The Environmental Fate of Cadmium in the Soils of the Waste Water Irrigation Area of Braunschweig - Measurement, Modelling and Assessment -

The study aimed at investigating the environmental fate of Cd in the soils of the waste water irrigation area of Braunschweig. The sandy acidic soils (28 km2) within this region have undergone high loads of heavy metals by irrigation of municipal waste water for up to 40 years. 161 soil monoliths (0-1.2 m) were sampled to study the current status of Cd accumulation as well as the horizontal and vertical variability of sorption characteristics. Moreover, Cd uptake was investigated at 40 potato, 40 sugar beet and 20 winter wheat fields. The model SEFAH was used to predict both the displacement of Cd and its uptake by plants. Spatial variability of soil properties was taken into account by using a parallel soil column approach. Simulations were performed either by deterministic 1D- simulations or by the Monte-Carlo method. Solute leaching in each column was modelled with the convection-dispersion equation. The sorption of Cd was described with an extended Freundlich equation. Deep ploughing was computed by the use of soil exchange rates. The uptake of Cd by plants was modelled using a transpiration- based approach. The results of hindcast simulations agreed well with both the averaged profiles of measured Cd concentrations in soil and observed Cd contents in plants. After validation the model was used to calculate several retrospective and prospective scenarios. Error analysis of block kriging estimates using conditional simulations showed that based on the current sampling density the predictive power of estimates is strongly restricted. Finally, two simple tools to assess the effect of soil Cd on ground water and food quality are presented, the determination of tolerable total Cd contents (TTC) and the calculation of breakthrough times (BTT).Ziel der vorliegenden Arbeit war die Untersuchung des Umweltverhaltens von Cadmium (Cd) in den Böden des Abwasserverregnungsgebietes Braunschweig (43 km2). In die sorptionsschwachen Böden des Gebiets sind über die Verregnung kommunaler Abwässer in den letzten 40 Jahren Schwermetalle eingetragen worden. Um sowohl den aktuellen Zustand der Cd-Verlagerung im Boden als auch die horizontale und vertikale Variabilität der Sorptionseigenschaften zu untersuchen wurden 161 Bodenmonolithe (0-1.2 m) beprobt. Darüber hinaus wurde die pflanzliche Cd-Aufnahme an 40 Kartoffel-, 40 Zuckerrüben- und 20 Winterweizenstandorten untersucht. Für die Simulation der Verlagerung und der Pflanzenaufnahme wurde das Modell SEFAH eingesetzt. In dem Modell wird der Stofftransport in jeder Säule über die Konvektion-Dispersions-Gleichung und einer erweiterten Freundlich-Isotherme beschrieben. Tiefpflugmaßnahmen wurden über Bodenaustauschraten berücksichtigt. Die Pflanzenaufnahme wurde über einen massenflußbasierten Ansatz berechnet. Die räumliche Variabilität der Bodeneigenschaften wurde über verschiedene „parallel soil column approaches“ in die Modellrechnungen eingebunden. Die Ergebnisse der „Hindcast“ Simulationen stimmten sowohl mit den beobachteten mittleren Verlagerungsprofilen als auch mit den gemessenen Pflanzengehalten gut überein. Nach der Validierung wurde das Modell für verschiedene Prognosesimulationen eingesetzt. Darüber hinaus wurde über konditionierte Simulationen die Unsicherheit von Block-Kriging Schätzern untersucht. Abschließend werden zwei einfache Verfahren zur Bewertung von Cd-Einträgen in Böden vorgestellt: Die Berechnung von tolerierbaren Gesamtgehalten und Durchbruchszeiten

Anpassung der Barometrischen Prozess-Separation (BaPS) für die Anwendung in kalkhaltigen Böden

Es wird ein neues Konzept zur Anpassung der Barometrischen Prozess-Separation (BaPS) an alkalische Bodenbedingungen vorgestellt und es werden erste vorläufige Ergebnisse präsentiert. Das methodische Problem der BaPS in kalkhaltigen Böden besteht im zunehmenden Einfluss der CO2-Lösung in der Bodenlösung (Kalk-Kohlensäure-Gleichgewicht) auf die Gasbilanzrechnungen. Dies wirkt sich auf die Bestimmung der C- und N- Umsatzraten aus. Anstelle den ?CO2aq-Term mit dem Massenwirkungsgesetz für CO2 anzu-nähern, soll er nun mit der Fumigations-CO2-Injektions Methode experimentell bestimmt und charakterisiert werden

Independent external validation of a stroke recurrence score in patients with embolic stroke of undetermined source

Abstract Background Embolic stroke of undetermined source (ESUS) accounts for a substantial proportion of ischaemic strokes. A stroke recurrence score has been shown to predict the risk of recurrent stroke in patients with ESUS based on a combination of clinical and imaging features. This study aimed to externally validate the performance of the ESUS recurrence score using data from a randomized controlled trial. Methods The validation dataset consisted of eligible stroke patients with available magnetic resonance imaging (MRI) data enrolled in the PreDAFIS sub-study of the MonDAFIS study. The score was calculated using three variables: age (1 point per decade after 35 years), presence of white matter hyperintensities (2 points), and multiterritorial ischaemic stroke (3 points). Patients were assigned to risk groups as described in the original publication. The model was evaluated using standard discrimination and calibration methods. Results Of the 1054 patients, 241 (22.9%) were classified as ESUS. Owing to insufficient MRI quality, three patients were excluded, leaving 238 patients (median age 65.5 years [IQR 20.75], 39% female) for analysis. Of these, 30 (13%) patients experienced recurrent ischaemic stroke or transient ischemic attack (TIA) during a follow-up period of 383 patient-years, corresponding to an incidence rate of 7.8 per 100 patient-years (95% CI 5.3–11.2). Patients with an ESUS recurrence score value of ≥ 7 had a 2.46 (hazard ratio (HR), 95% CI 1.02–5.93) times higher risk of stroke recurrence than patients with a score of 0–4. The cumulative probability of stroke recurrence in the low-(0–4), intermediate-(5–6), and high-risk group (≥ 7) was 9%, 13%, and 23%, respectively (log-rank test, χ2 = 4.2, p = 0.1). Conclusions This external validation of a published scoring system supports a threshold of ≥ 7 for identifying ESUS patients at high-risk of stroke recurrence. However, further adjustments may be required to improve the model’s performance in independent cohorts. The use of risk scores may be helpful in guiding extended diagnostics and further trials on secondary prevention in patients with ESUS. Trial registration: Clinical Trials, NCT02204267. Registered 30 July 2014, https://clinicaltrials.gov/ct2/show/NCT02204267

Infiltration from the pedon to global grid scales: an overview and outlook for land surface modelling

Infiltration in soils is a key process that partitions precipitation at the land surface in surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in Land Surface Models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hill slope, and grid cell scale of LSMs. Despite the progress that has been made, upscaling of local scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows, that there is a large variety in approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few land surface models consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. In order to tackle the above challenges and integrate current knowledge on soil processes affecting infiltration processes on land surface models, we advocate a stronger exchange and scientific interaction between the soil and the land surface modelling communities

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects

Altered energy partitioning across terrestrial ecosystems in the European drought year 2018

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO(2)exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO(2)uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'

Noah-MP simulated surface energy fluxes and temperature for a generic crop, early covering crops (ECC) and late covering crops (LCC) for Kraichgau region, southwest Germany

The site under study is the agricultural field belonging to the farm "Katharinentalerhof". The field is located north of the city of Pforzheim (48.920N, 8.700E). The central research site is a part of the Kraichgau region, southwest Germany. Simulations were performed for a generic crop, early covering crops (ECC) and late covering crops (LCC). We also considered different ECC-LCC ratios. Additionally, we tested the performance of the Noah-MP on latent heat flux (LE) data measured with the Eddy Covariance (EC) technique. For the simulation with Noah-MP, we used measured GVF and LAI data. The USGS land use dataset was used. The vegetation type index was set to 2 (Dryland cropland and Pasture) and soil type index to 4 (Silt loam). The model was forced with half-hourly weather data (wind speed, wind direction, temperature, humidity, pressure, precipitation, downwelling longwave and shortwave radiation) measured from 2011 to 2012. Simulations were initialized with a spin up period of one year (2011) and run with a time step of 1800 seconds

Land Cover Impacts on Land-Atmosphere Coupling Strength in Climate Simulations With WRF Over Europe

Land use and land cover changes are important human forcings to the Earth's climate. This study examines the land-atmosphere coupling strength and the relationship between surface fluxes and clouds and precipitation for three land cover scenarios in the European summer. The WRF model was used to simulate one scenario with extreme afforestation, one with extreme deforestation, and one with realistic land cover for the time period between 1986 and 2015. The simulations were forced with ERA-Interim reanalysis data. The analysis followed a two-step approach. First, the convective triggering potential–low-level humidity index framework was applied to locate potential coupling hot spots, which were then analyzed with regard to their sensitivity toward land use and land cover changes. Second, actual feedbacks between evaporative fraction, cloud cover, and precipitation were analyzed statistically with focus on sign and location of the feedbacks. The results demonstrate that coupling hot spots, exhibiting predominantly positive feedbacks, were identified over parts of Eastern Europe and Scandinavia. In this strongly coupled region, afforestation and deforestation modified the atmospheric humidity and stability by changing the surface flux partitioning. Afforestation is associated with a net drying of the atmosphere due to a disproportionately strong increase in the sensible heat flux. In contrast, deforestation initiated a moistening of the atmosphere. The total precipitation changed only in limited areas significantly, which are mostly located in mountainous regions and the northeast of the domain. In summary, the results indicate a land surface influence on the atmospheric background conditions, and an impact on the potential strength of land surface-precipitation feedbacks

Interannual variability of methane storage and emission during autumn overturn in a small lake

Methane emissions from freshwater systems, and especially from small lakes source a significant proportion of naturally produced atmospheric methane. In small temperate lakes, storage flux, i.e. the diffusive emission of methane that was stored in anoxic waters during the seasonal overturn of the water column, can contribute a large fraction of annual methane emissions. Here we use an extensive field dataset to quantify methane storage in anoxic deep water and identify as well as quantify the sources and losses of this methane. The comparison of measurements from four years in a small temperate lake (Illmensee) shows that methane storage can differ substantially between years. In 2012 and 2018, the annual maximum of the methane stored in the entire water column was around twice as high (5350 kg and 5822 kg) as in 2013 and 2017 (2722 kg and 2295 kg). A methane mass balance approach suggests that the variability of methane storage in the anoxic water between the years was not caused by the methane flux at the anoxic-oxic water interface, but rather was related to changes in the methane source from the anoxic sediments. The interannual differences in sediment flux could not be explained by sediment temperature, but rather by the differing supply of organic matter. Our findings suggest that phytoplankton blooms promote methane storage within the same year and thus cause interannual variability in emissions during autumn overturn.publishe