The Puebla-Morelos earthquake (19 September 2017) was the most damaging event in central Mexico since 1985. The seismic shaking produced hundreds of shallow landslides on the slopes of Popocatépetl volcano. The larger landslides transformed into large flows of sediment and water that travelled for kilometres. We describe this dramatic mass-wasting cascade and its predisposing factors, which have important implications for both the evolution of the volcanic edifices and for hazard assessment.

Sandy coasts are areas that undergo a lot of changes, which are caused by different influences, such as tides, wind or human activity. Permanent laser scanning is used to generate a 3-dimensional representations of a part of the coast continuously over an extended period. By comparing three unsupervised learning algorithms, we develop a methodology to analyse the resulting data set and derive which processes are dominating changes in the beach and dunes.

Forested, gravel bed streams possess complex channel morphologies which are difficult to objectively characterize. This manuscript describes a novel technique using a remotely piloted aircraft (RPA) to characterize these systems below the forest canopy. The results demonstrate the accuracy and coverage of RPAs for objectively characterizing and classifying these systems relative to more traditional, time consuming techniques that are generally used in these environments.

The 17 June 2017 Karrat landslide in Greenland caused a tsunami that killed four persons. We apply a multidisciplinary workflow to reconstruct a timeline of events and find that three historic landslides occurred in 2009, 2016 and 2017. We also find evidence of much older periods of landslide activity. Three newly discovered active landslides might pose a future hazard. We speculate that the trigger for the recent events is melting permafrost due to a warming climate.

Existing ways of modeling the flow of water amongst landscape depressions such as swamps and lakes take a long time to run. However, as our previous work explains, depressions can be quickly organized into a data structure – the depression hierarchy. This paper explains how the depression hierarchy can be used to quickly simulate the realistic filling of depressions including how they spill over into each other, and, if they become full enough, how they merge into one another.

Mountain streams often display a stepped morphology but the conditions under which these steps form, remain stable, and eventually collapse are still not entirely clear. We run flume experiments to study how (a) the amount of sediment input and (b) channel width variations affect steps dynamic in steep channels. Steps form preferentially in areas of flow convergence (channel narrowing) and their frequency is higher when sediment supply is larger than zero but smaller than the transport capacity.

We propose a machine learning approach for the classification and analysis of large delta systems. The approach uses remotely sensed data, channel network extraction, and the analysis of 10 metrics to identify clusters of island with similar characteristics. The 14 clusters are grouped into 6 main classes related to morphological processes acting on the system. The approach allows to identify spatial patterns in large river deltas to inform modeling and the collection of field observations.

Part of the inaccuracies when estimating bedload transport in gravel-bed rivers is because we are not considering the wide distributions of shear stress in these systems. We modified a subsurface-based bedload transport equation to include these distributions. By doing so, our approach accurately predicts bedload transport rates when the pavement layer is still present while the original one predicts zero transport. For high flows, our method had a similar performance than the original equation.

Alternate bars are large sediment deposits that tend to naturally form in rivers when the channel width is sufficiently large. Our laboratory experiments on a scaled model reveal that equilibrium properties of self-formed alternate bars highly depend on the water discharge with respect to the relevant theoretical thresholds. This work provides fundamental information for predicting the response of rivers to natural or human alterations of the flow regime.

Our new Holocene sea level curve are not only different to previously published data, but also different to global GIA models. We see that as soon as ice melting has ceased, local processes control shoreline migration and coast evolution. This indicates that more emphasis should be placed on regional coast and sea-level change modelling under a global sea-level rising future as the local government need more specific and effective advice to deal with coastal flooding.

Shape characteristics of rocks and sediments can provide crucial information about their origin and their environment, but the automation of their measurement is often time-consuming and complicated. We introduce a workflow based on a portable 3D scanner and a computer algorithm that allows for the fast and efficient recording and evaluation of the shapes of rocks. Using this method, we can examine the geometry of hundreds of particles in a few days without transporting or storing them.

One of the most interesting problems in geomorphology concerns the conditions that mobilise sediments grains in rivers. Newly developed smart pebbles allow for the measurement of those conditions directly, if a suitable framework for analysis is followed. This paper connects such a framework with the physics used to described sediment motion and presents a series of laboratory and field smart-pebble deployments. Those quantify how grain shape affects the motion of coarse sediments in rivers.

Accurate and continuous data collection is challenging in physical scale experiments. A novel means to augment measurements is to numerically model flow over the experimental digital elevation maps. We tested this modelling approach for one tidal and two river scale experiments and showed that modelled water depth and flow velocity closely resemble the measurements. The implication is that conducting experiments requires fewer measurements and results in flow data of better overall quality.

Rockfall size and frequency in two deglaciating cirques in the Central Austrian Alps is analysed based on six-year rockwall monitoring with terrestrial LiDAR (2011-17). The erosion rates derived from this data set are very high due to a frequent occurrence of large rockfalls in freshly deglaciated areas. The results obtained are important for rockfall hazard assessments as in rockwalls affected by glacier retreat historical rockfall patterns are not good predictors of future events.