Governance models for nature-based solutions: Seventeen cases from Germany

Abstract

Nature-based solutions (NBS) for mitigating climate change are gaining popularity. The number of NBS is increasing, but research gaps still exist at the governance level. The objectives of this paper are (i) to give an overview of the implemented NBS for flood risk management and mitigation in Germany, (ii) to identify governance models that are applied, and (iii) to explore the differences between these models. The results of a hierarchical clustering procedure and a qualitative analysis show that while no one-size-fits-all governance model exists, polycentricism is an important commonality between the projects. The study concludes by highlighting the need for further research on traditional governance model reconversion and paradigm changes. We expect the findings to identify what has worked in the past, as well as what is important for the implementation of NBS for flood risk management in future projects.

Keywords: Financing instruments; Flood risk mitigation; Institutional structures; Polycentric governance; River Management; Stakeholder participation.

Fig. 1

Methodology outlining the analytical framework of the case study

Fig. 2

Location of the selected case sites

Fig. 3

Overview of cases. a Case number per decision level as framing organizational structure; b box plot of financing costs (excluding outliers); c land transactions for the implementation of NBS on land, riverbank, and river locations; d number of financing sources

Fig. 4

Cluster dendrogram obtained through hierarchical clustering of cases using the Gower distance as a dissimilarity measure and complete linkage criterion to reveal similarity of cases, i.e., common occurrences of predictor factors

Fig. 5

Map of individuals along the first three dimensions. The color of the cases indicates the factor loading on the third component, i.e., blue individuals have negative loads on the third principal component, whereas red individuals load highly on said dimension

Fig. 6

Cluster solution obtained through the hierarchical clustering of principal components, suggesting four clusters as the optimal number of groups

Fig. 7

Simple visualization of the network of actors for each case. Each dot correspond to an actor and lines correspond to cooperative exchange to design NBS. Public actors are colored in blue, private actors are colored in orange, NGOs are colored in green, and civil society actors are colored in yellow. The coordinating actor when known is indicated with the symbol of a box