Community Research and Development Information Service - CORDIS

FP7

ENHANCE Report Summary

Project ID: 308438
Funded under: FP7-ENVIRONMENT
Country: Netherlands

Final Report Summary - ENHANCE (Enhancing risk management partnerships for catastrophic natural disasters in Europe)

Executive Summary:
The frequency and economic damage of natural disasters has increased sizeably, in Europe. Losses are expected to continue to rise as a result of urban- and economic activities and climate change. Disaster risk reduction (DRR) is required to reduce the risk from natural hazards. DRR, however, is a complex task that involves many actors and often cuts across sectors and geographical scales. For this, the ENHANCE project The ENHANCE recommends (new) Multi-Sector Partnerships (MSPs) for managing DRR, based on 10 case studies. MSPs involve a mix of partners from the public and private sectors and civil society organizations. Project results show MSPs have the potential to significantly improve disaster risk management. Using the ‘capital approach’, MSPs were assessed on their healthiness to cope with natural disasters, resulting in the following general recommendations that support the UNISDR Sendai Framework for DRR and the UNFCCC Loss and Damage discussion:

A. Risk Assessment:
• Risk extremes and economic damage should be taken into account in international risk reduction and risk financing initiatives. This supports both the Sendai Framework as the UNFCCC Loss and Damage approach.
• Reliable and accurate risk information is key for the well-functioning of an MSP. For this, the availability of empirical loss data is imperative, and a concerted action is needed to make such data public.
• Risk assessment methods of extremes through extreme value analysis and joint probability distributions (Copula’s) significantly enhance the reliability of risk scenario’s.
• In-direct economic effect from disasters in areas that are not directly affected, but are linked to the disaster area through supply of goods and services, may account up to 40% of the total damage. More research is needed to further assess adaptation options to reduce this risk.

B. Perception and Behaviour
• Risk perception is an important driver for DRR. Risk perception is largely influenced by factors such as: experience with previous disasters, financial incentives and socio-economic conditions, of individuals.
• By better targeting Individual behaviour of households towards DRR through e.g. communication and providing financial incentives such insurance deductibles, risk reduction can be improved up to 35%.
• EU regulation such as the Flood directive should provide more incentives to households, activating the enormous potential of DRR through individuals.
• Insurance schemes should be better linked to EU regulation (flood directive, Solvency II, EU Solidarity fund), as they already have close ties with individual households, and can stimulate DRR at local levels.
• For this, we need an improved understanding of individuals’ perception and behaviour towards disaster risk. Agent Based Models are powerful tools to simulate effects from human behaviour on DRR

C. Insurance & Economic Instruments
• Risk transfer schemes such as insurance and the EU solidarity fund, are only viable in the future with an considerable increase in physical protection measures / DRR
• Without DRR, premiums for e.g. flood insurance in several EU countries such as Germany and France may increase up to 120%.

D. Disaster Risk Reduction / Adaptation
• DRR measures may significantly decrease risk; more efforts are needed to involve individual households.
• Adaptation/DRR efforts should include the whole realm: from warning systems, protection to spatial planning effort

Please see Deliverable 1.4 Final publishable summary report for the complete report including graphs and pictures

Project Context and Objectives:
1. ENHANCE: Disaster Risk and Multi Sectoral Partnerships (MSPs)
During the past decades, the frequency and economic damage of natural disasters has increased sizeably, both worldwide (Munich Re, 2014) and in Europe. A number of major disasters have left their marks across Europe, prompting high economic damage and losses, casualties, and social disruption. Examples include the 2010 eruptions of the Eyjafjallajökull volcano in Iceland; earthquakes in Italy in 2009 and 2012; droughts and forest fires in Portugal and Spain in 2012; heavy rainfall that caused record floods in Central Europe in 2013; floods in the UK in the summer of 2007, and the winters 2014/15 and 2015/16 (Munich Re, 2015).

Natural disaster risks and losses in Europe are expected to continue rising as a result of the projected expansion of urban and economic activities in disaster-prone areas. In addition, climate change might increase the frequency and severity of certain extreme climate and weather related events, such as droughts, heat-waves, and heavy precipitation (IPCC, 2012; IPCC, 2014). These phenomena will continue to unfold as human induced climate change will become more pronounced. Hence, it is imperative to take comprehensive action on disaster risk reduction (DRR) to improve the resilience of European societies to natural hazards.

Increasing resilience to disasters that are caused by natural hazards is a complex task that involves many actors and often cuts across sectors and geographical scales. The ENHANCE project has contributed to DRR by further developing Multi-Sector Partnerships (MSPs) for disaster risk management, which are key to addressing the Sendai challenges. MSPs involve a mix of partners from the public and private sectors and civil society organizations. MSPs have the potential to significantly improve disaster risk management, but in practice, the cooperation across partners is often ineffective. The ENHANCE project had the following main objectives:
a) to assess the characteristics of (un-) successful partnerships in improving DRR
b) to develop (future-) risk scenarios, including disaster extremes
c) to enhance DRR by linking MSPs to economic instruments, including insurance
d) to provide policy recommendations for the horizontal integration of risk management and climate-proofing in policies.

The Sendai Framework for Disaster Risk Reduction and the Warsaw Mechanism
Global disaster risk reduction activities have been informed by the efforts of the United Nations Office for Disaster Risk Reduction (UNISDR). Until 2015, UNISDR coordinated the implementation of the Hyogo Frame-work for Action: 2005-2015 (HFA), which was organized around the main challenges that countries face in terms of natural disaster risk management (UNISDR, 2011). These challenges include: (1) improved risk assessment based on a multi-hazard and multi-risk approach; (2) a more vigorous pursuit of multi-sector partnerships; and (3) improved financial and disaster risk reduction schemes.

As a follow up to the HFA, the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14–18 March 2015, Sendai, Japan) identified new commitments and targets, which led to the Sendai Framework for Disaster Risk Reduction 2015-2030. Together with partner UNISDR, the ENHANCE project supported the Sendai conference and provided scientific backup and policy recommendations (e.g. Mysiak et al., 2016) to the targets of the Sendai Framework. Which are: to reduce the impact of future disasters, mortality, economic damage, and damage to health and educational facilities (e.g. Jongman et al., 2015). Other targets aim to extend local and national DRR strategies, and are an extension of the HFA’s call for better coordination of disaster risk activities with development and other sectorial policies (UNISDR, 2015).

In addition, ENHANCE has pushed the role of DRR within the climate change community, through a leading role in the United Nations Framework Convention on Climate Change (UNFCCC) (Mechler et al., 2014; Mechler and Schinko, 2016). The Paris Agreement, negotiated at the end of 2016 under the UNFCCC, sets a global goal of adaptation for the first time to build adaptive capacity, strengthen resilience, and reduce vulnerability to climate change. This new policy emphasizes that responses must account for local, subnational, national, regional, and international dimensions and actors across scales. One particular issue in relation to disaster risk is the ‘loss and damage’ discussion, which has also been formally recognized with the inclusion of the ‘Warsaw Loss and Damage Mechanism’ into the agreement. This mechanism informs the action of efforts to manage risk from losses beyond adaptation, and in addition to discussing responsibility and liability, a large part of the debate has focused on bolstering comprehensive DRR (UNFCCC, 2015).

Multi Sectoral Partnerships
An important part of the Sendai Framework guiding principles calls for partnerships to achieve improved risk management. The challenge is to improve the way that different institutions and sectors (jointly) cooperate to develop and implement DRR measures. To achieve this, the ENHANCE project has specifically studied multi-sector partnerships (MSPs). MSPs are partnerships that involve a mix of actors from the public and private sectors and civil society organizations. MSPs have the potential to significantly improve disaster risk management, but joint action with the aim of lowering risk involves different stakeholders and can also be challenging (Pahl Wostl et al., 2007; UNISDR, 2011).

The different responses to heat-waves in Europe in 2003, 2006, and 2010 and the UK floods in 2015 demonstrate that the roles of public, private, and civil society actors (including individuals) in preparing for and responding to catastrophic impacts are often not clear or effective. Moreover, actors must often base their risk management strategies on scarce, limited, or inaccurate risk information. This is not surprising, since empirical data on low probability-high impact events is not recorded in avail-able datasets. Together, these factors can lead to the development of ineffective and unacceptable disaster risk management measures and an unexpectedly large impact of natural disasters (financial, ecological, health, and social). In preparing for and responding to natural hazard impacts, there is also often a lack of clarity on financial responsibilities about who pays for what, how often, and when. Knowing that the challenge of managing risks that result from natural hazards has increased, it is clear that these risks cannot be handled by the private sector or the government as single actors, and strategies to in-crease resilience should therefore incorporate all sectors of society (including cooperation between sectors). The main goal, therefore, of the ENHANCE project was to develop and analyze new ways to enhance society’s resilience to catastrophic natural hazard impacts. The key to achieving this goal is to analyze new multi-sector partnerships that aim to reduce or re-distribute risk and increase resilience. Within ENHANCE, we define MSPs as:

‘Voluntary but enforceable commitments between partners from different sectors (public authorities, private services/enterprises, and civil society), which can be temporary or long-lasting. They are founded on sharing the same goal in order to gain mutual benefit, reduce risk, and increase resilience’.

2. The ENHANCE approach
Figure 1 describes the general approach that was followed by ten ENHANCE case studies (see Table 1). Following the components of Figure 1, the main activities of each case study were (1) to assess the capacity of each existing MSP to reduce or manage risk; (2) to assess current and future risk, including extremes and effects from both climate change and socio-economic developments; and, (3) to explore DRR measures that were developed and governed by the MSP with the aim of reducing risk. The relationship between resilience and good governance of MSPs is assessed in ENHANCE by the Capital Approach Framework (CAF) that was developed during the project to assess governance performance. The CAF assesses risk governance performance and the influence of risk perception of MSPs on risk management strategies. Furthermore, for the risk assessment activities, different modelling and statistical techniques were implemented to assess the magnitude and frequency of extreme events, such as ‘extreme value analysis’ and joint distribution of risk (‘copula’s’). Finally, the project explored different economic instruments, such as pricing and insurance, as part of the different DRR actions, and explored what type of EU- (Solidarity Fund, Flood Directive, etc.) and national policies are required to develop and maintain such instruments to enhance MSPs.

Table 1. Ten ENHANCE case studies on different natural hazards, scales, and multi-sector partnership types. Note: MSP types: E = Emergency response MSP; R = Risk reduction strategy MSP; F = Financial MSP.

Project Results:
1. Assessing the healthiness of MSPs
In order to assess whether MSPs have the capacity to anticipate natural disaster risk, the ENHANCE project merged resilience concepts and indicators with a framework for analysing (un)successful governance processes. Twigg (2009) describes 11 factors that provide a basis for identifying ‘(un)-healthy’ characteristics of an MSP for building resilience or shaping new partnership development: integration of activities, shared vision, consensus, negotiation, participation, collective action, representation, inclusion, accountability, volunteerism, and trust. We converted these ‘resilience – governance factors’ into MSP indicators, using the Capital Approach Framework (CAF). The CAF draws from different theories such as risk governance (e.g. Fürth, 2003; IRGC, 2005), and aims to assess: (a) the concept of the institutional fit of an MSP, which is ‘the degree of compliance by an organization with the organisational form of structures, routines, and systems prescribed by institutional norms’ (Kondra and Hinings, 1998); (b), use the capital theory, which is the idea of linking sustainable development to the concept of the five capitals (see Table below) (Goodwin, 2003; OEDC, 2008).

The different capitals provide MSPs with the capacity to react to natural hazards. Capital or capacity is hereby understood as the assets, capabilities, and properties, which collectively represent the good functioning of an MSP. The CAF differentiates between five capitals: financial, social, human, natural (environmental), and political capital. Political capital has been added by the ENHANCE project and refers to the capability of institutions to enact rules, laws, or frameworks that might change the course of actions. The resilience indicators that are described by Bahadur et al. (2010) and the 11 factors that are described by Twigg (2009) can be allocated within one of these five capitals. The rationale behind this approach is that the maintenance or enlargement of the five capitals will assure the capability of a partnership to react to environmental hazards. In an ideal situation, a sustainable MSP will focus on maintaining and/or enhancing its capitals. The quality of these five capitals is contingent upon existing development and health baselines, as well as the legacy of past disaster impacts.

BOX: The five capitals needed for healthy MSPs are:

• Social: the relationships, networks, and shared norms and values that qualify and quantify social interactions, which have an effect on partnership productivity and well-being.
• Human: focused on individual skills and knowledge. This includes social and personal competencies, knowledge gathered from formal or informal learning, and the ability to increase personal well-being and to produce economic value. In the case of partnership, the human capital will be the addition of its individual skills and knowledge.
• Political: focuses on the governmental processes, which are done/per-formed by politicians who have a political mandate to enact policy. It also includes laws, rules, and norms, which are juristic outcomes of policy work.
• Financial: involves all types of wealth (e.g. funds, subsidies, etc.) that are provided, as well as financial resources that are bounded in economic systems, production infrastructure, and banking industries. Financial capital permits fast reactions to disasters.
• Environmental: comprehends goods and values that are related to land, the environment, and natural resources.

BOX: Managing Air traffic disruption and Volcanic ash outbursts.

With increasing interconnectedness, a disturbance of air traffic in one part of the world can have long-ranging financial and social effects on other parts. The eruption of the Eyjafjallajökull volcano in April 2010 (Iceland) illustrated this memorably. The eruption prevented millions of passengers, as well as goods, from reaching their destination, as air traffic was halted in Europe for several days (Ulfarsson and Unger, 2011). As part of the EU project ENHANCE, this case study has sought to obtain insights into how the European aviation sector can advance its risk management with regard to volcanic ash since the eruption in 2010. The MSP members consist of EU wide information providers, crisis coordination and network management, air navigation service providers, global-, international and national regulators and aircraft operators.

To evaluate the functioning of the MSP, two extreme volcanic ash scenarios were developed (the most extreme scenario is depicted below). One of the recommendations is to further elaborate training of MSP members with extreme scenarios. After the eruption in 2010, 70 airlines participated in the VOLCEX exercise. Around 50 airlines were involved in the last exercise. For the MSP to be successful, as many stakeholders as possible should participate in the exercise and use the platform simultaneously to exchange experience, knowledge, views and opinions.

2. Risk Assessment
In order for an MSP to manage risk, accurate risk assessment and information is critical to any DRR decision. Risk assessment looks to understand future permutations by constantly updating projections of risk scenarios through risk assessment and reflection (e.g. Tschakert and Dietrich, 2010). Risk assessment can play an important role in measuring the relative influence of an MSP on risk reduction through its actions, for example through applying risk information in decision support, evaluation, and cost-benefit analysis processes (e.g. Watkiss et al., 2014). Risk information also plays an important role in assessing the DRR strategies in anticipation of future risk conditions.

Generally speaking, there are two approaches to assess natural disaster risks: statistical risk assessments and catastrophe models. The first approach looks only at the past and estimates risk from historical loss data using extreme value theory (e.g. Embrechts et al., 1997). A fundamental challenge is how to model the rare phenomena that lie outside of the range of available observation. While much real world data approximately follows a normal distribution, which implies that the estimation of distributional parameters can be done based on such assumptions, for natural hazard extremes, the tails (rare outcomes) are much fatter than normal distributions predict. This is accounted for in extreme value theory, according to which, natural disaster risk distributions are estimated using, for example, Gumbel, Weibull, or Frechet distributions. Typical steps in such an assessment are provided in ENHANCE for all case studies for which sufficient hazard or loss data is available. In the second approach, catastrophe models are applied, which are computer-based models that estimate the loss potential of natural disasters (Grossi and Kunreuther, 2005). This is usually done by overlaying the properties or assets that are at risk (exposure module) with hazard and vulnerability information captured in damage curves (Figure 3).

It is important to understand the dynamics of the underlying causes of risk. For example, the projections of climate variability and change should ideally be based on an ensemble of (regional) climate models that capture a broad spectrum of underlying uncertainties. Moreover, information about exposed economic assets and their vulnerability to hazards is needed. In ENHANCE, new approaches (Copula’s) were applied to flood- and forest fires cases to avoid the underestimation of such low-probability/high-impact events (e.g. Jongman et al., 2014). With this new approach, EU flood risk was estimated 17% higher as compared to conventional methods.

BOX: Case study: Austrian Railways and Alpine hazards

The railway transportation system of the Alpine country Austria plays an important role in the European transit of passengers and freights. The mountainous environment poses a particular challenge to railway transport planning and management. Railway lines often follow flood-plains or are located along steep unsteady slopes, which considerably exposes them to flooding and in particular to alpine hazards, e.g. debris flows, rockfall, avalanches or landslides. As a result, railway infrastructure and operation has been repeatedly impacted by alpine hazards. For example, in June 2013, floods and debris flow events caused substantial damage to the railway infrastructure in Austria. The national railway operator ÖBB reported a total damage of about EUR 75 million to its railway network.

In order to better plan, negotiate, and decide on investments in protection measures, reliable models for estimating potential flood losses to railway infrastructure are needed. Therefore, the ENHANCE case study ‘Building railway transport resilience to alpine hazards’ has developed an empirical modelling approach for estimating direct structural flood damage to railway infrastructure and associated financial losses. The Figure below shows potential structural damage at the Northern Railway in Austria for three synthetic flood scenarios: a) a 30-year event, b) a 100-year event, and c) a 300-year event. In damage class 1 the track`s substructure is (partly) affected, but there is no or only little notable damage. In damage class 2 the track section is fully inundated and significant structural damage has occurred (or must be expected), while in damage class 3 additional damage to substructure, superstructure, catenary and/or signals occurred so that a full restoration of the cross-section is required (Kellermann et al., 2015).

Figure 4. Three different flood inundation scenarios (1/100, 1/1000, 1/10000) for a segment of a railway in Austria, and the projected damage classes (1-low to 3- high losses)

BOX: Direct and in direct effects of flooding: case study Port of Rotterdam

The port of Rotterdam in the Netherlands is the second largest in the world and the Largest Port in Europe. The harbour is situated in the south-western river delta of the Netherlands and is prone to natural hazards (wind storms, flooding) and the impact of climate change on these natural hazards. Potential elements at risk are industries, energy plants, port facilities, railways, tunnels, and container terminals. Severe economic damage can occur from long-term closures of the port and its industry. Similar to the Austrian case study, flood inundation maps with different return periods (probabilities) were used to estimate potential flood losses. In risk assessment studies, one can distinguish between direct and indirect effects (Koks et al., 2014). Direct effects can be defined as the impacts on buildings infrastructure and people. Indirect effects (Figure), on the other hand, are often caused by the direct impacts, but are the result of interferences within industrial supply chains (Okuyama and Santos, 2014). Most importantly, indirect effects may also occur outside the hazard area: e.g., companies that are not flooded (e.g. Carrera et al., 2015), but that have economic relations with households and industries that are flooded. These linked supply businesses, cannot supply or demand their goods and services to the business and people in the flooded area, and therefore, indirectly suffer from the flood (Koks et al., 2016). These costs (e.g. business interruption) can amount to 40% of the total damage (Hallegatte et al., 2012).

Figure 5. Indirect economic effects per region in the European Union for three extreme floods in the region of Rotterdam: 1/100, 1/1000 and a very extreme flood of 1/10000 (Koks et al., 2017, in review).

The UNFCCC Loss and Damage discussion (Mechler et al., 2015)
ENHANCE has further pushed the role of DRR within the climate change community, through a leading role in the UNFCCC (Mechler et al., 2014; Mechler and Schinko, 2016). An important decision in the COP 21 Paris Agreement was the endorsement of the Warsaw International Mechanism (WIM) for Loss and Damage (L&D). As disaster risk is special, a comprehensive approach involves targeting risk management interventions according to disaster return periods — ‘risk layering’. Risk layering can help to differentiate between distinct levels of risk organized around return periods (or probability) and the degree of stress imposed by risk. Risk layering is a concept underlying many areas of risk policy, especially agricultural and insurance risk management. This approach can reveal risk management options that are differentially effective for low-, medium- and high-probability events as well as tailored to the different risk bearing capacities of communities, governments and international organizations. Such nuanced understanding of risk management can also be helpful in identifying risks that are ‘beyond adaptation’.

The approach classifies different layers of risk: Frequent, low-impact risk for which DRR is typically the preferred adaptation (benefit–cost studies have shown great potential for reducing risks at this lower level); Medium-layer risks for which risk reduction can be combined with insurance and other risk-financing instruments that transfer residual risk, rare and catastrophic events; and finally, a very high- level risk layer for which the capacity of international aid agencies can be exceeded.

Figure 6. Schematic representation of Risk Layering, as an approach to support the UNFCCC Loss and Damage discussion (Mechler et al., 2016; Mechler and Schinko, 2016)

3. Risk Assessment and Policy implications for risk assessment
The importance of quality-assured, systematically collected and thorough datasets on impacts of natural hazards, the loss data systems (LDS) have been highlighted by the Sendai Framework for Disaster Risk Reduction 2015-2030 and the OECD. Currently, empirical data on losses from natural hazards in Europe are fragmented and inconsistent. Because open and accessible records on disaster impacts and losses are prejudiced by data gaps, European policy-makers have little choice but to resort to proprietary data collection. The Sendai Framework calls on the national and regional government to better appreciate the (knowledge of) risk. Empirical and evidence-based risk analysis and assessment are a vital part of the disaster risk reduction efforts (e.g. JRC, 2015). Therefore, the open-ended intergovernmental expert working group (IEWG) was instituted to develop a set of indicators for measuring global progress.

The Sendai Framework is not alone in this quest. The OECD invited the member countries to better prepare for catastrophic and critical risks (OECD, 2010, 2014). The draft Sendai Framework indicators focus currently on direct damage and structural/physical losses. However, the OECD recommended considering the whole distributional and implied ripple or spillover effects of natural hazards, which is now also discussed between countries and UNISDR. Furthermore, the European Union Civil Protection Mechanism (EC, 2013) compels the EU member states to conduct risk assessments, where possible also in economic terms, at national or appropriate sub-national level. They also have to make a summary of the relevant elements thereof available to the Commission by December 2015 and every three years thereafter. For both purposes, the Joint Research Centre (JRC) is developing loss indicators that should be part of operational disaster loss databases (De Groeve et al., 2013; 2014).

4. DRR and Risk Perception
Disaster risk is perceived differently by people, and risk management approaches are influenced by what people perceive as ‘risky’. Risk perception influence risk management, and for example, when protected by high levees, people behind the levee often perceive they are save. However, probabilities increase over time because of climate change, and exposure changes as well, because more people settle behind the ‘safe levee’. This is also referred to as the ‘levee effect’ (Tobin, 1995). Another important factor influencing risk perception is past experiences of extreme events. Protection Motivation Theory, shown schematically in Figure 8, has become an important socio-psychological model of individual flood risk-preparedness decisions (Bubeck et al., 2012). It offers a useful framework to analyse how risk communication, as a form of verbal persuasion, can influence a person’s threat or coping/DRR appraisal, and how risk management preparedness is affected. Communicating for instance the probability of a flood, as is done by the FEMA flood maps in the United States, aims to change people’ s threat appraisal. Communicating about the costs and the effectiveness of certain protection measures aims to change people’s coping appraisal.

Figure 8. A schematic overview of Protection Motivation Theory (adapted from Rogers and Prentice-Dunn (1997)

ENHANCE has assessed the perceived risk of MSP representatives in an online survey. It appeared that risk assessment and regular monitoring are considered as the most useful tools for objective formulation of risk perception and are mandatory in many cases. In some MSPs, perception is always at a certain base level, because of the continuous presence of natural hazards (e.g. the drought case study in Spain), and DRR measures are anchored as part of their risk culture. The survey also showed other DRR measures that are perceived valuable to managing risk: knowledge and technology transfer, information and networking, and applying future climate scenarios and simulations. Most MSPs have some form of risk management and risk emergency plans (Figure 9). Most of these plans, however, are older than 10 years, and in 60% of the cases they are considered mandatory. Emergency plans are considered mandatory in all the cases (100% of the cases analysed). Regarding action to support DRR (Figure 10), awareness raising is implemented for more than 10 years in 50% of the cases. 92% of the analysed MSPs implement this measure. On the other hand, insurance is only used in 17% of the cases.

Figure 9. Policies and programs implemented to enhance risk preparedness (%).

Figure 10. Policies and programs implemented to support prevention and mitigation

5. Risk perception: Policy Implications.
The effectiveness of MSPs are partly shaped by the perception of risk of the people involved in the partnership. There is a need to support MSPs and governments could assist the creation of multi-sector partnerships to manage risks and take advantage of the synergies between stakeholders. For example, through providing better risk communication to MSPs but also individuals, and by including guidelines and criteria for the creation of MSPs that will in turn help to further analyse the effectiveness of MSPs. Online accessibility of risk maps is important, as well as information for people of how households can develop and implement DRR measures themselves. In the latter context, insurance can play an important role, as they are equipped to target individuals and have the financial tolls (e.g. premium discount, deductibles) to provide incentive for DRR and to communicate risk to their policy holders. The theme of risk perception and DRR was further discussed between UNISDR, ENHANCE and the European Forum for Disaster Risk Reduction (EUFDRR) in both 2014 and 2015. As a follow up, we asked our survey respondents from the EUFDRR on the activities of those national platforms. National platforms are responsible for the coordination of actions oriented to develop guidelines for monitoring and management, to foster agreements between stakeholders, and elaborate information and its dissemination. It appeared More than 70% of the survey respondents agreed risk perception and communication of risk is key for effective DRR policies in Europe.

BOX: Agent Based Models: MSPs and behaviour on Risk Management

Agent Based Models (ABMs) can be used to characterize different stakeholders in a risk sharing arrangement such as an MSP for flood insurance. Simulation of the risk in an ABM can be used to assess the effect of different risk sharing options, which encourage overall risk reduction. This approach has been applied to the ENHANCE cases of London and Rotterdam (e.g. Haer et al., 2016; Jenkins et al., 2016). ABMs were found to be highly attractive, because stakeholders could easily see how different management options changed risk over time and showed what the implication are for policy. The ABM was for Greater London was applied to a case study of the Camden area of London, an area at high risk of surface water flooding. The ABM includes six different agents: people, houses, an insurer, a bank, a developer and a local government, each with their own behavior (Jenkins et al., 2016). The model was used to assess the interplay between different adaptation options; how risk reduction could be achieved or incentivized by different agents; and the role of flood insurance and DRR. The study by Haer et al (2016) focuses on the Port of Rotterdam, and evaluates the effect of different flood risk communication strategies on DRR, using an agent-based modelling approach (Figure 11). The results show that tailored, people-centred, flood risk communication can be significantly more effective than the common approach of top-down government communication. Furthermore, communication on how to protect against floods, in addition to providing information about flood risk, is much more effective than the traditional strategy of communicating only about flood risk. Another main finding is that a person’s social network can have a significant effect on whether or not individuals take protective action. This leads to the recommendation that social media can play an effective role in DRR.

Figure 11. Comparison of the implementation rates (%) of disaster risk reduction options over time, with and without including the effect if social networks between households (Haer et al., 2016).

6. Insurance, DRR and behaviour
While households have only limited control over the occurrence of a natural disaster, their actions determine the extent of losses during and after the event. An ENHANCE study for Germany applied Propensity Score Matching techniques to estimate flood damage reduction of DRR actions by households. Think for example of elevating houses of flood proofing the basement or lower floors of a building. The results show that DRR measures lowered damage during floods between €6,700 and €14,000 per flood event (Hudson et al., 2017). Another study also shows that flood damage mitigation measures implemented by households in France substantially saved damage during a variety of different flood events, and that these measures can be cost-effective (Poussin et al., 2015). However, households commonly do not invest in DRR measures, even when they are cost-effective. They insufficiently prepare for natural disasters, for example, because they underestimate low-probability natural disaster risk and the benefits of DRR.

Furthermore, the implementation of household DRR measures differs between individuals with, and without, flood insurance coverage in Germany (Hudson et al., 2014). The results show that individuals with flood insurance coverage in Germany are significantly more likely to have employed mobile flood barriers that keep flood water out of their home, while other risk reducing measures were often implemented by insured and non-insured individuals equally. These findings suggest that the moral hazard effect of insurance coverage is absent since households with flood insurance prepare more for floods. Additional analysis indicates that the better flood preparedness of the insured is related with activities of seeking information about flood risk, which can signal that the individuals who purchase flood insurance are more careful.

Figure 12. A summary table of the estimated average insurance premiums (EUR/per year) for Germany and France in 2015 and 2040 (Hudson et al., 2016).

Another ENHANCE study examined whether financial incentives offered by risk-based pricing of insurance in Germany and France can stimulate policyholder adaptation to flood risk (Hudson et al., 2016). This risk-based pricing implies that households receive a premium discount when they take measures that reduce flood risk. The effectiveness of such incentives is analysed using an integrated model of household level mitigation behaviour and public-private flood insurance. The results indicate that insurance based incentives are able to promote adaptation by correcting for individual misperceptions of flood risk and related benefits of DRR. The incentives could reduce residential flood risk by 12% in Germany and 24% in France by 2040. The higher level of flood risk in France results in a strong present incentive to reduce risk. Rapid growth of flood risks in Germany results in more effective incentives in later periods. An overall drawback of risk-based pricing is that flood insurance becomes potentially unaffordable for households who face a high risk. The study shows that such concerns for affordability can be overcome by providing insurance vouchers that help low-income households pay for flood insurance coverage. This voucher system that overcomes affordability concerns with risk-based flood insurance has a lower cost by 2040 than the benefits it brings of additional risk reduction. A main policy recommendation that follows from this study is that strengthening the link between insurance and DRR is worthwhile, but secondary policies may be needed to compensate additional costs for low-income households.

7. EU Solidarity Fund
The European Union Solidarity Fund (EUSF), is an ex-post loss-financing vehicle for EU member states and candidate countries for use in cases where a disaster exceeds the government’s re-sources to cope. Until 2014 the fund operated with an annual budget of €1 billion. However, the latest Multiannual Financial Framework (MFF 2014–2020) has halved its budget to €500 million (2011 prices). It covers only a fraction of the total damages in Europe: compensation has averaged about 3% of total direct losses since 2002. ENHANCE research shows an increase in expected losses, especially for extremes in 2050. This due to socioeconomic growth (~2/3) and climate change (~1/3). The increasing losses also give rise to a strong rise of 1/200 insured loss (Solvency II capital requirement) from ~€ 116 billion in 2013 to ~€ 236 billion by 2050 due to the large increase in losses. ENHANCE identified three different options for multi-stakeholder partnership development of the EUSF to cope with these future challenges:
• Option 1: eliminate the upper limit of the Fund, which is currently €500 million annually (with option-al borrowing from previous/subsequent years)
• Option 2: further strengthen the link between the EUSF and disaster risk reduction contributions to the Fund not only to take into account the economic performance of member states but also the risk reduction measures implemented by the country.
• Option 3: completely or partially transform the EUSF into a pre-disaster instrument that supports (reinsures) a national (public/private) insurance system with more affordable premiums.

Figure 13. Different adaptation schemes to reduce flood risk in Europe (Jongman et al., 2014)

8. Insurance and DRR
Insurance is a key economic instrument in the context of DRR, offering a shift in the mobilization of financial re-sources away from ad hoc post-event payments, where funding is often unpredictable and delayed, toward more strategic and, in many cases, more efficient approaches that were arranged in advance of disastrous events (Linnerooth–Bayer and Hochrainer-Stigler, 2015). The main function of insurance is the financial transfer of risks and compensation for losses. However, if correctly designed and implemented, it can also support DRR and climate adaptation (Surminski et al., 2015). Within this context, insurance may be delivered using a range of approaches, such as risk pools, private insurance, or public insurance schemes, addressing different hazards at different scales, including proper-ty, agriculture, and sovereign risk insurance. Feasibility, effectiveness, and the potential for incentivizing behavioural change vary across the different types and forms of insurance. Methodologies for comparing and assessing these characteristics are currently starting to emerge (for Europe see Paudel et al., 2012). While it is clear that insurance can contribute to disaster risk management, a range of challenges also exists, including a lack of comprehensive information and cognitive biases, as well as financial constraints and moral hazard.
ENHANCE introduces six different methodologies for assessing the linkages between insurance and risk reduction: Stress testing, investigation of flood insurance and moral hazard, estimation of effectiveness of house-hold-level flood risk mitigation measures, assessment of risk-based insurance pricing incentives for flood risk mitigation, analysis through a risk reduction framework, and investigation of the design principles of insurance.

Based on the case studies, our analysis reveals a range of important insights that are relevant to individuals who consider, design, operate, or participate in insurance schemes. An area of particular interest is the role of MSPs for the provision of disaster insurance. Here, our case studies highlight the importance of increased evidence and understanding of underlying risk issues, enhanced collaboration of stakeholders, and openness about limitations and costs. The issue spans many dimensions, which makes innovation and re-form challenging for political decision-makers and private companies.

9. Policy implications Insurance and DRR
The discourse about disaster insurance in Europe highlights the key challenges of managing current risks and preparing for future climate risks: at the core lies the issue of collective versus individual responsibility, and solidarity versus market-based approaches. The ENHANCE analysis shows that flood insurance and DRR need to be closely linked and integrated in the face of rising losses in order for insurance schemes to remain viable in the future. However, as our case studies show, there are significant barriers facing public and private stakeholders. This requires policy action—at EU and national, as well as regional level. The key question therefore is how to determine and define the roles of industry and policy-makers, recognizing that this is likely to differ from country to country (Surminski et al., 2015). At European level the facilitation of DRR and adaptation, which will determine risk levels and viability of insurance going forward, can be supported by EU-led policies. However, the design and operation of insurance schemes can also play a role in this. Here national governments have a role to play.

BOX: Wildfires Portugal

Every year, forest fires have a major impact on urban areas and the environment in Portugal. In 2003, the district of Santarém, Central Portugal, was severely affected by wildfires, with almost 64 thousand hectares burned. The goal of the Portuguese case study was to analyse the Multi-Sector Partnership (MSP) and the economic instruments (e.g. insurance) which could promote the society’s resilience to forest fires. Risk assessment show estimated losses above €100 million for the Santarém district, for the three most extreme years (1991, 2003 and 2005). Fire Weather System index (DSR) analysis for the period 2002-2012 shows that large burned areas only occur as a result of wildfire in the few days that the weather is extreme (See Figure below).

Figure 14. Burned areas per DSR (Daily Severity Rating) class (left graph) and number of days per DSR class (right)

An economic instrument that is already used by the MSP, is the Permanent Forest Fund, which supports the Forestry Technical Offices. Research suggests the European Solidarity Fund (EUSF) has supported the recovery of fire losses (EC, 2016), but the perception within the MSP is that, although there were many resources available after a major disaster, there was no incentive for new DRR for preventing future disasters. The recommendation to the EUSF is to provide mandatory rules for DRR when losses are compensated.

The ENHANCE analysis on the EU Solidarity Fund (Jongman et al., 2014) shows that socio-economic development and climate change can substantially increase pressure on risk transfer or financing mechanisms, unless more risk reducing measures are applied, such as flood defences, stricter building codes and/or land use (zoning) policies. Improved risk assessment and data sharing amongst stakeholders are essential for developing those forward-looking solutions in an integrated way. National, local and household level DRR activities could be used as a mechanism for reducing the pressure placed on risk transfer schemes. In other words, risk reduction efforts are essential in maintaining the insurability of these risks, especially in the context of flooding and other extreme weather events. Effective adaptation may actually become a condition for granting insurance cover in the future (Surminski et al., 2015). However, the ENHANCE analysis suggests that until today efforts to reform disaster compensation mechanisms in Europe have been predominantly focused on dealing with the financial losses, without considering the implications of these mechanisms for managing and reducing the underlying risks.

Table 2. Relation between EU legislation, Insurance and DRR (Surminski et al., 2016)

Our modelling approach and findings are highly relevant for wider discussions on the potential of insurance schemes to incentivize flood risk management and climate adaptation in the EU and beyond. In Table 2, we show the links between EU policies and insurance, and where there is a potential to steer insurance schemes to increase incentives for DRR and risk assessment. There is a clear current momentum at international level to use insurance to incentivize risk prevention and adaptation, as highlighted by the increased efforts to design new insurance schemes in developing countries through the new G7 ‘insu-resilience’ initiative, and underpinned by the UNFCCC’s Paris Agreement (see Surminski et al., 2016). As we have shown across the different ENHANCE case studies, the engagement of multi-sector partners and the clarification of their roles and responsibilities will determine if and how those new schemes can support climate resilience. This is an opportunity, and the lessons from across Europe provide important insights that can help to harness disaster insurance for risk reduction and climate adaptation.

10. DRR and other economic instruments
Economic instruments, such as risk financing instruments, water pricing and water markets, private-public partner-ships, taxes, and others, can produce incentivizing behaviour and increase the uptake and efficiency of adaptation measures by MSPs. The effectiveness of these instruments at reducing risk is frequently debated in the policy and science spheres. Yet, the evidence base on their effectiveness remains limited (even for insurance-related instruments) and there are few conceptual and numerical analyses (Agrawala and Fankhauser, 2008; Kunreuther and Michel-Kerjan, 2009; Bräuninger et al., 2011). By synthesizing recent literature, we have considered two broad types of instrument categories that are relevant for DRR (see also Chambwera et al., 2014; Bräuninger et al., 2011):
1. Market-Based Instruments (MBI) are instruments administered by government regulators that provide a monetary/economic incentive promoting risk management and adaptation. According to the EU white paper, the definition of MBI is broad (see EU Commission, 2009) and in the interpretation of this chapter it includes natural resource pricing, taxes, subsidies, marketable permits, payments for ecosystem services, licences, property rights and habitat banking.
2. Risk Financing Instruments (RFI) comprise all instruments that promote the sharing and transfer of risks and losses. They generally can be classified as pre-disaster arrangements, and comprise insurance, weather derivatives and catastrophe bonds, and many of those are indeed market-based as well.

Using these two instruments, ENHANCE identified three channels through which these economic instruments can contribute to risk management: (1) direct risk reduction: for example, risk financing provides direct compensation payments, which reduce follow-on impacts from an event; (2) indirect risk reduction: incentives for risk management and increased resilience help to reduce and manage risks, (3) managing systemic risk: both down-and upside risk are managed; the insurance takes the down-side (bad risks) risks out of investment decisions, and focuses on harnessing upside risks (good risks).

BOX: Jucar basin; Droughts and water pricing

The Júcar River Basin is a complex water resources system located in eastern Spain, highly regulated and with a high share of water for crop irrigation (about 83%), in which water scarcity, irregular hydrology and groundwater overdraft cause droughts to have significant economic, social and environmental consequences. The basin has been used as a test case to apply scarcity-based water pricing policies and water markets as potential instruments to manage drought risk. Scarcity-based water pricing policies are based on the marginal economic value of water (Pulido-Velazquez et al., 2013, Macian-Sorribes et al., 2015). When water storage is high, the marginal value of water is low, while low storage (drought periods) is associated with high marginal values.

In order to assess the impacts of these economic instruments, two new tools were developed and applied to allocate available water resources through simulation and optimization approaches. The simulation tool (SIMGAMS) allocates water resources according to system priorities and operating rules, evaluating the scarcity costs through economic demand functions. The optimization tool (OPTIGAMS) allocates water resources to maximize net benefits (or minimize total water scarcity cost plus operating cost at river basin scale). SIMGAMS allows for simulating incentive-based water pricing policies based on water availability in the system (scarcity pricing), while OPTIGAMS is used to simulate the effect of ideal water markets by economic optimization.

As the Júcar River Basin has a high share of water use for crop irrigation (around 80%), we also assessed the impact of drought on irrigated agriculture production using an econometric approach (Lopez-Nicolas et al. 2015). For this purpose, a two-stage approach has been applied (Gil-Sevilla et al., 2010 and 2011): first, an econometric model has been fitted to explain the impacts of water resource availability and crop price volatility on the agricultural production value. Monte-Carlo algorithms are then used to consider the contribution of the variability of the hydrology on drought risk and impacts.

The results show the potential of applying economic instruments to deal with drought risk management. Water pricing policies and water markets have a positive impact on drought risk management, reducing the total scarcity cost during drought periods. Scarcity-based water pricing policies send a scarcity signal to water users (when the storage decreases water price increases). So this works as an incentive to-wards a more efficient water use.

Figure 15. Jucar river (left) and the elements considered in the drought risk analysis

ENHANCE results show risk transfer could play an important role in risk reduction by incentivizing the take-up of risk reduction measures. Risk transfer removes or reduces the risk of experiencing an uncertain financial loss. However, if designed and operated appropriately, it can also play a role in physical risk reduction and adaptation. Measuring this effectiveness remains a challenge, particularly in the context of public-private partnerships because success or failure often only becomes evident after another risk event, and it requires in-depth data collection on the ground.

ENHANCE examined the scope of different economic instruments for enhancing resilience and managing risk, and applied a common framework based on multi-criteria analysis to assess economic instruments in the case studies, in order to specify the suitability of those instruments. The criteria (and associated) indicators comprised the following aspects: economic efficiency, including the link to incentivize disaster risk management, social equity, political and institutional applicability, and environmental effectiveness. Operationalizing the criteria universe with a multi-criteria decision-making approach allowed ENHANCE analysts to apply a qualitative scoring matrix to economic instruments across five ENHANCE case studies.

11. References
Agrawala, S. Fankhauser, S. (2008). Economic Aspects of Adaptation to Climate Change. Costs, Benefits and Policy Instruments. OECD, Paris.
Bräuninger, M., Butzengeiger-Geyer, S., Dlugolecki, A., Hochrainer, S., Köhler, K., Linnerooth-Bayer, J., Mechler, R., Michaelowa, A., Schulze, S. (2011). Application of economic instruments for adaptation to climate change. Report to the European Commission, Directorate General CLIMA, Brussels.
Bubeck P., W.J.W. Botzen, J.C.J.H. Aerts (2012) A review of risk perceptions and other factors that influence flood mitigation behavior. Risk Anal., 32 (2012), pp. 1481–1495 http://dx.doi.org/10.1111/j.1539-6924.2011.01783.x
Carrera, L., Standardi, G., Koks, E., Feyen, L., Aerts, J., Mysiak, J. and Bosello, F.: Economic impacts of flood risk under current and future c limate, Clim. Change, 2015.
Dasgupta and Serageldin ed. (2000). Social Capital. A Multifaceted Perspective. The World Bank, Washington DC. Paperback edition in 2005 from Oxford University Press, Oxford, 420 pp.
De Groeve, T., Poljansek, K. and Ehrlich, D. (2013). Recording Disaster Losses Recommendations for a European approach.
De Groeve, T., Poljansek, K., Ehrlich, D. and Corbane, C. (2014). Current status and best practices for disaster loss data recording in EU Member States, European Commission - Joint Research Centre: Institute for the Protection and the Security of the Citizen, Ispra.
Embrechts, P., Klüppelberg, C., Mikosch, T. (2013). Modelling Extremal Events: for Insurance and Finance. 1st ed. 1997. Corr. 4th printing 2013. Springer, Berlin.
Goodwin, N.R. (2003). Five Kinds of Capital: Useful Concepts for Sustainable Development. http://www.ase. tufts.edu/gdae/publications/working_papers/03-07sus-tainabledevelopment.pdf.
Grossi, P., Kunreuther, H.C. (2005). Catastrophe Mode-ling: A New Approach of Managing Risk. Springer, New York.
Herweijer, C., Ranger, N. Ward, R.E. (2009). Adaptation to climate change: threats and opportunities for the insurance industry. The Geneva Papers on Risk and Insurance, 34, 360-380.
Hochrainer-Stigler, S., Linnerooth-Bayer, J. and Lorant, A. (2015). The European Union Solidarity Fund: an assessment of its recent reforms, Mitig. Adapt. Strateg. Glob. Chang., 1–17, doi:10.1007/s11027-015-9687-3.
Hudson, P., Botzen, W., Bubeck, Ph., Kreibich, H., Aerts, J.C.J.H. (2015) An evaluation of flood damage mitigation measures in Germany: A first application of Propensity Score Matching. Nat. Hazards Earth Syst. Sci, 14, 1731–1747, 2014
Hudson, P., Botzen, W., Czajkowski, J., Kreibich, H. (2017). Moral Hazard in natural Disaster Insurnace Markets: Empirical Evidence from Germany and the United States. Land Economics, 93 (2), 179-208
Hudson, P., Botzen, W.J.W., Feyen, L. & Aerts, J.C.J.H. (2016). Incentivising flood risk adaptation through risk based insurance premiums: trade-offs between affordability and risk reduction. Ecological Economics, 125, 1-13. doi: 10.1016/j.ecolecon.2016.01.015
IPCC (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.J., Ebi, K.L., Mastrandrea, M.D., Mach, K.J., Plattner, G.K., Allen, S.K., Tignor, M., Midgley, P.M. (eds.). Cambridge: Cambridge University Press.
IPCC (2014). Impacts, Adaptation and Vulnerability. Working Group II Contribution to the Fifth Assessment Re-port of the Intergovernmental Panel on Climate Change. Cambridge University Press.
IRGC (2005). http://www.irgc.org/risk-governance/irgc-risk-governance-framework/.
Johnson, B. B. and V. T. Covello (eds) (1987). The Social and Cultural Construction of Risk: Essays on Risk Selection and Perception. Boston, MA: D. Reidel.
Jongman B, Hochrainer-Stigler S, Feyen L, Aerts JCJH, Mechler R, Wouter Botzen WJ, Bouwer LM, Pflug GC, Rojas R, Ward PJ (2014), Increasing stress on disaster-risk finance due to large floods. Nature CC, 4(4):264-268
Jongman, B., Winsemius, H., Aerts, J.C.J.H., Coughlan de Perez, E., van Aalst, M.K., Kron, W., Ward Ph.J. (2015). Declining vulnerability to river floods and the global benefits of adaptation. PNAS. E2271–E2280, doi: 10.1073/pnas.1414439112
Kellermann, P., Schöbel, A., Kundela, G., and Thieken, A. H. (2015c): Estimating flood damage to railway infrastructure – the case study of the March River flood in 2006 at the Austrian Northern Railway, Nat. Hazards Earth Syst. Sci., 15, 2485-2496, doi:10.5194/nhess-15-2485-2015.
Koks, E.E., Bockarjova, M., Moel, H. de & Aerts, J.C.J.H. (2014). Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis. Risk Analysis. 10.1111/risa.12300
E.E. Koks, O. Jonkeren, L. Carrera, J.C.J.H. Aerts, T.G. Husby, M. Thissen, G. Standardi, and J. Mysiak (2016) Research article Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models. NHESS, 16, 1911-1924, doi:10.5194/nhess-16-1911-2016
Kondra, A.Z. and Hinings, C.R. (1998). ‘Organizational diversity and change in institutional theory’, Organization Studies,19 (5):743–67.
Kunreuther, H., Michel-Kerjan, E. (2009). At War with the Weather: Managing Large-Scale Risks in a New Era of Catastrophes. MIT Press, New York.
Linnerooth-Bayer, J., Hochrainer-Stigler, S. (2015). Financial instruments for disaster risk management and climate change adaptation. Climatic Change, pp.1-16. Article in Press.
Luhmann N. (1993). Risk: A Sociological Theory. Berlin: De Gruyter.
Maynard, T. Ranger, N. (2011). What role for ‘long-term’ insurance in adaptation? An analysis of the prospects for and pricing of multi-year insurance contracts. Working Paper No. 62. Grantham Research Institute on Climate Change and the Environment, London.
Mechler, R., Bouwer, L.M., Linnerooth-Bayer, J., Hochrai-ner-Stigler, S., Aerts, J.C.J.H., Surminski, S., Williges, K. (2014). Managing unnatural disaster risk from climate extremes. Nature Climate Change, 4: 235–237.
Mechler, R. and T. Schinko (2016). Identifying the policy space for climate loss and damage. Science 354 (6310), 290-292
Moel, H. de, Mathijs van Vliet and Jeroen C.J.H. Aerts (2014) Evaluating the effect of flood damage reducing measures: a case study of the un-embanked area of Rotterdam, the Netherlands. Regional Environmental change, 14, 895-908, DOI 10.1007/s10113-013-0420-z
Munich Re (2014). Natural catastrophes 2013: Analyses, assessments, positions. Topics GEO. Munich Re, Munich.
Munich Re (2015). Loss events worldwide 2014: 10 costliest events ordered by insured losses. Munich Re Geo Risks Research, NatCatSERVICE.
Mysiak, J., Surminski, S., Thieken, A., Mechler, R., and Aerts, J. (2016). Brief communication: Sendai framework for disaster risk reduction – success or warning sign for Paris? NHESS, in review.
OECD (2008). Measuring sustainable development. Re-port of the Joint UNECE/OECD/Eurostat Working Group on Statistics for Sustainable Development. http://www. oecd.org/greengrowth/41414440.pdf.
Pahl-Wostl, C., Sendzimir, J., Jeffrey, P., Aerts, J., Berkamp, G., and Cross, K. (2007). Managing change toward adap-tive water management through social learning. Ecology and Society 12 (2), 30.
Paudel, Y., Aerts, J., Botzen, W. (2012). Public private catastrophe insurance. Geneva Papers on Risk and Insurance, 37, 257-285.
Poussin, J., Botzen, W.J., Aerts, J.C.J.H. (2014). Factors of influence on flood damage mitigation behaviour by households. Environmental Science and Policy DOI: 10.1016/j.envsci.2014.01.013
Poussin, J.K., Botzen, W.J.W., Aerts, J.C.J.H. (2015) Effectiveness of flood damage mitigation measures: Empirical evidence from French flood disasters. Global Environmental Change 31, 74-84
Renn, O. (2008). Risk Governance. Coping with Uncertainty in a Complex World. London: Earthscan.
Rhodes, R. A. W. (1997). Understanding governance: policy networks, governance, reflexivity and accountability. Buckingham.
Sadoff, C.W., Hall, J.W., Grey, D., Aerts, J.C.J.H., Ait-Kadi, M., Brown, C., Cox, A., Dadson, S., Garrick, D., Kelman, J., McCornick, P., Ringler, C., Rosegrant, M., Whittington, D. and Wiberg, D. (2015) Securing Water, Sustaining Growth: Report of the GWP/OECD Task
Force on Water Security and Sustainable Growth, University of Oxford, UK, 180pp.
Serageldin, I., Steer, A. (Eds.) (1994). Making Development Sustainable: From Concepts to Action. Washing-ton, World Bank, Environmentally Sustainable Development Occasional Paper Series, No 2.
Slovic, P. (1999). Trust, Emotion, Sex, Politics, and Science: Surveying the Risk-Assessment Battlefield. Society Risk Analysis, 19(4), 689-701.
Slovic, P., Finucane, M.L., Peters, E. and MacGregor, D.G. (2004). Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality. Risk Analysis, 24(2), 1-12.
Smit (1776). http://eepat.net/doku.php?id=human_capi-tal_theory_and_education.
Stallings, R. A. (1990). `Media Discourse and the Social Construction of Risk’, Social Problems 37(1): 80-95.
Surminski, S. and Oramas-Dorta, D. (2014). Flood Insurance Schemes and Climate Adaptation in Developing Countries. International Journal of Disaster Risk Reduction (in Press).
Surminski, S., Aerts, J. C. J. H., Botzen, W. J. W., Hudson, P., Mysiak, J. and Pérez-Blanco, C. D. (2015). Reflections on the current debate on how to link flood insurance and disaster risk reduction in the European Union. Natural Hazards, 79(3), pp.1451-1479.
Surminski, Swenja and Eldridge, Jillian (2015) Flood insurance in England: an assessment of the current and newly proposed insurance scheme in the context of rising flood risk. Journal of Flood Risk Management . ISSN 1753-318X
Tschakert, P., and K. A. Dietrich (2010). Anticipatory learning for climate change adaptation and resilience. Ecology and Society 15(2): 11.
Twigg, J. (2009). Characteristics of a Disaster-Resilient Community. A Guidance Note. Version 2. November 2009. DFID Disaster Risk Reduction Interagency Coordination Group. UK Department for International Development: London.
Ulfarsson, G. F. and Unger, E. A.: Impacts and Responses of Icelandic Aviation to the 2010 Eyjafjallajokull Volcanic Eruption, Transportation Research Record, J. Transport. Res. Board, 2214, 144–151, 2011.
UNFCCC (2015). Adoption of the Paris Agreement. Decision FCCC/CP/2015/L.9. https://unfccc.int/resource/ docs/2015/cop21/eng/l09r01.pdf.
UNISDR (2011). GAR 2011. Global Assessment Report on Disaster Risk Reduction. Revealing Risk, Redefining Development. United Nations International Strategy for Disaster Reduction Secretariat, Geneva.
UNISDR (2015). Sendai Framework for Disaster Risk Reduction 2015–2030, A/CONF.224/CRP.1, 18 March 2015, 2015b.
Watkiss, P. et al. (2014). ‘The use of new economic decision support tools for adaptation assessment: A review of methods and applications, towards guidance on applicability’, Climatic Change, http://dx.doi.org/10.1007/ s10584-014-1250-9.

Potential Impact:
ENHANCE was a project with scientific objectives, but strongly engaged with EU policymaking communities across the different sectors (energy, water, agriculture, transportation, and health) covered by the project. The primary impacts of the project are in terms of its scientific outputs, as evidenced by the many scientific outputs (detailed in the periodic reports) produced by project partners on the basis of ENHANCE research. Also our research contributed to, or has been acknowledged and quoted in, several high-level policy reports or documents. A dissemination plan, including an open communications platform, was developed at the start of the project, and updated throughout the project to be sure we were reaching the audiences and policy domains potentially interested in the results, and to be able to link to new opportunities which came into existence during the project. Also, project partners were stimulated to synthesize and disseminate the scientific knowledge into policy relevant information, understandable for a broad public This was the framework within which the dissemination and impact of the project was managed.

1. Scientific impact
The ENHANCE project has produced a considerable scientific output, and has supported many scientific conferences across the globe. With over 78 peer reviewed papers and book chapters, under which 7 in Science PNAS and Nature, the scientific output can be considered as good. In the Science paper by Aerts et al. (2014) we showed how risk assessment and Cost benefit Analysis can help policy makers in develop DRR and adaptation strategies to reduce risk from flooding in coastal cities. This paper was applied to New York City, a partner city of the ENHANCE case study Rotterdam. Furthermore, in Jongman et al. (2015) we showed that vulnerability, albeit difficult to determine, is an important driver of disaster damage and that annual hazard variability alone only explains a minor part of the observed variation in the recorded damage. Munch RE was supporting the paper by providing the latest empirical data of global flood losses. Finally, in the papers by Mechler et al. (2014; 2016) contributions were made to the Warsaw Mechanism for Loss and Damages. Both publications were used during COP 21 and 22 in Paris and Marrakesh, respectively.
All scientific results have been compiled in an ENHANCE synthesis book. This book has been published with VU University press, and is also online available: www.enhanceproject.eu/deliverables/3

High impacts papers are:
Aerts, J.C.J.H., Botzen, W.J.W., Emanuel, K., Lin, N., de Moel, H., Michel-Kerjan, E.O., (2014). Evaluating flood resilience strategies for coastal megacities. Science, 344, 473-475.
Aerts, J.C.J.H., Botzen, W.J.W., (2014). Cities’ response to climate risks. Nature CC. 4 (9), 759-760.
Jongman, B., Winsemius, H., Aerts, J.C.J.H., Coughlan de Perez, E., van Aalst, M.K., Kron, W., Ward P.J., (2015). Declining vulnerability to river floods and the global benefits of adaptation. PNAS. E2271–E2280.
Jongman, B., Hochrainer-Stigler, S., Feyen, L., Aerts, J.C.J.H., Mechler, R., Botzen, W.J.W., Bouwer, L.M., Pflug, G.C., Rojas, R., Ward, P.J., (2014). Increasing stress on disaster-risk finance due to large floods. Nature CC, 4(4), 264-268.
Mechler, R., Bayer, J., Surminski, S., Aerts, J.C.J.H., Williges, K. (2014). Managing unnatural disaster risk from climate extremes. Nature CC, 4(4), 235-237.
Mechler, R., Schinko, T. (2016). Identifying the policy space for climate loss and damage. Science 354 (6310), 290-292.
Surminski, S., Bouwer, L.M., Linnerooth-Bayer, J., (2016). How insurance can support climate resilience. Nature CC, 6, 333–334.

ENHANCE furthermore has coordinated a special issue in the high-level journal ‘Earth Future’. The special issue will comprise about 15 papers on disaster risk reduction and Multi Sectoral Partnerships (MSPs). The issue is closed and the review procedures are ongoing.

Figure 16. Earth Future journal (left) that is used as special issue for ENHANCE on Multi Sectoral Partnerships. And a cover of the high level paper in PNAS on flood vulnerability (right)

In addition, ENHANCE has presented in numerous scientific conferences, and has co-organized scientific session. A selection of those events include: the European Geophysical Union (EGU), which is yearly held in Vienna. The Understanding Risk conferences, The American Geophysical Union (AGU, San Francisco), and The Global Conference for Environmental Economy.

2. Specific scientific contributions by ENHANCE:
A. Risk Assessment: Assessing Extremes and Copulas
In a publication in Nature CC (Jongman et al., 2014) we extended existing approaches to estimate risk from extremes. Current methods estimate risk from historical loss data using extreme value theory, according to which, natural disaster risk distributions are estimated using, for example, Gumbel, Weibull, or Frechet distributions. Risk and losses, however, are spatially correlated and this is often not accounted for in these techniques. In ENHANCE, a new approach (Coppula’s) was applied to assess flood risk in the EU (e.g. Jongman et al., 2014). With this new approach, EU flood risk was estimated 17% higher as compared to conventional methods.

In addition, Jongman et al. (2014) shows that it is important for risk assessments to understand the dynamics of the underlying causes of risk. For example, the projections of climate variability and change should ideally be based on an ensemble of (regional) climate models that capture a broad spectrum of underlying uncertainties. Moreover, information about exposed economic assets and their vulnerability to hazards is needed. Jongman et al. (2014) highlighted that combining these three dimensions is a non-trivial task, especially for the assessment of extremes. In response to this, ENHANCE recommends to develop open access databases with information on historical losses from natural hazards.

B. Indirect economic effects.
In risk assessment studies, one can distinguish between direct and indirect effects (Koks et al., 2014). Direct effects can be defined as the impacts on buildings, infrastructure, and people. Indirect effects are effects outside the impacted area, because business and other stakeholders that have economic ties to the impeded region cannot produce or deliver/receive goods to/from the impacted region (Okuyama and Santos, 2014). In several novel publications (e.g. Carrera et al., 2015; Koks et al., 2014; 2015; 2016) we show the economic relations between households and industries located outside a flooded area, with the activities inside a flooded area. These linked supply businesses, cannot supply or receive their goods and services to/from the business and people in the flooded area, and therefore, indirectly suffer in case a flood happens (Koks et al., 2016). These costs (e.g. business interruption) can amount up to 40% of the total damage. ENHANCE recommends EU policies to improve the assessment of indirect economic damages, and to develop new policies that require companies to evaluate whether they are equipped to recover business when supply areas (such as port cities) are flooded.

C. Influence of behaviour / perception on risk: Agent based Models
In an analysis of global food vulnerability in the high level journal PNAS (Jongman et al., 2015), we showed that vulnerability has a large influence on assessing risk. For example, when zooming in on Pakistan, it appeared that large fatalities were recorded in during the 1993 floods. However, a few years later in 1995, a larger flood occurred in Pakistan, but fatalities were much lower. This can predominantly be explained by different perception and behaviour of people. Because individuals had the experience from the previous flood, and the communication and warning systems had been improved, people could better prepare themselves, reducing losses significantly.

ENHANCE research applied Agent based Models (ABM) to simulate the effects from such individual household behaviour. We used ABMs to aggregate the effect of all these individual DRR (Disaster Risk Reduction) activities, and estimate their effect on the overall risk in a region or country. This research confirms trends in flood risk in the Netherlands showing that without considering individual behavioural aspects of households, (future-) risk is overestimated by a factor 2 (Haer et al., 2016).

Figure 17. relation between fatalities and floods in Pakistan. While there were many fatalities in 1993 during a flood, an even larger flood in 1995 did result in much lower number of fatalities, This can only be explained by risk reduction and reduced vulnerability (Jongman et al., 2015).

Learning about the behaviour of individuals towards adaptation, risk, and how people perceive risk can also contribute to an improved risk communication to those living and working in hazard prone areas. Targeted communication to individuals should show the consequences of disasters to them and their property if they do not undertake protective measures now, but should also demonstrate the socio-economic benefits of adaptation. Behavioural risk modelling using ABM can compare the effects of different communication strategies (Jenkins et al. 2016; Haer et al., 2016), and tap into the enormous –aggregate- potential of individuals that can significantly contribute to risk reduction.
ENHANCE, therefore recommend to further develop current EU policies such as the flood directive and EU Solidarity fund, to ask member states informing individuals about their risk, But also inform them how they can implement DRR at the local scale. Note in this respect, that much DRR efforts are targeted at large urban centres, and less on the rural areas –these latter areas still account for a significant portion of all disaster losses in the EU.

D. Insurance, DRR and households
While households have only limited control over the occurrence of a natural disaster, their actions determine the extent of losses during and after the event. An ENHANCE study for Germany estimated flood damage reduction of DRR actions by households. The results show that DRR measures lowered damage during floods between €6,700 and €14,000 per flood event (Hudson et al., 2015). Another study also shows that flood damage mitigation measures implemented by households in France substantially saved damage during a variety of different flood events, and that these measures can be cost-effective (Poussin et al., 2014; 2015). However, households commonly do not invest in DRR measures, even when they are cost-effective. They insufficiently prepare for natural disasters, for example, because they underestimate low-probability natural disaster risk and the benefits of DRR.

The implementation of household DRR measures differs between individuals with, and without, flood insurance coverage in Germany (Hudson et al., 2016). The results of this study show that individuals with flood insurance coverage are significantly more likely to have employed mobile flood barriers that keep flood water out of their home, while other risk reducing measures were often implemented by insured and non-insured individuals equally. These findings suggest that the moral hazard effect of insurance coverage is absent since households with flood insurance prepare more for floods.

E. Insurance policy recommendation
The analysis of ENHANCE case studies shows that for flood- and fire disaster, insurance schemes and DRR need to be closely linked and integrated in the face of rising losses in order for insurance schemes to remain viable in the future. An example is given in the Figure below on the Flood RE scheme in the UK, where without DRR, premiums will steeply rise in the future. However, as our case studies show, there are significant barriers facing public and private stakeholders. This requires policy action—at EU and national, as well as regional level. The ENHANCE analysis on the EU Solidarity Fund (Jongman et al., 2014) shows that socio-economic development and climate change can substantially increase pressure on risk transfer or financing mechanisms, unless more risk reducing measures are applied, such as flood defences, stricter building codes and/or land use (zoning) policies. Effective adaptation may actually become a condition for granting insurance cover in the future (Surminski et al., 2015; Hudson et al., 2015). However, the ENHANCE analysis suggests that until today efforts to reform disaster compensation mechanisms in the EU have been predominantly focused on dealing with the financial losses, without considering the implications of these mechanisms for managing and reducing the underlying risks.

Figure 18. Example UK flood insurance: UK taxpayers exposed to rising risks as Flood Re fails to incentivise risk reduction.

F. EU Solidarity Fund
ENHANCE research (Jongman et al., 2014; Hochrainer-Stigler et al., 2015) shows an increase in expected losses, especially for extremes in 2050. This due to socioeconomic growth (~2/3) and climate change (~1/3). The increasing losses also give rise to a strong rise of 1/200 insured loss, which is the Solvency II capital requirement, from ~€ 116 billion in 2013 to ~€ 236 billion by 2050 due to the large increase in losses (see Figure below). ENHANCE identified three different options for multi-stakeholder partnership development of the EUSF to cope with these future challenges:
• Option 1: eliminate the upper limit of the EUSF, which is currently €500 million annually (with option-al borrowing from previous/subsequent years)
• Option 2: further strengthen the link between the EUSF and disaster risk reduction contributions to the Fund not only to take into account the economic performance of member states but also the risk reduction measures implemented by the country.
• Option 3: completely or partially transform the EUSF into a pre-disaster instrument that supports (reinsures) a national (public/private) insurance system with more affordable premiums, and hence a higher market penetration.

G. UNFCCC Loss and Damage: risk Layering
ENHANCE has further pushed the role of DRR within the climate change / UNFCCC community, through a leading role in the UNFCCC (Mechler et al., 2014; Mechler and Schinko, 2016). In a concept called Risk layering, it was demonstrated this can help to differentiate between distinct levels of risk organized around return periods (or probability) and the degree of stress imposed by risk. Risk layering is a concept underlying many areas of risk policy, especially agricultural and insurance risk management. This approach can reveal risk management / adaptation options that are differentially effective for low-, medium- and high-probability events as well as tailored to the different risk bearing capacities of communities, governments and international organizations. Such nuanced understanding of risk management can also be helpful in identifying risks that are ‘beyond adaptation’.

Figure 19. increase flood losses in the EU, for different flood probability scenarios (1/10; 1/20; 1/30, etc), until the year 2050 (Jongman et al., 2014)

3. Main dissemination activities
The ENHANCE project had a number of different mechanisms for interactions with policymakers, stakeholders and the wider public.

A. Meetings and conferences with policymakers and stakeholders
ENHANCE has presented its results at international conferences for policy makers and stakeholders throughout the project (UNISDR, Geneva 2013; Adaptation Futures 2014), Delta conference (Rotterdam, 2014), Third UN World Conference on Disaster Risk Reduction (WCDRR, Sendai/Japan, March 14-18, 2015), the European Climate Change Adaptation Conferences (Copenhagen, May 2015), ENHANCE has presented on several European Forum on Disaster Risk Reduction (EFDRR) meetings, in 2014, 2015 and 2016, at sessions at several COPs, and at the OECD High level conference on flood risk (Paris, May 12-13 2016). We also organised a high policy level workshop on possible reform of the European Solidary Fund (Brussels, October 2015).

More specific on the topic of insurance we have undertaken the following activities:
• The ENHANCE core group on insurance has officially responded to the EU green paper on Insurance: ENHANCE Consortium’s response to “Green paper on the insurance of natural and man-made disasters (COM(2013) 213 final)” in
July 2013 (http://enhanceproject.eu/news/articles/22 ).
• Concurrently and in order to discuss implications for the Green Paper, the project took the lead in organising the successful High Level ‘Think Tank’ meeting with the insurance industry on “Public-Private partnerships in Flood Risk Management and Insurance” at the Munich RE office in Munich, Germany (December 2013).
• EC DG CLIMA workshop on disaster insurance (2016).
• Meetings with the EU Loss Data Systems initiative under auspices of the DRMKC.

During the project we had several direct meetings with policymakers, examples are the invitations to give evidence on flood insurance at a meeting of the Oireachtas Joint Committee on Finance, Public Expenditure and Reform in the Irish Parliament; and to participate in the stakeholder meeting at the Prime Minister Office Coordination unit on flood risk. Besides these meetings we have had bilateral meetings with EU ambassadors (Malta, Bulgaria, Netherlands, etc) and European Commission/Parliament.

B. Meetings and conferences with scientific audiences
• EGU (Vienna, 2015, 2016), Society for Risk Analysis Europe (Istanbul 2014; Denver 2015) to mention the most important. See table A2 for the full list of dissemination activities of the project.
• The ENHANCE project organized summer schools, capacity building workshops, stakeholder meetings and webinars to engage and bring together young-professionals from the private and scientific domain.

C. Project website
A well designed and active project website (www.enhanceprojcect.eu) was developed and maintained throughout the project. During the course of the project we received 50.000 unique visitors. This website will continue to be hosted at the VU University website for at least 3 years. It contains the following information:
o Interviews with project partners on their achievements
o External interviews with people who are involved with the topics we are working on, and to make our website even more attractive to external visitors. As for example the interview with Kristalina Georgieva, Commissioner for International Cooperation, Humanitarian Aid and Crisis Response (2008-2014)
o Public deliverables are made available to the general public
o Policy briefs (6) on specific topics available to the general public
o Informative videos with infographics to present ENHANCE and to explain with case studies examples the positive impacts multi-sector partnerships can have.

D. Booklet
Early on in the project (October 2015) we have developed a booklet, for increasing ENHANCE’s visibility at international conferences and events. The booklet contains general information about the project, its case studies and the methods that are used and developed. It also explains concisely the importance of multi-sector partnerships and explain what disaster risk reduction means. This booklet was very helpful in reaching a wider public and to make clear what the project was about.

E. Policy briefs
A series of policy briefs (6) on variouw topics were developed throughout the project. These were made available via the mailing list, which contains 900 people, and the website. Feedback suggests that these policy briefs were well received as substantive contributions to policy debates to the general public.

F. Synthesis book
We have published a synthesis book on the final results of the ENHANCE project at VU University press. This book is also available online. The book summarises and shows the key results of the scientific WPs and the case studies.

G. Social media
Twitter was used by ENHANCE as a part of its dissemination strategy to raise the project’s visibility online. For the first half of the project, EBN tried to engage with stakeholders interested in the topics covered by the ENHANCE project and its case studies using the hashtags #enhanceproject and #DisasterRiskReduction. As the results are scheduled later on in the project and as EBN focused mainly on the key deliverables and tasks on the year one of the project, Twitter has not been used extensively. Twitter was mainly used to share information about ENHANCE and the case studies.

4. Exploitation of results
Our research has inspired, set-off or otherwise informed new research and innovation actions including the Climate-KIC funded pathfinder Cost Adapt (FEEM), the Copernicus Climate Change Services (IVM-VU), and the others. Motivated by our results, the Port of Rotterdam – a private company - has invested more than 200.000 Euro in research to further investigate the risk from flood and climate change. The Wadden Sea Forum, established to advise the Trilateral Wadden Sea Convention, extended its focus to include disaster risk, as a result of the Enhance research. These are major acknowledgements of the impacts our research has on public and private choices, and a proof of broad knowledge-transfer.

Our research contributed to, or has been acknowledged and quoted in several high-level policy reports or documents including the OECD ‘Securing water, sustaining growth’, the EFDRR Outcome document, the 2016 EEA Report on Flood risks and environmental vulnerability -Exploring the synergies between floodplain restoration, water policies and thematic policies; the Bank of England’s 2015 report The impact of climate change on the UK insurance sector, and in the upcoming 2017 EEA Report on Disaster Risk Management and Climate Adaptation policies. Enhance project contributed to the EU Data Loss System initiative under auspices of the Join Research Centre (JRC), and the European Environmental Agency’s assessment of the disaster losses in Europe. We have submitted a contribution to the consultation initiated by the UN Open-Ended Intergovernmental Expert Working Group (OIEWG) on Indicators and Terminology. We have provided recommendations of how to integrate and reform various European and international policies on sharing and storing disaster loss data.

ENHANCE was referred to in the EEA’s review of the disaster losses in Europe. Furthermore, we have contributed to the consultation initiated by the UN Open-Ended Intergovernmental Expert Working Group on Indicators and Terminology (Mysiak et al., 2015) and developed recommendations on how to integrate and reform various European and international policies on sharing and storing disaster loss data. Finally, the ENHANCE project organized summer schools, capacity building workshops, stakeholder meetings and webinars to engage and bring together young-professionals from the private and scientific domain.

Based on the case study results, the ENHANCE project played a major role in further streamlining the merging realms of Climate change adaptation (CCA) and disaster risk reduction (DRR). For this, the ENHANCE project has been actively engaged with its partner UNISDR in the UN Sendai Framework for Disaster Risk Reduction 2015-2030, the Addis Ababa Action Agenda on risk financing, and the Paris Agreement on Climate Change on climate adaptation (Loss and Damage Discussion). The ENHANCE project contribution can be summarized as; (i) better understanding of risk and evidence-based and risk-informed public policies by introduction new risk assessment methods and data; and (ii) managing risk by means of assessing he pros and cons of novel Multi Sectoral Partnerships (MSPs). This risk-based approach has been actively communicated to high policy level through UNISDR and UNFCCC, but also to the private sector such as Munich RE, Port of Rotterdam and Austrian railways.

List of Websites:
Project public website and contact details
Project website: www.enhanceproject.eu
Contact details: Jeroen.aerts@vu.nl ; ralph.lasage@vu.nl

Related information

Contact

Jeroen Aerts, (Senior researcher)
Tel.: +31205989528
Fax: +31205989553
E-mail
Record Number: 197773 / Last updated on: 2017-05-10
Follow us on: RSS Facebook Twitter YouTube Managed by the EU Publications Office Top