment transport, and the potential for bedrock erosion. Observations of plunging flows are limited, and the frequency and statistical properties of this hydraulic phenomenon have not been investigated. Here, we define metrics to identify velocity inversions and use them to detect instances of plunging flows through a 375 km reach of the Fraser River where channel morphology is controlled by bedrock. Isolated plunging flows are identified as well as plunging flow complexes where a series of plunges cause the core of maximum velocity to remain depressed in the water column for a prolonged distance. A significant relationship between plunging flows and bedrock exposure is identified, and plunging flows occupy more than half of the bedrock confined reaches. Stronger plunging flows are correlated with deeper and narrower channels with higher maximum shear stresses. Plunging flows are also concentrated in steeper reaches, which likely represent knickzones in the river profile. We use particle abrasion-based bedrock erosion models to show that plunging flows drive reach-scale incisions in bedrock rivers, creating deep bedrock pools. These pools dominate the incision into the bedrock, which sets the base level for their drainage areas and in turn sets the pace of landscape evolution.

This study presents a micro-mechanical numerical investigation of the fundamental aspects of progressive fragmentation and its effects on rock avalanche dynamics. The simulations involve breakable rock assemblies that are released along an inclined plane and subsequently collide onto a horizontal surface. A discrete-continuous numerical model is adopted to effectively capture progressive particle breakage and complex interparticle interactions. By incorporating variations in fracture mechanics parameters, the model systematically evaluates the influence of progressive grain fragmentation on rock avalanche dynamics. A multi-layer analysis method and the interlayer transmitting coefficient are proposed to analyze the temporal and spatial kinematics, stress distribution and the ongoing particle size reduction process. The results indicate that grain fragmentation significantly influences rock avalanche motion, identified as the “retard-boost” effect in this study. At low fragmentation degrees, densely packed rock particles exhibit an interlayer transmitting effect, with kinematic energy dissipation primarily resulting from grain breakage. Conversely, full mobilization of rock fragmentation from the base upwards enhances flow mobility by reducing basal friction through the agitation of fragments. The findings indicate a competition between positive feedback, which enhances rock avalanche mobility at high fragmentation levels, and negative feedback, which results in energy dissipation at low fragmentation levels, with the predominance of these effects varying according to the degree of fragmentation.

River channel changes during floods, including bank erosion and bar deposition, are difficult to predict but important for infrastructure, river management, and riparian zone health. Upstream dams can also drive disequilibrium changes to channel morphology, potentially changing bar and bank susceptibility to flooding. To understand feedback between bar morphology, flood flow, bank erosion and channel cross-sectional evolution, we (a) evaluate how bank erosion during natural floods in six gravel-bed rivers with alternate and/or mid-channel bars varied with bar and bank height, and (b) conduct laboratory experiments scaled to the Chubetsu River in Japan, a pseudo-meandering gravel-bed river that has experienced bank erosion influenced by alternate bars. The field data show a strong correlation between bank erosion during floods and the bar to bank height ratio measured before the respective floods. We also find that rivers with upstream dams tend to have higher bar to bank height ratios. In the experiments, we systematically vary flood discharge, initial bar height, and initial bank height, and measure bank erosion and bar evolution. We experimentally find that bank erosion initially increases with bar height and flood discharge. As bar height evolves, bank erosion rates tend to converge under different initial conditions. Bank erosion rate increases with decreasing bank height. Because bars in natural rivers tend to not be adjusted to the largest floods, our experimental results and field data suggest that surveyed ratios of bar height to bank height could be used to infer relative bank erosion risks prior to large floods.

Snow avalanches pose a significant threat to settlements and their inhabitants. Consequently, hazard maps that delineate avalanche runout areas serve as valuable tools for mitigating their destructive impact. Dynamic models have been used to visualize areas affected by avalanches; however, these models require uncertain inputs. This study develops probabilistic hazard maps by quantifying uncertain input variables through probability density functions. These maps represent the probability of model outputs, such as maximum flow thickness, exceeding specific thresholds, allowing for more quantitative hazard assessments. Three uncertainty quantification methods—Monte Carlo, Latin hypercube sampling, and polynomial chaos quadrature (PCQ)—are employed to generate probabilistic hazard maps for snow avalanches. These maps are compared with a reference hazard map created using parameter sets that cover the entire parameter space. Among the three methods, PCQ yields the most accurate results for a given number of simulations, assuming a uniform distribution for each input. The optimal PCQ settings, which deliver superior results with fewer simulations, are then determined. Additionally, a PCQ application is proposed to generate hazard maps based on non-uniform input distributions without requiring extra simulations. This approach reduces the computational cost associated with creating hazard maps for non-uniform distributions if PCQ has already been applied to a uniform case. The application generates two types of probabilistic hazard maps: one considering all potential parameter ranges during the snow season using uniform distributions, and another reflecting non-uniform distributions that account for uncertainty in near-term current snow cover conditions.

Bank erosion in a natural alluvial river is influenced not only by near-bank hydraulic conditions but also predominantly by bank soil properties. These factors exhibit considerable uncertainties, which are seldom considered in previous bank erosion models. Therefore, this study proposes a probabilistic process-based model of bank erosion by embedding the probability distributions of different bank soil parameters. The model was applied to simulate the bank erosion process in the Middle Yangtze River (MYR), and it was validated against field measurements. Results show that: (a) bank soil parameters including critical shear stress, friction angle and cohesion, followed the Log-Normal or Gamma distribution, with large variation coefficients of 0.44, 0.59, and 0.50; (b) the expected values of the calculated bank erosion widths agreed closely with measurements (with a relative error of 5%), and the high probability of mass failure occurred within a seasonal timescale (during September–November 2019), despite the high uncertainties in soil properties; and (c) the incorporation of water content variation into the stochastic model further increased the uncertainty of the results by several-fold, indicating that considering more influencing factors in the model may reduce prediction accuracy. Besides, from a large-scale perspective, the high diversity of river morphology (channel width) is also closely related to these uncertainties.

Massive ground ice in Arctic regions underlain using continuous permafrost influences hydrologic processes, leading to ground subsidence and the release of carbon dioxide and methane into the atmosphere. The relation of massive ground ice such as ice wedges to water tracks and seasonally saturated hydrologic pathways remains uncertain. Here, we examine the location of ice wedges along a water track on the North Slope of Alaska using Ground-Penetrating Radar (GPR) surveys, in situ measurements, soil cores, and forward modeling. Of nine unique GPR surveys collected in the summers of 2022 and 2023, seven exhibit distinctive “X”-shaped reflections above columnar reflectors that are spatially correlated with water track margins. Forward modeling of plausible geometries suggests that ice wedges produce reflection patterns most similar to the reflections observed in our GPR profiles. Additionally, a large magnitude (∼71 mm) rain event on 8 July 2023 led to a ground collapse that exposed four ice wedges on the margin of the studied water track, ∼100 m downstream of our GPR surveys. Together, this suggests that GPR is a viable method for identifying the location of ice wedges as air temperatures in the Arctic continue to increase, we expect that ice wedges may thaw, destabilizing water tracks and causing ground collapse and expansion of thermo-erosional gullies. This ground collapse will increase greenhouse gas emissions and threaten the Arctic infrastructure. Future geophysical analysis of upland Arctic hillslopes should include additional water tracks to better characterize potential heterogeneity in permafrost vulnerability across the warming Arctic.

The sliding speed of glaciers depends strongly on the water pressure at the ice-sediment interface, which is controlled by the efficiency of water transport through a subglacial hydrological system. The least efficient component of the system consists of “distributed” flow everywhere beneath the ice, whereas the “channelized” drainage through large, thermally eroded conduits is more efficient. To understand the conditions under which the subglacial network channelizes, we perform a linear stability analysis of distributed flow, considering competition between thermal erosion and viscous ice collapse. The calculated growth rate gives a stability criterion, describing the minimum subglacial meltwater flux needed for channels to form, but also indicates the tendency to generate infinitely narrow channels in existing models. We demonstrate the need to include lateral heat diffusion when modeling melt incision to resolve channel widths, which allows continuum models to recover Röthlisberger channel behavior. We also show that low numerical resolution can suppress channel formation and lead to overestimates of water pressure. Our derived channelization criterion can be used to predict the character of subglacial hydrological systems without recourse to numerical simulations, with practical implications for understanding changes in ice velocity due to changes in surface melt runoff.