Auflistung nach Autor:in "Tum, Markus"
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- KonferenzbeitragA new validation approach to assess the quality of modeled agricultural biomass potentials using BETHY/DLR(Integration of Environmental Information in Europe, 2010) Tum, Markus; Niklaus, Markus; Günther, Kurt P.; Kappas, Martin WernerA new validation approach is presented to assess the quality of modeled agricultural biomass potentials with statistical data on high resolution. First investigations in Germany and Austria show coefficients of determination (r²) of up to 0.79 on district level. Our modeled net primary productivity is computed with the dynamic biomass model BETHY/DLR. Primarily the photosynthetic rate of vegetation types is computed with time steps of one hour and currently with a spatial resolution of about 1km x 1km. Included models compute the water balance and radiative energy transfer between atmosphere, vegetation and soil. The model is driven by meteorological data provided by the European Center for Medium Range Weather Forecast (ECMWF), remote sensing data derived through SPOTVEGETATION and soil type information by the Food and Agriculture Organisation (FAO). The model output (gross primary productivity (GPP)) is calculated daily. Net primary productivity (NPP) is determined by subtracting the cumulative plant maintenance respiration from GPP. In order to validate the modeled NPP, data of crop yield estimations derived from national statistics are used to calculate above ground biomass by using conversion factors about corn to straw relations. Furthermore conversion factors about shoot to root relations are used to determine total biomass. Finally the carbon content of dry matter is estimated. With this method coefficients of determination (r²) of up to 0.67 combined with a slope of 0.83 are found for Germany. For Austrian NUTS-3 units slightly higher coefficients of determination are found (0.74) combined with a slope of 1.08. The results show that modelling NPP using the process model BETHY/DLR and remote sensing data and meteorological data as input delivers reliable estimates of above ground biomass when common agricultural conversion factors are taking into account.
- KonferenzbeitragA pre-market service to map biomass potentials on a regional level(Proceedings of the 27th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management, 2013) Tum, Markus; Günther, KurtIn the framework of the EU FP7 project ENDORSE (Energy Downstream Services Providing energy components for GMES) a pre-market service is developed to estimate the annual above ground biomass increase for forests in Germany. This development is driven by the requirements of a prime user (Forest Competence Center Eberswalde) and done in close cooperation with experts in the field of forestry. One aim of the service is to develop a cost and time efficient method to deliver yearly estimates of above ground forest biomass increase using satellite measurements and modelling techniques as the BETHY/DLR SVAT model. Another aim is to use mainly satellite observations coming from GMES services and/or GMES space components. Our yearly estimates of above ground forest biomass increase covering the time span from 2000 to 2012 will fill the gaps of the national forest inventories. In Germany the first and second National Forest Inventory (NFI) took place in the years 1987 and 2002 while the third inventory was performed in 2011 and 2012. This large-scale ground mapping of the forest status and forest productivity uses random sampling of forest parameters for the entire territory of the Federal Republic of Germany. The new pre-market service allows monitoring forest growth on a regional level with 1km x 1km spatial resolution with respect to local meteorological conditions
- KonferenzbeitragEnerGEO biomass pilot(Proceedings of the 27th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management, 2013) Tum, Markus; Günther, Kurt P; McCallum, Ian; Balkovic, Jurai; Khabarov, Nikolay; Kindermann, Georg; Leduc, Sylvan; Biberacher, MarkusIn the framework of the EU FP7 project EnerGEO (Earth Observation for Monitoring and Assessment of the Environmental Impact of Energy Use) sustainable energy potentials for forest and agricultural areas were estimated by applying three different model approaches. Firstly, the Biosphere Energy Transfer Hydrology (BETHY/DLR) model was applied to assess agricultural and forest biomass increases on a regional scale with the extension to grassland. Secondly, the EPIC (Environmental Policy Integrated Climate) a cropping systems simulation model was used to estimate grain yields on a global scale and thirdly the Global Forest Model (G4M) was used to estimate global woody biomass harvests and stock. The general objective of the biomass pilot is to implement the observational capacity for using biomass as an important current and future energy resource. The scope of this work was to generate biomass energy potentials for locations on the globe and to validate these data. Therefore, the biomass pilot was focused to use historical and actual remote sensing data as input data for the models. For validation purposes, forest biomass maps for 1987 and 2002 for Germany (Bundeswaldinventur (BWI-2)) and 2001 and 2008 for Austria (Austrian Forest Inventory (AFI)) were prepared as reference. The output of BETHY/DLR, EPIC and G4M was used as input for the energy scenario-models REMIX (Renewable Energy Mix for Sustainable Electricity Supply in Europe, developed and operated by DLR-TT) , TASES (Time And Space resloved Energy Simulation, developed and operated by Research-Studio, Salzburg) and BeWhere (a techno-economic model developed by IIASA and Lud university and operated by IIASA). The EPIC modelling results for agricultural areas are input to TASES and REMIX. G4M also provided input data for TASES on a global scale starting with the year 2000 and ending in 2050 with 10 years steps. The main conclusions from the Biomass Pilot are: 1) It is possible to calculate biomass energy potentials for wood and agricultural crops by applying BETHY/DLR, EPIC or G4M models for Europe (1x1 km2) and the globe (0.5 x 0.5 ). 2) The outcomes of biomass energy models are sensitive to input data by 40% or more. This is a consequence of biological sensitiveness to factors that determine growth such as weather, soil, species and cultivation. Collecting more and better input data is therefore essential. 3) Intensive effort was put on validation activities for all three models as well as a model intercomparison. For agricultural and forested areas all models showed significant linear relationship with reference data (R2 up to 0.95). 4) Remote sensing data can be used for generating some input data for biomass potential modelling such as weather and land use data 5) Remote sensing data have to be further developed before a differentiation can be made between different species and crops or biomass stacks can be modelled.
- KonferenzbeitragModeling Carbon Sinks and Sources in semi-arid Environments for a Land Degradation Assessment Approach(Integration of Environmental Information in Europe, 2010) Niklaus, Markus; Tum, Markus; Günther, Kurt P.Contrary to wetlands or moderate climates, the understanding of carbon exchange between ecosystem and atmosphere in arid and semi-arid environments is more challenging due to the sensible feedback of terrestrial ecosystems to environmental variability. Especially in the savannah regions of South Africa the biomes are strongly affected on the one hand by low and sporadic precipitation and on the other hand by intense land use of livestock farming. This leads to wide degraded areas under the process of desertification and the loss of huge carbon stocks in soil and vegetation. To quantify the carbon sinks and sources in these regions we ran our dynamic vegetation model BETHY/DLR for South Africa which generates maps of Net Primary Productivity, NPP, in spatial resolution of 1 km. These results can help assessing the status and development of land degradation for the whole country of South Africa.