• Energy Research
• Open Access close
• Restricted close
• 15. Life on land close
• German close

Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli), other species may gain (Polygonum persicaria) or loose (Viola arvensis) large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis).

Increasing maize cultivation and changed cropping practices promote the selection of typical maize weeds that may also profit strongly from climate change. Predicting potential weed problems is of high interest for plant production. Within the project KLIFF, experiments were combined with species distribution modelling for this task in the region of Lower Saxony, Germany. For our study, we modelled ecological and damage niches of nine weed species that are significant and wide spread in maize cropping in a number of European countries. Species distribution models describe the ecological niche of a species, these are the environmental conditions under which a species can maintain a vital population. It is also possible to estimate a damage niche, i.e. the conditions under which a species causes damage in agricultural crops. For this, we combined occurrence data of European national data bases with high resolution climate, soil and land use data. Models were also projected to simulated climate conditions for the time horizon 2070 - 2100 in order to estimate climate change effects. Modelling results indicate favourable conditions for typical maize weed occurrence virtually all over the study region, but only a few species are important in maize cropping. This is in good accordance with the findings of an earlier maize weed monitoring. Reaction to changing climate conditions is species-specific, for some species neutral (E. crus-galli), other species may gain (Polygonum persicaria) or loose (Viola arvensis) large areas of suitable habitats. All species with damage potential under present conditions will remain important in maize cropping, some more species will gain regional importance (Calystegia sepium, Setara viridis).

To satisfy national sustainability targets in Germany, both bioenergy and organic farming claim a growing area of farmland. Analyses with a land use model and ac-companying expert interviews show, how the competition for land is growing in certain regions. A restricted area potential for energy crops – even with an ever intensifying farming opposes targets for an increasing share of land for organic agriculture and nature conservation. Thus there is a need for policy action, to discuss and solve this goal conflict. An ongoing study currently develops strategies for two selected German regions for a more ecologically compatible bioenergy production.

To satisfy national sustainability targets in Germany, both bioenergy and organic farming claim a growing area of farmland. Analyses with a land use model and ac-companying expert interviews show, how the competition for land is growing in certain regions. A restricted area potential for energy crops – even with an ever intensifying farming opposes targets for an increasing share of land for organic agriculture and nature conservation. Thus there is a need for policy action, to discuss and solve this goal conflict. An ongoing study currently develops strategies for two selected German regions for a more ecologically compatible bioenergy production.

Das Projekt umfasst eine Planungsaufgabe in Johannesburg in Südafrika und befindet sich daher für den Verfasser in einem kulturell fremden Kontext. Die Umsetzung dieser Aufgabe setzt im Vorfeld eine Recherche und Analyse über den Projektstandort in geographischer, demographischer und klimatischer Hinsicht voraus. Diese Recherche soll einen Einblick in das Planungsgebiet und dessen Rahmenbedingungen verschaffen. Die zwei Kollektive AMbush Gardening Collective und African Center for Biodiversity möchten den Bewohnern des Bezuidenhout Valley in Johannesburg ein Gemeindezentrum mit den Themenschwerpunkten Urban Farming und Permakultur zur Verfügung stellen. Hierfür wurde ein Grundstück ausgewählt und den grundsätzlichen Bedarf und die Anforderungen an das potentielle Zentrum geäußert. Bereits realisierte Projekte im kulturell fremden Kontext zeigen, dass die Umsetzung eines solchen Projektes sehr zeitintensiv ist. Neben den anfänglichen Geldsammelaktionen wird der gesamte Planungs- und Ausführungsprozess in stark partizipativen Prozessen abgewickelt. Diese enge Kommunikation bringt viele Vorteile mit sich: Nutzerzufriedenheit, Identifikation mit dem Gebauten, Austausch von Erfahrungen und Wissenszuwachs aller Beteiligten. Für die Bearbeitung dieser Masterarbeit ist die Kernaufgabe auf die realitätsnahe Planung des Gemeindezentrums beschränkt. Der partizipative Teil dieser Planungsaufgabe wird durch Recherchearbeit durch den Verfasser und die Vermittlung der Erfahrungswerte der Masterarbeits-Betreuerin kompensiert. Das Ergebnis der Arbeit wird den Entwurfsvorschlag der Thematik aufzeigen und kann in weiterer Folge dem Kollektiv für die Akquise der finanziellen Mittel dienen. The project comprises a planning task in Johannesburg in South Africa and is therefore in a culturally foreign context for the author. The implementation of this task requires prior research and analysis of the project location from a geographical, demographic and climatic point of view. This research should provide an insight into the area and its framework. PROJECT ACCESS The two collectives AMbush Gardening Collective and African Center for Biodiversity would like to provide the inhabitants of the Bezuidenhout Valley in Johannesburg with a community center focusing on urban farming and permaculture. For this purpose, a plot of land was selected and the basic needs and requirements for the potential centre were expressed. Projects already realised in a culturally foreign context show that the realization of such a project is very time-consuming. In addition to the initial fundraising activities, the entire planning and execution process is carried out in highly participatory processes. This close communication brings many advantages with it: user satisfaction, identification with the building, exchange of experiences and knowledge growth of all participants. For the work on this Master‘s thesis, the core task is limited to the realistic planning of the community centre. The participative part of this planning task is compensated by the research work of the author and the communication of the empirical values of the master thesis supervisor. The result of the work will point out the draft proposal of the topic and can serve in further consequence the collective for the acquisition of the financial means. vorgelegt von: Karin Purker Wien, FH Campus Wien, Masterarb., 2018

Das Projekt umfasst eine Planungsaufgabe in Johannesburg in Südafrika und befindet sich daher für den Verfasser in einem kulturell fremden Kontext. Die Umsetzung dieser Aufgabe setzt im Vorfeld eine Recherche und Analyse über den Projektstandort in geographischer, demographischer und klimatischer Hinsicht voraus. Diese Recherche soll einen Einblick in das Planungsgebiet und dessen Rahmenbedingungen verschaffen. Die zwei Kollektive AMbush Gardening Collective und African Center for Biodiversity möchten den Bewohnern des Bezuidenhout Valley in Johannesburg ein Gemeindezentrum mit den Themenschwerpunkten Urban Farming und Permakultur zur Verfügung stellen. Hierfür wurde ein Grundstück ausgewählt und den grundsätzlichen Bedarf und die Anforderungen an das potentielle Zentrum geäußert. Bereits realisierte Projekte im kulturell fremden Kontext zeigen, dass die Umsetzung eines solchen Projektes sehr zeitintensiv ist. Neben den anfänglichen Geldsammelaktionen wird der gesamte Planungs- und Ausführungsprozess in stark partizipativen Prozessen abgewickelt. Diese enge Kommunikation bringt viele Vorteile mit sich: Nutzerzufriedenheit, Identifikation mit dem Gebauten, Austausch von Erfahrungen und Wissenszuwachs aller Beteiligten. Für die Bearbeitung dieser Masterarbeit ist die Kernaufgabe auf die realitätsnahe Planung des Gemeindezentrums beschränkt. Der partizipative Teil dieser Planungsaufgabe wird durch Recherchearbeit durch den Verfasser und die Vermittlung der Erfahrungswerte der Masterarbeits-Betreuerin kompensiert. Das Ergebnis der Arbeit wird den Entwurfsvorschlag der Thematik aufzeigen und kann in weiterer Folge dem Kollektiv für die Akquise der finanziellen Mittel dienen. The project comprises a planning task in Johannesburg in South Africa and is therefore in a culturally foreign context for the author. The implementation of this task requires prior research and analysis of the project location from a geographical, demographic and climatic point of view. This research should provide an insight into the area and its framework. PROJECT ACCESS The two collectives AMbush Gardening Collective and African Center for Biodiversity would like to provide the inhabitants of the Bezuidenhout Valley in Johannesburg with a community center focusing on urban farming and permaculture. For this purpose, a plot of land was selected and the basic needs and requirements for the potential centre were expressed. Projects already realised in a culturally foreign context show that the realization of such a project is very time-consuming. In addition to the initial fundraising activities, the entire planning and execution process is carried out in highly participatory processes. This close communication brings many advantages with it: user satisfaction, identification with the building, exchange of experiences and knowledge growth of all participants. For the work on this Master‘s thesis, the core task is limited to the realistic planning of the community centre. The participative part of this planning task is compensated by the research work of the author and the communication of the empirical values of the master thesis supervisor. The result of the work will point out the draft proposal of the topic and can serve in further consequence the collective for the acquisition of the financial means. vorgelegt von: Karin Purker Wien, FH Campus Wien, Masterarb., 2018

The main goal of TERENO was to create observation platforms on the basis of an interdisciplinary and long‐term aimed research program. By the aid of SoilCan‐lysimeters, an ideal network was built between the four different TERENO‐observatories with their highly instrumented test sites. Within the four TERENO‐observatories at 13 different experimental sites, in total 126 lysimeters were filled monolithically and the measurements were started in October 2010. The lysimeters have been cultivated as grassland or arable land with a standardized crop rotation: winter wheat – winter barley – winter rye – oat.

The main goal of TERENO was to create observation platforms on the basis of an interdisciplinary and long‐term aimed research program. By the aid of SoilCan‐lysimeters, an ideal network was built between the four different TERENO‐observatories with their highly instrumented test sites. Within the four TERENO‐observatories at 13 different experimental sites, in total 126 lysimeters were filled monolithically and the measurements were started in October 2010. The lysimeters have been cultivated as grassland or arable land with a standardized crop rotation: winter wheat – winter barley – winter rye – oat.

Urban drainage infrastructure has to adapt to challenges such as climate change, but also to trends such as population and settlement development. At the same time, the opportunities offered by digitization can be used to meet these challenges. In this thesis, therefore, two geoinformation-based models are developed, which use the advancing digitization to contribute to the adaptation of urban drainage to demographic and climate change. An important aspect of municipal flood protection are nature-oriented measures for the rainwater management as part of water-sensitive urban development. According to the recognized rules of technology, the overriding goal of rainwater management is to approximate the natural water balance. The estimate of this target value is difficult to determine. The potential offered by decentralized rainwater management measures to achieve or approach this target as well. One geoinformation-based model pursues these two goals. The first goal is the estimation of the water balance deficit. The second goal is a limitation of the potential measures for the best compensation of this deficit. For this purpose, structural, geological and hydrogeological restrictions are taken into account. The model works exclusively with geo-referenced data and thus offers direct localization of the results. Furthermore, the model combines the approach of the empirically determined water balance distribution functions of the DWA-A 102 and a GIS-based calculation. The advantages of this combination are the scaling of a selectable study area and the on the fly consideration of restrictions for the measures of decentralized rainwater management. The second geoinformation-based model is an artificial neural network (ANN) for calculating flood areas caused by heavy rain. The trained ANN is suitable for known areas, works in real time and substitute a conventional hydrodynamic model. Therefore, a supervised learning multi-layer feed-forward ANN was set up and trained. After that, it was then examined and assessed for its suitability. For the substitution of a hydrodynamic numerical model for calculation of flooding risks (flood areas or surface runoff) by an ANN, the ANN must 'learn' the hydrological processes of the conventional model. For this learning process, the ANN requires input values that essentially determine the hydrological processes (e.g. precipitation, digital elevation model, type of sealing, barriers and culverts, etc.). Moreover, the AAN requires target values. For the ANN, the target values are areas with a certain height water level caused by a precipitation event (flood areas with flood level). These target values were first calculated using a hydrodynamic numerical model.The developed model shows that ANNs are more suitable than conventional hydrodynamic numerical models for certain applications due to their computing speed. Even if the generalizability of the trained ANN to other model areas could not be successfully demonstrated, the ANN however was able to predict good results for a sufficiently known range of values.The biggest advantage of the ANN is the low computing time for predicting flood areas. In contrast to hydrodynamic numerical models, the ANN predicts flood areas with sufficient accuracy in a few seconds. The application possibilities of the developed model thus specialize in cases in which these strengths are indispensable. One indispensability is the prediction of flood area caused by spontaneously and spatially limited heavy rain. This indispensability is also a demand of the municipal flood protection. Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2021; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen, Diagramme (2021). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2021 Published by RWTH Aachen University, Aachen

Urban drainage infrastructure has to adapt to challenges such as climate change, but also to trends such as population and settlement development. At the same time, the opportunities offered by digitization can be used to meet these challenges. In this thesis, therefore, two geoinformation-based models are developed, which use the advancing digitization to contribute to the adaptation of urban drainage to demographic and climate change. An important aspect of municipal flood protection are nature-oriented measures for the rainwater management as part of water-sensitive urban development. According to the recognized rules of technology, the overriding goal of rainwater management is to approximate the natural water balance. The estimate of this target value is difficult to determine. The potential offered by decentralized rainwater management measures to achieve or approach this target as well. One geoinformation-based model pursues these two goals. The first goal is the estimation of the water balance deficit. The second goal is a limitation of the potential measures for the best compensation of this deficit. For this purpose, structural, geological and hydrogeological restrictions are taken into account. The model works exclusively with geo-referenced data and thus offers direct localization of the results. Furthermore, the model combines the approach of the empirically determined water balance distribution functions of the DWA-A 102 and a GIS-based calculation. The advantages of this combination are the scaling of a selectable study area and the on the fly consideration of restrictions for the measures of decentralized rainwater management. The second geoinformation-based model is an artificial neural network (ANN) for calculating flood areas caused by heavy rain. The trained ANN is suitable for known areas, works in real time and substitute a conventional hydrodynamic model. Therefore, a supervised learning multi-layer feed-forward ANN was set up and trained. After that, it was then examined and assessed for its suitability. For the substitution of a hydrodynamic numerical model for calculation of flooding risks (flood areas or surface runoff) by an ANN, the ANN must 'learn' the hydrological processes of the conventional model. For this learning process, the ANN requires input values that essentially determine the hydrological processes (e.g. precipitation, digital elevation model, type of sealing, barriers and culverts, etc.). Moreover, the AAN requires target values. For the ANN, the target values are areas with a certain height water level caused by a precipitation event (flood areas with flood level). These target values were first calculated using a hydrodynamic numerical model.The developed model shows that ANNs are more suitable than conventional hydrodynamic numerical models for certain applications due to their computing speed. Even if the generalizability of the trained ANN to other model areas could not be successfully demonstrated, the ANN however was able to predict good results for a sufficiently known range of values.The biggest advantage of the ANN is the low computing time for predicting flood areas. In contrast to hydrodynamic numerical models, the ANN predicts flood areas with sufficient accuracy in a few seconds. The application possibilities of the developed model thus specialize in cases in which these strengths are indispensable. One indispensability is the prediction of flood area caused by spontaneously and spatially limited heavy rain. This indispensability is also a demand of the municipal flood protection. Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2021; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen, Diagramme (2021). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2021 Published by RWTH Aachen University, Aachen