Impacts of climate change on agriculture have been predominantly analyzed by using biophysical and crop specific model applications. Vulnerability assessments which identify the vulnerability of regions with their farming systems are urgently required, because agricultural adaptations to climate change are related to regional specifics, and therefore research has to consider the regional level. Therefore sector- and system-specific approaches have to be developed. This paper presents the methodology of a vulnerability assessment for organic farming systems in the Brandenburg Region, which considers regional-specific climatic impact, as well as the regional-specific adaptive capacity. In this region, the cultivation and management of legume-grass swards have a key position, especially the climate change impact on legume symbiotic nitrogen fixation and nitrogen mineralization. Adaptation strategies of crop production systems include reduced soil tillage, which plays an important role also in organic farming systems (reducing soil erosion, improving water infiltration, reducing evaporation and improving soil structure, control of N-dynamics) are developed and tested by means of an action research approach.
The precipitation data of the Regional Climate Model CLM are used for the water management impact models within the dynaklim networking and research project. For this purpose, it is necessary to apply a bias correction to the CLM
precipitation data. First, the bias assessed for varying temporal resolutions and precipitation characteristics is described. Subsequently, a method for the bias correction is introduced. The developed methodology is a modified form of the socalled
quantile mapping. The focus lies on the corrections of the dry days and the heavy rainfall events. They are considered separately, deviating from other quantile mapping procedures.
“Adaptation to climate change” as a new field of knowledge challenges agricultural and horticultural (vocational) education and extension. Farmers and horticulturists are confronted with vague scientific findings at best. A broad variety of global climate scenarios is “projected” onto regions and exact predictions are usually not possible. Often, personal observations and experiences seem to contradict scientific assertions. Under this condition farmers and policy makers must decide about future land use.
What does this imply for capacity building? How to transform insecurity into concrete educational measures and programs?
The authors discuss their first experiences within a German R&D network (INKA BB) in which they develop capacity building programs. Two examples from urban agriculture / urban gardening will be used as case studies. Strengths and weaknesses of the development processes and their management will be discussed.
Since the topic is complex and adaptation is a continuous activity, learning in connection with climate change adaptation ideally begins on elementary level, continues in higher and vocational training, and does not end with extension. In other words: “learning chains” must be developed which enable life-long learning in formal, non-formal and informal learning environments.
Competencies are needed beyond classical technological and economic skills. Problem solving - from problem perception, analysis, generation of alternative solutions, to implementation and evaluation - with a key competence in critical analysis and reflection of contemporary research findings - gain in importance.
In INKA BB, participation is seen as axiomatic. As a consequence, an action-oriented, participatory approach has been chosen which enables mutual learning among partners from research, formal and informal, elementary, higher and vocational education.
A crucial point is the question of “Who could be the bridge between science and the educational practitioner?” In INKA BB, a specific working group (the subproject on “Knowledge Management and Transfer”) facilitates the development processes and therefore plays a liaison role between theory and practice. In the long-run, sustainable ownership of this process must be achieved. A combination of network building, mutual learning in permanent work groups, provision of technical trainings, and joint planning, testing, monitoring and evaluation is seen as a precondition.
Based on concepts for innovation processes and co-production of knowledge, approaches are investigated that address the urgent and complex problems related to climate change, because especially the participation of, and close collaboration with, practice partners is needed. The paper presents the agricultural knowledge management approach in the organic agriculture module of the R&D project INKA BB (Innovation Network for Climate Change Adaptation Brandenburg Berlin) in north-eastern Germany (Knierim et al. 2009). The methodology for the science-practice collaboration follows an action research approach that supports the communication and cooperation of researchers and practitioners. The framework is the action research cycle with iterative stages of planning, action, and reflection. The organic agriculture module, which addresses individual research questions on several farms, is presented as a good practice example for close transdisciplinary network cooperation. The workshop contribution will provide reflections on the innovation development process over two project years.
Information about possible changes of extreme wave heights are essential for the future safe design of coastal and flood protection structures likes dykes, flood protection dunes, revetments etc. In this study, scenarios of regional climate change up to 2100 are used for the evaluation of changes of wave conditions. Analyses on calculated significant wave heights derived from extreme value statistics are showing a different signal of change for the selected locations along the German Baltic Sea Coast. The results are showing that extreme wave heights with a return level of 200 years can increase up to +14%. But also a decrease of down to -14% were found compared to actual conditions, depending on the location and climate change scenario applied. At the location of Warnemünde a slight increasing trend for the change of extreme wave heights could be found for 3 of 4 scenario runs with a maximum increase of +7%.
A statistical downscaling method has been developed to produce highly resolved precipitation data from regional climate model (RCM) output, using the model CLM (2 runs, scenario A1B). The procedure is based on the analogue method with the predictors precipitation (daily sums on CLM grid points) and objective weather types (DWD). Analogue days of the time period 2001-2009 are searched using corrected and adjusted data of radar Essen and DWD measurements of objective weather types. The radar data is used to produce high-resolution precipitation data sets (1km², 5min) with realistic spatial and temporal correlations for three catchments in North Rhine-Westphalia. Results in
the reference period (1961 - 1990) are examined using extreme value statistics and compared to corrected station data. Data sets of the near and the far future (2021-2050, 2071-2100) are analysed with respect to future trends, and uncertainties of the downscaling procedure are discussed.
Rainfall statistics are composed based on data gained by precipitation measurements and from climate models. These statistics are carried out for both periods in the past and the future. When analysing the time series, different trends can be seen in the measured data of the past and the model data for future periods. Influences on the statistically determined precipitation amounts caused by changes can be neglected for past periods. However, significant increases of the statistical precipitation amounts can be observed for the future. Here a pragmatic approach is presented, showing how to consider possible increases in the statistical precipitation amounts – due to the climate change signal – in the dimensioning of water management systems.