Rainwater Harvesting and Social Networks: Visualising Interactions for Niche Governance, Resilience and Sustainability
Ward, SL; butler, D
Date: 11 November 2016
Journal
Water
Publisher
MDPI
Publisher DOI
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Abstract
Visualising interactions across urban water systems to explore transition and change processes requires the development of methods and models at different scales. This paper contributes a model representing the network interactions of rainwater harvesting (RWH) infrastructure innovators and other organisations in the UK RWH niche to ...
Visualising interactions across urban water systems to explore transition and change processes requires the development of methods and models at different scales. This paper contributes a model representing the network interactions of rainwater harvesting (RWH) infrastructure innovators and other organisations in the UK RWH niche to identify how resilience and sustainability feature within niche governance in practice. The RWH network interaction model was constructed using a modified participatory social network analysis (SNA). The SNA was further analysed through the application of a two-part analytical framework based on niche management and the safe, resilient and sustainable (‘Safe and SuRe’) framework. Weak interactions between some RWH infrastructure innovators and other organisations highlighted reliance on a limited number of persuaders to influence the regime and landscape, which were underrepresented. Features from niche creation and management were exhibited by the RWH network interaction model, though some observed characteristics were not represented. Additional Safe and SuRe features were identified covering diverse innovation, responsivity, no protection, unconverged expectations, primary influencers, polycentric or adaptive governance and multiple learning-types. These features enable RWH infrastructure innovators and other organisations to reflect on improving resilience and sustainability, though further research in other sectors would be useful to verify and validate observation of the seven features.
Engineering
Faculty of Environment, Science and Economy
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