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.

Full text

NATURE-BASED SOLUTIONS IN RIVER LANDSCAPES
Governance models for nature-based solutions: Seventeen cases
from Germany
Aude Zingraff-Hamed , Frank Hu
¨esker, Christian Albert,
Mario Brillinger, Joshua Huang, Gerd Lupp, Sebastian Scheuer,
Mareen Schla
¨tel, Barbara Schro
¨ter
Received: 31 March 2020 / Revised: 24 June 2020 / Accepted: 6 October 2020
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
INTRODUCTION
Change in climate patterns cause the increase of extreme
hydro-meteorological events which results in more floods
and droughts (Beniston 2007; De Paola et al. 2018;EC
2020). While flooding is a natural process that is essential
for biological health and riverine functions (Junk et al.
1989), it also represents one of the most common natural
hazards that lead to catastrophes in Europe (EEA 2016).
Floods have caused not only damages and disruptions, but
also various health effects including deaths, injuries, poor
sanitation, and poor water quality (Hajat et al. 2005; Doocy
et al. 2013). Hydro-meteorological experts estimate that
climate change may induce more flood risk due to an
increase in the intensity and frequency of extreme weather
events (EEA 2016). Annual monetary damages from
flooding in Europe is expected to rise from 6 billion to
about 108 billion USD by 2080 if no further prevention and
adaptation measures are implemented (EC 2014).
To address growing flooding risk and related impacts,
nature-based solutions (NBS) are becoming more popular
as an effective complement or partially replacement of
conventional technical approaches such as static flood
protection infrastructures (UN 2018). The benefits of intact
ecosystems is since early twenty-first century recognized
(Cohen-Shacham et al. 2016) and some concepts such as
‘‘more room for the river’’ in France, the Netherlands, and
Germany acknowledged the benefits of dynamic environ-
mental processes. However, in the past two decades, the
implementation of ecosystem-based management has
become more popular worldwide, and the need for con-
sistent terminology has resulted in the use of the term NBS.
NBS can consist of different levels of natural components
(Eggermont et al. 2015). For flood risk mitigation, exam-
ples of NBS include providing more space for rivers, e.g.,
Nesttunvassdraget in Norway (CoB 2007), revitalizing
floodplains, e.g., Grand Park Garonne in France (Van de
Kreek and Etienne 2012) establishing green infrastructure
in cities, e.g., The Green Ring, Antwerpen in Belgium
(Haine 2014), and implementing decentralized rainwater
management, e.g., Rewitalizacja rzeki Białej in Poland
(Sadowska-Dubicka 2015). NBS are defined as ‘‘actions
which are inspired by, supported by or copied from nature’’
Electronic supplementary material The online version of this
article (https://doi.org/10.1007/s13280-020-01412-x) contains sup-
plementary material, which is available to authorized users.
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https://doi.org/10.1007/s13280-020-01412-x

(EC 2015b), or more specifically, actions that (i) alleviate a
well-defined societal challenge, (ii) utilize ecosystem pro-
cesses, and (iii) are embedded within viable governance
models (Albert et al. 2019). Governance models are ideal
governance types explaining the interrelation of different
actors and institutions in the context of rules and rule-
making systems to coordinate interdependencies and hier-
archical market and community management (Wamsler
et al. 2017).
The concept of NBS has recently gained attention in
science and public policy (Nessho
¨ver et al. 2017; Frant-
zeskaki et al. 2019) following its introduction by the
International Union for Conservation of Nature (Cohen-
Shacham et al. 2016,2019) and the European Union (EU).
A large number of long-term research projects have
recently been funded (EC 2015a,b), such as Physicos
1
and
ReConect
2
. A common strategy of those projects is to
stimulate transdisciplinary research and to optimize and
upscale pilot solutions to other sites while financially
supporting implementation and providing governance
support to enhance collaborative planning. Increased
efforts have been undertaken recently to document and
synthesize cases of NBS application in online databases
(e.g., Oppla
3
). They aim to cross-fertilize and are useful for
extracting technical and societal knowledge from success
stories and cases that are recognized as good practice.
Unfortunately, the number of NBS is still low and
implementations are often slowed down by barriers in
governance (Kabisch et al. 2016; Ershad Sarabi et al.
2019). This indicates that investigating governance models
may be a key to learning about more effective NBS
implementation. Presently, there is little comparative
research on NBS governance. Furthermore, because of
different policy frameworks and local societal challenges,
comparison and upscaling of research results are very
limited (exception Martin 2019). Study showed that dif-
ferent water governance culture exist between the EU
countries and that while EU directives highly influence the
EU member policy, its incorporation in national law and its
implementation vary between the countries and cause bias
in regional governance comparison (Zingraff-Hamed et al.
2017b). Governance models have been mostly investigated
in theoretical terms (Kooiman 2003; Treib et al. 2007), in
the context of environmental policy (Arnouts et al. 2012),
governance of ecosystem services (Vatn 2010; Schro
¨ter
et al. 2019), and water governance (Pahl-Wostl
2015,2019), but not in the context of NBS and not in a
systematic way.
Consequently, our research question is as follows:
Which governance models led to NBS implementation for
flood risk management and mitigation? Specifically, our
objectives are (i) to give an overview of the implemented
NBS for mitigating flood risk in Germany, focusing on
their governance models, (ii) to identify governance mod-
els that are applied in implemented cases, and (iii) to
explore the differences between the models that are
applied, in order to discuss future water governance chal-
lenges and to formulate recommendations for further
implementation of NBS. In order to investigate the
implementation of NBS in more detail from a governance
perspective while avoiding comparison bias caused by
policy variability, we decided to conduct an analysis that
focused on Germany. As a federal state, Germany is
characterized by a hierarchical share of competencies and
state governments of the 16 states are responsible for
policy implementation (Ja
¨nicke et al. 2001; Schroeter
2018). The state governments have much flexibility in the
NBS planning process making Germany an interesting field
for investigation of the design and implementation of NBS
under different regional governance models (e.g., Newig
et al. 2016).The results from our analysis are expected to
give insights for implementing NBS in Germany and all
around the globe.
MATERIALS AND METHODS
The methodology that we used in our analytical framework
consists of the identification of predictor variables for the
identification of key governance features, case selection
and data collection, and the subsequent analysis of cases
related to key governance features and their interpretation
(Fig. 1).
Selection of predictors
To identify relevant variables for the governance analysis,
we first identified and reviewed relevant literature. A pre-
liminary list of variables was discussed during a workshop
in February 2019 with seven NBS governance researchers
from PlanSmart, Rivercare, Phusicos and ReConect. This
result of this workshop was a list of twelve governance
features, from which six were specifically selected (fram-
ing and implementing organizational structures, project
coordination, participation level, institutional setting,
financing model, and property rights constellation) because
of their importance and potential for further analysis. In a
second workshop, the working group further detailed the
six selected governance features and categorized them by a
number of possible predictor variables. For each variable, a
characteristic question was formulated to simplify the
1
www.phusicos.eu.
2
www.reconect.eu.
3
https://oppla.eu/case-study-finder.
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subsequent data collection. For most variables, we defined
a selection of qualitative and quantitative list of modalities
(Table S1).
Case selection and data collection
We identified successfully implemented NBS for flood risk
mitigation in Germany by querying existing NBS databases
developed by several EU funded research projects in order
to document the best practices of NBS implementation. An
online search (June 2019, terms applied: ‘‘Nature-based
solutions’’ AND ‘‘database’’) identified 59 relevant NBS
databases. Then, they were filtered for German NBS for
flood mitigation. We added to the selection German cases
of the ongoing EU Horizon 2020 funded research projects.
Then, we screened the results to identify cases with
available data on governance. Cases without information or
cases with insufficient information were excluded. Then,
we screened the 28 remaining cases in the form of a
qualitative content analysis (Mayring 2007) on project
documentation, related press releases, project descriptions,
case website contents, publications of scientific monitoring
and articles available online. If information for few vari-
ables could not be found online, we contacted the person in
charge for the respective projects for the missing infor-
mation. For two cases, a full telephone interview was
needed to gather the requested information. For ten cases,
information could not be collected because either staff
turnover did not allow us to contact the person in charge of
the project, and the staff was not able to provide the nec-
essary information or we were not able to reach a person in
charge of the project by e-mail or phone. 17 cases (Fig. 2
and Table 1) could be fully documented for analysis and
interpretation.
Data analysis and interpretation
The collected project data were transferred into a spread-
sheet and prepared for statistical analysis by coding vari-
ables to numeric values (Table S1). Variables for which
there was no information found were excluded from the
analysis. The three variables that were excluded were
coordination procedures, exchange platforms to support the
participatory process, and participation process intensity
Fig. 1 Methodology outlining the analytical framework of the case study
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and frequency. The codified data set was then assessed by
applying exploratory multivariate data analysis using R
version 3.6.2 in order to identify patterns and similarities
across the cases (p\0.05).
First, an agglomerative bottom-up hierarchical cluster-
ing algorithm was used for an initial identification of
groups of similar cases. Hierarchical clustering was chosen
as it is commonly considered suitable for smaller sample
sizes. The dissimilarity matrix for clustering of cases is
computed as the Gower distance metric (Gower 1971)
which is suitable for mixed-type (categorial and numeric)
data (Maechler et al. 2019). The complete linkage criterion
was applied.
Then, a Multiple Correspondence Analysis (MCA) was
applied to uncover the underlying structure of the data, i.e.,
the combinations of, and association between factors that
govern the dissimilarity of cases in the groups identified
and to subsequently describe and refine them. MCA is well
suited for the determination of associations between cate-
gorial data (Greenacre 2006; Husson et al. 2017). MCA is
commonly used for the identification of groups of indi-
viduals with similar profiles, e.g., in answer patterns of
surveys, as well as to elicit associations between variable
categories. The MCA was applied to the full data set. The
categorical variables were included as explanatory vari-
ables, and numerical variables were included as supple-
mentary information. The first three principal components
chosen cumulatively account for about 40% of the variance
in the data. The first component alone accounts for about
15% of variance. The second and third dimension, account
for about 13.2% and 11.6%, respectively.
Next, in order to refine the initial cluster findings, the
cases were subsequently clustered using hierarchical clus-
tering on principal components (HCPC) (Le et al. 2008)
using k-means method to allow agglomerative clustering of
multivariate data with different metric and structured into
themes (Husson et al. 2017). Thus, the most descriptive
predictors were identified for each cluster of governance
models. Finally, the identified types of governance models
were qualitatively compared to existing types of gover-
nance models defined in the literature.
RESULTS
The 17 cases (Fig. 2and Table 1) showed a broad spectrum
of NBS ranging from river restoration to green roofs. Only
one of the NBS served a single goal, while the rest had
multiple purposes. More than the half of the projects were
in the framework of city governments (9 of 17 cases), but
most of the NBS resulted from a cross-sectorial decision
process (12 of 17 cases). Most of the projects have been
implemented under the lead of the city (N= 7) or regional
(N= 6) government. Information on project costs were
Fig. 2 Location of the selected case sites
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Table 1 Overview of the selected case sites
Full Title (including location) Short Title (for
figures and
tables)
Year Cost
(USD)
Description
Polder Management in Altenheim, Baden-
Wuertemberg
Polder
Management
1987 773
185
Project improved the riverine ecological functionality
and created floodable space dedicated to recreational
uses. Implemented measures included floodplain
restoration and management, the restoration and
reconnection of seasonal streams, the reconnection of
oxbows, and the implementation of forest riparian
buffers. Challenging issues were forest management,
rising groundwater levels and potential increase of
mosquito population
Ruhr River Restoration in Binnerfeld,
Arnsberg-Neheim, North Rhine-Westphalia
Ruhr
Restoration
2006–2011 1 215
005
Project was implemented on a total river length of
4.5 km to stimulate river dynamics, to improve its
ecological status and structural diversity as well as
flood protection. Measures included the removal of
bank fixation to initiate bank-side erosion, the
creation of flood-prone areas, the widening of the
river bed, the creation of side arms, the restructuring
of the river bed and banks by sediment addition and
the placement of large pieces of wood
Lahn River Restoration in Co
¨lbe, Hesse Lahn
Restoration
2000 – Project intended to improve the river hydro-
morphological status and functions by removing bank
fixation, initiating bank-side erosion, creating side
arms and restructuring of river bed and banks
Lech River Restoration in Donauwo
¨rth,
Augsburg, Bavaria
Lech
Restoration
Since 2013 966
481
The project intends to improve the ecological status and
functions of the river Lech from the south of
Augsburg to the mouth of the river. The regional
water management authority in charge uses a Living
Lab approach to include various stakeholders and
citizens in the development of suitable and widely
accepted solutions
‘Living Lab Deusenberg to the Huckarde’ in
Dortmund, North Rhine-Westphalia
Emscher
Corridor
2018–2023 1 300
055
Besides creating green infrastructure with multiple
benefits, one central aspect of this project is also rain
water management and reducing rainwater runoff.
The project includes community-based urban farms
and gardens, food forests, a permaculture orchard and
the introduction of pollinator friendly plants using a
Living Lab approach and involving citizens for
monitoring
Wetland Restoration at Duemmer Lake,
Osnabru
¨ck, Lower-Saxony
Weser
Restoration
2007–2012 3 424
105
The wetlands were restored due to the European
Development Fund in order to address the Habitats
Directive, and Birds Directive. Measures
implemented in 2007 and 2012 included the
restoration of meadows and pastures, reduced tillage,
and a reduced stocking density. A wide variety of
stakeholders were involved in the implementation
process, ranging from nature conservation agencies
and NGO’s, as well as water managers to local
farmers
Lippe Floodplain Restoration in Klostermersch
Lippstadt, North Rhine-Westphalia
Lippe
Restoration
1991–1997 2 209
100
Project intended to stop incision of the river and to
improve the ecological status of the river. Starting in
1991, the intensity of the land use was gradually
reduced. Fortified embankments were lifted and the
river was broadened to 42 m to permit natural
dynamics. To stimulate the development of rich
structured half-open floodplain landscapes, grazing
with Heck cattle was introduced. Restoration
measures were discussed with different interest
groups and private land owners were invited to
participate
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Table 1 continued
Full Title (including location) Short Title (for
figures and
tables)
Year Cost
(USD)
Description
Spree River Restoration at
Mo
¨nchwinkel Gru
¨nheide, Brandenburg
Spree
Restoration
2013 1 855
644
Project aimed to stabilize the riverbed and improve
riverine ecological status. Side arm meanders were
reconnected to the river to slow down flows, reduce
incision and enhance the ecological qualities of the
river. The project was coordinated by the state
involving interest groups and NGOs. The renaturation
lead to intense controversies, as local land owners
and residents were affected by rising water levels and
feared damages caused by more frequent flooding
events and accumulation of sediment in the river
‘Nature in Grey Zones’ in Duisburg (North
Rhine-Westphalia), Erfurt ( Thuringia) and
Wiesloch ( Baden-Wuertemberg)
Desealing cities 2013–2016 703
598
Project encourages land owners, e.g., companies and
private persons to green up their paved areas in three
case study cities to enhance biodiversity and to
improve rain water management. Together with a
central coordination point and citizen foundations,
private companies and land owners as local partners,
the three pilot cities of Erfurt, Wiesloch and
Duisburg, redesigned paved areas to natural green
spaces
Erft River Restoration in Weilerswist, North
Rhine-Westphalia
Erft Restoration 2002–2009 791
962
To develop a structure-rich, ecologically permeable
stretch of the river with regularly flooded meadows
and a high potential for self-development, the dam
has been removed and groynes have been built in the
river bed to add morphological diversity and initiate
lateral erosion
Green Roof Strategy in Hamburg Green Roofs 2014–2019 3 313
650
In the climate change adaption plan, the green roof
strategy is part of the ‘‘Urban and landscape
planning’’ action field for climate friendly urban
development but also for rain water management.
The project subsidizes greening of roofs for at least
70% of both the new buildings and existing
suitable roofs
Inner-City-Discharge Program in Hamburg Runoff Control 2009 - Two main sewers were rehabilitated to reduce discharge
and overflows caused by heavy rain to urban water
bodies. The program was part of a project on
integrated stormwater management for the city of
Hamburg
‘Stream Action Day’ in Hamburg Stream
Restoration
2006 2507 Stream restoration measures were carried out on a few
streams such as the Osterbeek (220 m section) and
the Middle Bille (150 m section) to implement the
Water Framework Directive. The morphology of the
river bed and embankments were improved to
upgrade the watercourse structure and thus create
habitats for typical flora and fauna for this location
Flood Protection and Nature Conservation at
Polder Holter-Hammrich, Leer, Lower-
Saxony
Green Polders 2008–2011 13 917
330
In order to combine nature conservation and flood
protection, various measures were implemented, e.g.,
dike reinforcement, construction of a new polder
canal, conversion to extensive agricultural use and
creation of wet shallow water zones
Elbe Dyke Relocation in Lenzen, Brandenburg Dyke
Relocation
2002–2011 14 359
150
In this project, a dike was relocated, reconnecting the
river to the floodplains and afforestation of a
floodplain was accomplished. The biosphere reserve
‘‘Flusslandschaft Elbe-Brandenburg’’ initiated the
project and coordinated stakeholders participation
Cold Air Corridors in Stuttgart, Baden-
Wuertemberg
Green
Infrastructure
– - This project created green infrastructure corridors to
reduce runoff, decrease heat waves and to purify
urban air. NGOs were involved in planning processes
by legal binding consultation procedures
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available for 15 NBS, which totaled to approximately 1.6
million USD (Fig. 3). 70% of the NBS received money
from multiple sources (12 of 17), and most of them were
funded by public subsidies (e.g., European Agricultural
Fund for Rural Development) (15 of 17). 65% of the pro-
jects we studied (11 of 17) have been implemented outside
of floodplains to reduce runoff, e.g., green roofs. Only 60%
of the projects required land acquisition from the private
sector. Four projects included measures implemented either
in the riverbed and at the riverbank or in the wider sur-
rounding landscape.
The initial assessment of case similarity based on the
hierarchical cluster analysis computed from the Gower
dissimilarity matrix (Fig. 4) indicated one isolated case
(e.g., Desealing cities) and the following similar cases
(e.g., Lahn Restoration and stream restoration).
The MCA (Fig. 5) distributed the cases in the three-
dimensional space that is spanned by the first three prin-
cipal components (Table 2) and further described by case
typology. In particular, MCA results showed that runoff
control, green roofs, and green infrastructure form a group
that was negatively loaded in the first dimension, positively
loaded in the second component, and negatively loaded in
the third dimension. Furthermore, the results suggested that
stream restoration, Lahn Restoration, and desealing cities
were loaded distinctively high in the third dimension,
which means that they were characterized by entities
smaller than municipalities as the dominant decision level
in implementation and participation, and high participation
levels such as in co-decision-making and co-design. This
exception appears to be in line with the hierarchical cluster
analysis that identified the Lahn Restoration, and stream
restoration as comparatively similar to each other but rather
different to the remaining cases. This is also the case for
desealing cities.
The HCPC cluster algorithm suggests a four-cluster
solution (Fig. 6and Table 3):
The type 1 cluster (‘‘Cooperation and Incitation’’) con-
tains runoff control, green roofs, and e green infrastructure.
All of these cases are at least partly funded by the city
government, but only half of the cases funded by the city
government are in the type 1 cluster. None of the type 1
cases implemented measures at the river bank. The most
representative case is green infrastructure, as represented in
Fig. 6by the closeness of this item to the gravity center of
the cluster. The stakeholder analysis (Fig. 7) showed the
importance of the public–private cooperation to design and
implement the NBS. Nevertheless, the planning process
still resulted from a central decision center. The mean
project cost of the type 1 cluster was 48 600 200 USD.
The type 2 cluster (‘‘Co-design’’) is the biggest cluster
and is composed of the Spree Restoration, polder man-
agement, the Lech Restoration, the Erft Restoration, the
Ruhr Restoration, the Isar Restoration, the Lippe Restora-
tion, and the Emscher Corridor. All these projects except
the Emscher Corridor implemented measures in the riv-
erbed, and these projects make up 80% of all the river
restoration projects. All of the projects benefited from
already having some land available for use since the state
or municipality that owned the land required for NBS
implementation was also the project leader. There were a
few instances where some land acquisition was still nee-
ded. 87.5% of projects in the type 2 cluster were funded by
regional agencies. All the cases that used co-design as
participatory forms are type 2 projects. The cluster is best
characterized by the Erft Restoration and least character-
ized by the Lippe Restoration. The stakeholder analysis
(Fig. 7) showed that a great diversity of actors from the
public, private, civil society, and NGO categories were
participating in the design and implementation of the
solution. The type 2 cases are the most expensive cases
with a mean cost of 187 773 500 USD. This is more than
500 times more expensive than type 3 projects.
The type 3 cluster (‘‘Citizen Power’’) is composed of the
Lahn Restoration, The Stream Action Day in Hamburg, and
desealing cities. The case closest to the cluster center is the
Lahn Restoration. The characteristics of this cluster are the
decision levels of implementation and participation that are
Table 1 continued
Full Title (including location) Short Title (for
figures and
tables)
Year Cost
(USD)
Description
Isar River Restoration in Munich, Bavaria Isar Restoration 2000–2011 38 659
250
Intensive collaborative planning between numerous
stakeholders and a large public participation process
lead to new life for the Isar project. It had multiple
goals including the improvement of the ecological
status of the river, the decrease of the flood risk, and
the improvement of the riverscape and recreational
potential
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composed of entities smaller than municipalities. The
funding was mainlyfrom private contributions. No land
acquisition is required. The stakeholder analysis (Fig. 7)
showed the importance of civil society and NGOs. The
type 3 cases are the cheapest with a mean cost of 353 456
USD.
The type 4 cluster (‘‘Top-Down’’) is composed of the
Weser Restoration, the Flood Protection and Nature
Conservation at the Holter-Hammrich Polder, and dyke
relocation with wetland restoration being the most char-
acteristic case. All of the projects are decided by the EU
and funded by both the EU and the state. The implemen-
tation requires land acquisition from private owners. The
stakeholder analysis (Fig. 7) showed the dominance of the
public component. The mean cost of type 4 projects were
10 603 680 USD.
Fig. 3 Overview of cases. aCase number per decision level as framing organizational structure; bbox plot of financing costs (excluding
outliers); cland transactions for the implementation of NBS on land, riverbank, and river locations; dnumber of financing sources
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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
Table 2 Description of the 5 first principal components of the first three dimensions of the MCA (at p \0.05)
Variable Modality R2 Estimate
1st Dimension
Institutional setting of the project……interplay mechanisms 0.68 0.80
Financing source ……NGO 0.53 0.56
Implementation at the level of ……the state 0.67 0.85
Participation in the decision at the level of. …the state 0.66 0.84
Lead coordinating actor ……the state 0.63 0.68
Property rights ……other than state or municipality 0.43 0.34
2nd Dimension
Financing source ……regional funds 0.63 0.37
Land transactions……are not necessary 0.49 0.33
Decision level of the implementation ……smaller entity than municipality 0.63 0.58
Participation of the decision at the level of. …the EU 0.33 0.28
Participation of the decision at the level of. …smaller entity than municipality 0.52 0.24
3rd Dimension
Financing source……private 0.37 0.35
Decision level of the implementation……smaller entity than municipality 0.55 0.60
Participation of the decision at the level of. …smaller entity than municipality 0.51 0.60
Institutional setting of the project……state 0.44 0.89
Participation lead……central 0.30 0.26
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The qualitative comparison between the types of gov-
ernance models identified and governance model types
described in the literature is synthesized in Table 4. On the
one hand, there were some similarities between the gov-
ernment model types, but on the other hand, there were also
clear differences between the model types based on the
observation of practices (method presented in this paper)
and model types described at the theoretical level (method
found in literature).
DISCUSSION
This paper has investigated governance models for the
implementation of NBS for mitigating flood risk in Ger-
many. The selection of NBS followed a systematic method,
and the resulting data set showed a wide variety of
implemented measures and few data on governance. Cases
in each cluster share distinctive similarities in their gov-
ernance features. However, the HCPC showed four gov-
ernance models: (1) ‘‘cooperation and incitation’’, (2) ‘‘co-
design’’, (3) ‘‘citizen power’’ and (4) ‘‘top-down’’. This
mirrors the whole spectrum of participation level ranging
from single information to decision making (Arnstein
1969).
The diversity of stakeholder groups and the direction of
mainstreaming at the operational and institutional level
differentiate the clusters. Type 1 projects contain NBS such
as green roof design with a dominant goal in climate
adaptation strategy while also improving flood risk miti-
gation. These projects intend to reduce hazard exposure
more than the vulnerability of the exposed area since they
are implemented in the city or in other landscapes rather
than along the river. Because of property rights, many
private actors are responsible or involved in the imple-
mentation of these NBS which are planned by the city
government. Therefore, the linking of on-the-ground actors
with the city government to implement long-term and
large-scale measures aimed at hazard exposure reduction is
crucial to ensure implementation. This is often the case
when NBS are related to adaptive behavior such as the
change in usage of existing open private green space
(Wamsler et al. 2017). The opposite model is the type 3
projects. These projects illustrate how citizens can drive
action and develop innovative financing models. Type 4 is
different from type 1 and 3 because of the simple top-down
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
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style stakeholder constellation. This does not always mean
that only one powerful entity drives NBS implementation
but that other stakeholders are underrepresented. Most
cases are type 2 where NBS are co-designed by complex
stakeholder constellations. Type 2 projects are very
expensive and rely on funding security and land
Fig. 6 Cluster solution obtained through the hierarchical clustering of principal components, suggesting four clusters as the optimal number of
groups
Table 3 Main project-type characteristics to which project types are associated (at p\0.05)
Governance features Type 1
Cooperation and
Initiatives
Type 2 Co-
Design
Type 3 Citizen Power Type 4 Top-Down
Framing and implementing
organisational structures
Entities smaller than the municipalities as the
dominant implementation level (100%)
Implementation under the
lead of the State (70%)
Project coordination State
Participation level Central Co-design Citizen power
Institutional setting City government
and private
Entities smaller than the municipalities as the
dominant decision level (100%)
EU, Decision taken at the
level of the State (70%)
Financing model No regional
funding
Municipal funding
(100%)
Regional funding
(100%)
Private contributions (70%) or Municipal EU and State (100%)
Property rights
constellation
No land
transactions
State or City
government
(100%)
Localization River bank
(100%)
River restoration No implementation in the
river bed
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availability from project leaders. These projects are the
most comprehensive in applying the four approaches to
reduce climate risks: reducing hazard exposure, reducing
vulnerability of exposed area, ensuring effective response
during risk and ensuring effective recovery (Wamsler et al.
2017).
Our analysis showed that NBS design and implemen-
tation resulted mostly from collaborative planning includ-
ing stakeholders from single or multiple stakeholder
groups, i.e., public, private, NGO, and civil society. The
numerous NBS goals may be an explanation for the broad
spectrum of stakeholders included in the planning and
implementation (Zingraff-Hamed et al. 2019). Because of
their inherent makeup, NBS can achieve these multiple
goals (Raymond et al. 2017; Cohen-Shacham et al. 2019).
Governance models with a large spectrum of stakeholders
from different geographic and juridical levels are often
regarded to be more effective in facing water issues
because of their higher resilience and their capacity to deal
with complex systems (Lee 2009; Wuijts et al. 2018). This
study showed that these governance models are also
effective for the implementation of NBS.
In line with previous studies, the 17 German cases
studied are advocated at different levels (Wamsler 2015;
von Wirth et al. 2019). This observation has been already
made for urban parks (Buijs et al. 2019). However, the
results of our study show that municipalities, citizens and
NGOs, are important pieces of the stakeholder constella-
tion that drives NBS implementation in urban as well as in
rural areas. Previous studies concerning ecosystem-based
climate change adaptation measures already suggest that in
Germany, landscape planning is most advanced in cities in
which earlier efforts in environmental planning led to
multiple and decentralized decision centers (Wamsler
2015). While collaborative, interdisciplinary, and interde-
partmental governance approaches are key for imple-
menting NBS (Kabisch et al. 2016; Frantzeskaki et al.
2019), our study showed that local authorities have a cru-
cial role in integrating NBS into location-based planning
strategies. In particular, the ‘‘local champion’’ has a deci-
sive political role in mitigating natural hazards (Martin
et al. 2019). A comparison of ecosystem-based adaptation
measures for climate change between German and Swedish
cases already suggested that in Germany, committed
politicians at the municipal level drive the integration of
climate change mitigation measures into landscape plan-
ning and thus compensating for a lack of clear guidance
from the state and regional level (Edelenbos 2005; Wam-
sler 2015).
In our study, we compared our results to existing gov-
ernance model typologies. In contrast to these theoretical
models deduced from governance theories, our method is
inductive meaning that types are based on real-life
governance features of various cases. Inductive methods to
develop typology are also used in different fields of policy
science (e.g., Mattijssen et al. 2018; Celata and Coletti
2019). We found that our typology is in line with existing
governance models described in Table 4, which confirms
the validity of our results on a broader scale beyond the 17
cases in Germany. Our typology is relatively close to
Arnouts et al. (2012) typology, especially because at the
difference of for instance Kooiman (2003) that developed
three different governance models (hierarchical gover-
nance, co-governance and self-governance) along the
dimension of the role of governmental and non-govern-
mental actors, Arnouts et al. (2012) divided co-governance
as closed and open co-governance. However, differences
exist. Other model as for example, Pahl-Wostl’s gover-
nance typology (2015) used another approach and differ-
entiates between hierarchical, network and market
governance. Compared to this governance typology, there
is a difference in presence of the market dimension.
Besides the market dimension however, the models are
similar in terms of distinguishing between hierarchies and
networks. Treib et al. (2007) seems to better address the
initiator of the NBS then our typology. Finally, Vatn
(2010) is based on the dimensions of the power of decision
making and resource allocation and distinguished between
hierarchies-based, market-based, and community-based
management. Interestingly, when we compared our typol-
ogy to the governance models of Vatn (2010), we found
that the hybrid models with market elements were not very
distinctive. This may be due to data collection limitations.
Data on resource allocation, financing models, and prop-
erty rights constellation were partly lacking. Therefore, the
topic of market-based approaches has to be explored in
future research. Specifically, business models for NBS
need to be investigated whether market approaches are
suitable governance models for NBS implementation.
Our systematic approach to identify a governance model
typology was based on cases in Germany. However,
observation of international cases shows the value of
investigating a broader scale. Implemented cases included
in the ReConect project show that a high exposure to risks,
e.g., in the Austrian Alps, is correlated to type 4 gover-
nance models. Type 2 governance models have been
institutionalized in the Netherlands for centuries but co-
design in this case has led to grey infrastructure rather than
NBS. Ongoing Phusicos and ReConect cases are located all
around the world and intend to incorporate co-design NBS
and cover the four identified types of governance models.
These insights showed that although NBS can be the result
of a traditional state power model, the interest for coop-
eration-based models and the effectiveness of these models
are growing. This highlights the shift from government to
governance (Edelenbos 2005).
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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
The Author(s) 2020
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Table 4 Synthesis of the main results of the governance model typology
Governance
models
identified
Dimensions Description Politics Reference
Hierarchical
governance
Network
governance
Market
governance
Formality of institutions and the role of state
versus non-state actors
The hierarchical style is characterized by the
dominant role of the government, while the
network mode includes all forms of
cooperation between government and non-
state actors. In the market mode, the
government delivers services to non-state
actors but choices are free and ruled by
prices and negotiations
Water Pahl-Wostl
(2015)
hierarchical
governance
Co-
governance
Self-
governance
Role of governmental and non-governmental
actors
Hierarchical governance has at one end of the
spectrum a top-down influence by the
government and at the other end, self-
governance where actors are not controlled
by government. Co-governance where public
and private actors interact with each other is
located in between the two ends
No specific
politics
Kooiman
(2003)
Hierarchical
governance
Closed co-
governance
Open co-
governance
Self-
governance
Actors, power and rules Amplification of Kooimans spectrum by
dividing co-governance as closed and open
co-governance. Closed co-governance
contains a selected mixed group of actors,
restricted cooperation and pooled power
relations while open co-governance contains
a large mix with diffused power and flexible
rules of cooperation
Nature policy Arnouts et al.
(2012)
Coercion
Voluntarism
Targeting
Framework
regulation
State intervention versus societal autonomy
but along the three dimensions of polity
(political form), policy (policy content)
and politics (political processes)
This typology puts emphasis on the role and
the self-empowerment of the state and
integrates the European multi-level
governance system. Important criteria are,
whether legislation is binding; and whether
implementation is rigid
European
Union
Treib et al.
(2007)
Hierarchies,
Markets, and
Community-
based
approaches
Power of decision making and resource
allocation
Hierarchies are based on command and control
and resource allocation occurs through
authority and power structures. Market-
based approaches are driven by the voluntary
exchange among individual actors, and
resource allocation is based on willingness to
pay. Community management is based on
cooperation among actors, and resource
allocation is taking into account individual
as well as common goals
Ecosystem
Services
Vatn (2010)
Centralized
governance
Decentralized
governance
Public–Private
governance
Interactive
Governance
Self-
governance
Actor features, institutional features and
feature contents
Models are distinguished according to
initiating actors, stakeholder position, policy
level and power base (actor features); model
of representation, rules of interaction, and
mechanism of social interaction
(institutional features); and goals and targets,
instruments, policy integration, and science-
policy interface (features content)
Environmental
governance
Driessen et al.
(2012)
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To face future water governance challenges, the EU is
actively encouraging type 2 governance models by funding
research and action projects. The EU identified polycentric
governance as a driver for successful NBS implementation
(EC 2003) and provided clear guidance encouraging col-
laborative planning through different policies, e.g., the
Flood Directive, the Water Framework Directive and the
Public Participation Directive. However, some of the col-
laborative planning processes to co-design NBS struggle to
find consensus. Many challenges (Graversgaard et al. 2017)
and lessons (Zingraff-Hamed et al. 2019) from polycentric
governance and NBS co-design have been identified. Fur-
ther research may provide valuable insight on the success
of the co-design process in different traditional planning
contexts. The investigation of adaptability potential and
process to more collaborative models of traditional gov-
ernance constellation is especially relevant for future
governance guidance.
While large-scale NBS is crucial for effectiveness,
implementation remains at the level of a pilot area or at a
local government scale (Hartmann and Spit 2016). How-
ever, the Flood and the Water Framework Directives
require management plans that exceed the municipal level.
In Germany, two historical governance barriers need to be
overcome. First, flood protection strategy historically relied
on the regional authorities which did not have jurisdiction
over the river catchment area or river basin district (Hart-
mann and Spit 2016; Bro
¨dner 2019). Second, stakeholders
are accustomed to implementing technical solutions that
address local risks (Lu
¨nenbu
¨rger 2006; Bro
¨dner 2019). A
paradigm change is urgently needed to implement large-
scale solutions as requested by the EU directives.
Our study has few limitations. This investigation did not
identify how local authorities integrate NBS into their
plans, policies and strategies. Furthermore, we did not
identify the best governance model. Moreover, the results
depend on the methods applied. It should be noted that we
only used NBS documented in online databases and con-
sequently, only successfully implemented solutions. It is
probable that not all existing NBS were included. We also
relied on the information presented in these databases,
which provided a relatively small amount of information
on governance issues. Our data analysis applied standard
statistical methods that have already been proven effective
in identifying project typologies (Zingraff-Hamed et al.
2017a). However, the relatively low number of cases and
the large number of variables addressed influenced the
outcomes of the analysis. Finally, the study did not try to
identify the characteristics of a successful water gover-
nance structure.
CONCLUSION
This paper investigates governance model that led to 17
NBS implementation in Germany to mitigate flood risk and
provides important insights for researchers and practition-
ers interested in investigating, successfully designing, and
implementing NBS. First, this contribution presents a novel
attempt in clustering governance models in an inductive
Table 4 continued
Governance
models
identified
Dimensions Description Politics Reference
Self-
governing
Governing by
provision
Governing by
authority
Governing
through
enabling
Government vs. other actors Governance modes vary according to the
capacity of local government and practice to
deliver particular forms of services and
resources up to the traditional forms of
authoritarian regulation
Climate Bulkeley and
Kern (2006)
Cooperation
and
Initiatives
Co-Design
Citizen Power
Top-down
Framing and implementing organizational
structures
Project Coordination
Participation level
Institutional setting
Financing model
Property rights, constellation and
localization
Governance models range from more
participation and private funding to more
top-down ruling and state funding
Nature-based
solutions
This
contribution
The Author(s) 2020
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manner instead of deductive one. This investigation shows
that different models lead to NBS implementation and
suggests that no ‘‘one-size-fits-all’’ model can be identified.
However, an important commonality between the gover-
nance models exists, namely, the inclusion of different
stakeholder groups. This suggests that collaborative gov-
ernance approaches are a key factor for successful imple-
mentation of NBS.
Second, this paper suggests that a high degree of
cooperation between the stakeholders improves NBS
implementation potential. The EU intends to encourage
NBS implementation via polycentric governance. How-
ever, local, historical, and cultural differences in gover-
nance approaches cause difficulties in implementing
collaborative planning and context conditions seem to
influence the governance models applied. It is extremely
important that NBS research projects analyze governance
models systematically. Future governance will be chal-
lenged to adapt traditional governance models to imple-
ment large-scale solutions with higher number of
stakeholders.
Finally, this investigation identifies municipalities, citi-
zens, and NGOs as crucial pieces of the stakeholder con-
stellation to NBS design and implementation. Many
empirical but few evidence-based work on governance
structures for NBS underscore these results. This contri-
bution addresses this gap. Interestingly, while the impor-
tance of on-the-ground stakeholders for the design and
implementation process of NBS may sound as common
sense, in many governance systems, they are not yet rec-
ognized. We hope that with the evidence that this contri-
bution provides, planners and managers will be encouraged
to take up the ideas of more inclusive governance models
in practice.
Acknowledgements This contribution is a result of the SmartNBS
research task force between PHUSICOS research group of the
Technical University of Munich, RECONECT research group of the
Helmholtz Centre for Environmental Research Leipzig (UFZ), the
Plansmart Junior Research group at Ruhr University Bochum, and
Leibniz Centre for Agricultural Landscape Research (ZALF) in
Mu
¨ncheberg. AZH, GL, and JH were funded by the project PHUSI-
COS that has received funding from the European Union’s Horizon
2020 research and innovation program under grant agreement No
776681. FH was funded by the project RECONECT that has received
funding from the European Union’s Horizon 2020 research and
innovation program under Grant Agreement No 776866. MB, MS,
CA, and BS were funded by the German Federal Ministry for Edu-
cation and Research (Bundesministerium fu
¨r Bildung und Forschung -
BMBF) through a grant for the PlanSmart research group (grant no:
01UU1601A and B) as part of the funding priority ’’Social-Ecological
Research’’ within the Research for Sustainability Program (FONA
3
).
SS was funded by the project CONNECTING NATURE funded by
the Horizon 2020 Framework Programme of the European Union
under Grant Agreement No 730222 and the project CLEARING
HOUSE funded by the European Union’s Horizon 2020 Research and
Innovation Program under Grant Agreement No 821242. We thank all
the data providers and external reviewers. We like to express sincere
appreciation to all who contributed time, experience, and knowledge
to support the development of this contribution. The authors espe-
cially like to thank the stakeholders who took time for responding to
our questions.
Funding Open Access funding enabled and organized by Projekt
DEAL.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as
long as you give appropriate credit to the original author(s) and the
source, provide a link to the Creative Commons licence, and indicate
if changes were made. The images or other third party material in this
article are included in the article’s Creative Commons licence, unless
indicated otherwise in a credit line to the material. If material is not
included in the article’s Creative Commons licence and your intended
use is not permitted by statutory regulation or exceeds the permitted
use, you will need to obtain permission directly from the copyright
holder. To view a copy of this licence, visit http://creativecommons.
org/licenses/by/4.0/.
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AUTHOR BIOGRAPHIES
Aude Zingraff-Hamed (&) is a research associate and lecturer at the
Technical University of Munich, Chair for Strategic Landscape
Planning and Management. Her research focus are river restoration,
urban studies, nature-based solution, hydro-meteorological risk, cli-
mate change, water governance, ecosystem-based management, nat-
ure conservation, recreational uses, and socio-ecological system.
Address: Technical University of Munich, Chair for Strategic Land-
scape Planning and Management, Emil-Ramann-Str. 6, 85354 Freis-
ing, Germany.
e-mail: aude.zingraff-hamed@tum.de
Frank Hu
¨esker is a post-doc at the Helmholtz-Centre for Environ-
mental Research in Leipzig. His research interests include water
governance, micropollutants, nature-based solutions, and water-en-
ergy-food nexus.
Address: Helmholtz Centre for Environmental Research, Permoserstr.
15, 04318 Leipzig, Germany.
e-mail: frank.hueesker@ufz.de
Christian Albert is Professor for Environmental Analysis and
Planning in Metropolitan Regions at Ruhr University Bochum,
Institute of Geography. His research interests include theories and
methods of landscape planning, ecosystem services, and sustainability
sciences.
Address: Ruhr-Universita
¨t Bochum, Institute of Geography, Univer-
sita
¨tsstr. 150, 44805 Bochum, Germany.
e-mail: christian.albert@rub.de
Mario Brillinger is a doctoral candidate at Viadrina University
Frankfurt (Oder) and researcher at Ruhr University Bochum, Institute
of Geography. He holds a Master’s degree in agricultural science
focusing on resource management and environmental economics. His
research interests include theories and methods of collective decision-
making, water governance research, and qualitative social science.
Address: Ruhr-Universita
¨t Bochum, Institute of Geography, Univer-
sita
¨tsstr. 150, 44805 Bochum, Germany.
e-mail: brillinger@umwelt.uni-hannover.de
Joshua Huang is a research assistant at the Technical University of
Munich. His research interests include risk analysis and assessment,
risk mitigation, social and ecological urban river restoration,
and flood management climate change mitigation.
Address: Technical University of Munich, Chair for Strategic Land-
scape Planning and Management, Emil-Ramann-Str. 6, 85354 Freis-
ing, Germany.
e-mail: Josh.J.Huang@gmail.com
Gerd Lupp is a research associate at the Technical University of
Munich and received his Ph.D. in forest sciences. His research
interests include participatory processes, climate change and climate
adaptation, assessment of ecosystem services, nature-based recre-
ation, renewable energies, nature conservation, and sustainable forest
management practices.
Address: Technical University of Munich, Chair for Strategic Land-
scape Planning and Management, Emil-Ramann-Str. 6, 85354 Freis-
ing, Germany.
e-mail: gerd.lupp@tum.de
Sebastian Scheuer is a post-doc in geography at the Humboldt-
Universita
¨t zu Berlin. His research includes nature-based solutions for
climate change adaptation in urban areas with special attention to
Urban Forests, climate change impact assessment, multi-criteria risk
assessment, natural hazard research, flooding in particular, and
quantitative and semi-qualitative analysis of global patterns and
processes of urbanization.
Address: Humboldt-University Berlin, 10099 Berlin, Germany.
e-mail: sebastian.scheuer@geo.hu-berlin.de
Mareen Schla
¨tel is a research assistant at at the Leibniz University
Hannover for the junior research group PlanSmart. Her research
interests include nature-based solution, water governance, environ-
mental planning, and river restoration.
Address: Ruhr-Universita
¨t Bochum, Institute of Geography, Univer-
sita
¨tsstr. 150, 44805 Bochum, Germany.
e-mail: mareen.schlaetel@stud.uni-hannover.de
Barbara Schro
¨ter is a post-doc at the Leibniz Centre for Agricultural
Landscape Research (ZALF) in the working group ‘‘Governance of
Ecosystem Services’’. Her research interests include social-ecological
research, governance and institutional analysis, social network anal-
ysis, and environmental justice.
Address: Leibniz Centre for Agricultural Landscape Research,
Working Group ‘‘Governance of Ecosystem Services’’, Eberswalder
Str. 84, 15374 Mu
¨ncheberg, Germany.
e-mail: Barbara.Schroeter@zalf.de
123 The Author(s) 2020
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