Scaling the nexus: towards integrated frameworks for analysing water, energy and food

McGrane, S. J.; Acuto, M.; Artioli, F.; Chen, P.-Y.; Coomber, R.; Cottee, J.; Farr-Wharton, G.; Green, N.; Helfgott, A.; Larcom, S.; McCann, J. A.; O'Reilly, P.; Salmoral, G.; Scott, M.; Todman, Lindsay C.; van Gevelt, T.; Yan, X.

Scaling the nexus: towards integrated frameworks for analysing water, energy and food

2019

The emergence of the water-energy-food (WEF) nexus concept following the 2011 Bonn Nexus Conference has resulted in a change to the way we perceive our natural resources. Global pressures such as climate change, and population growth have highlighted the fragility of our WEF systems, necessitating integrated solutions across multiple scales and levels. Whilst a number of frameworks and analytical tools have been developed since 2011, a comprehensive WEF nexus tool remains elusive, hindered in part by our limited data and understanding of the interdependencies and connections across the WEF systems. To achieve this, the community of academics, practitioners and policy-makers invested in WEF nexus research are addressing several critical areas that currently remain as barriers. Firstly, the plurality of scales (e.g., spatial, temporal, institutional, jurisdictional) necessitates a more comprehensive effort to assess interdependencies between water, energy and food, from household to institutional and national levels. Secondly, and closely related to scale, a lack of available data often hinders our ability to quantify physical stocks and flows of resources. In this paper, we elucidate many of the challenges that have arisen across nexus research, including the impact of multiple scales in operation across the nexus, and concomitantly, what impact these scales have on data accessibility. We review some of the critical frameworks and tools that are applied by nexus researchers and discuss some of the steps required to develop from nexus thinking to an operationalizable concept, with a consistent focus on scale and data availability.

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