5,712 research outputs found

    Assessment of Urban Water Infrastructure System Resilience

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    Urban water infrastructure systems are exposed to the impacts of various chronic and acute stressors such as climate change, population growth/decline, aging infrastructure, and extreme events (e.g., natural disasters). The ability and capacity of infrastructure systems to cope with the impacts of these stressors is characterized as resilience. Water utility agencies and infrastructure managers face significant challenges (due to deep uncertainty, funding constraints, lack of knowledge, etc.) to enhance the long-term resilience of their urban water infrastructure systems under the impacts of external stressors. To enable informed resilience planning and adaptation decisions, the present study adopted a complex system perspective to comprehensively assess the long-term resilience of water infrastructure systems. Through this perspective, different components of the complex water infrastructure system (i.e., physical infrastructures, human actors, external stressors) were captured, modeled, and analyzed using a simulation approach for theory development and exploratory assessment. This research conducted four interrelated studies focused on both supply and demand sides of the water infrastructure resilience. As aging water distribution infrastructures near the end of their useful lifespan, first two studies focused on the resilience of water distribution systems. The first study established a framework to understand the long-term resilience of water distribution infrastructure systems based on performance regimes and tipping point behaviors under various scenarios of renewal strategies, funding levels, and population changes. The second study, examined the long-term performance of dual water distribution networks, as an alternative infrastructure solution proposed for improving the resilience of water distribution systems, in comparison with the conventional singular networks. The third study was prompted to deal with the impacts of climate change on coastal water supply infrastructures. This study specifically, evaluated the influence of adaptation decision-making processes of utility agencies on the long-term resilience of water supply systems under the impacts of sea-level rise and saltwater intrusion. Finally, the fourth study focused on the evaluation of demand-side solutions to enhance the resilience of urban water infrastructure systems, where due to population growth, climate change, and other factors making water scarcer, the supply-side solutions may no longer be sufficient. The last study particularly analyzed the underlying mechanisms affecting the adoption of water conservation technology by households to uncover the potential for residential water demand reduction. Accordingly, four sets of important theoretical constructs related to long-term resilience of water infrastructure systems were identified from the analysis of simulated data: (i) the long-term performance regime of water distribution infrastructure system is shaped by its internal dynamics related to stressors-humans-infrastructure interactions; (ii) implementation of dual water distribution systems would improve the long-term performance (by decreasing water loss and energy loss by 28% and 80%, respectively) but with three times higher life-cycle costs; (iii) the state of nature (i.e., sea-level rise severity) is the most important determinant of coastal water supply infrastructure system resilience, regardless of the attributes of adaptation decisions; and (iv) households’ decision regarding the adoption of water conservation technology is driven mostly by income level and water pricing structure. The simulation results highlighted the importance and capabilities of the proposed frameworks in better understanding of water supply infrastructure system resilience. The insights of this research would also benefit water utilities, city planners, municipalities, and other stakeholders endeavoring to strengthen the resilience performance of water infrastructure systems. Progress in this domain improves the overall resilience of communities’ infrastructure systems to normal wear-and-tear and natural disasters alike

    Flexibility of multi-agent system models for rubber agroforest landscapes and social response to emerging reward mechanisms for ecosystem services in Sumatra, Indonesia

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    Payments for ecosystem services (PES) have been widely recognized as an innovative management approach to address both environment conservation and human welfare while serving as a policy instrument to deal with the ecosystem service (ES) trade-offs resulting from land-use/ cover change (LUCC). However, there is no solid understanding of how PES could affect the synergies and trade-offs among ES. This research focuses on the LUCC and its inherent ES trade-offs in the context of social-ecological systems (SES) that incorporates key feedbacks and processes, and explores the possible impacts of management regimes, i.e., PES schemes (e.g., eco-certification and reduced emissions from deforestation and degradation (REDD)). To address the complexity of this research, a multi-agent simulation (MAS) model (LB-LUDAS - Lubuk Beringin - Land Use DynAmics Simulator) was applied in which process-based decision-making sub-models were incorporated in the decision-making mechanism of agents. The model was developed to explore policy scenarios by quantifying the potential ES trade-offs resulting from the agents’ land-use choices and preferences. It was first implemented for the rubber agroforest landscape in Jambi Province (Sumatra), Indonesia. Species richness, carbon sequestration, opportunity costs, and decision processes such as PES adoption and future land-use preferences sub-models were incorporated to capture as much as possible the real SES of a rubber agroforest landscape. Three scenarios were simulated over a 20-year period, namely the PES scenario, the scenario land-use preference if supported by financial assistance/subsidies (SUB), and the current trend as the baseline scenario. From the simulations, the key findings show that there was a minimal land-cover change under the PES scenario, where an estimated 22% of the species richness in rubber agroforests could be conserved and 97% of the carbon emissions reduced compared to the baseline scenario. For the SUB scenario, an estimated 6% of the species richness could be conserved and 47% of the carbon emissions reduced. With regard to livelihoods, only under the PES scenario was wealth inequality reduced up to 50%. Regarding the return for land investment, the profitability of a land-use type depends considerably on each scenario; however, rubber agroforests would be highly profitable (20%) if a price premium were to be implemented under an eco-certification scheme. The main conclusions of this study are firstly, that PES schemes for rubber agroforests could offer synergies among carbon emission reduction, biodiversity and livelihoods, thus reducing the trade-offs resulting from possible land-use/cover change, and secondly that the LB-LUDAS model as an integrated and MAS model is a useful tool to capture the ES trade-offs as an emergent property of the dynamic social-ecological systems at the same time serving as a negotiation-support system tool to support the design of land-use policies. The use of process-based decision making in the LB-LUDAS model is recommended in order to incorporate intended decisions of agents in various situations. In this way, the triggers, options and temporal and spatial aspects of agents’ reactions are captured in a relatively realistic way.FlexibilitĂ€t von Multi-Agenten-Modellen fĂŒr Gummi-Agroforste-Landschaften und die soziale Reaktion auf die neu entstehenden Belohnungsmechanismen fĂŒr Ökosystemdienstleistungen in Sumatra, Indonesien Bezahlungen fĂŒr Ökosystemdienstleistungen (PES) sind weit verbreitet und anerkannt als ein Managementansatz sowohl fĂŒr den Umweltschutz als auch fĂŒr das menschliche Wohlbefinden. Gleichzeitig dienen sie als Politikinstrument zur Behandlung der Folgen (ES trade-offs) durch VerĂ€nderungen in der Landnutzung/-bedeckung (LUCC). Es gibt jedoch kein solides Wissen darĂŒber, wie sich PES auf die Synergien und trade-offs zwischen den ES auswirken könnten. Der Schwerpunkt dieser Studie liegt auf den LUCC und ihren inhĂ€renten ES trade-offs im Kontext von sozial-ökologischen Systemen (SES), die wichtige Feedbacks und Prozesse berĂŒcksichtigen. Die Studie untersucht die möglichen Auswirkungen von Managementregimen, d.h., PES-Systeme (z.B. Ökozertifizierung und reduzierte Emissionen von Entwaldung und Degradation (REDD)). Um die KomplexitĂ€t des Themas zu erfassen, wurde ein Multi-Agentensimulationsmodel (MAS; LB-LUDAS - Lubuk Beringin - Land Use DynAmics Simulator) eingesetzt, in dem prozessbasierte Entscheidungs-Submodelle in den Entscheidungsmechanismus der Agenten berĂŒcksichtigt werden. Das Modell wurde entwickelt, um verschiedene Szenarien durch die Quantifizierung der potentiellen ES trade-offs, die durch die Wahl bzw. Vorlieben der Agenten hinsichtlich der Landnutzung entstehen, zu untersuchen. Es wurde zuerst fĂŒr die Landschaften der Gummi-Agroforste in Jambi Provinz (Sumatra), Indonesien, eingesetzt. Sub-Modelle wie Artenvielfalt, Kohlenstoffspeicherung, OpportunitĂ€tskosten und Entscheidungsprozesse wie Anwendung von PES und zukĂŒnftige PrĂ€ferenzen wurden berĂŒcksichtigt, um so weit wie möglich die tatsĂ€chlichen SES von Gummi-Agroforsten zu erfassen. Drei Szenarien wurden ĂŒber eine Periode von 20 Jahren simuliert nĂ€mlich das PES-Szenario, das Szenario LandnutzungsprĂ€ferenz, wenn mit finanzieller UnterstĂŒtzung bzw. Subventionen (SUB), sowie der aktuelle Trend als Grundszenario. Die wichtigsten Ergebnisse der Simulationen zeigen eine minimale VerĂ€nderung der Landnutzung im PES-Szenario wobei ca. 22% der Artenvielfalt in den Gummi-Agroforsten erhalten und die Kohlenstoffemissionen um 97% reduziert werden konnten verglichen mit dem Grundszenario. Bei dem SUB-Szenario konnten ca. 6% der Artenvielfalt erhalten und die Kohlenstoffemissionen um 47% reduziert werden. Hinsichtlich der Lebensgrundlagen wurden nur beim PES-Szenario die Wohlstandsungleichheit um bis zu 50% reduziert. Bei den Renditen fĂŒr Investitionen in Land hĂ€ngt Wirtschaftlichkeit sehr stark vom Landnutzungstyp ab; Gummi-Agroforste wĂ€ren jedoch sehr profitabel (20%) bei einem Preisaufschlag in einem Ökozertifizierungsprogramm. Die wichtigsten Schlussfolgerungen dieser Untersuchung sind erstens, dass PES-Programme fĂŒr Gummi-Agroforste zu Synergien zwischen Reduzierung von Kohlenstoffemissionen und BiodiversitĂ€t sowie Lebensgrundlagen fĂŒhren und damit die trade-offs reduzieren, die durch mögliche VerĂ€nderungen in der Landnutzung/-bedeckung entstehen können und zweitens, dass das LB-LUDAS-Modell als integriertes sowie als MAS-Modell ein nĂŒtzliches Instrument darstellt, um die ES trade-offs als eine zu Tage tretende Eigenschaft der dynamischen sozialen-ökologischen Systemen zu erfassen. Gleichzeitig dient das Modell als Instrument zur UnterstĂŒtzung von Verhandlungen bei der Planung von Landnutzungsmaßnahmen. Der Einsatz prozessbasierter Entscheidungen im LB-LUDAS-Modell um geplante Entscheidungen von Agenten in verschiedenen Situationen zu berĂŒcksichtigen, wird empfohlen. Auf diese Art können die Auslöser, die Optionen sowie die zeitlichen und rĂ€umlichen Aspekte der Reaktionen der Agenten auf relativ realistische Weise erfasst werden

    From the Ground Up: A Complex Systems Approach to Climate Change Adaptation in Agriculture

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    Climate change presents an unprecedented challenge to global agriculture and food security. Small farms are especially vulnerable to the local impacts of large-scale drivers of change. Effective adaptation in agriculture requires working across scales, and geographic, political, and disciplinary boundaries to address barriers. I use elements of case study, agent-based modeling and serious games, to design a model of farmer decision-making using the sociocognitive framework of climate change adaptation. I examine how adaptation functions as a process, how complex dynamics influence farmer behavior, and how individual decisions influence collective behavior in response to climate change. This novel approach to adaptation research in agriculture examines the relationships between the contextual, compositional, and cognitive elements of the sociocognitive theory. The tools developed for this research have broad practical and theoretical future applications in climate adaptation research and policymaking. This dissertation is available in open access at AURA (https://aura.antioch.edu) and OhioLINK ETD Center (https://etd.ohiolink.edu)

    Representation of decision-making in European agricultural agent-based models

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    The use of agent-based modelling approaches in ex-post and ex-ante evaluations of agricultural policies has been progressively increasing over the last few years. There are now a sufficient number of models that it is worth taking stock of the way these models have been developed. Here, we review 20 agricultural agent-based models (ABM) addressing heterogeneous decision-making processes in the context of European agriculture. The goals of this review were to i) develop a framework describing aspects of farmers' decision-making that are relevant from a farm-systems perspective, ii) reveal the current state-of-the-art in representing farmers' decision-making in the European agricultural sector, and iii) provide a critical reflection of underdeveloped research areas and on future opportunities in modelling decision-making. To compare different approaches in modelling farmers' behaviour, we focused on the European agricultural sector, which presents a specific character with its family farms, its single market and the common agricultural policy (CAP). We identified several key properties of farmers' decision-making: the multi-output nature of production; the importance of non-agricultural activities; heterogeneous household and family characteristics; and the need for concurrent short- and long-term decision-making. These properties were then used to define levels and types of decision-making mechanisms to structure a literature review. We find most models are sophisticated in the representation of farm exit and entry decisions, as well as the representation of long-term decisions and the consideration of farming styles or types using farm typologies. Considerably fewer attempts to model farmers' emotions, values, learning, risk and uncertainty or social interactions occur in the different case studies. We conclude that there is considerable scope to improve diversity in representation of decision-making and the integration of social interactions in agricultural agent-based modelling approaches by combining existing modelling approaches and promoting model inter-comparisons. Thus, this review provides a valuable entry point for agent-based modellers, agricultural systems modellers and data driven social scientists for the re-use and sharing of model components, code and data. An intensified dialogue could fertilize more coordinated and purposeful combinations and comparisons of ABM and other modelling approaches as well as better reconciliation of empirical data and theoretical foundations, which ultimately are key to developing improved models of agricultural systems.Swiss National Science Foundatio

    Modelling and Simulation of Human-Environment Interactions

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    Computational models provide intelligent environmental decision support systems to understand how human decisions are shaped by, and contribute to changes in, the environment. These models provide essential tools to tackle the important issues raised by climate change, including migrations and conflicts due to resource scarcity (e.g., water resources), while accounting for the necessity of co-managing ecosystems across a population of stakeholders with diverse goals. Such socio-environmental systems are characterized by their complexity, which is reflected by an abundance of open questions. This book explores several of these open questions, based on the contributions from over 50 authors. While several books account for methodological developments in modeling socio-environmental systems, our book is unique in combining case studies, methodological innovations, and a holistic approach to training the next generation of modelers. One chapter covers the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation. In another chapter, we show that the benefits of simulations are not limited to managing complex eco-systems, as they can also serve an educational mission in teaching essential rules and thus improve systems thinking competencies in the broader population
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