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The Illgraben is a 10 km² steep side valley located in Switzerland. This active debris flow catchment supplies 5-15% of the total sediment load of the Rhône River upstream of Lake Geneva. The 30-80° steep catchment slopes host frequent rock falls and slides. From 2012 to 2014, a network of up to ten Nanometrics Trillium Compact 120s broadband seismometers, sampled by Digos DataCube³ext loggers at 200 Hz (and later by centaur), was deployed in and around the catchment to monitor distributed geomorphic activity.

Gravitational mass wasting prediction requires understanding of the factors controlling failure. Prior to slope failure, cracks in the weakened rock are thought to grow and coalesce, eventually forming a continuous failure plane. Here, we apply a hidden Markov machine learning model to seismic data, revealing the temporal evolution of cracks prior to a major rockslide event in the Swiss Alps. After prolonged linear increase of the crack cumulative number, an S-shaped crack rate pattern occurred in the day before the rockslide. A simple mechanistic model can explain this behaviour, showing that total crack boundary length is the key factor controlling failure plane evolution immediately before mass movement. Our findings imply that cracks should be treated as 2-D, rather than 1-D objects, and that slope failure can be driven predominantly by internal rather than external processes. Our model offers a novel, physically based approach for early warning of slope failures., Communications Earth & Environment, 4 (1), ISSN:2662-4435

About 10% of Europe's surface area is prone to rapid flooding of rivers confined in valleys. The devastating potential of such floods is exacerbated by the deficits of existing gauging networks, including low station densities and recording frequencies, and lack of information beyond stage height. Here, we use seismic data of the July 2021 Ahrtal flood, Germany, to extract information to complement sparse hydrometric data, and to reconstruct the rapid evolution of this fatal event. We show that a seismic station can deliver essential flood metrics such as magnitude, propagation velocity and debris transport rate. These seismic products provide high resolution insight to the non‐linear flood behavior. We argue that an approach combining distributed low‐cost seismometers with existing seismic stations, can provide important real time data on future catastrophic floods and associated hazards in upland catchments, offering precious response time also in currently ungauged landscapes., Plain Language Summary: Rapidly evolving floods are a major hazard for 10% of European landscapes. They are hard to adequately detect and describe by the classic gauge station scheme, but seismic sensors provide a valuable alternative to this difficulty. A seismometer can sense a flood like the devastating one that hit the Ahr valley, Germany, in July 2021 up to 1.5 km away. The seismic footprint of the flood allows to provide information on flood magnitude, velocity and trajectory at sub‐minute resolution and at near real time. We show how this new approach can be utilized for future flood protection., Key Points: Seismic sensing of valley confined floods improves classic detection approaches. Near‐real time information on flood magnitude, trajectory, and velocity. Gate keeper seismometer networks can improve flood risk management in Europe., GFZ German Research Centre for Geosciences, Helmholtz Centre Potsdam—GFZ German Research Centre for Geosciences http://dx.doi.org/10.13039/501100010956, German Research Foundation

Bedload transport is a key process in fluvial morphodynamics and hydraulic engineering, but is notoriously difficult to measure. The recent advent of stream-side seismic monitoring techniques provides an alternative to in-stream monitoring techniques, which are often costly, staff-intensive, and cannot be deployed during large floods. Seismic monitoring is a surrogate method requiring several steps to convert seismic data into bedload data. State-of-the-art approaches of conversion exploit physical models predicting the seismic signal generated by bedload transport. Here, we did an active seismic survey (2017-11) and used seismic data from a flood event (2016-02-22) on the Nahal Ehstemoa to constrain a seismic bedload model. We conducted the active seismic survey to determine the local seismic ground properties, i.e., the Green’s function. We also used water depth and bedload grain size distribution to constrain the seismic bedload model and were able to compare the bedload flux obtained from the seismic data using the model with high-quality independent bedload measurements from slot samplers on the site. The complementary non-seismic data is published in a separate data publication (Lagarde et al., 2020).

Cliffs line many erosional coastlines. Localized failures can cause land loss and hazard, and impact ecosystems and sediment routing. Links between cliff erosion and forcing mechanisms are poorly constrained, due to limitations of classic approaches. Combining multi-seasonal seismic and drone surveys, wave, precipitation and groundwater data we study drivers and triggers of seismically detected failures along the chalk cliffs on Germany's largest island, Rügen. The network consists of four (later five) seismic stations along the 8.6 km long chalk cliff coast. Waveforms are available from the Geofon data centre, under network code 4K, and are embargoed until Jan 2021.

Large rock slope failures play a pivotal role in long-term landscape evolution and are a major concern in land use planning and hazard aspects. While the failure phase and the time immediately prior to failure are increasingly well studied, the nature of the preparation phase remains enigmatic. This knowledge gap is due, to a large degree, to difficulties associated with instrumenting high mountain terrain and the local nature of classic monitoring methods, which does not allow integral observation of large rock volumes. Here, we analyse data from a small network of up to seven seismic sensors installed during July--October 2018 (with 43 days of data loss) at the summit of the Hochvogel, a 2592 m high Alpine peak. We develop proxy time series indicative of cyclic and progressive changes of the summit. Fundamental frequency analysis, horizontal-to-vertical spectral ratio data and end-member modelling analysis reveal diurnal cycles of increasing and decreasing coupling stiffness of a 126,000 m^3 large, instable rock volume, due to thermal forcing. Relative seismic wave velocity changes also indicate diurnal accumulation and release of stress within the rock mass. At longer time scales, there is a systematic superimposed pattern of stress increases over multiple days and episodic stress release within a few days, expressed in an increased emission of short seismic pulses indicative of rock cracking. We interpret our data to reflect an early stage of stick slip motion of a large rock mass, providing new information on the development of large-scale slope instabilities towards catastrophic failure.

Bedload transport is a key process in fluvial morphodynamics and hydraulic engineering, but is notoriously difficult to measure. The recent advent of stream-side seismic monitoring techniques provides an alternative to in-stream monitoring techniques, which are often costly, staff-intensive, and cannot be deployed during large floods. The Nahal (river) Eshtemoa is a gravel-bed river draining 119 km² of the Southern Hebron Mountains and the Northern Negev, northeast of Beer Sheva, Israel. The climate in the catchment is semi-arid, with a mean annual precipitation of 286 mm. Rainfall mainly occurs between October and May. The river is ephemeral with flash floods occurring on average five times per year (Alexandrov et al., 2009). The recurrence interval of the bankful discharge of 26 m3 s-1 has been estimated to be 1.25 years (Powell et al., 2012). Bedload fluxes are high by worldwide standards with sediment transport as much as 400 times more efficient than in a typical perennial humid river (Laronne and Reid, 1993; Reid and Laronne, 1995). The river is equipped with a monitoring station in a straight channel section with a trapezoidal cross section. The banks are nearly vertical, 1.2 m high, and comprise aeolian fines and interbedded gravel. The mean channel slope is 0.0075, which is generally mirrored by the water surface slope, with exception during the arrival of a flashflood bore (Meirovich et al., 1998). The data presented here are for the flood of the 22nd February 2016.They show a high bedload flux with peaks exceeding 1 kg/sm and water level between 0.5 and 0.8 m. The event has been previously described by Dietze et al. (2019). The data were used to assess the quality of a physical model (Tsai et al. 2012) predicting the seismic spectrum generated by the impact of bedload particles moving along the channel bed. The model requires knowledge on stream and sediment characteristics to constrain the source terms, e.g., the channel geometry and grain size distribution, as well as ground properties affecting the wave propagation, i.e., frequency-dependent wave velocity or attenuation characteristics. The complementary controlled source and passive seismological data are published in a separate data publication (Lagarde et al., 2020).

Rockfall in deglaciated mountain valleys is perhaps the most important post-glacial geomorphic process for determining the rates and patterns of valley wall erosion. Furthermore, rockfall poses a significant hazard to inhabitants and motivates monitoring efforts in populated areas. Traditional rockfall detection methods, such as aerial photography and terrestrial laser scanning (TLS) data evaluation, provide constraints on the location and released volume of rock but have limitations due to significant time lags or integration times between surveys, and deliver limited information on rockfall triggering mechanisms and the dynamics of individual events. Environmental seismology, the study of seismic signals emitted by processes at the Earth's surface, provides a complementary solution to these shortcomings. However, this approach is predominantly limited by the strength of the signals emitted by a source and their transformation and attenuation towards receivers. To test the ability of seismic methods to identify and locate small rockfalls, and to characterise their dynamics, we surveyed a 2.16 km2 large, near-vertical cliff section of the Lauterbrunnen Valley in the Swiss Alps with a TLS device and six broadband seismometers. During 37 days in autumn 2014, 10 TLS-detected rockfalls with volumes ranging from 0.053 ± 0.004 to 2.338 ± 0.085 m3 were independently detected and located by the seismic approach, with a deviation of 81−29+59 m (about 7 % of the average inter-station distance of the seismometer network). Further potential rockfalls were detected outside the TLS-surveyed cliff area. The onset of individual events can be determined within a few milliseconds, and their dynamics can be resolved into distinct phases, such as detachment, free fall, intermittent impact, fragmentation, arrival at the talus slope and subsequent slope activity. The small rockfall volumes in this area require significant supervision during data processing: 2175 initially picked potential events reduced to 511 potential events after applying automatic rejection criteria. The 511 events needed to be inspected manually to reveal 19 short earthquakes and 37 potential rockfalls, including the 10 TLS-detected events. Rockfall volume does not show a relationship with released seismic energy or peak amplitude at this spatial scale due to the dominance of other, process-inherent factors, such as fall height, degree of fragmentation, and subsequent talus slope activity. The combination of TLS and environmental seismology provides, despite the significant amount of manual data processing, a detailed validation of seismic detection of small volume rockfalls, and revealed unprecedented temporal, spatial and geometric details about rockfalls in steep mountainous terrain.

Our understanding of the effects of ice on channel morphodynamics and bedload transport in northern rivers, frozen for several months, are hindered by the difficulties of ‘seeing’ through the ice. We use continuous seismic records of a small network at the Sävar River in northern Sweden to interpret processes and quantify water and sediment fluxes. We apply a seismic inversion approach to determine seasonal differences in hydraulics and bedload sediment transport under ice-covered vs. open-channel flow conditions and provide a first-order estimation of sediment flux in that Fennoscandian river. Analysis of seismic signals of ice-cracking support our visual interpretation of ice break-up timing and the main ice break-up mechanism as thermal rather than mechanical. Waveform data are available from the GEOFON data centre, under network code 8E.

This data publication contains the data sets of a study aiming to reconstruct environmental conditions during the Holocene in the upper part of the Kali Gandaki valley, Nepal. The data are for samples taken from paleosol sections in the Upper Mustang region (Menges et al. 2019). On these samples we measured the grain size distribution to gain information about the depositional processes, pollen data to reconstruct past vegetation, 14C isotopes in the humin fraction of organic matter for soil formation ages, and hydrogen isotopic composition on n-alkanes to reconstruct past hydrological conditions. This is complemented with optically stimulated luminescence data for additional depositional age information, surface water samples and modern soil samples to constrain modern hydrological conditions, and sediment concentration data to gain insights into erosion processes. The data was generated between 2013-02 and 2018-12. The data files are provided in Excel and tab-delimited text versions.

Geomorphic concepts and hypotheses are usually formulated based on empiric data from the field or the laboratory (deduction). After translation into models they can be applied to case study scenarios (induction). However, the other way around - expressing hypotheses explicitly by models and test these by empiric data - is a rarely touched trail. There are several models tailored to investigate the boundary conditions and processes that generate, mobilise, route and eventually deposit sediment in a landscape. Thereby, the last part, sediment deposition, is usually omitted. Essentially, there is no model that explicitly focuses on mapping out the characteristics of sedimentary deposits - the material that is used by many disciplines to reconstruct landscape evolution. The R-package sandbox is a model framework that allows creating and analysing virtual sediment sections for exploratory, explanatory, forecasting and inverse research questions. sandbox is a probabilistic and rule-based model framework for a wide range of possible applications. It has been advanced and linked to another model to allow the full work flow of modelling luminescence measurements. This contribution introduces news about recent developments and shows a set of applications.

Hintergrund: Die Dynamik der frühen AMD lässt sich aktuell nur schwer vorhersagen. Einzelnukleotidpolymorphismen (SNPs) im CFH- und ARMS2-Gen sind bekannte maßgebliche Risikofaktoren einer Progression zu Spätformen der AMD. Ziel: Durch eine spezifischen funktionelle und morphologische[zum vollständigen Text gelangen Sie über die oben angegebene URL], 29. Jahrestagung der Retinologischen Gesellschaft