ALBERT

Description: We present a probabilistic sediment cascade model to simulate sediment transfer in a mountain basin (Illgraben, Switzerland) where sediment is produced by hillslope landslides and rockfalls and exported out of the basin by debris flows and floods. The model conceptualizes the fluvial system as a spatially lumped cascade of connected reservoirs representing hillslope and channel storages where sediment goes through cycles of storage and remobilization by surface runoff. The model includes all relevant hydrological processes that lead to runoff formation in an Alpine basin, such as precipitation, snow accumulation, snow melt, evapotranspiration, and soil water storage. Although the processes of sediment transfer and debris flow generation are described in a simplified manner, the model produces complex sediment discharge behavior which is driven by the availability of sediment and antecedent wetness conditions (system memory) as well as the triggering potential (climatic forcing). The observed probability distribution of debris flow volumes and their seasonality in 2000-2009 are reproduced. The stochasticity of hillslope sediment input is important for reproducing realistic sediment storage variability, although many details of the hillslope landslide triggering procedures are filtered out by the sediment transfer system. The model allows us to explicitly quantify the division into transport and supply-limited sediment discharge events. We show that debris flows may be generated for a wide range of rainfall intensities because of variable antecedent basin wetness and snowmelt contribution to runoff, which helps to understand the limitations of methods based on a single rainfall threshold for debris flow initiation in Alpine basins.

Description: ABSTRACT Landslides and rockfalls are key geomorphic processes in mountain basins. Their quantification and characterization are critical for understanding the processes of slope failure and their contributions to erosion and landscape evolution. We used digital photogrammetry to produce a multi-temporal record of erosion (1963 – 2005) of a rock slope at the head of the Illgraben, a very active catchment prone to debris flows in Switzerland. Slope failures affect 70% of the study slope and erode the slope at an average rate of 0.39 ± 0.03 m yr¯¹. The analysis of individual slope failures yielded an inventory of ~2500 failures ranging over 6 orders of magnitude in volume, despite the small slope area and short study period. The slope failures form a characteristic magnitude-frequency distribution with a rollover and a power-law tail between ~200 m³ and 1.6x10⁶ m³ with an exponent of 1.65. Slope failure volume scales with area as a power law with an exponent of 1.1. Both values are low for studies of bedrock landslides and rockfall and result from the highly fractured and weathered state of the quartzitic bedrock. Our data suggest that the magnitude-frequency distribution is the result of two separate slope failure processes. Type (1) failures are frequent, small slides and slumps within the weathered layer of highly fractured rock and loose sediment, and make up the rollover. Type (2) failures are less frequent and larger rockslides and rockfalls within the internal bedded and fractured slope along pre-determined potential failure surfaces, and make up the power-law tail. Rockslides and rockfalls of high magnitude and relatively low frequency make up 99% of the total failure volume and are thus responsible for the high erosion rate. They are also significant in the context of landscape evolution as they occur on slopes above 45° and limit the relief of the slope. Copyright © 2012 John Wiley & Sons, Ltd.

Description: ABSTRACT Many rivers worldwide show converging sections where a characteristic limiting front for vegetation establishment on gravel bars is observed. An important conceptual model was advanced by Gurnell and Petts (2006), who demonstrated that for the convergent section of the Tagliamento River, the downstream front of vegetation establishment can be explained by unit stream power. We introduce a theoretical framework based on 1-D ecomorphodynamic equations modified to account for the biological dynamics of vegetation. We obtain the first analytical result explaining the position and river width where vegetation density is expected to vanish in relation to a characteristic streamflow magnitude and both hydraulic and biologic parameters. We apply our model to a controlled experiment within a convergent flume channel with growing seedlings perturbed by periodic floods. For a range of timescales where hydrological and biological processes interact, we observe the formation of a front in the convergent section beyond which vegetation cannot survive, the location of which is explained by flow magnitude. This experiment confirms that the timescales of the involved processes and the unit stream power determine the existence and the position of the front within convergent river reaches, respectively. Copyright © 2014 John Wiley & Sons, Ltd.

Description: Bedload sediment transport and erosion processes in channels are important components of water induced natural hazards in alpine environments. A raster based distributed hydrological model, TOPKAPI, has been further developed to support continuous simulations of river bed erosion and deposition processes. The hydrological model simulates all relevant components of the water cycle and non-linear reservoir methods are applied for water fluxes in the soil, on the ground surface and in the channel. The sediment transport simulations are performed on a sub-grid level, which allows for a better discretization of the channel geometry, whereas water fluxes are calculated on the grid level in order to be CPU efficient. Several transport equations as well as the effects of an armour layer on the transport threshold discharge are considered. Flow resistance due to macro roughness is also considered. The advantage of this approach is the integrated simulation of the entire basin runoff response combined with hillslope-channel coupled erosion and transport simulation. The comparison with the modelling tool SETRAC demonstrates the reliability of the modelling concept. The devised technique is very fast and of comparable accuracy to the more specialised sediment transport model SETRAC.

Description: There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.

Description: This paper presents a method to identify intense warm season storms of convective character based on intensity thresholds and lightning, and analyzes their statistical properties. Long records of precipitation and lightning data at 4 stations and 10 min resolution in different climatological regions in Switzerland are used. Our premise is that thunderstorms associated with lightning generate bursts of high rainfall intensity. We divided all storms into those accompanied by lightning and those without lightning and found the threshold I* that separates intense events based on peak 10 min intensity Ip ≥ I* for a chosen misclassification rate α. The performance and robustness of the selection method was tested by investigating the inter-annual variability of I* and its relation to the frequency of lightning strikes. The probability distributions of the main storm properties (rainfall depth R, event duration D, average storm intensity Ia and peak 10 min intensity Ip) for the intense storm subsets show that the event average and peak intensities are significantly different between the stations, and highest in Lugano in southern Switzerland. Non-parametric correlations between the main storm properties were estimated for the subsets of intense storms and all storms including stratiform rain. The differences in the correlations between storm subsets are greater than those between stations, which indicates that care must be exercised not to mix events when they are sampled for multivariate analysis, e.g. copula fitting to rainfall data.

Description: This paper presents a method to identify intense warm season storms with convective character based on intensity thresholds and the presence of lightning, and analyzes their statistical properties. Long records of precipitation and lightning data at 4 stations and 10 min resolution in different climatological regions in Switzerland are used. Our premise is that thunderstorms associated with lightning generate bursts of high rainfall intensity. We divided all recorded storms into those accompanied by lightning and those without lightning and found the threshold I* that separates intense events based on peak 10 min intensity Ip ≥ I* for a chosen misclassification rate α. The performance and robustness of the selection method was tested by investigating the inter-annual variability of I* and its relation to the frequency of lightning strikes. The probability distributions of the main storm properties (rainfall depth R, event duration D, average storm intensity Ia and peak 10 min intensity Ip) for the intense storm subsets show that the event average and peak intensities are significantly different between the stations. Non-parametric correlations between the main storm properties were estimated for intense storms and all storms including stratiform rain. The differences in the correlations between storm subsets are greater than those between stations, which indicates that care must be exercised not to mix events of different origin when they are sampled for multivariate analysis, for example, copula fitting to rainfall data.

Description: Sediment transport and erosion processes in channels are important components of water induced natural hazards in alpine environments. A distributed hydrological model, TOPKAPI, has been developed to support continuous simulations of river bed erosion and deposition processes. The hydrological model simulates all relevant components of the water cycle and non-linear reservoir methods are applied for water fluxes in the soil, on the surface and in the channel. The sediment transport simulations are performed on a sub-grid level, which allows for a better discretization of the channel geometry, whereas water fluxes are calculated on the grid level in order to be CPU efficient. Flow resistance due to macro roughness is considered in the simulation of sediment transport processes. Several transport equations as well as the effects of armour layers on the transport threshold discharge are considered. The advantage of this approach is the integrated simulation of the entire water balance combined with hillslope-channel coupled erosion and transport simulation. The comparison with the modelling tool SETRAC and with LiDAR based reconstructed sediment transport rates demonstrates the reliability of the modelling concept. The modelling method is very fast and of comparable accuracy to the more specialised sediment transport model SETRAC.