In glacial landscapes, debris supply rates vary spatially and temporally. Rockwall erosion rates derived from cosmogenic ¹⁰Be concentrations in medial moraine debris at five Swiss glaciers around Pigne d'Arolla indicate an increase in erosion from the end of the Little Ice Age towards deglaciation but temporally more stable rates over the last ∼100 years. Rockwall erosion rates are higher where rockwalls are steep and north-facing, suggesting a potential slope and temperature control.

River deltas encompass many depositional environments (like channels and wetlands) that interact to produce coastal environments that change through time. The processes leading to sedimentation in wetlands are often neglected from physical delta models. We show that wetland sedimentation constrains flow to the channels, changes sedimentation rates, and produces channels more akin to field-scale deltas. These results have implications for the management of these vulnerable coastal landscapes.

A novel, artificial-intelligence-based riverbed sediment analysis methodology is introduced that uses underwater images to identify the characteristic sediment classes. The main novelties of the procedure are as follows: underwater images are used, the method enables continuous mapping of the riverbed along the measurement vessel’s route contrary to conventional techniques, the method is cost-efficient, and the method works without scaling.

Packing models promise efficient and accurate porosity predictions of fluvial sediment deposits. In this study, three packing models were reviewed, calibrated, and validated. Only two of the models were able to handle the continuous and large grain size distributions typically encountered in rivers. We showed that an extension by a cohesion model is necessary and developed guidelines for successful predictions in different rivers.

Debris flows are mixtures of mud and rocks that can travel at high speeds across steep landscapes. Here, we propose a new model to describe how landscapes are shaped by debris flow erosion over long timescales. Model results demonstrate that the shapes of channel profiles are sensitive to uplift rate, meaning that it may be possible to use topographic data from steep channel networks to infer how erosion rates vary across a landscape.

Predicting how shorelines change over time is a major challenge in coastal research. We here have turned to deep learning (DL), a data-driven modelling approach, to predict the movement of shorelines using observations from a camera system in New Zealand. The DL models here implemented succeeded in capturing the variability and distribution of the observed shoreline data. Overall, these findings indicate that DL has the potential to enhance the accuracy of current shoreline change predictions.

Seasonality in precipitation (P) and vegetation (V) influences catchment erosion (E), although which factor plays the dominant role is unclear. In this study, we performed a sensitivity analysis of E to P–V seasonality through numerical modeling. Our results suggest that P variations strongly influence seasonal variations in E, while the effect of seasonal V variations is secondary but significant. This is more pronounced in moderate and least pronounced in extreme environmental settings.

This paper proposes a method for describing large-wood behavior in terms of the convection equation and the storage equation, which are associated with active sediment erosion and deposition. Compared to the existing Lagrangian method, the proposed method can easily simulate the behavior of large wood in the flow field with active sediment transport. The method is applied to the flood disaster in the Akatani River in 2017, and the 2-D flood flow computations are successfully performed.

Predicting river morphology evolution is very complicated, especially for mountain rivers with complex morphologies such as the Lac des Gaves reach in France. A 2D hydromorphological model was developed to reproduce the channel's evolution and provide reliable volumetric predictions while revealing the challenge of choosing adapted sediment transport and friction laws. Our model can provide decision-makers with reliable predictions to design suitable restoration measures for this reach.

Vegetation influences how rivers change through time, yet the way in which we analyse vegetation is limited. Current methods collect detailed data at the individual plant level or determine dominant vegetation types across larger areas. Herein, we use UAVs to collect detailed vegetation datasets for a 1 km length of river and link vegetation properties to channel evolution occurring within the study site, providing a new method for investigating the influence of vegetation on river systems.

In this paper, we investigate the 28 June 2022 collapse of the Chaos Canyon landslide in Rocky Mountain National Park, Colorado, USA. We find that the landslide was moving prior to its collapse and took place at peak spring snowmelt; temperature modeling indicates the potential presence of permafrost.  We hypothesize that this landslide could be part of the broader landscape evolution changes to alpine terrain caused by a warming climate, leading to thawing alpine permafrost.

Even under forests, soil is eroded by rainfall. This is particularly true when human impact damages vegetation layers. We found that the erosion risk can be greatly increased by structural drip points at branches forming large drops under the tree canopy in the foliated and non-foliated seasons. Our measurements with sand-filled splash cups in Japanese beech forests showed drop energies up to 50 times greater than under freefall precipitation, indicating locally severe sediment detachment.

Secondary bedforms that are superimposed on large, primary dunes likely play a large role in fluvial systems. This study demonstrates that they can be omnipresent. Especially during peak flows, they grow large and can have steep slopes, likely affecting flood risk and sediment transport dynamics. Primary dune morphology determines whether they continuously or intermittently migrate. During discharge peaks, the secondary bedforms can become the dominant dune scale.