Institute of Rural Studies
Institute of Rural Studies
Kunkel R.,Jülich Research Center |
Kreins P.,Institute of Rural Studies |
Tetzlaff B.,Jülich Research Center |
Wendland F.,Jülich Research Center
Journal of Environmental Sciences | Year: 2010
We used the interdisciplinary model network REGFLUD to predict the actual mean nitrate concentration in percolation water at the scale of the Weser river basin (Germany) using an area differentiated (100 m × 100 m) approach. REGFLUD combines the agro-economic model RAUMIS for estimating nitrogen surpluses and the hydrological models GROWA/DENUZ for assessing the nitrate leaching from the soil. For areas showing predicted nitrate concentrations in percolation water above the European Union (EU) groundwater quality standard of 50 mg NO3-N/L, effective agri-environmental reduction measures need to be derived and implemented to improve groundwater and surface water quality by 2015. The effects of already implemented agricultural policy are quantified by a baseline scenario projecting the N-surpluses from agricultural sector to 2015. The REGFLUD model is used to estimate the effects of this scenario concerning groundwater and surface water pollution by nitrate. From the results of the model analysis the needs for additional measures can be derived in terms of required additional N-surplus reduction and in terms of regional prioritization of measures. Research work will therefore directly support the implementation of the Water Framework Directive of the European Union in the Weser basin. © 2010 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences.
Offermann F.,Institute of Farm Economics |
Deblitz C.,Institute of Farm Economics |
Golla B.,Institute for Strategies and Technology Assessment |
Gomann H.,Institute of Rural Studies |
And 11 more authors.
Landbauforschung Volkenrode | Year: 2014
This article presents selected results of the Thünen-Baseline as well as the assumptions upon which these results are based. The Thünen-Baseline is established using and combining several models of theThünen model network. It provides a reference scenario for the analysis of the impacts of alternative policies and developments. The projections are based on data and information available as of winter 2013/14. The baseline assumes a continuation of the current policy framework and the implementation of already decided policy changes. For the Thünen-Baseline 2013 to 2023, this implies the implementation of the EU-CAP reform decided in 2013 and its national implementation according to the decisions made at the German Ministers of Agriculture conference. Overall, the Thünen-Baseline 2013 to 2023 draws a picture of a competitive agricultural sector in Germany, which adapts well to the changes of the latest policy reform and seizes the opportunities for expanding production, especially in the dairy sector. On the other hand, the projections also highlight that - under the assumptions made and with unchanged policy conditions - the problems that may accompany intensive livestock production will not simply dissolve. In contrast, in view of the projected high profitability of intensive pig and poultry production the related challenges could increase.
Kostner B.,TU Dresden |
Wenkel K.-O.,Leibniz Center for Agricultural Landscape Research |
Berg M.,Leibniz Center for Agricultural Landscape Research |
Bernhofer C.,TU Dresden |
And 2 more authors.
European Journal of Agronomy | Year: 2014
One of the most decisive natural framework conditions of agriculture - the regional climate - is in transition. This requires considering climate change and climate change impact for decision making. Although this knowledge is uncertain and depends on future green-house gas emission, it is rapidly expanding and improving. Therefore, it is important to create flexible systems with adaptable data bases and analytical tools to integrate knowledge of future climate change in agronomy for impact studies and adaptation planning. The joint project LandCaRe (Land, Climate, and Resources) 2020 aimed at developing a conceptual framework and prototype of a model-based decision support system (DSS) based on improved process knowledge and stakeholder communication. The final product, the LandCaRe DSS should combine grid-based information on regional climate and land surface, robust climate impact models and socio-economic boundary conditions to develop spatially explicit climate impact scenarios. Emphasis was put on the integration of different knowledge from science and practice. Climate projections had to be adapted to the needs of impact modelling of agricultural and ecological processes at regional and farm scale. Impact modelling included new process knowledge, especially related to the CO2 fertilisation effect on crop rotations. A new Free Air Carbon Dioxide Enrichment Experiment (FACE) on the C4 plant maize was conducted during the project. A new agro-ecosystem model was developed which integrates soil-plant-atmosphere exchange and plant production to predict crop yield as well as water, carbon and nitrogen fluxes. Stakeholders included representatives of agricultural and environmental administrations, managers of agro-enterprises and large farms as well as organisations for regional planning and nature conservation. Their central common interests were future land use, water availability and management. Stakeholders from agriculture requested not only to assess potential impacts of regional climate change on yield but also to interpret climate impact on farm economy. This required the design of a farm-economy module linking effects of management and adaptation on crop yield with scenarios of costs and prices. Here an introduction to the project, components of the DSS and its further perspectives are presented. © 2013 Elsevier B.V.