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Systems Analysis to Promote Frames and Mental Models for Sustainable Water Management
Published: 01 November 2013 by MDPI in The 3rd World Sustainability Forum session Sustainable Development Policy, Practice and Education
Abstract: The water sector has experienced numerous failures in projects aiming at sustainable development and has seen some, but less numerous, examples of successes. However, the most striking observation is the near universal failure to learn from these examples. Somehow, scientists and managers have allowed the indications of new approaches and opportunities go undetected because they did not fit with their mindsets or perceptual apparatus.We discuss some of the mental frames that have hampered the progress towards sustainable development by creating confusion and inconsistency in the interpretation of sustainable development concepts. We analyze where these frames come from, who is promoting or defending them, and what can be done to change these frames in ways that are more in line with the basic tenets of sustainable development. We conclude that most sustainability initiatives have failed because the environment and development were not properly brought together. The “environment” is where we live and “development” is what we all do in attempting to improve our lot within that abode. The two are unseparable (Our Common Future). Thus, there is a need to draw on diverse disciplinary perspectives and to cut across sectoral boundaries to counter the monovalent approaches that have dominated mainstream enquiry and practice. To that end, we discuss how systems analysis can help produce adequate mental models and enabling frameworks for process changes. These frameworks should define general objectives and means of verification of progress without specifying uniform approaches and activities. Systems analysis is also a methodology that can help make sure that problems posed are adequately defined and dismiss biased goal formulations stemming from twisted frames imposed by dominant actors or “solution-oriented approaches.