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Scenario modelling of the sustainable development goals under uncertainty

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journal contribution
posted on 2021-01-01, 00:00 authored by Enayat A. Moallemi, Lei Gao, Sibel Eker, Brett BryanBrett Bryan
Models are increasingly used to inform the transformation of human-natural systems towards a sustainable future, aligned with the United Nations Sustainable Development Goals (SDGs). However, the future uncertainty and complexity of alternative socioeconomic and climatic scenarios challenge the model-based analysis of sustainable development. Obtaining robust insights, which can remain valid under a larger diversity of plausible futures, requires a systematic processing of uncertainty and complexity not only in input assumptions, but also in the diversity of model structures that simulates the multisectoral dynamics of Earth and human interactions. Here, we quantify and explore the impacts of model uncertainty and structural complexity on the projection of global change scenarios for sustainable development. We implement the Shared Socioeconomic Pathways and the Representative Concentration Pathways in a feedback-rich, integrated assessment model of system dynamics. With our model’s broad scope for SDG analysis, we evaluate the impacts of these scenarios on the global trajectories of 16 sustainable development indicators related to food and agriculture, well-being, education, energy, economy, sustainable consumption, climate, and biodiversity conservation under uncertainty. The results show internally consistent (across sectors), yet quantitatively different (compared to other models) realisations of reference scenarios. They also demonstrate the sensitivity of sustainability indicators to reference global scenarios, driven by the complex and uncertain multisectoral dynamics that underlay the SDGs. These results highlight the importance of enumerating global scenarios and their uncertainty exploration with a diversity of models of different input assumptions and structures to capture a wider variety of future possibilities in planning for sustainability.




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