4.6 Article

Resilience Analysis Framework for a Water-Energy-Food Nexus System Under Climate Change

Journal

FRONTIERS IN ENVIRONMENTAL SCIENCE
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fenvs.2022.820125

Keywords

system resilience; engineering resilience; ecological resilience; sensitivity analysis; climate change; system dynamics modeling; causal loop diagrams; water-energy-food-climate nexus

Funding

  1. European Union's Horizon (2020) Research and Innovation Programme [1010003881]

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The article discusses the impact of climate change on water-energy-food security, presents a resilience analysis framework, and introduces a national case study of Greece. Parametric sensitivity analysis and system dynamics modeling are used to quantify system resilience, and two policies are tested to improve the resilience of the system.
Climate change impacts the water-energy-food security; given the complexities of interlinkages in the nexus system, these effects may become exacerbated when feedback loops magnify detrimental effects and create vicious cycles. Resilience is understood as the system's adaptive ability to maintain its functionality even when the system is being affected by a disturbance or shock; in WEF nexus systems, climate change impacts are considered disturbances/shocks and may affect the system in different ways, depending on its resilience. Future global challenges will severely affect all vital resources and threaten environmental resilience. In this article, we present a resilience analysis framework for a water-energy-food nexus system under climate change, and we identify how such systems can become more resilient with the implementation of policies. We showcase results in the national case study of Greece. Parametric sensitivity analysis for socioecological systems is performed to identify which parameter the model is the most sensitive to. The case study is based on the structure of a system dynamics model that maps sector-specific data from major national and international databases while causal loop diagrams and stock-and-flow diagrams are presented. Through engineering and ecological resilience metrics, we quantify system resilience and identify which policy renders the system more resilient in terms of how much perturbation it can absorb and how fast it bounces back to its original state, if at all. Two policies are tested, and the framework is implemented to identify which policy is the most beneficial for the system in terms of resilience.

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