In this paper we argue that there is nothing intrinsically wrong with case studies or environmental modelling. But what is missing is the articulation of necessary complimentary measures (reflected in theory, method, models and techniques for data transformation and valorization) that have the potential to explain and then bridge the gaps between science and policy. Although scientists very often refer to use of multisectoral tools that include representations of multiple sectors in a single analytical platform, this approach has not been widely applied at regional and subregional scales to continuously strengthen feedback loops between data, management systems and policy and programme learning and evaluation outcomes. We point out that place-based observatories by systematically organizing linked databases, online learning tools and mixed methods through support for transdisciplinary research can support the development and pilot-testing of typologies of water–energy–food interactions thereby enhancing the potential of scientific modelling to inform robust monitoring of the Sustainable Development Goals (SDG's).
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Social Sciences(all)