River ecosystems are strongly influenced by landform and human activities within their catchments. Most rivers worldwide have been severely altered by a combination of different anthropogenic interventions, leading to dramatic changes in the aquatic habitat and the organism community. With information about species composition, abundance, dominance and population structure it is possible to make reliable predictions about the status of the river ecosystem. Therefore, fishes have been established as a biological indicator for the good water status in the European Union and in accordance with the European Water Framework Directive. In this context, the ALFFA INTERREG project between Italy and Austria has the aim of evaluating the effect of human activities on water quality and streamflow regimes, and therefore on the fish fauna, with special focus on Tyrol and South Tyrol. For this study area, 80 sampling points have been selected, where the impacts of all influencing drivers (e.g. land cover, agriculture, fisheries, fish-eating birds, water chemistry, pesticides, hydrology, etc.) needs to be evaluated. From the landscape perspective, a crucial aspect is the estimation of the anthropogenic alteration (i.e. degree of disturbance) of the river ecosystems and their catchments, due to agriculture, housing estates, fertilizer used by farmers etc. To this aim, we used an integrative approach for analysing habitat diversity, landscape structuring, urban sprawl and land use in diverse cultivated and natural mountain areas. Additionally, with electrofishing and water sampling we have investigated fish populations and the amount of macrozoobenthos which have shown that Tyrol and South Tyrol display large differences in these categories. The evaluation of the responsible drivers has not been done so far. Lastly, we will incorporate all results into river management plans to provide guidelines for future decisions making.

The Afromontane regions are some of the places that harbour the richest biodiversity and are the hope for the water security in most parts of Africa. One such area is the Drakensberg which extends 1000 km and separates South Africa and Lesotho. At its foot, towards the south-western side, lies the small region of the Maluti-a-Phofung with two river systems, Elands and Wilge Rivers, which drain into the Vaal River basin. While the Wilge River system feeds off the Elands River system, both these river systems receive the treated wastewater effluent from the two wastewater treatment plants in the Maluti-a-Phofung region respectively. However, the water chemistry of these rivers especially as it relates to the contribution of heavy metals by the two treatment plants in the region has not been profiled. The present study therefore aimed to profile the heavy metals concentration of the Elands River and the Wilge River in order to understand the contribution of the local wastewater treatment plants to their heavy metal content. Inductively coupled plasma mass spectrometry was used to analyse the water samples for selected heavy metals. The results of this assessment indicate significant contribution (P<0.05) of heavy metals to the Wilge River by the Harrismith wastewater treatment plant. In contrast, the Phuthaditjhaba wastewater treatment plant’s contribution was not significant (P>0.05) with most of the heavy metals being contributed by activities before the discharge point. In order to provide ecological relevance to our findings, both wastewater treatment plants and rivers are part of ongoing ecotoxicological studies.

Mountainous basins are the strategic area of both water resources and flood control in Japan. Therefore, the accurate reproduction and reliable prediction of runoff from mountainous basins are significant issue. However, hydrological models still have uncertain parameters on which the accuracy of the model performance depends. In order to develop reliable hydrological model, this study investigate the property of the parameters in the storage–discharge relationship for low flows and floods. In addition, the hydrological analysis is carried out to estimate the runoff variation in the future using GCM data.

We selected four snowy mountainous basins with area from 206 to 331 km², which located in different regions of topographical, geological and climatological conditions. The hydrological model used in this study consists of the infiltration model presented by Diskin and Nazimov (1995) and the storage–discharge relations originally described by Horton (1936). The storage–discharge equation comprises two parameters, the exponent and the constant, which are different in each basin and each flood events.

The hydrological analysis is carried out for the term of 14 years and 15 years by hourly time step for each basin, while changing the values of the two parameters using a double-loop algorithm.

The simulation for future runoff projections is carried out for the period of 2080–2099 with MIROC5, provided based on ISI-MIP, in accordance with the emissions scenario RCP8.5. The adjustment of this data to the basin scale is performed for 0.5-degree resolution surrounding the study basin using the observed current data.

The results show that, a) the two parameters for low flow have inverse relationship, b) the two parameters for floods have the relationship which is represented by exponential function. c) The snowfall is conspicuously decreased and it will be affected to the water resources of the snowy region in Japan.

Mountainous regions are highly sensitive to climatic changes. The warming trend of the last decades and the related retreat of glaciers and permafrost consequently imply strong changes regarding sediment transport patterns due to intensive melting and the (re-)activation of potential sediment sources. The present study aims to present a holistic approach to analyze sediment cascades in this climatic and geomorphological context.

The study area, the partly glaciated Solda / Sulden catchment in the area of Val Venosta / Vinschgau (Italian Alps), was mapped geomorphologically to define the spatial distribution of source, transport and deposition areas. Subsequently, potential sediment pathways between topographically connected geomorphological landforms form the base to analyse the network of transport processes within the catchment in detail. The identification of spatial and temporal hot-spots as well as triggering factors of these sediment transport processes will be obtained by combining the results of the network analysis with results of DEMs of Difference (DoDs) representing different time intervals (months/years). Furthermore, measurements of fluvial sediment transport play an important role to qualitatively validate the findings. The monitoring combines regularly conducted direct measurements of both bedload and suspended sediments and continuous indirect measurements (e.g. geophones, turbidimeters). Sampling points are located at glacier outlets, in the proglacial river and at the outlet of the catchment.

Finally, based on the overall result of the study, the significance of extreme meteorological events, like heavy rain storms or heat waves, for the intensity and spatial distribution of sediment transport will be estimated to outline potential risks for infrastructure or population.

Processes like fluvial flows (floods with or without intensive bedload transport) or debris flows represent extreme events in torrential catchments that can transfer large amounts of sediment to the receiving river or alluvial fan. In contrast to fluvial flows, the formation of debris flows is the result of a critical combination of water, sufficient sediment that can be mobilized, and topographic slope. In alpine regions, excessive water input typically results from long lasting rainfall (LLR), short duration storms (SDS) or intense snow melt (SM). In a recent study, we derived multiple hydro-meteorological variables from long-term hydrological simulations to investigate the trigger conditions of fluvial flows and debris flows in six regions in Austria. We found distinct regional and seasonal differences, but overall roughly 2/3 of the debris flows were initiated by SDS events and 1/4 by LLR events, the remaining by SM. Fluvial flows tend to results from a higher total precipitation input than debris flows. When ex-post predicting the susceptibility for debris flow initiation with a Naïve Bayes Classifier model, we found that multi-variable trigger models outperformed simple intensity-duration thresholds. The remaining uncertainty we largely attribute to the unknown sediment dynamics in the watersheds that were not included in the susceptibility assessment. We conclude that the consideration of different hydro-meteorological trigger types improves engineering risk assessment.

Prediction of a watersheds temporal susceptibility to debris flows using multiple hydro-meteorological variables

Prenner D., Kaitna R., Mostbauer K., Hrachowitz M.

Debris flows represent a threat for societies in alpine regions and are typically triggered by excessive water input from long lasting rainfall (LLR), short duration storms (SDS) or intense snow melt (SM) into torrential watersheds. The prediction of debris flow events mostly relies on rainfall intensity and duration (I-D) alone, which is often less reliable for practical applications because of the high spatial variability of precipitation. To overcome this limitation, we utilize multiple hydro-meteorological variables like snow melt, evapotranspiration, soil moisture from a hydrological simulation besides station data of precipitation and temperature to predict the temporal susceptibility of the Montafon watershed to debris flows between 1953 and 2013. Therefore, we setup four Naive Bayes Classifier models of different complexity, ranging from simple rainfall only to multi-variable, multi-trigger type as well as a classical I-D curve and evaluate the performance using Receiver Operating Statistics. Results show that the watershed is in very different states in dependence of the trigger of either LLR, SDS or SM on the 38 documented debris flow event days in the region. The multi trigger-type models outperform the simpler models as well as I-D curve by showing both, higher true positive rates and lower false alarm rates. We conclude that, the consideration of hydro-meteorological variables can help to improve debris flow prediction in future.

Plastics may serve as a technofossil and stratigraphic marker for the geological Anthropocene. The oceans are the primary longer-term sink of plastics, forming large plastic islands and slowly sinking down to the sea bottom to mix with deeper-marine sediments. Microplastic particles are globally distributed in the technosphere, from glaciers to soils and ingested by various organisms including humans.

We identified the microplastics (<5 mm) contamination of alpine catchments and river sediments along the river course using two case studies from the river Alz (Bavaria) and the river Triesting (Lower Austria). Along the Alz (24 sites) and the Triesting (10 sites) river bank sediment samples were collected. Sediment grains were visually subdivided using a microscope. Extrapolated onto one kilogram of dry sediment a maximum amount of (suspect plastic) 81,000 particles (Alz) and 35,000 particles was found. Raman-spectroscopy and partly infrared spectroscopy was used for testing selected suspect particles groups and to reduce the large error bar introduced by visual (mis-)identification. Upscaling still indicates at least a mean of several thousand of microplastic particles per kg dry sediment, mainly fibres, subordinate microbeads, fragments and films, present from the river head in alpine catchments downstream. Around bigger cities or small-scale industrial areas, the total amount of particles and percentages of microbeads increased significantly. Total numbers of small microplastic particles in those alpine river sediments are similar to river and lake shore sediments from highly industrial and densely populated areas like the river Rhine or Lake Ontario, marking the global contamination of the environment by plastics.

Debris flows are dangerous natural hazards that every year cause fatalities and damages to infrastructures. One of the challenges of the last decades is to predict the dynamics of such events using specific numerical models. The aim of this study is to satisfactorily reproduce the progressive erosion dynamic of a debris flow starting from a channelized water flux. This kind of process was reproduced exploiting the functionality of the r.avaflow model that is capable to simulate a two-phase mixture of gravity mass flows.

The investigated study case occurred near the village of Cortina D’Ampezzo (Veneto Region, Italy) during the 2017 summer. The debris flow was triggered by an extreme rainfall event that caused an intense runoff, entraining sediment materials from the channel bed and then generating a mature granular debris flow. To reproduce the erosion pattern, the modelling approach developed in r.avaflow was improved. Specifically, the input erosion coefficient was varied according to a calibrated exponential function of the local slope. Another simulation was performed using the best constant erosion coefficient to assess the performance of the improved model.

The results of these two simulations were then compared with the observed (LiDAR surveys) erosion pattern. In particular, using a slope dependent erosion coefficient, the entrained volumes and the erosion trend resulted in a more reliable topography than those produced by a constant erosion coefficient. The same good performance was obtained in terms of bulked peak discharge flowing 1.4 km downstream of the input water hydrograph.

In conclusion, the research has highlighted the satisfactorily simulation of debris flow triggering for r.avaflow model and provided a supplementary methodology of model implementation for a more accurate prediction of debris flow erosion.

Understanding morphology changes and sediment spreading along a debris-flow channel is a key step in hazard mitigation planning.
This research analyses a 10 years evolution of erosion/deposition patterns in an active debris-flow upper channel located on the Dolomites (rio Soial, Val di Fassa, Trento, Italy). The morphologic evolution of the channel has been analysed performing a Difference of DEM (DoD) and comparing the 2008 LiDAR-derived DTM of the Autonomous Province of Trento with a DTM created from a UAV-based point cloud of the July 2018. This data set was also used to determine the changes of the sediment Connectivity Index (CI), which explains the existing degree of linkage between sediment sources and channel network. During the period 2008-2018 five debris flow events have occurred. Each associated rainstorm was analysed in order to assess the evolution of the threshold rain intensities for the triggering in relation to the evolution of the channel-valley morphology.
The results on the CI analysis show a general decrease in CI values, meaning an increased disconnection between the head basin areas and the outlet at the end of the transport reach. Also, the rain thresholds show a slight increase after the lasts event, indicating a gradual stabilization of the basin and a possible reduction of the expected frequency of debris flow events.