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International audience; Context. Top-down chemistry is believed to be responsible for the formation of the large molecular compounds such as the polycyclic aromatic hydrocarbon-like molecules and the fullerenes observed in the interstellar medium. The release of these large molecules from the parent grains remains an important issue to be investigated. Aims. Cosmic rays irradiate the dust grains during their journey in the interstellar medium. In this study we probe to what extent electronic sputtering and/or desorption processes induced by high-energy ion projectiles contribute to the creation of the large molecular component in space. Methods. Carbonaceous dust analogues were produced in an ethylene flame. The resulting soot nanoparticles generated under well-defined conditions were irradiated by swift heavy ions, and mass spectra of the ionic and neutral molecular fragments emitted shortly after the impact were monitored. Results. Large molecular fragments were detected, including neutral and ionic polycyclic aromatic hydrocarbons containing up to several tens of carbon atoms, as well as ionic fullerenes. Although the absolute efficiencies were not obtained, these experiments provide a proof of principle of a top-down scenario involving interaction processes of interstellar dust with high-energy projectiles yielding large molecular compounds observed in space.

Conversion of natural forest (NF) to other land uses could lead to significant changes in catchment hydrology, but the nature of these changes has been insufficiently investigated in tropical montane catchments, especially in Africa. To address this knowledge gap, we aimed to identify stream water (RV) sources and flow paths in three tropical montane sub-catchments (27–36 km2) with different land use (natural forest, NF; smallholder agriculture, SHA; and commercial tea and tree plantations, TTP) within a 1021 km2 catchment in the Mau Forest complex, Kenya. Weekly samples were collected from stream water, precipitation (PC) and mobile soil water for 75 weeks and analysed for stable isotopes of water (δ2H and δ18O) for mean transit time (MTT) estimation with two lumped parameter models (gamma model, GM; and exponential piston flow model, EPM) and for the calculation of the young water fraction. Weekly samples from stream water and potential endmembers were collected over a period of 55 weeks and analysed for Li, Na, Mg, K, Rb, Sr and Ba for endmember mixing analysis (EMMA). Solute concentrations in precipitation were lower than in stream water in all catchments (p −3.0–24.2) and 50.2 (30.5–65.5) % during low flow to 20.7 (15.2–34.7), 53.0 (23.0–91.3) and 69.4 (43.0–123.9) % during high flow in the natural forest, smallholder agriculture and tea plantation sub-catchments, respectively. Our results indicate that groundwater is an important component of stream water, irrespective of land use. The results further suggest that the selected transit time models and tracers might not be appropriate in tropical catchments with highly damped stream water isotope signatures. A more in-depth investigation of the discharge dependence of the young water fraction and transit time estimation using other tracers, such as tritium, could therefore shed more light on potential land use effects on the hydrological behaviour of tropical montane catchments.

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which are resulting in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (ANalyses Of VAriance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of 5 climate models and up to 13 hydrological models, for 9 large scale river basins across the globe, under 4 emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge – however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

The agricultural water footprint addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). By considering site-specific properties when calculating the crop water footprint, this methodology can be used to support decision making in the agricultural sector on local to regional scale. We therefore developed the spatial decision support system SPARE:WATER that allows us to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirements and water footprints are assessed on a grid basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume inefficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water is defined as the water needed to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept, we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr−1 for 2008, with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional estimation of crop water footprints.

Background: Heart failure (HF) is highly prevalent among patients with acute ischemic stroke. Stroke etiology is referred to cardioembolism with presumed atrial or ventricular origin in most cases. However, heart failure can be transient and concurrent causes of stroke might remain undetected. Methods: Clinical cohort study among patients with ischemic stroke and acute recanalising therapies between 2006 and 2016 at a universitary stroke center.Results: 1209 patients with acute ischemic stroke undergoing intravenous thrombolysis and/or mechanical recanalization were included. HF was present in 378 patients (31%) and showed to be an independent predictor of unfavorable outcome. 32% had the diagnosis of HF established prior to hospital admission for stroke. The medical treatment regimen for HF was consistent with the recommendations of international guidelines in only 53%. 207/378 patients (55%) used anti-platelet therapy and 50 patients (13%) used oral anticoagulation. In 61% ischemic stroke was considered to be of cardioembolic origin (atrial fibrillation: 56%). In 10% another determined etiology of stroke was present: 8% macroangiopathy with high-grade arterial stenosis, 1% microangiopathy and 1% other etiologies. The etiology remained undetermined in 29%. In patients without HF, the rate of unknown causes (45%) was higher and cardioembolic origin less common (35%, p

This paper addresses education and communication in hydrology and geosciences. Many approaches can be used, such as the well-known seminars, modelling exercises and practical field work but out-door learning in our discipline is a must, and this paper focuses on the recent development of a new out-door learning tool at the landscape scale. To facilitate improved teaching and hands-on experience, we designed the Studienlandschaft Schwingbachtal. Equipped with field instrumentation, education trails, and geocache, we now implemented an augmented reality App, adding virtual teaching objects on the real landscape. The App development is detailed, to serve as methodology for people wishing to implement such a tool. The resulting application, namely the Schwingbachtal App, is described as an example. We conclude that such an App is useful for communication and education purposes, making learning pleasant, and offering personalized options.

GSI Scientific Report 2014 - GSI Report 2015-1

Weekly samples from surface waters, springs, soil water and rainfall were collected in a 76.9 km2 mountain rain forest catchment and its tributaries in southern Ecuador. Time series of the stable water isotopes δ18O and δ2H were used to calculate mean transit times (MTTs) and the transit time distribution functions (TTDs) solving the convolution method for seven lumped-parameter models. For each model setup, the generalized likelihood uncertainty estimation (GLUE) methodology was applied to find the best predictions, behavioral solutions and parameter identifiability. For the study basin, TTDs based on model types such as the linear–piston flow for soil waters and the exponential–piston flow for surface waters and springs performed better than more versatile equations such as the gamma and the two parallel linear reservoirs. Notwithstanding both approaches yielded a better goodness of fit for most sites, but with considerable larger uncertainty shown by GLUE. Among the tested models, corresponding results were obtained for soil waters with short MTTs (ranging from 2 to 9 weeks). For waters with longer MTTs differences were found, suggesting that for those cases the MTT should be based at least on an intercomparison of several models. Under dominant baseflow conditions long MTTs for stream water ≥ 2 yr were detected, a phenomenon also observed for shallow springs. Short MTTs for water in the top soil layer indicate a rapid exchange of surface waters with deeper soil horizons. Differences in travel times between soils suggest that there is evidence of a land use effect on flow generation.

With the global warming it is essential to study water resources in the arid regions like the Ferghana Valley (~79,000 km² with surround highland) in Central Asia, where agricultural production heavily depends on irrigation. Main water resources for irrigation are currently provided by the Naryn and Karadarya river systems. The surrounding mountainous areas of the valley with their large glacial water storages play a big role in the annual water balance of these rivers. The decrease of glaciers due to the global temperature rise will most likely lead to the runoff reduction. An impact analysis of the climate change on the water resources is of utmost importance both for economic as well as ecological issues in the region. The overall objective of the study is to estimate the relative contribution of small-sized catchments with mainly precipitation driven runoff (in total 19 catchments) and the large Naryn and Karadarya rivers which are dominated by glacial melt water to the Ferghana Valley water balance under current and future climatic conditions. Any future model-based prediction of the water resources availability is depended on a thorough understanding of the hydrological cycle under current conditions. Therefore, the aim is at investigating the water balance of the small surrounding catchments using the conceptual HBV-light model. In this study it is shown the model setup for the Kugart River (1,010 km²), Kurshab River (2,010 km2), Akbura River (2,260 km²) and Shakhimardan River (1,180 km²) catchments in Kyrgyzstan. Model setup is highlighted especially in the view of data availability limitations. Thus, the MODAWEC model that calculates daily meteorological data from monthly is applied for the four studied catchments (the correlation coefficient for generated and measured average temperature varies from 0.84 to 0.91). The HBVlight model is employed successfully for measured allocated climate data and generated (temperature) allocated data to the central part of the basins with the Nash-Sutcliffe efficiency coefficient (NSE) both for calibration (1980-1983) and validation (1984-1985) periods in the range of 0.50 to 0.89 for the studied basins. The acceptable parameter sets for the model after using of threshold (NSE ≥ 0.50, NSE log ≥ 0.50, and the difference in annual water balance ± 20 mm) ranges from 21 to 558. Thus, the hydrological modelling using generated meteorological data and the HBV-light model will be applied for the remaining 15 small catchments that discharge into the Fergana Valley. And for the assessment of climate change impact on the water resources in the Ferghana Valley it is planned to apply the different climate change scenarios in the near future.

The surrounding landscape of a stream has crucial impacts on the aquatic environment. This study pictures the hydro-biogeochemical situation of the Tyrebækken creek catchment in central Jutland, Denmark. The intensively managed agricultural landscape is dominated by rotational croplands. The small catchment mainly consist of sandy soil types besides organic soils along the streams. The aim of the study was to characterise the relative influence of soil type and land use on stream water quality. Nine snapshot sampling campaigns were undertaken during the growing season of 2009. Total dissolved nitrogen (TDN), nitrate (NO3−), ammonium nitrogen and dissolved organic carbon (DOC) concentrations were measured, and dissolved organic nitrogen (DON) was calculated for each grabbed sample. Electrical conductivity, pH and flow velocity were measured during sampling. Statistical analyses showed significant differences between the northern, southern and converged stream parts, especially for NO3− concentrations with average values between 1.4 mg N l−1 and 9.6 mg N l−1. Furthermore, throughout the sampling period DON concentrations increased to 2.8 mg N l−1 in the northern stream contributing up to 81% to TDN. Multiple-linear regression analyses performed between chemical data and landscape characteristics showed a significant negative influence of organic soils on instream N concentrations and corresponding losses in spite of their overall minor share of the agricultural land (12.9%). On the other hand, organic soil frequency was positively correlated to the corresponding DOC concentrations. Croplands also had a significant influence but with weaker correlations. For our case study we conclude that the fractions of coarse textured and organic soils have a major influence on N and DOC export in this intensively used landscape. Meanwhile, the contribution of DON to the total N losses was substantial.

Hydro-biogeochemical models are used to foresee the impact of mitigation measures on water quality. Usually, scenario-based studies rely on single model applications. This is done in spite of the widely acknowledged advantage of ensemble approaches to cope with structural model uncertainty issues. As an attempt to demonstrate the reliability of such multi-model efforts in the hydro-biogeochemical context, this methodological contribution proposes an adaptation of the Reliability Ensemble Averaging (REA) philosophy to nitrogen losses predictions. A total of 4 models are used to predict the total nitrogen (TN) losses from the well-monitored Ellen Brook catchment in Western Australia. Simulations include re-predictions of current conditions and a set of straightforward management changes targeting fertilization scenarios. Results show that, in spite of good calibration metrics, one of the models provides a very different response to management changes. This behaviour leads the simple average of the ensemble members to also predict reductions in TN export that are not in agreement with the other models. However, considering the convergence of model predictions in the more sophisticated REA approach assigns more weight to previously less well calibrated models that are more in agreement with each other. This method also avoids having to disqualify any of the ensemble members, which is always sensible.