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A Biophysically Based Coupled Model Approach For the Assessment of Canopy Processes Under Climate Change Conditions
A Biophysically Based Coupled Model Approach For the Assessment of Canopy Processes Under Climate Change Conditions
The central questions of this thesis are concerned with the investigation of vegetation related landsurface parameters under the impact of changing climate conditions. The spatial extent of the study is limited to the borders of the Upper Danube drainage basin, according to the requirements of the cooperative Project GLOWA-Danube (Global change of the Hydrological Cycle), funded by the German Ministry of Education and research (BMB+F). Current publications are indicating that the dynamic behaviour of the vegetation cover often is inadequately accounted for in studies that are investigating the impacts of climate change with respect to the landsurface water cycle. In order to enable a dynamic feedback between the animate land cover and the atmosphere, which might be sensitive enough to trace active reactions of the vegetation cover on changing climatic conditions, the physically based land surface process model PROMET (Process of Radiation Mass and Energy Transfer Model) was enhanced by an explicit description of the growth activity of different plant types. The introduced model approach was tested against measured data for a variety of parameters. The different validation efforts all returned good to very good results. It therefore can be stated that the model soundly demonstrated its capability concerning the precise reproduction of a variety of structural landsurface variables on different scales under observed climatic conditions. An application of the model to the calculation of climate scenarios therefore seems appropriate. In order to enable comparability with international research approaches, the internationally acknowledged global change scenarios developed by the Intergovernmental Panel on Climate Change (IPCC), are basically applied. The moderate A1B emissions scenario, which is based on the assumption of a balanced future development of different energy technologies, was selected and modified by a regional impact factor that is assumed to apply to the local situation of the Upper Danube catchment. Being applied to the regionally adapted IPCC A1B climate scenario, the model returned clear statements, projecting a possible future development of selected landsurface parameters within the Upper Danube area. Concerning the phenological behaviour of forest trees, the model simulated a strong trend towards earlier incidence of the leaf emergence of deciduous as well as of the mayshoot of coniferous trees, contributing to a significant elongation of the vegetation period. These longer phases of active growth in combination with the rising temperatures and the elevated supply of atmospheric carbon dioxide led to an increase of biological activity in the model results that manifested in increasing rates of biomass accumulation for the Upper Danube area. The increased biological activity in combination with the strong decrease of summer precipitation, which was assumed in the climate scenario, again led to an escalating frequency of drought stress events in the Upper Danube Basin. Not only the average count of water stress events per year was modelled to increase, but also a spatial extension of the regions that are affected by drought stress was mapped by the model. This general increase of water stress and the significant decrease of summer precipitation entailed a slight decline of the transpiration and evapotranspiration of the Upper Danube area in the scenario results. The modelled decline of the summer precipitation also resulted in a noticeable decrease of the modelled average discharge rates at the main gauge of the basin. The base flow rates during the summer months thereby are likely to be primarily affected. Since the model results for the scenario period featured temporal and spatial variations and standard deviations that were closely matching the statistics of the reference period, while at the same time they showed clear trends though they were avoiding extreme realizations, the scenario assumptions can be considered to be reliable. The baseline scenario, which was spot-checked for a set of reference proxels, did not return any trends as expected, indicating that the observed future trends are not of systematic origin. The further development of the introduced model approach is an appealing challenge, which might considerably contribute to the improvement of computer aided decision support systems. It can be assumed that the progress of the development of physically based models due to a more profound understanding of the processes on one hand and the sophistication and refinement of the model algorithms that result from the increase of knowledge on the other, may contribute to the development of reliable systems, that will be able to sustainably assist humanity with the handling of future environmental challenges. The author gratefully acknowledges the finacial support of the German Research Foundation (DFG) in the frame of the project "Coupled Analysis of Vegetation Chlorophyll and Water Content Using Hyperspectral, Bidirectional Remote Sensing".
Climate Change, GLOWA-DANUBE, PROMET, Landsurface Modelling, Photosynthesis
Hank, Tobias Benedikt
2008
Englisch
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Hank, Tobias Benedikt (2008): A Biophysically Based Coupled Model Approach For the Assessment of Canopy Processes Under Climate Change Conditions. Dissertation, LMU München: Fakultät für Geowissenschaften
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Abstract

The central questions of this thesis are concerned with the investigation of vegetation related landsurface parameters under the impact of changing climate conditions. The spatial extent of the study is limited to the borders of the Upper Danube drainage basin, according to the requirements of the cooperative Project GLOWA-Danube (Global change of the Hydrological Cycle), funded by the German Ministry of Education and research (BMB+F). Current publications are indicating that the dynamic behaviour of the vegetation cover often is inadequately accounted for in studies that are investigating the impacts of climate change with respect to the landsurface water cycle. In order to enable a dynamic feedback between the animate land cover and the atmosphere, which might be sensitive enough to trace active reactions of the vegetation cover on changing climatic conditions, the physically based land surface process model PROMET (Process of Radiation Mass and Energy Transfer Model) was enhanced by an explicit description of the growth activity of different plant types. The introduced model approach was tested against measured data for a variety of parameters. The different validation efforts all returned good to very good results. It therefore can be stated that the model soundly demonstrated its capability concerning the precise reproduction of a variety of structural landsurface variables on different scales under observed climatic conditions. An application of the model to the calculation of climate scenarios therefore seems appropriate. In order to enable comparability with international research approaches, the internationally acknowledged global change scenarios developed by the Intergovernmental Panel on Climate Change (IPCC), are basically applied. The moderate A1B emissions scenario, which is based on the assumption of a balanced future development of different energy technologies, was selected and modified by a regional impact factor that is assumed to apply to the local situation of the Upper Danube catchment. Being applied to the regionally adapted IPCC A1B climate scenario, the model returned clear statements, projecting a possible future development of selected landsurface parameters within the Upper Danube area. Concerning the phenological behaviour of forest trees, the model simulated a strong trend towards earlier incidence of the leaf emergence of deciduous as well as of the mayshoot of coniferous trees, contributing to a significant elongation of the vegetation period. These longer phases of active growth in combination with the rising temperatures and the elevated supply of atmospheric carbon dioxide led to an increase of biological activity in the model results that manifested in increasing rates of biomass accumulation for the Upper Danube area. The increased biological activity in combination with the strong decrease of summer precipitation, which was assumed in the climate scenario, again led to an escalating frequency of drought stress events in the Upper Danube Basin. Not only the average count of water stress events per year was modelled to increase, but also a spatial extension of the regions that are affected by drought stress was mapped by the model. This general increase of water stress and the significant decrease of summer precipitation entailed a slight decline of the transpiration and evapotranspiration of the Upper Danube area in the scenario results. The modelled decline of the summer precipitation also resulted in a noticeable decrease of the modelled average discharge rates at the main gauge of the basin. The base flow rates during the summer months thereby are likely to be primarily affected. Since the model results for the scenario period featured temporal and spatial variations and standard deviations that were closely matching the statistics of the reference period, while at the same time they showed clear trends though they were avoiding extreme realizations, the scenario assumptions can be considered to be reliable. The baseline scenario, which was spot-checked for a set of reference proxels, did not return any trends as expected, indicating that the observed future trends are not of systematic origin. The further development of the introduced model approach is an appealing challenge, which might considerably contribute to the improvement of computer aided decision support systems. It can be assumed that the progress of the development of physically based models due to a more profound understanding of the processes on one hand and the sophistication and refinement of the model algorithms that result from the increase of knowledge on the other, may contribute to the development of reliable systems, that will be able to sustainably assist humanity with the handling of future environmental challenges. The author gratefully acknowledges the finacial support of the German Research Foundation (DFG) in the frame of the project "Coupled Analysis of Vegetation Chlorophyll and Water Content Using Hyperspectral, Bidirectional Remote Sensing".