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.
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.
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.
Current and future global warming will cause the degradation of mountain permafrost, which may strongly influence the stability of permafrost slopes or rock walls with potentially hazardous consequences. Due to the strong heterogeneity of both the thermal regime and the ground composition of mountain permafrost, its response to atmospheric forcing can however be highly variable for different landforms and within short distances. The spatial distribution of ice and liquid water is important for determining the sensitivity of a specific permafrost occurrence to climate change because of their large influence on the pace of temperature changes (by effects of latent heat) and their importance for geotechnical properties of the ground. Detailed knowledge of the material properties and internal structures of frozen ground is therefore an important prerequisite to determine the sensitivity of permafrost to climate change. Except for the active layer ice and water contents and their temporal and spatial variability usually cannot be measured directly. Geophysical methods are sensitive for the ice and liquid water content in the ground. With the proposed collaboration, two similar but complementary approaches to quantify the composition of the ground based on 2D sections of geophysical data will be combined for an improved determination of ice and water contents in permafrost regions. The so-called 4-phase model (4PM) is based on two simple petrophysical relationships for electrical resistivity and seismic velocity and estimates volumetric fractions of ice, water, and air within the pore volume of a rock matrix by jointly using complementary data sets from electric and seismic measurements. Due to inherent ambiguities in the model it is still restricted to specific cases and often allows only a rough estimation of the phase fractions. Major drawbacks of the current 4PM comprise the unsatisfactory discrimination between rock and ice and its under-determinedness, requiring the prescription of the porosity and further parameters. The so-called RSANN model (developed and used by the host institution) uses the technique of simulated annealing (a Monte-Carlo-type stochastic simulation approach) as an optimization tool for the integration of electrical resistivity and P-wave velocity to derive 2D sections of porosity, water saturation and volumetric water content. The simulated annealing technique allows - due to its iterative procedure - more parameters to be predicted instead of being prescribed as in the 4PM. The objective of the proposed collaboration is to combine the advantages of the two algorithms (4PM and RSANN) to overcome the shortcomings of the 4PM in order to improve the reliability of the determined ice and liquid water contents. (...)
The research is carried out in cooperation with KU Leuven, Forschungszentrum Jülich and Kasetsart University in Bangkok, Thailand, and aims at improving our understanding of how spatial variability in soil properties and vegetation characteristics control water flow and transport processes in the soil at the field scale, and how it determines resource use efficiency of agro-ecosystems. It focuses on the spatio-temporal dynamics of water contents and competition for water uptake in mixed cropping systems. The emphasis is on spatial variation that is caused by the cropping pattern and landscape. To this end, a set of monitoring techniques will be used with which spatial patterns of crop status and subsurface soil water contents can be imaged in a non-invasive manner. Soil water content distributions will be determined using geophysical methods: electrical resistivity tomography and time domain reflectometry. The state of the crop and its spatial pattern will be monitored using leaf area index (LAI) sensors and an infrared camera. These techniques will be complemented with 13C stable isotope analysis of plants, which is a measure of the integrated stress of the plant over the growing season. In order to interpret the obtained datasets, a soil-crop model will be developed which considers light interception, photosynthesis and stomatal control, water flow within the plant, root growth and root water uptake, and heat fluxes within the canopy in more detail than in currently available crop growth models.
The major aim of CARCINOGENOMICS is to develop in vitro methods for assessing the carcinogenic potential of compounds, as an alternative to current rodent bioassays for genotoxicity and carcinogenicity. The major goal is to develop a battery of mechanism-based in vitro tests accounting for various modes of carcinogenic action. These tests will be designed to cover major target organs for carcinogenic action e.g. the liver, the lung, and the kidney. The novel assays will be based on the application of 'omics' technologies (i.e. genome-wide transcriptomics as well as metabonomics) to robust in vitro systems (rat/human), thereby also exploring stem cell technology, to generate 'omic' responses from a well-defined set of model compounds causing genotoxicity and carcinogenicity. Phenotypic markers for genotoxic and carcinogenic events will be assessed for the purpose of anchoring gene expression modulations, metabolic profiles and mechanism pathways. Through extensive biostatistics, literature mining, and analysis of molecular-expression datasets, differential genetic pathways will be identified capable of predicting mechanisms of chemical carcinogenesis in vivo. Furthermore, generated transcriptomic and metabonomic data will be integrated into a holistic understanding of systems biology, and applied to build an iterative in silico model of chemical carcinogenesis. Subsequently, predictive gene expression profiles, typically consisting of some 150-250 genes, will be loaded onto high throughput dedicated DNA-chips, thus accelerating the analysis of transcriptomic responses by a factor of 100. It is expected that the outcome of this project will generate a platform enabling the investigation of large numbers of compounds for their genotoxic and carcinogenic potential, as envisaged under the REACH initiative. This will contribute to speeding the identification of potential harmful substances to man, while lowering costs and reducing animal tests. Prime Contractor: Maastricht, University, Health Risk Analysis and Toxicology (Grat); Maastricht, Nederland.
The verification of precipitation forecasts from numerical models is essential for the future improvement of quantitative precipitation forecasts (QPF). There are various options when defining a QPF verification strategy, concerning for instance the temporal resolution, the choice of the evaluation data set, the verification domains, the weather-type stratification and the applied error measures. In this project new techniques will be developed to verify QPFs from the weather prediction models LM, GME and ECMWF over Germany on very short time scales (typically 1 hour). A currently developed technique is used to derive an evaluation data set of hourly precipitation analyses from rain-gouge measurements and radar composites. The verifications will be done for the catchment areas of the major river systems and the QPFs will be categorized into different synoptic weather patterns. Finally, new error measures will be implemented that consider the spatial patterns of precipitation, in contrast to more traditional measures that evaluate the similarity of two fields on a point-by-point basis. Such an pattern-oriented approach provides novel and meaningful information about the qualities and deficiencies of a particular QPF. The results will be directly useful for the interpretation of model output in operational weather forecasting and for their quantitative use in impact applications such as runoff forecasting.
Soil moisture - the water stored in soil within reach of the plants - is a crucial parameter for a large number of applications. Consequently, the field of microwave remote sensing of soil moisture has been an important research topic since the 1970s. But only in the last few years significant progress towards operational soil moisture services has been made. This progress became possible due to advances in sensor technology and new algorithmic approaches. With the improved algorithms it has been possible to derive soil moisture from existing operational microwave sensors. The first global soil moisture dataset derived from ERS-1/2 scatterometer measurements was released in 2002. The first near-real-time operational soil moisture service was started by EUMETSAT in May 2008 based on METOP ASCAT, which is the successor instrument of the ERS-1/2 scatterometer. Austria has made important contributions to these developments. The algorithms for retrieving soil moisture from the C-band scatterometers on board of ERS-1/2 and METOP have been developed by the Vienna University of Technology (TU Wien). Within EUMETSAT's Satellite Application Facility in Support to Operational Hydrology and Water Management (Hydrology SAF) the Austrian meteorological service (ZAMG) coordinates the soil moisture activities and is responsible for building up operational services for value-added METOP ASCAT soil moisture products. The overall goal of the proposed project is to advance the use of soil moisture services based on METOP ASCAT and complementary satellite systems, most importantly SMOS and ENVISAT ASAR, by extending the Hydrology SAF products to Africa and Australia, carrying out extensive calibration and validation (Cal/Val) activities and by developing novel water hazards applications. The considered applications are weather forecasting, drought and yield monitoring, hydrologic prediction, epidemiological modelling, climate change, desertification monitoring and societal risks assessment. A project of comparable thematic focus and breath has not been proposed before. It is expected that the interdisciplinary cooperation of specialists from different fields will lead to important scientific innovations that will promote a wide use of satellite technology in water hazards applications.
Farm households, whose living standard largely depend on the successful management of natural resources, have a low per capita income and are in danger of further impoverishment due to unsustainable resource management. Investigations in the first phase confirmed the hypothesis. A great number of farms were analyzed and clustered in representative types in both countries. Sustainability was measured using a sustainability index, which indicates tremendous environmental effects and variation between individual farms and ethnic groups.Sub-project G1.1 will follow three major tasks. The first is to evaluate sustainability strategies on the farm and farming system level, as it was done in the previous phase, but on the basis of a significantly extended data base. The second is to aggregate farm household data to the regional level. For this, a comparative-static approach is chosen. The third is to develop a multi-agent-based simulation model. Multi-agent simulation models (MAS) as well as GIS-tools are gaining increasing importance as tools for simulating future agriculture resource use, since they allow the integration of a wide range of different stakeholder's perceptions. It becomes possible to simulate the dynamic effects of changing land use patterns, environmental policy options, and technical innovation together with environmental constraints and structural change issues. The MAS approach is used to model heterogeneous farm-household and political decision makers perspectives by capturing their socio-economic, environmental, and spatial interactions explicitly. The integration of economic and spatial processes facilitates the consideration of feedback effects and the efficient use of scarce land resources. The simulation runs of the model will be carried out with a socio-economic and GIS data set, which is provided by the previous project phase in the attempt to generate effective ways of land use resource management. Land use efficiency is strongly influenced by the overall land allocation policy analyzed in project F1. Therefore, this is an important area further integrated research using MAS in combination with GIS as modeling tools.To achieve a continuous integration of results in the best possible way, a computer-based discussion/communication platform is developed. This serves as the conceptual basis for the development of the final multi-agent simulation model. Results of the discussion/communication platform and the agent-based simulation model will continuously be passed on to downstream sub-projects to be integrated into the ongoing research activities.
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