Die Geosuche ist ein Webservice, welcher über die EGovernment-Basiskomponente Geodaten (GeoBAK) bereitgestellt wird. Die Geosuche ermöglicht eine multikriterielle Recherche nach ausgewählten Geobasisdaten und Geofachdaten, Geoinformationen (Metadaten) sowie Portalinhalten (Webseiten, Dokumente). Sie ist zentraler Bestandteil des Geoportals Sachsenatlas und als Freie Suche bzw. Volltextsuche ausgelegt. Die Umsetzung der Suche im Geoportal als singuläres Suchfeld (Omnibox, Einfeldsuche) analog zu bekannten Internetsuchmaschinen, ermöglicht einen schnellen Einstieg der Nutzer. Die Geosuche ermöglicht im Gegensatz zu standardisierten OGC-Geodatendiensten wie z.B. OGC-WFS-Gazetteer eine performanceoptimierte Recherche, welche nicht nur auf Geodaten beschränkt ist. Die Geosuche ermöglicht aufgrund der Filter- und Sortiermöglichkeiten die Umsetzung von über die Einfeldsuche hinausgehenden Recherchemöglichkeiten. Im Geoportal ist dies über die erweiterte Suche mit z.B. räumlicher und zeitlicher Auswahlmöglichkeit umgesetzt. Weiterhin sind einzelne Objekte untereinander verknüpft. Damit ist beispielsweise die Recherche nach allen Hausnummern einer Straße möglich (Drilldown). Die Umsetzung von Formularen mit Auswahllisten für eine Recherche, die die Geosuche aufrufen, ist möglich.
Although global pesticide use increases steadily, our field-data based knowledge regarding exposure of non-target ecosystems is very restricted. Consequently, this meta-analysis will for the first time evaluate the worldwide available peer-reviewed information on agricultural insecticide concentrations in surface water or sediment and test the following two hypotheses: I) Insecticide concentrations in the field largely exceed regulatory threshold levels and II) Additional factors important for threshold level exceedances can be quantified using retrospective meta-analysis. A feasibility study using a restricted dataset (n = 377) suggested the significance of the expected results, i.e. an threshold level exceedance rate of more than 50Prozent of the detected concentrations. Subsequent to a comprehensive database search in the peer-reviewed literature of the past 60 years, analysis of covariance with the relevant threshold level exceedance as the continuous dependent variable (about 10,000 cases) will be performed and the impact of significant predictor variables will be quantified. Parameters not yet considered in pesticide exposure assessment will be included as independent variables, such as compound class, environmental regulatory quality, and sampling design. The simultaneous presence of several insecticide compounds as a well as their metabolites will also be considered in the evaluation. The present approach may provide an innovative and integrated view on the potential environmental side effects of global high-intensity agriculture and in particular of pesticides use.
In hydrology, the relationship between water storage and flow is still fundamental in characterizing and modeling hydrological systems. However, this simplification neglects important aspects of the variability of the hydrological system, such as stable or instable states, tipping points, connectivity, etc. and influences the predictability of hydrological systems, both for extreme events as well as long-term changes. We still lack appropriate data to develop theory linking internal pattern dynamics and integral responses and therefore to identify functionally similar hydrological areas and link this to structural features. We plan to investigate the similarities and differences of the dynamic patterns of state variables and the integral response in replicas of distinct landscape units. A strategic and systematic monitoring network is planned in this project, which contributes the essential dynamic datasets to the research group to characterize EFUs and DFUs and thus significantly improving the usual approach of subdividing the landscape into static entities such as the traditional HRUs. The planned monitoring network is unique and highly innovative in its linkage of surface and subsurface observations and its spatial and temporal resolution and the centerpiece of CAOS.
The formation of biogeochemical interfaces in soils is controlled, among other factors, by the type of particle surfaces present and the assemblage of organic matter and mineral particles. Therefore, the formation and maturation of interfaces is studied with artificial soils which are produced in long-term biogeochemical laboratory incubation experiments (3, 6, 12, 18 months. Clay minerals, iron oxides and charcoal are used as major model components controlling the formation of interfaces because they exhibit high surface area and microporosity. Soil interface characteristics have been analyzed by several groups involved in the priority program for formation of organo-mineral interfaces, sorptive and thermal interface properties, microbial community structure and function. Already after 6 months of incubation, the artificial soils exhibited different properties in relation to their composition. A unique dataset evolves on the development and the dynamics of interfaces in soil in the different projects contributing to this experiment. An integrated analysis based on a conceptual model and multivariate statistics will help to understand overall processes leading to the biogeochemical properties of interfaces in soil, that are the basis for their functions in ecosystems. Therefore, we propose to establish an integrative project for the evaluation of data obtained and for publication of synergistic work, which will bring the results to a higher level of understanding.
The investigation of high-silica rhyolitic rocks collected in the recent ICDP drilling from the Snake River Plain (SRP) volcanic province (western United States) as well as rocks from the adjacent rhyolitic complexes offers a unique opportunity to track the evolution of magma storage conditions in time and space in the 'Yellowstone hotspot' intracontinental volcanic province. The application of various geothermometers which can be used to determine pre-eruptive temperatures show a general trend indicating a general decrease of temperature over the last 16 Ma. However, the depth (or pressure) of the magma chambers is difficult to constrain and remains mainly unknown because the mineral assemblage in the rhyolitic systems is not suitable for geobarometry. As an alternative to mineral compositions, the silica content of rhyolitic melts can be used to constrain pressure, provided that the silicate melts have cotectic compositions (melts coexisting with quartz and feldspar), which is the case for most SRP rhyolites. From studies in synthetic systems, it is well known that the silica content of cotectic melts decreases with increasing pressure and that it may be used as barometer in pressure ranges of ca 1000 - 50 MPa. However, the evolution of silica content with pressure is not calibrated for natural systems containing up to 2 wtProzent Cao and 4 wtProzent FeO. In this study, we plan to determine the role of pressure on the silica content of cotectic melts compositions relevant for SRP compositions. The experimental data are crucial to interpret the natural glass compositions (matrix glass and glass inclusions) analyzed in the ICDP core samples and will be used to extract quantitative information on the depth of magma storage prior to eruption. The dataset obtained from various eruptive events (samples from ICDP drillings and other SRP rhyolites) will be used to check if there is an evolution of the depth of magma storage over the lifetime of the 'Yellowstone hotspot' in the last 16 Ma and if there is a correlation between the pre-eruptive pressure, the volume of erupted material, the temperature (or differentiation level) and the water activity of magmas. This study will be conducted in close cooperation with other U.S. groups who are in charge of the analysis of ICDP rhyolitic samples. It is emphasized that the experimental database obtained in this project can also be applied to other case studies (high silica rhyolites, A-type granites).
The goal of this study was to enable a prognosis on the future rainfall conditions of the Nile Equatorial Lakes regions by delivering time-series of monthly rainfall sums for the time-period from 2021 to 2050 that can be used for all kinds of applications. One example might be the dimensioning of hydraulic structures. In these very long lasting investments, future climatic conditions have to be considered during present planning and construction.The principal sources of information on future climate conditions are General Circulation Models (GCMs). These are physically based atmospheric models that resemble a numerical weather prediction system but on a much coarser scale. This forecast cannot be perfect. Especially, it cannot predict single values, e. g. if January 2050 will be rather wet or dry, but only climatic references, i.e. state, if Januaries in general will become wetter or dryer in the future. Even if the predictions of a GCM were perfect, its output could not be used directly for hydrological purposes, due to its coarse resolution. The monthly precipitation values that are provided by the GCM present the spatially averaged precipitation over a grid cell of several thousand square kilometres. This 'block rainfall' can differ significantly from rainfall measured at the ground. Rain gauges are influenced by local effects like micro climatic conditions or orographic effects of mountain ranges that GCMs are not able to resolve.This study combined the information from different data sources. As global trend information, monthly precipitation values from two GCMs (ECHAM5 and HadCM3) were used. Three CO2-emission scenarios (A1b, A2 and B1) were considered in this data. As local ground reference observed monthly rainfall sums from several rain gauges in East Africa as well as from three reanalysis projects (Climate Research Unit, University of Delaware and GPCC) were used.At each rain gauge or observation point in the reanalysis a technique called 'Quantile-Quantile-Transformation' was applied to establish a relationship between the Cumulative Distribution Function (CDF) of the GCMs and that of the ground references during the calibration period from 1961-1990. The CDFs were fitted by non-parametric Kernel-Smoothing. To account for potential shifts in the annual cycles of GCMs and ground references, the transformations was done separately for each month.Assuming that the relation between Global Model and local response will be constant in the future, the global predictions of the GCM can be downscaled to local scale, leading to future rainfall scenarios that are coherent with observed past rainfall.Combining the data from three CO2-emission scenarios of two GCM with three reanalysis data sets, an ensemble of 18 different rainfall time-series was created for each observation point. The range of this ensemble helps to estimate the possible uncertainties in the prognosis of future monthly precipitation sums from 2021 to 2050.
Globalization raised the importance of food safety and quality concerns. Developed countries implement precautionary food regulation policies to protect their affluent consumers from unsafe food imported from developing and transition countries. However, the alarming number of trade disputes at WTO evidences cases of abuse of such policies. While claims on protectionist nature of food regulations are valid in principle, yet there is little empirical evidence about their economic effects. The questions of 1) quantification of trade impact of food standards and 2) investigation of national food regulation systems are absolutely essential for the new trade agenda. These problems for developing countries are on the focus of trade policy debate, whereas for transition countries are not considered seriously. Such a research for these recently liberalized markets gains a special significance. - The proposed research will employ Gravity Model for quantitative estimation of impact of EU aflatoxin standards on transition countries- exports.- Russian food regulations for cereal value chain, their enforcement and monitoring mechanisms will be investigated through value chain and cost-benefit analysis.- Compliance of Russian norms with EU standards will be estimated applying comparative advantage analysis.The study area is Stavropol region of the Russian Federation. Local experts will contribute to the construction of the research data set and analysis. The results of the research will assist 1) international policy makers in designing new global trade agenda and 2) Russian producers, exporters and decision makers in improving cereal value chain.
An estimate of sediment transport rates in alluvial rivers is important in the context of erosion, sedimentation, flood control, long-term morphological assessment, etc. Extensive research during the last decades has produced a plethora of sediment transport models. Sediment transport is complex and often subject to semi-empirical or empirical treatment. Most of the sediment transport functions are based on simplified assumptions that the rate of sediment transport could be determined by one or two dominant factors, such as water discharge, average flow velocity, energy slope, and shear stress (Yang, 1996). In many practical situations prediction errors of these models are observed to be high.An alternative approach is to use data driven modelling, which is especially attractive for modelling processes about which adequate knowledge of the physics is limited, like in the case of sediment transport. Over the last decade fuzzy rule-based models have been introduced in engineering as a powerful alternative modelling tool. The fuzzy rule-based approach introduced by Zadeh (1965) is being widely utilized in various fields of engineering. It is a qualitative modelling scheme in which the system behaviour is described using a natural language (Sugeno & Yasukawa, 1993). This research focuses on the applicability of a data-driven fuzzy rule-based modelling approach in estimating sediment transport rates. It also aims at the comparison of the results of the fuzzy rule-based model with the results of other commonly utilized sediment transport functions.A number of variables play important roles in determining sediment transport capacity. These variables are: flow depth, particle fall velocity, particle diameter, flow velocity, energy or water surface slope, shear velocity, shear stress, fluid density, sediment density, stream power, unit stream power, and discharge. Additionally; size, shape, and unit weight of bed composition; morphology of bed forms and availability of sediment from source area affect sediment transport capacity. The most significant factors affecting sediment transport capacity will be identified and used for constructing a fuzzy model. The fuzzy model identification is usually carried out in two steps: (1) determining the number of fuzzy rules and their associated membership functions and (2) optimizing the fuzzy model. The fuzzy logic toolbox in MATLAB will be used for performing the fuzzy modelling.A general fuzzy system has the components of fuzzification, fuzzy rule base, fuzzy output engine, and defuzzification. Fuzzification converts each piece of input data to degrees of membership by a look-up in one or more several membership functions. Intuition, fuzzy clustering, neural networks, genetic algorithms, and inductive reasoning can be among many ways to assign membership values or functions to fuzzy variables...
Quality standards to assess the chemical status of water bodies under the Water Framework Directive are often based on a few standardized laboratory tests and fixed assessment factors for extrapolation to the field situation. If larger data sets including tests with non-standard species are available, a statistical extrapolation approach, the Species Sensitivity Distribution approach (SSD) is applied. For assessing the remaining uncertainty on the SSD, the threshold concentration derived can be compared with data from field monitoring or model ecosystem studies. Taking the priority substance Ni as an example we present the use of microcosms to test the protectiveness of the quality standard derived from laboratory toxicity tests. The study was conducted in 14 microcosms including a natural sediment layer and an overlaying water volume of 750 L located in a greenhouse. After a pre-treatment period for establishing a diverse aquatic community of phytoplankton, zooplankton, periphyton and snails, Ni solution was added to reach concentrations of 6, 12, 24, 48 and 96 micro g Ni/L in two microcosms each. Four microcosms served as untreated controls. To achieve the intended constant exposure over the test period of four months, Ni concentrations were frequently determined in the microcosms and appropriate amounts of nickel solution were added mostly on a daily basis. Parameters known to affect Ni toxicity, i.e. water hardness, pH, and dissolved organic carbon, were also measured. Population abundance and community structure were analysed for difference to the dynamics in the controls. In the microcosms with 48 and 96 micro g Ni/L long-term effects on phytoplankton, rotifers, snails and, due to reduced grazing by snails, indirectly on the periphyton biomass were observed. Only minor, and/or temporary deviations from controls, i.e., for single sampling dates, were found for a few algae taxa at lower concentrations. Because these deviations showed no clear dose-response and were not found at the end of the study they were not seen as adverse effects. However, for the snail (Lymnaea stagnalis), effects on the trend of population development could not be excluded at 24 micro g/L. Thus, the overall No Observed Effect Concentration (NOEC) for a chronic exposure to nickel in this microcosm study was considered to be 12 micro g Ni/L. This NOEC confirms the protectiveness of the quality standard derived from the laboratory single species tests.
In contrast to their advances in other areas, weather forecast models have not been successful in improving the Quantitative Precipitation Forecast during the last 16 years. One reason for this stagnation is the lack of comprehensive, high-quality data sets usable for model validation as well as for data assimilation, thus leading to improved initial fields in numerical models. Theoretical analyses have identified the requirements measured data have to meet in order to close the gaps in process understanding. In field campaigns, it has been shown that the newest generation of remote sensing systems has the potential to yield data sets of the required quality. It is therefore time to combine the most powerful remote sensing instruments with proven ground-based and airborne measurement techniques in an Intensive Observations Period (IOP). Its goal is to serve as a backbone for the SPP 1167 by producing the demanded data sets of unachieved accuracy and resolution. This requires a sophisticated scientific preparation and a careful coordination between the efforts of the institutions involved. For the first time, the pre-convective environment, the formation of clouds and the onset and development of precipitation as well as its intensity will be observed in four dimensions simultaneously in a region of sufficient size. This shall be achieved by combining the IOP with international programs and by collaboration between leading scientists in Europe, US and other countries. Thus, the IOP is a unique opportunity to make Germany the setting of an international field campaign featuring the newest generation of measurement systems such as scanning radar and lidar and leading to outstanding advances in atmospheric sciences.
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