Our daily lives depend on the provision of services by different ecosystems in which an important contribution is made by groundwater. To balance competing demands placed on groundwater for socioeconomic and ecological benefits constitute major challenges for water managers. At the policy-science interface the ecosystem service concept represents an appropriate approach to communicate management challenges in which researchers and politicians must take into account human and biophysical characteristics as intertwined systems. This study investigated the complexity of groundwater governance, and linkages between management and corresponding effects on ecosystem services. Empirical insights were derived from case studies in South Africa, Spain and Germany. The analytical focus includes (a) the degree of vertical (multi-level) and horizontal (cross-sectoral) integration which frame crucial characteristics of an adaptive governance regime and (b) the role of formal and informal institutions governing groundwater. In doing so, an conceptual and analytical approach was applied, especially developed to support a systematic and consistent investigation of policy and management processes. Evidence highlights that higher degrees of integration: (i) opens up the political arena for environmental perspectives, (ii) increases the quality of management plans, (iii) accelerates the implementation of measurements, (iv) mitigates conflicts between different groundwater users, and (v) increases the awareness of various ecosystem services. Further the results indicate that having well-crafted institutions in place does not automatically indicate successful groundwater management in the sense of bringing about positive results for socioeconomic or ecological sustainability. This work made a significant contribution to interdisciplinary research in the field of groundwater governance and ecosystem service management that builds the foundations for improving the policy-science interface.

Achieving sustainability requires major changes in several areas in which society makes use of technology to meet human needs and while doing so influences the environment, such as agriculture, mobility, power production and water management. The awareness of a need for radical changes is accompanied by an increasing recognition of the interconnectedness of technological, socio-cultural and environmental elements and processes. This has led to an increasing amount of research on system innovations. System innovations refer to changes to a "structurally different" system involving radical changes in the technological and socio-cultural domains and are often contrasted to incremental (technological) change. System innovations involve many actors and many factors, and developments at multiple levels interact. Control over such processes is distributed, they are laden with uncertainty and they exhibit sometimes surprising and unexpected behaviour due to non-linear dynamics and emergent properties involved. Our current understanding of system innovations is limited and the need for an enhanced understanding has clearly been recognized. Computer simulation models seem a promising tool to that end as they already proved to be useful to enhance the understanding of complex systems in many fields like complex chemistry, ecosystems and physics. However, system innovations are mostly processes in social systems. In the social sciences, the application of formal simulation models has a far shorter history and the availability of formalized (and widely accepted) theories and generalizations is low compared to the natural sciences. It is thus not clear-cut which role computer simulation models can play with respect to system innovations. This thesis fathoms the potential of computer simulation models for enhancing our understanding of system innovations and takes some first steps towards fruitful application of models. A theoretical and methodological discussion outlines how models can in principle contribute to an understanding of social macro-processes through facilitating a causal reconstruction of processes that account for the respective observed phenomenon. The view adopted regarding the representation of the social world thereby is that of reciprocity of agency and structure. Compared to the sociological literature the perspective is extended beyond comprising actors and institutions but encompasses also other entities, especially technological artefacts. The thesis then relates the current state of empirical and conceptual work in the field of transition research (the terms "transition" and "system innovation" are used interchangeably) to insights from modelling of complex systems. The intrinsic characteristics of system innovations and the knowledge base available to study them are explicated and implicated challenges and opportunities for model application are discussed. This is complemented by a review of the few existing models of system innovations. The thesis further develops a specification of the regime concept. A regime refers to a dominant structure which originates incremental change but resists system innovations. The concept of "regime" is at the heart of the multi-level perspective, the most widely used framework of transition research, but it is yet only loosely defined. The absence of shared definitions, concept specifications and operationalizations of key concepts of transition research is a major obstacle for defining (and especially for comparing) models. In this thesis, five defining characteristics of regimes are developed and a method to structure and graphically represent knowledge about a regime is introduced. Furthermore, theoretical and conceptual work has been complemented by hands-on experience to make methodological and theoretical deliberations tangible. An agent-based model has been developed which addresses the transition from rainfed to irrigated agriculture in the Upper Guadiana, Spain. The purpose of the model is to bridge a gap in the explanation for the observed process. Case specific literature provides information on driving forces (technological development, changes in regulations) and consequences (amount of irrigation). The model focuses on the farmers which "translate" driving forces into practices of irrigation and water use. It studies the effect of weights farmers attach to a list of priorities. The main findings are that interactions of factors have to be considered and that it is important to acknowledge heterogeneity of farm types to understand empirically observed land-use changes. Based on the outlined work, different possibilities to model system innovations have been abstracted and discussed with respect to their advantages and limitations: a) functional subsystems, b) interacting structures (niches, regimes and landscape) as suggested by the multi-level perspective and c) micro-level entities (actors, technological artefacts, institutions, etc.). None of these representations is superior to the other ones per se but each features certain advantages and drawbacks. The model purpose is a necessary guideline to choose an appropriate representation and to distinguish those parts and aspects of a system which need to be captured from negligible ones. The main findings of this thesis can be summarized as follows: System innovations feature several characteristics which put model-based approaches to this topic on the most challenging edge of the broader endeavour of understanding and modelling social systems. Those are the significance of emergent decay and re-creation of structure during system innovations; the vast scope of system innovations involving several types of subsystems (consumption, production, governance, and nature); the intertwinement of system innovations with their governance – a field which is hardly accessible to modelling; the complexity of the topic; and the unpredictability of innovations. Still, it is concluded that models can be useful as thinking tools. In any case, given the complexity of the topic and the underdeveloped knowledge base, adhering to transparency is essential. In a field as vast and complex as system innovations this requires either very strong simplifications or restricting a model's scope to some parts or aspects of an overall process. This thesis proposes to make use of existing building blocks of understanding of an intermediate level of complexity – e.g. timing and kind of multi-level interactions - to define abstractions and model scope. The challenge to identify, specify, understand and relate conceptual building blocks, to identify the contexts and situations in which each of them becomes relevant and to explicate their role in the overall system innovation could be an agenda for transition modelling for the coming years. Modelling system innovations will remain a huge challenge in the near future. However, this thesis fathoms that models can be valuable tools contributing to the enhancement of the knowledge base of the field; little by little adding to answers of the "big questions". The specific role(s) models of system innovations can play in this endeavour needs to be further explored and discussed.

In this thesis, a conceptual framework and related methodological approaches for complex system design are developed and tested. The approaches are based on insights from the fields of Systems Engineering (SE) and System-of-Systems Engineering (SoSE), as well as Natural Resources Management (NRM). The focus of this thesis is on: 1) the development of the System-of-Systems Design Framework “FRESCO”, 2) the development of a methodological framework for participatory systems design, 3) the application of the framework in two case studies, and 4) the development of an evaluation scheme to qualitatively measure the effectiveness of the methodological framework. The overall objectives of this doctoral dissertation are to highlight synergies between SE and NRM and to develop a methodological framework for designing decision making processes in a human-nature-technology context. The complexity of coupled and complex adaptive systems (CAS) such as the Water-Energy-Food Nexus (WEF-Nexus) and sustainability strategies, influences the design of decision-making processes and strategy building. Integrated process design which is promoted by the developed frameworks can assist in such tasks on an urban, regional, and national level.

There is an increasing concern for the impact of humans on the environment. Traditionally, ecological models consider human influence as a constant or linearly varying parameter, whereas socioeconomic models and frameworks tend to oversimplify the ecological system. But tackling complex environmental challenges faced by our societies requires interdisciplinary approaches due to the intricate feedbacks between the socioeconomic and ecological systems involved. Thus, models of social-ecological systems couple an ecological system with a socioeconomic system to investigate their interaction in the integrated dynamical system. We define this coupling formally and apply the social-ecological approach to three ecological cases. Indeed, we focus on eutrophication in shallow freshwater lakes, which is a well-known system showing bistability between a clear water state and a turbid polluted state. We also study a model accounting for an aquifer (water stock) and a model accounting for a biotic population exhibiting bistability through an Allee effect. The socioeconomic dynamics is driven by the incentive that agents feel to act in a desirable or undesirable way. This incentive can be represented by a difference in utility, or in payoff, between two strategies that each agent can adopt: agents can cooperate and act in an environment-friendly way, or they can defect and act in an ecologically undesirable way. The agents' motivation includes such factors as the economic cost of their choice, the concern they feel for the environment and conformism to the collective attitude of the human group. Thus, the incentive to cooperate responds to the state of the ecological system and to the agents' collective opinion, and this response can be linear, nonlinear and monotonic, or non-monotonic. When investigating the mathematical form of this response, we find that monotonic non-linear responses may result in additional equilibria, cycles and basins of attraction compared to the linear case. Non-monotonic responses, such as resignation effects, may produce much more complicated nullclines such as a closed nullcline and weaken our ability to anticipate the dynamics of a social-ecological system. Regarding the modelling of the socioeconomic subsystem, the replicator dynamics and the logit best-response dynamics are widely used mathematical formulations from evolutionary game theory. There seems to be little awareness about the impact of choosing one or the other. The replicator dynamics assumes that the socioeconomic subsystem is stationary when all agents adopt the same behaviour, whereas the best-response dynamics assumes that this situation is not stationary. The replicator dynamics has formal game theoretical foundations, whereas best-response dynamics comes from psychology. Recent experiments found that the best-response dynamics explains empirical data better. We find that the two dynamics can produce a different number of equilibria as well as differences in their stability. The replicator dynamics is a limit case of the logit best-response dynamics when agents have an infinite rationality. We show that even generic social-ecological models can show multistability. In many cases, multistability allows for counterintuitive equilibria to emerge, where ecological desirability and socioeconomic desirability are not correlated. This makes generic management recommendations difficult to find and several policies with and without socioeconomic impact should be considered. Even in cases where there is a unique equilibrium, it can lose stability and give rise to sustained oscillations. We can interpret these oscillations in a way similar to the cycles found in classical predator-prey systems. In the lake pollution social-ecological model for instance, the agents' defection increases the lake pollution, which makes agents feel concerned and convince the majority to cooperate. Then, the ecological concern decreases because the lake is not polluted and the incentive to cooperate plummets, so that it becomes more advantageous for the agents to defect again. We show that the oscillations obtained when using the replicator dynamics tend to produce a make-or-break dynamics, where a random perturbation could shift the system to either full cooperation or full defection depending on its timing along the cycle. Management measures may shift the location of the social-ecological system at equilibrium, but also make attractors appear or disappear in the phase plane or change the resilience of stable steady states. The resilience of equilibria relates to basins of attraction and is especially important in the face of potential regime shifts. Sources of uncertainty that should be taken into account for the management of social-ecological systems include multistability and the possibility of counterintuitive equilibria, the wide range of possible policy measures with or without socioeconomic interventions, and the behaviour of human collectives involved, which may be described by different dynamics. Yet, uncertainty coming from the collective behaviour of agents is mitigated if they do not give up or rely on the other agents' efforts, which allows modelling to better inform decision makers.

Die Windenergie an Land (Onshore-Windenergie) ist neben der Photovoltaik eine der tragenden Säulen der Energiewende in Deutschland. Wie schon in der Vergangenheit wird auch zukünftig der Ausbau der Onshore-Windenergie, mit dem Ziel eine umweltgerechte und sichere Energieversorgung für zukünftige Generationen aufzubauen, durch die Politik massiv vorangetrieben. Für eine planvolle Umsetzung der Energiewende, insbesondere im Bereich der Windenergie, müssen Kenntnisse über den zur Verfügung stehenden Raum und der Wirkungsweise standortspezifischer Faktoren auf planungsrechtlicher Ebene vorhanden sein. In der vorliegenden Arbeit wurde die Region Deutschland auf das für dieWindenergie an Land nutzbare Flächenpotenzial analysiert, von diesem allgemein gültige Energiepotenziale abgeleitet und in einer Sensitivitätsanalyse die Einflüsse verschiedener Abstände zwischen den Windenergieanlagen und Siedlungsstrukturen auf das ermittelte Energiepotenzial untersucht. Des Weiteren wurden für die beobachteten Zusammenhänge zwischen den Distanz- und Energiepotenzialänderungen mathematische Formeln erstellt, mit deren Hilfe eine Energiepotenzialänderung in Abhängigkeit von spezifischen Siedlungsdistanzänderungen vorhersagbar sind. Die Analyse des Untersuchungsgebiets (USG) hinsichtlich des zur Verfügung stehenden Flächenpotenzials wurde anhand eines theoretischen Modells, welches die reale Landschaft mit ihren unterschiedlichen Landschaftstypen und Infrastrukturen widerspiegelt, umgesetzt. Auf Basis dieses Modells wurden so genannte „Basisflächen“ sowie für die Onshore-Windenergie nicht nutzbare Flächen (Tabu- oder Ausschlussflächen) identifiziert und mittels einer GIS-Software (Geographisches Informationssystem) verschnitten. Die Identifizierung der Ausschlussflächen erfolgte über regionalisierte beziehungsweise im gesamten USG geltende multifaktorielle Bestimmungen für die Platzierung von Windenergieanlagen (WEA). Zur Gewährleistung einer einheitlichen Konsistenz wurden die verschiedenen Regelungen, welche aus den unterschiedlichsten Quellen stammen, vereinheitlicht, vereinfacht und in einem so genannten „Regelkatalog“ festgeschrieben. Die Berechnung des im USG maximal möglichen Energiepotenzials erfolgte durch eine Referenzanlage, welche im USG räumlich verteilt platziert wurde. Die Energiepotenziale (Leistungs- und Ertragspotenzial) leiten sich dabei aus der Kombination der räumlichen Lage der WEA, den technischen Leistungsspezifikationen der Referenzanlage und dem regionalem Windangebot ab. Eine wesentliche Grundvoraussetzung für die Berechnung der Energiepotenziale lag in der im Vorfeld durchzuführenden Windenergieanlagenallokation auf den Potenzialflächen begründet. Zu diesem Zweck wurde die integrierte Systemlösung „MAXPLACE“ entwickelt. Mit dieser ist es möglich, WEA unter Berücksichtigung von anlagenspezifischen, wirtschaftlichen und sicherheitstechnischen Aspekten in einzelnen oder zusammenhängenden Untersuchungsregionen zu platzieren. Im Gegensatz zu bereits bestehenden Systemlösungen (Allokationsalgorithmen) aus anderen Windenergie-Potenzialanalysen zeichnet sich die integrierte Systemlösung „MAXPLACE“ durch eine sehr gute Effizienz, ein breites Anwendungsspektrum sowie eine einfache Handhabung aus. Der Mindestabstand zwischen den WEA und den Siedlungsstrukturen stellt den größten Restriktionsfaktor für das ermittelte Energiepotenzial dar. Zur Bestimmung der Einflussnahme von Siedlungsdistanzänderungen auf das Energiepotenzial wurde mit Hilfe des erstellten Landschaftsmodells eine Sensitivitätsanalyse durchgeführt. In dieser wurden die vorherrschenden Landschafts- und Infrastrukturen analysiert und daraus standortbeschreibende Parameter abgeleitet. Neben der konkreten Benennung der Energiepotenzialänderungen, wurden für das gesamte USG mathematische Abstraktionen der beobachteten Zusammenhänge in Form von Regressionsformeln ermittelt. Diese Formeln ermöglichen es, ohne die in dieser Arbeit beschriebene aufwendige Methodik nachzuvollziehen, mit nur wenigen Parametern die Auswirkungen einer Siedlungsdistanzänderung auf das Energiepotenzial innerhalb des Untersuchungsgebiets zu berechnen.

A fundamental change in societal values and economic structures is required to address increasing pressures on ecosystems and natural resources. Transition research has developed in the last decades to analyze the co-dynamics of technological, institutional, social and economic elements in the provision of key functions such as energy, water and food supply. This doctoral dissertation provides conceptual and methodological contributions to the pro-active governance of sustainability transitions. Three research gaps are identified that are addressed in this dissertation. First, a comprehensive conceptualization of learning in sustainability transitions is currently missing that comprises learning at multiple societal levels (ranging from individuals to policy-actors). Learning concepts are often not explicitly discussed in transition research even though learning is considered as fundamental for innovation processes, niche formation and development as well as breakthrough and diffusion of innovations. Second, methods for the analysis and design of transition governance processes are lacking that specify case-specific intervention points and roles of actors in the implementation of innovations. Third, participatory modeling approaches are only applied to a limited extent in transition research despite a high potential for supporting communication and learning. The conceptualization of multi-level learning developed in this doctoral research conceptualizes learning at different societal levels as specific learning contexts ranging from individual and group contexts to organizational and policy contexts. The conceptual framework further differentiates between learning processes, intensity, objects, outcomes, subjects and factors, allowing for a more detailed analysis of learning within and across learning contexts. Thus, learning contexts can be linked by processes that involve actors from different learning contexts (e.g., community groups and policy-makers), as well as exchanges of physical aspects, institutions and knowledge (in the form of ‘learning factors’). This research has also provided a classification of model uses in transition research that supports a purposeful discussion of the opportunities of modeling and promising future research directions. The methodology developed in this doctoral research aims at the analysis and design of transition governance processes by specifying the various opportunities to contribute to sustainability transitions through purposeful action at different societal levels, as well as related roles of stakeholders in implementing such processes of change. The methodology combines different streams of previous research: 1) a participatory modeling approach to identify problem perceptions, case-specific sustainability innovations as well as related implementation barriers, drivers and responsibilities; 2) a systematic review to identify supportive and impeding learning factors from the general literature that can complement case-specific factors; and 3) a method for the analysis and design of case-specific transition governance processes. Three case studies in Canada (topic: sustainable food systems), Cyprus (water-energy-food nexus) and Germany (sustainable heating supply) have been selected to test and iteratively develop the methodology described above. The results for each case study reveal that there are learning objects (i.e., learning requirements) in all learning contexts, which underscores the importance of multi-level learning in sustainability transitions, ranging from the individual to the group, organizational and policy levels. Actors have various opportunities to actively facilitate societal transformations towards sustainable development either directly through actions at their particular societal levels (i.e., context-internal learning) or indirectly through actions that influence learning at other societal levels. In fact, most of the learning factors require cooperation across learning contexts during the implementation process. The comparing of learning factors across case studies underline the importance of several factor categories, such as ‘physical a ‘disturbance or crisis’, ‘information and knowledge’. Of the 206 factors identified by stakeholders, 40 factors are case-specific and not contained in the general, review-based factor list. This underscores the value of participatory research, as general, top-down analyses might have overlooked these case-specific factors. The methodology presented in this dissertation allows for the identification and analysis of case-specific intervention points for sustainability transitions at multiple societal levels. The methodology furthermore permits the analysis of interplay between individual, group, organizational and policy actions, which is a first step towards their coordination. The focus on sustainability innovations links the broad topic of sustainability transitions to a set of opportunities for practical interventions and overcoming their implementation barriers. The methodology presented allows for the analysis and design of these interlinkages between learning contexts. While the methodology cannot provide any ‘silver bullets’ for inducing sustainability transitions, it is flexible enough to identify an appropriate abstraction level for analyzing and designing transition governance processes. The methodology developed in this doctoral research also provides several contributions for the development of participatory modeling methods in transition research. Thus, the participatory method supports an integrated analysis of barriers and drivers of sustainability innovations, and allows application in practice and education. The concepts and methods developed in this research project allow for reflection on transition governance processes from a systemic viewpoint. Experiences in the case studies underline the applicability of the concepts and methods developed for the analysis of case-specific transition governance processes. Despite substantial differences in the geographic location, culture and topics addressed, all case studies include promising sustainability innovations and the engagement of multiple actors in their implementation. The diversity and multitude of initiatives in the case study regions provides an optimistic outlook on future opportunities for large-scale sustainability transitions.