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.
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.
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.
Objective: Integrated assessment and energy-economy models have become central tools for informing long-term global and regional climate mitigation strategies. There is a large demand for improved representations of complex system interactions and thorough validation of model behaviour in order to increase user confidence in climate policy assessments. ADVANCE aims to respond to this demand by facilitating the development of a new generation of integrated assessment models. This will be achieved by substantial progress in key areas where model improvements are greatly needed: end use and energy service demand; representation of heterogeneity, behaviour, innovation and consumer choices; technical change and uncertainty; system integration, path dependencies and resource constraints; and economic impacts of mitigation policies. In the past, methodological innovations and improvements were hindered by the unavailability of suitable input data. The ADVANCE project will make a large and coordinated effort to generate relevant datasets. These datasets, along with newly developed methodologies, will be made available to the broader scientific community as open-access resources. ADVANCE will also put a focus on improved model transparency, model validation, and data handling. A central objective of ADVANCE is to evaluate and to improve the suitability of models for climate policy impact assessments. The improved models will be applied to an assessment of long-term EU climate policy in a global context, and disseminated to the wider community. The ADVANCE consortium brings together long-standing expertise in integrated assessment and energy-economy modelling with a strong expertise in material flows, energy system integration, and energy service demand.
Understanding the drivers behind the loss of biodiversity currently observed is of major importance in the context of the global change discussion. For studies of biodiversity at broad spatial scales, satellite remote sensing is the premier source of information, as it is uniquely capable of covering large areas of the Earth at high temporal resolution. The underlying assumption is that satellite-derived geophysical surface parameters, such as vegetation greenness, are related to biodiversity. For that purpose, concepts such as the Dynamic Habitat Index (DHI) were recently developed. The DHI combines information on the overall greenness, the base level of vegetation cover, and vegetation seasonality at a certain location. By comparing the annual DHI with a long term mean, areas undergoing disturbances or recovery events can be delineated, which are indicative of changes in species composition and diversity. The concept of the DHI was developed for data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) post-2000. However, for climate change impact studies a longer time series is desirable. The only sensor system suitable for such applications is the Advanced Very High Resolution Radiometer (AVHRR), which has been in orbit on various platforms since the early 1980ies. The purpose of this project was to develop a methodology to derive long term information on habitat conditions at continental scales based on historical satellite data. In particular, the goal was to adopt the principle of the DHI as developed for the MODIS sensor to an AVHRR archive at 1 km spatial resolution over Canada and to analyze long term variations in the DHI. In a first project phase, an AVHRR data set of vegetation greenness, generated in the framework of the project, was validated against the reference MODIS product. The results demonstrated a very good agreement between both data sets for a wide range of vegetation types and on various spatial and temporal scales. A historical baseline of habitat conditions post-1987 based on the DHI was subsequently generated based on the long term AVHRR data. The analysis of the DHI showed that certain areas, particularly northern parts of the Province of Quebec as well as southwestern Canada, experienced significant changes over the past two decades, which may have had significant impacts on species diversity and abundance in these areas. In the future, the methods developed in the framework of this project may be used to obtain information on long term variations in habitat conditions in areas covered by other historical satellite archives, e.g., for Europe based on an AVHRR archive hosted at the University of Bern.
EAGER is a core group of international scientists trying to improve and harmonize national ammonia emission inventory calculations. Through the exchange they strive to continuously improve their respective N flux models. Six N-flow models used to calculate NH3 emissions from agriculture for inventories and policy implementation in UK, DK, NL, DE, CH were compared using standard activity data sets. For liquid manure the results were well comparable. For solid manure larger differences indicated greater uncertainties. In a third WP a survey on punlished and unpulished experimental data on emissions from solid manure was therfore conducted. Project goal: EAGER aims at achieving a detailed overview of the present best available inventory techniques, compiling and harmonizing the available knowledge on emission factors (EF) and initiating a new generation of NH3 emission inventories. Results: EAGER is a core group of international scientists trying to improve and harmonize national ammonia emission inventory calculations. Through the exchange they strive to continuously improve their respective N flux models
The accuracy of hydrology and weather predictions depends to a large extent on our understanding of small-scale flow phenomena at the land-atmosphere interface. The overall goal of this grant concerns improved understanding of the effects of complex alpine terrain on included field studies of air flow over steep slopes during morning and evening transition periods and thermal circulations that develop driven by differential heating on the earths surface from variations in solar heating and surface thermal properties. We have also developed improved turbulence simulations of the lower atmosphere using the immersed boundary method (IBM) and have tested our results against measurement studies in the open literature (laboratory and field). This grant has supported two PhD students (Daniel Nadeau & Marc Diebold). Nadeau was responsible for field studies and analysis of flows over steep slopes and successfully defended his PhD at the end of 2011 and is now Assistant Professor at Polytechnique in Montreal. Diebold is primarily focused on numerical simulation based upon the Large Eddy Simulation (LES) technique and is completing field campaigns (2011-2013) in the Val Ferret watershed on turbulent flow over snow covered terrain. His numerical work has focused on the implementation of new ideas in IBM and subgrid-scale (sgs) modeling. Simulation of local atmospheric flows around complex topography is of great importance for several applications in wind energy (e.g. short term wind forecasting and turbine siting and control), local weather predictions in mountainous regions and avalanche risk assessment. However atmospheric simulations around steep mountain topography remain difficult as the typical strategy used to introduce topographic elements, terrain following coordinates, becomes numerically unstable if the topography is too steep. The IBM provides a unique approach that is particularly well suited for efficient and numerically stable simulation of flows around steep terrain. To date the IBM has been used in conjunction with the EPFL-LES and tested against two unique data sets. In the first comparison, the LES was used to reproduce the experimental results from a wind tunnel study of a smooth three-dimensional hill. In the second study, we simulated the wind field around the Bolund Island, Denmark, and made direct comparisons with field measurements (this has been published recently in Boundary Layer Meteorology journal in 2013).
Satellite measurements strongly contribute to the understanding of the processes related to stratospheric ozone loss, e.g. by global and long term monitoring of ozone and its depleting substances. For instance, measurements performed in limb geometry by SCIAMACHY on ENVISAT largely improved the knowledge about the vertical distribution of species like BrO and OClO only recently. However, there are still important open questions, like e.g. the chlorine activation processes on different kinds of aerosols and polar stratospheric clouds. Also, the role of very short lived species in the stratospheric bromine budget or the effects of a possible enhancement of the Brewer-Dobson circulation are not fully understood.Globally, the vertical distribution of ozone depleting species varies significantly in space and time due to solar illumination, atmospheric chemistry and transport. Especially strong gradients occur near the twilight zone or across stratospheric transport barriers (polar vortex boundary, subtropical transport barriers). These regions are of particular importance for chemistry and transport of the lower stratosphere and upper troposphere, since they separate air masses on large scales but also enable exchange between them.Standard 1-D profile retrievals, which assume horizontal homogeneity, result in large systematic biases due to neglecting the effect of horizontal gradients on the measurement. We propose to develop, improve and apply a tomographic profile retrieval algorithm, which optimally combines the information provided by the SCIAMACHY limb and nadir measurements. An improved global dataset of 3D stratospheric profiles for NO2, BrO and OClO for the 10 years of the SCIAMACHY mission (2002-2012) will be developed, compared to atmospheric chemistry simulations and applied to selected questions of atmospheric science. The dataset developed in this project will be very useful for investigating the complex interplay of stratospheric chemistry and transport processes, and will help to reduce the uncertainties in the distribution of ozone depleting species, in particular for regions with large horizontal inhomogeneity.
The HGF Alliance 'Remote Sensing and Earth System Dynamics' aims at the development and evaluation of novel bio/geo-physical information products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In times of accelerated global change, the understanding and quantification of these processes is of primary importance. Spaceborne remote sensing sensors are predestined to produce bio-geo-information products on a global scale. The upcoming generation of spaceborne remote sensing configurations will be able to provide global data sets and products with unprecedented spatial and temporal resolution in the context of a consistent and systematic observation strategy. The integration of these data sets in existing environmental and climate science components will allow a new global view of the Earth system and its dynamics, initiating a performance leap in ecosystem and climate change modelling.
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).