Systematic learning in water governance: insights from five local adaptive management projects for water quality innovation

Adaptive management has been proliferating since the 1970s as a policy approach for dealing with uncertainty in environmental governance through learning. Learning takes place through a cyclical approach of experimentation and (possible) adjustment. However, few empirical studies exist that cover full iterations of adaptive management cycles. We report on five adaptive management projects on water quality enhancement, of which four led to innovations in the small-scale management of waterways in northern Germany. We trace processes as well as outcomes, to identify factors affecting learning, environmental improvement, and the successful delivery of a project throughout a management cycle. Our findings point to a key difference between two kinds of uncertainty in the studied processes: ecological uncertainty (whether and how interventions will be effective in improving water quality) and what we term "social uncertainty" (how stakeholders will respond to interventions). We find that those managers performed better who addressed both kinds of uncertainty. Factors for dealing with social uncertainties were usually rather different than the ones linked to knowledge gain for the results in the rivers, and their acknowledgment was decisive for successful project delivery. On a conceptual level, our findings suggest that the model of a dual feedback cycle, including both types of uncertainties, allows for more clear-cut conceptual differentiation and empirical outcome measurement of adaptive management processes.