Governance of Water-Energy-Food Nexus: A Social Network Analysis Approach to Understanding Agency Behaviour

  • Mathew KurianEmail author
  • Kent E. Portney
  • Gerhard Rappold
  • Bryce Hannibal
  • Solomon H. Gebrechorkos


Research seeks to treat each resource embedded in the nexus as connected to the other resources. This approach is unique from other natural resource research agendas where the primary focus is on system efficiencies or examinations of a single resource. The nexus by emphasizing trade-offs places a premium on coordination. From a governance perspective coordination is not limited to decisions involving finances and allocation of trained human resources among different agencies organized both vertically and horizontally within a multi-level governance framework. Coordination could also be extended to include uses of data between public agencies, private sector and individuals. Due to nexus interconnectivity, we suggest here that social network analysis (SNA) is an appropriate tool that can divulge and highlight the relational complexities that exist within the nexus and among stakeholders that work with the singular elements of the nexus. We suggest that in the cases of organisations with a high institutional capacity by means of expertise, resources, and other assets, the Water-Energy-Food (WEF) network will be highly connected between resource areas in the overall network. Two network tie characteristics—density and centrality—are particularly important to understand a critical mass of interests within a multi-level governance framework. The paper concludes by arguing for the organisation of data covering different dimensions of the Water-Energy-Food nexus through the mechanism of an observatory that could potentially improve our understanding of thresholds of environmental resource use and the incentives required for public agencies to act in support of sustainable development.


  1. ActionAid (2016) East Africa drought and food crisis—two years on|.
  2. Ansell C, Gash A (2008) Collaborative governance in theory and practice. J Public Adm Res Theor 18(4):543–71CrossRefGoogle Scholar
  3. Berardo R, Olivier T, Lavers A (2015) Focusing events and changes in ecologies of policy games: evidence from the Paraná River Delta. Rev Policy Res 32(4):443–464CrossRefGoogle Scholar
  4. Berardo R, Lubell M (2016) Understanding what shapes a polycentric governance system. Public Adm Rev 76(5):738–751CrossRefGoogle Scholar
  5. Berardo R, Scholz JT (2010) Self-organizing policy networks: risk, partner selection and cooperation in Estuaries. Am J Polit Sci 54(3):632–49CrossRefGoogle Scholar
  6. Bodin Ö, Crona BI (2009) The role of social networks in natural resource governance: what relational patterns make a difference? Glob Environ Change 19(3):366–374CrossRefGoogle Scholar
  7. Borgatti SP, Everett MG, Freeman LC (2002) Ucinet 6 for windows: software for social network analysisGoogle Scholar
  8. Borgatti SP, Everett MG, Johnson JC (2013) Analyzing social networks. Sage, Thousand Oaks, CAGoogle Scholar
  9. Chaney NW, Sheffield J, Villarini G, Wood EF (2014) Development of a high-resolution gridded daily meteorological dataset over Sub-Saharan Africa: spatial analysis of trends in climate extremes. J Clim 27(15):5815–35. Scholar
  10. FAO (2014) Adapting to climate change through land and water management in Eastern Africa. Food and Agricultural Organization of the United Nations and World Bank, Rome.
  11. Foran T (2015) Node and regime: interdisciplinary analysis of water-energy-food nexus in the Mekong region. Water Altern 8(1):675–694Google Scholar
  12. Funk C, Pete Peterson, Martin Landsfeld, Diego Pedreros, James Verdin, Shraddhanand Shukla, Gregory Husak, et al. 2015. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci Data 2, Article no. 150066. Scholar
  13. Jasny L, Lubell M (2015) Two-mode brokerage in Policy networks. Social Net 41:36–47CrossRefGoogle Scholar
  14. Krackhardt D (1992) The strength of strong ties: the importance of philos in organizations (pp 216–39). In: Nohria N, Eccles RG (eds) Networks and organizations: structure, form, and action. Boston, MA. Retrieved
  15. Kurian Mathew (2017) The water-energy-food Nexus: trade-offs, thresholds and transdisciplinary approaches to sustainable development. Environ Sci Policy 68:97–106CrossRefGoogle Scholar
  16. Kurian M, Veiga L, Boer R, Alabaster G (2016a) Wastewater reuse effectiveness index (WREI)—monitoring methodology for SDG target 6.3. UNU-FLORES, DresdenGoogle Scholar
  17. Kurian M, Ardakanian R, Veiga L, Meyer K (2016b) Resources, services and risks—how can data observatories bridge the science-policy divide in environmental governance. Springer, SwitzerlandCrossRefGoogle Scholar
  18. Leach WD, Pelkey NW, Sabatier PA (2002) Stakeholder partnerships as collaborative policymaking: evaluation criteria applied to watershed management in California and Washington. J Policy Anal Manage 21(4):645–670CrossRefGoogle Scholar
  19. Lubell M (2013) Governing forum complexity: the ecology of games framework. Policy Stud J 41(3):537–59CrossRefGoogle Scholar
  20. Lubell M, Scholz J, Berardo R, Robins G (2012) Testing policy theory with statistical models of networks. Policy Stud J 40(3):351–374CrossRefGoogle Scholar
  21. Lubell M, Henry AD, McCoy M (2010) Collaborative institutions in an ecology of games. Am J Polit Sci 54(2):287–300CrossRefGoogle Scholar
  22. Mannschatz T, Buchroithner M, Hulsmann S (2015) Visualization of water services in Africa: data applications for water governance. In: Kurian M, Ardakanian R (eds) Governing the Nexus—water, soil and waste resources considering global change. Springer, DordrechtGoogle Scholar
  23. Mannschatz T, Wolf T, Hülsmann S (2016) Nexus tools platform: web-based comparison of modelling tools for analysis of water-soil-waste Nexus. Environ Model Softw 76:137–53. Scholar
  24. Marwell G, Oliver Pamela (1993) The critical mass in collective action. Cambridge University Press, New YorkCrossRefGoogle Scholar
  25. Mason P (2016) Postcapitalism—a guide to our future. Penguin, LondonGoogle Scholar
  26. Mastrandrea KJ, Mach, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 1199–1265.
  27. Mewhirter J, Berardo R, Lubell M (2017) Policy influence across multiple forums in complex policy networks. Paper delivered at the 2017 Meetings of the Southern Political Science Association, New Orleans, LA, January 13Google Scholar
  28. Mochizuki J, Magnuszewski P, Linnerooth-Bayer J (2018) Games for aiding stakeholder deliberation on Nexus policy issues. In: Hülsmann S, Ardakanian R (eds) Managing water, soil and waste resources to achieve sustainable development goals: monitoring and implementation of integrated resources managementGoogle Scholar
  29. Niang I, Ruppel OC, Abdrabo MA, Essel A, Lennard C, Padgham J, Urquhart P (2014) Africa. In: Climate change 2014: impacts, adaptation, and vulnerability. Part B: regional aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change [Barros VR, Field CB, Dokken DJ, MD]Google Scholar
  30. Ostrom E (1990) Governing the commons—the evolution of institutions for collective action. Cambridge University Press, New YorkCrossRefGoogle Scholar
  31. Pikaar I, Matassa S, Rabaey K, Laycock B, Boon N, Verstraete W (2018) The urgent need to re-engineer nitrogen-efficient food production for the planet. In: Hülsmann S, Ardakanian R (eds) Managing water, soil and waste resources to achieve sustainable development goals: monitoring and implementation of integrated resources managementGoogle Scholar
  32. Rockstrom J, Steffen W, Noone K, Asa Persson F, Chapin S, Lambin EF, Lenton TM, Scheffer M, Folke C, Schellnhuber HJ, Nykvist B, de Wit CA, Hughes T, van der Leeuw S, Rodhe H, Sorlin S, Snyder PK, Costanza R, Svedin U, Falkenmark M, Karlberg L, Corell RW, Fabry VJ, Hansen J, Walker B, Liverman D, Richardson K, Crutzen P, Foley JA (2009) A safe operating space for humanity. Nature 461(7263):472–475CrossRefGoogle Scholar
  33. R Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
  34. Scholz JT, Berardo R, Kile B (2008) Do networks solve collective action problems? credibility, search, and collaboration. J Polit 70(2):393–406CrossRefGoogle Scholar
  35. Schulzweida U, Kornblueh L, Quast R (2009) CDO—Climate data operators-project management service (Version 1.4.1). Max Planck Institute for Meteorology, Hamburg, Germany.
  36. Scott CA, Kurian M, Wescoat JL Jr (2015) The water-energy-food Nexus: enhancing adaptive capacity to complex global challenges. In: Kurian M, Ardakanian R (eds) Governing the Nexus: water, soil and waste resources considering global change. Springer International, Cham, SwitzerlandGoogle Scholar
  37. Sheffield J, Goteti G, Wood EF (2006) Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J Clim 19(13):3088–3111. Scholar
  38. Wilby RL, Yu D (2013) Rainfall and temperature estimation for a data sparse region. Hydrol Earth Syst Sci 17(10):3937–55. Scholar

Copyright information

© United Nations University Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES) 2018

Authors and Affiliations

  • Mathew Kurian
    • 1
    Email author
  • Kent E. Portney
    • 2
  • Gerhard Rappold
    • 3
  • Bryce Hannibal
    • 2
  • Solomon H. Gebrechorkos
    • 1
  1. 1.United Nations University, Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES)DresdenGermany
  2. 2.Texas A&M UniversityCollege StationUSA
  3. 3.GIZBonn and EschbornGermany

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