Societal Impacts of Flood Hazards
Societal Impacts of Flood Hazards
- Philip Bubeck, Philip BubeckInstitute of Earth and Environmental Science, Potsdam University
- Antje OttoAntje OttoInstitute of Earth and Environmental Science, Potsdam University
- , and Juergen WeichselgartnerJuergen WeichselgartnerDepartment of Geography, University of Passau
Summary
Floods remain the most devastating natural hazard globally, despite substantial investments in flood prevention and management in recent decades. Fluvial floods, such as the ones in Pakistan in 2010 and Thailand in 2011, can affect entire countries and cause severe economic and human losses. Also, coastal floods can inflict substantial harm owing to their destructive forces in terms of wave and tidal energy. A flood type that received growing attention in recent years is flooding from pluvial events (heavy rainfall). Even though these are locally confined, their sudden onset and unpredictability pose a danger to areas that are generally not at risk from flooding. In the future, it is projected that flood risk will increase in many regions both because of the effects of global warming on the hydrological cycle and the continuing concentration of people and economic assets in risk-prone areas.
Floods have a large variety of societal impacts that span across space and time. While some of these impacts are obvious and have been well researched, others are more subtle and less is known about their complex processes and long-term effects. The most immediate and apparent impact of floods is direct damage caused by physical contact between floodwaters and economic assets, cultural heritage, or human beings, with the result for humans being injuries and deaths. Direct flood damage can amount to billions of US dollars for single events, such as the floods in the Danube and Elbe catchment in Central Europe in 2002 and 2013. More indirect economic implications are the losses that occur outside of the flood event in space and time, such as losses due to business disruption. The flood in Thailand in 2011, for instance, resulted in a lack of auto parts supplies and consequently the shutdown of car manufacturing within and outside the flood zone.
Floods also have long-term indirect impacts on flood-affected people and communities. Experiencing property damage and losing important personal belongings can have a negative psychological effect on flood victims. Much less is known about this type of flood impact: how long do these impacts last? What makes some people or communities recover faster than others from financial losses and emotional stress? Moreover, flood impacts are not equally distributed across different groups of society. Often, poor, elderly, and marginalized societal groups are particularly vulnerable to the effects of flooding inasmuch as these groups generally have little social, human, and financial coping capacities. In many countries, women regularly bear a disproportionately high burden because of their societal status.
Finally, severe floods often provide so-called windows of opportunities, enabling rapid policy change, resulting in new flood risk management policies. Such newly adopted policy arrangements can lead to societal conflicts over issues of interests, equity, and fairness. For instance, flood events often trigger large-scale investment in flood defense infrastructure, which are associated with high construction costs. Although these costs are usually borne by the taxpayer, often only a small proportion of society shares in their benefits. In addition, societal conflict can arise concerning where to build structural measures; what impacts these measures have on the ground regarding economic development potentials, different kinds of uses, and nature protection; and which effects are expected downstream. In such controversies, issues of participation and decision making are central and often highly contested.
While floods are usually associated with negative societal impacts in industrialized countries, they also have beneficial impacts on nature and society. In many parts of the world, the livelihood of millions of people depends on the recurring occurrence of flooding. For instance, farming communities in or near floodplains rely upon regular floodwaters that carry nutrients and sediments, enriching the soil and making it fertile for cultivation.
Subjects
- Floods
What Are the Societal Impacts of Flooding, and How Are They Addressed in the Natural Hazards Sciences?
Despite substantial investments in flood prevention and management in recent decades, floods remain the most devastating natural hazard globally (Munich Re, 2015). Fluvial floods such as the ones in Pakistan in 2010 and Thailand in 2011 can affect entire countries and cause severe economic and human losses. Also, coastal floods inflict substantial harm owing to their destructive forces in terms of wave and tidal energy, coupled with an increasing population and economic assets in coastal areas (Newton & Weichselgartner, 2014). A flood type that has received growing attention in recent years is flooding from pluvial events (heavy rainfall). Even though these are locally confined, their sudden onset and unpredictability also pose a danger to areas that are generally not at risk from flooding.
In the future, flood hazards are projected to further increase in many regions owing to the effects of global warming on the hydrological cycle. According to the Intergovernmental Panel on Climate Change (IPCC), heavy precipitation events will likely increase in frequency and intensity over many land areas. In addition, incidences and/or the magnitude of extreme high sea levels are likely to increase according to its latest assessment report (IPCC, 2013). Moreover, the risk of fluvial flooding is projected to increase in several regions, while decreasing in other areas (Hirabayashi et al., 2013; Winsemius et al., 2016).
Floods can have a variety of societal impacts that span across space and time. Some of these impacts, such as the physical destruction of houses and infrastructure elements, are clearly visible and frequently make it to the world’s headlines. This type of direct flood impact is also a commonly researched topic in the scientific literature. Other—more “silent”—societal impacts of flooding, such as long-term health effects of flood victims, receive less attention and, often, little is known about their complex processes.
A common approach to differentiate the types of negative societal flood impacts is to distinguish between direct and indirect as well as tangible and intangible flood impacts (Penning-Rowsell & Fordham, 1994; Smith & Ward, 1998). Direct impacts refer to those impacts that result from a direct physical contact between floodwaters and humans, economic assets, or other objects. Examples of direct impacts are the destruction of houses, crops, or livestock by floodwaters or the loss of life caused by drowning or injuries. Indirect impacts are those that occur outside of the flood event in both space and time, such as a loss in productivity resulting from a disruption in supply chains. Both direct and indirect impacts are further distinguished with regard to tangible and intangible impacts. Tangible impacts are those that can be easily expressed in monetary terms and thus refer to goods, for which a market price exists (Meyer et al., 2013). Examples of indirect impacts are losses in turnover or traffic disruptions. Impacts that are difficult to quantify in monetary terms because no market price exists, such as long-term health effects or the destruction of cultural heritage, are referred to as intangible impacts. An overview of this commonly used typology of societal flood impacts and examples for each category are provided in Table 1. It will subsequently serve as a framework for a discussion of the societal impacts of flood hazards and how they are addressed in natural hazards research.
Table 1. Typology of negative flood impacts and examples
Tangible (market goods) |
Intangible (nonmarket goods) |
|
---|---|---|
Direct |
Physical impact of floodwaters on economic assets – Infrastructure elements – Agricultural products – Houses |
Physical impact of floodwaters causing – Loss of life – Injuries – Loss of ecological goods |
Indirect |
Societal impacts outside of the flood zone (space and time) – Loss of turnover due to supply chain disruptions – Traffic disruptions |
Societal impacts outside of the flood zone (space and time) – Long-term health effects – Destruction of social life |
Source: Adapted from Penning-Rowsell et al. (2003); and Smith and Ward (1998).
What Are the Direct Tangible Impacts of Flood Hazards?
Images of severe flood events and their destructive force are a recurring topic in national and global media. Usually, the media’s coverage focuses primarily on the most immediate and obvious societal impact of flooding—namely, the loss of life and the destruction of physical objects such as houses, infrastructure, and other economic assets. In natural hazard research, this type of societal impact of flooding is referred to as direct tangible impact for two reasons: First, it is a result of a direct contact between floodwaters and a physical object. Second, the destroyed economic assets can easily be quantified in monetary terms (i.e., tangible), which means that a market price exists. For instance, the costs for rebuilding a house or repairing damaged traffic infrastructure can be rather easily quantified. For example, the costs of rebuilding railway tracks that were destroyed by a flood were estimated at approximately 700.000€ per 100-m track section (Kellermann et al., 2015). In the natural hazard sciences, research often focuses on direct tangible impacts, and a large body of literature is available on different aspects, such as ex post assessments of direct flood impacts or (ex ante) cost assessment methods (Merz et al., 2010; Meyer et al., 2013; Kreibich et al., 2014; Penning-Rowsell et al., 2014).
Since direct tangible impacts can be assessed with relative ease and quantified in a comparable way (i.e., money), information on this type of flood impact is recorded in national, regional, and global databases, as well as analyzed in the scientific literature and reports of international organizations and the (re)insurance industry. Two well-known examples of global databases on both direct tangible and other flood impacts are the Emergency Events Database (EM-DAT), maintained by the Centre for Research on the Epidemiology of Disasters (CRED), and the NatCatService, maintained by the reinsurance company Munich Re. EM-DAT is freely accessible to the public and provides information on disasters caused by natural and technical hazards. To be included in EM-DAT, events need to fulfill at least one of the following entry criteria: the event (1) caused 10 or more casualties; (2) affected 100 or more people; (3) caused the declaration of a state of emergency, or (4) prompted a call for international assistance.
Table 2 lists the 10 costliest flood events extracted from EM-DAT and the NatCatService. It demonstrates the enormous losses that single flood events can inflict on societies, amounting to up to 40 billion US dollars for a single event. The most expensive flood recorded in the last 35 years was the Chao Phraya River Flood in Thailand in 2011, during which large parts of the country and the capital, Bangkok, were flooded. Table 2 also illustrates the differences in ranking of events between the two databases. These variations relate to the difficulties and uncertainties associated with collecting disaster loss data and differences in the data collection methods (Guha-Sapir & Below, 2002; Gall et al., 2009), despite harmonization efforts (Below et al., 2009). Gall et al. (2009) discuss limitations of loss data that can lead to a number of misinterpretations by end-users. For instance, not all hazard types are represented in loss estimates (hazard bias); small events are often not included in regional or global databases (threshold bias); and the way loss data are collected and compiled can lead to a number of systematic biases. Also, Guha-Sapir and Below (2002) point out that there are still no internationally standardized definitions or methods for assessing losses from natural hazards. Moreover, data on disasters are often collected from a variety of sources such as newspaper, insurance, or governmental reports, which may apply different definitions (systematic bias). Efforts to standardize loss databases are being undertaken in the European Union (European Commission, 2013) and within the Sendai Framework for Disaster Risk Reduction, 2015–2030 (UNISDR, 2015a).
Table 2. The 10 costliest flood events since 1980 according to the EM-DAT and the NatCatService
EM-DAT |
Rank |
NatCatService |
||||
---|---|---|---|---|---|---|
Country |
Year |
Billion US$ |
Country |
Year |
Billion US$ | |
Thailand |
2011 |
40 |
1 |
Thailand |
2011 |
43 |
China |
1998 |
30 |
2 |
United States of America |
1993 |
21 |
China |
2010 |
18 |
3 |
China |
1998 |
16 |
India |
2014 |
16 |
4 |
DE, AT, CZ, HU, MD, CH, SK* |
2002 |
16.5 |
North Korea |
1995 |
15 |
5 |
North Korea |
1995 |
15 |
Germany |
2013 |
12.9 |
6 |
China |
1991 |
13.6 |
China |
1996 |
12.6 |
7 |
DE, AT, CZ, HU, PL, CH* |
2013 |
12.5 |
United States of America |
1993 |
12 |
8 |
United States of America |
2008 |
10 |
Germany |
2002 |
11 |
8 |
Italy |
1994 |
9.3 |
United States of America |
2008 |
10 |
10 |
Bangladesh, India, Nepal |
1993 |
8.5 |
Note:
* International ISO country codes.
Source: EM-DAT and NatCatService, retrieved September 6, 2016.
According to EM-DAT, a geographical analysis of global flood losses between 1980 and 2015 indicates that by far the highest losses occurred in Asia (62%), followed by Europe (19%) and the Americas (15%) (Figure 1, left panel). The analysis also suggests an increasing trend in flood losses (Figure 1, right panel). The observed increase in many regions in recent decades was predominantly associated with the accumulation of population and economic assets in floodprone areas (Barredo, 2009; Bouwer, 2010). While these areas are prone to flooding, they provide otherwise favorable living conditions, such as access to drinking water, fertile soils, and easy means of transportation (Kummu et al., 2011). It has also been argued that direct flood impacts are on the rise owing to the effects of anthropogenic climate change on the hydrological cycle. Thus far, however, natural hazard research has not established a significant influence of global warming on observed increases in flood losses (Barredo, 2009; IPCC, 2012; Kundzewicz et al., 2014).
The severity of direct flood impacts on structures depends on both impact and resistance (or technical vulnerability) parameters (Thieken et al., 2005). Flood impact parameters refer to the characteristics of the flood, such as inundation depth, flow velocity, and contamination of floodwaters. Resistance (vulnerability) parameters refer to the characteristics of the flood-affected object such as building material, construction type, and the existence of damage-reducing measures at the building level, for example, adapted building use or deployment of temporary water shutters. Such measures implemented by private households can significantly reduce direct flood impacts and are increasingly integrated in flood risk management policies (Kreibich et al., 2015).
Different flood risk management strategies can be applied to reduce direct tangible impacts from flooding, which can include flood prevention, protection, and preparedness for response and recovery (European Commission, 2007; Thieken et al., 2016a). Flood prevention strategies aim at minimizing flood damage by prescribing where and how to build through implementation of building codes and spatial zoning policies. Protection measures aimed at reducing the likelihood of flood events include building dikes or restoring floodplains and wetlands. Finally, preparedness for response and recovery refers to all activities and measures in a given area, which enable society to respond rapidly and effectively to disaster situations, including risk awareness programs, early warning, evacuation, and contingency planning as well as risk transfer schemes (for recovery).
A large body of literature exists in the natural hazard sciences on how to model and assess direct tangible flood losses. An influential approach has been the so-called Multi-Colored Manual (Penning-Rowsell et al., 2014), which was developed to assess flood losses in England and Wales.
Flood damage models have traditionally focused on the influence of water depth on flood damage using so-called depth-damage functions. Recent models, however, seek to integrate more impact and resistance factors, such as building quality, flood duration, contamination, and level of private precaution (Gerl et al., 2016). Despite substantial data collection and modeling efforts, uncertainties associated with the modeling of direct tangible flood damage remain high (Merz et al., 2010).
What Are the Direct Intangible Impacts of Flood Hazards?
Direct intangible impacts are directly caused by the physical effect of floodwaters, but the resulting impact cannot be easily expressed in monetary terms because no market value exists for the damaged or destroyed values. The most relevant direct intangible impact is the most serious and irreversible type of societal flood impact: the loss of human life. Other impacts are physical injury, the destruction of cultural heritage, ecosystems, and personal belongings of high emotional value, such as personal memorabilia.
In natural hazard research, a growing body of literature has addressed different aspects of losses of human life due to floods, including ex-post assessments of flood fatalities (Jonkman, 2005; Jonkman et al., 2009), and approaches that can be used ex-ante to predict flood mortality (Maaskant et al., 2009).1 Figures on flood fatalities can again be retrieved from the EM-DAT and the NatCatService databases. A list of the 10 deadliest fluvial flood events between 1980 and 2016 according to the EM-DAT database is provided in Table 3. It illustrates the great harm floods can pose to human life, with single events costing thousands of fatalities. The flood event that, by far, caused the highest number of fatalities occurred in Venezuela in 1999, when torrential rains led to flash floods, accompanied by thousands of land- and mudslides on the steep slopes of the Sierra de Avila killing 30,000 people (Wieczorek et al., 2001).
Table 3. The 10 deadliest fluvial floods since 1980 according to the EM-DAT database.
Rank |
Country |
Year |
Total deaths |
---|---|---|---|
1 |
Venezuela |
1999 |
30,000 |
2 |
China |
1980 |
6200 |
3 |
India |
2013 |
6054 |
4 |
China |
1998 |
3656 |
5 |
China |
1996 |
2775 |
6 |
Haiti |
2004 |
2665 |
7 |
Bangladesh |
1988 |
2379 |
8 |
Somalia |
1997 |
2311 |
9 |
Bangladesh |
1987 |
2055 |
10 |
India |
1994 |
2001 |
Source: EM-DAT, retrieved November 24, 2016.
A geographical analysis of global losses of human lives due to fluvial flooding since 1980 shows that the highest impact in terms of absolute fatalities occurred in Asia (67%), followed by the Americas (22%) and Africa (9%) (Figure 2, left panel). The regional distribution of fatalities differs from economic flood losses (Figure 1, left panel): Europe, for instance, which suffers a considerable share of global economic flood losses, is hardly affected in terms of flood fatalities. The fact that industrialized countries, such as the European member states, could substantially reduce the number of flood victims, has been associated with improved disaster management and especially improved early warning capacity (UNISDR, 2011).
The number of flood victims over time and separated by continents is illustrated in Figure 2 (right panel). The disastrous event in Venezuela in 1999 stands out. In contrast to monetary losses (Figure 1, right panel), no increasing trend in flood fatalities is suggested, despite the ongoing accumulation of people and economic assets in floodprone areas. The decrease in mortality relative to population size has been associated with the improvements in disaster management and early warning capacities in many regions (UNISDR, 2011).
The loss of human life depends on a number of flood severity and vulnerability characteristics. Flash floods, for instance, lead to a much higher average mortality than fluvial floods, or floods due to problems with the sewage system (Jonkman, 2005). Flash floods, dam breaks, and tsunamis are characterized by severe physical effects (e.g., high flow velocities) and limited possibilities for warning and evacuation due to their sudden onset. Moreover, the vulnerability of those affected by a flood event largely influences mortality. An analysis of flood victims of Hurricane Katrina in New Orleans showed that the majority were elderly people: almost 50% of the victims were older than 75 and only 15% were younger than 51. Given the fact that only 6% of the population of New Orleans was older than 75, this illustrates the high vulnerability of that age group, being usually dependent on assistance to evacuate and being least able to cope with the physical impact (Jonkman et al., 2009). Mortality is also influenced by the time and place where people are when they are hit by a flood and by the behavior of those hit by a flood. A detailed analysis of the causes and circumstances of death from 13 flood events analyzing 247 fatalities revealed that about 68% of the victims died from drowning. Out of these 68%, 25% were pedestrians and 33% drowned in a vehicle. The remaining 10% drowned from a boat or building accident or during a rescue operation (Jonkman & Kelman, 2005).
As indicated earlier, an important risk reduction strategy involves the implementation and upgrading of hydrometeorological information production and early warning capacity. Early warning systems require a good hydrometeorological gauge network and sound weather forecasting and hydrological models. Moreover, warnings can save lives and reduce losses only if the message is well understood and translated into adequate behavior (Penning-Rowsell et al., 2000). Implementation of these systems significantly reduced mortality in developed countries. However, the technological and financial means needed to set up such systems are not yet available in many regions of least developed and developing countries. A World Bank study estimated that upgrading hydrometeorological information production and early warning capacity in all developing countries could save an average of 23,000 lives per year (Hallegatte, 2012).
Other direct intangible impacts, such as damage to cultural heritage and the environment, usually receive less attention (Markantonis et al., 2012; Meyer et al., 2013). In contrast to economic damage and loss of life, there is no systematic collection of data on flood impacts on cultural heritage or the environment. As a result, less is known about the direct intangible impacts of floods, such as their effects on cultural heritage (Stovel, 1998; Lanza, 2003; Taboroff, 2003). The reasons for the ineffective risk management of cultural heritage and the environment are the lack of knowledge of the assets themselves, the difficulty of estimating their nonmarket value, and the failure to estimate the true losses in case an asset is damaged by flooding (Markantonis et al., 2012). However, recent political initiatives may improve awareness and thus reduce the impact of floods on cultural heritage. The EU Floods directive, which sets up a common framework for reducing and managing the risk of flooding in the EU, explicitly addresses cultural heritage and the environment. Member states are required to include both aspects in their risk assessments and management plans (European Commission, 2007). The flood risk maps for the Elbe Basin, for instance, include important cultural heritage, such as UNESCO World heritage sites and other sites of national importance (FGG Elbe, 2015) in their risk maps.
Despite the development of several methods to monetize direct intangible impacts, they often are not considered in traditional cost-benefit analyses, potentially resulting in biased and suboptimal risk management decisions (Kreibich et al., 2014). Methods to estimate the monetary value of the direct intangible impact of floods include revealed preferences methods, such as the Hedonic Pricing Method, the Travel Cost Method, and the Replacement Cost Method, as well as stated preferences methods, such as Contingent Valuation Method, Choice Modeling Method, and Life Satisfaction Analysis (Markantonis et al., 2012). Also, Multicriteria Analysis can be used to integrate direct intangible societal impacts in a decision-making framework.
What Are the Indirect Tangible Impacts of Flood Impacts?
Floods also have impacts that occur outside of the flood event, in both space and time. If these impacts can be expressed rather easily in monetary terms, they are referred to as indirect tangible impacts. An important example of an indirect tangible impact is losses due to a disruption of business processes. At a regional level, indirect damage can make a substantial proportion of overall impacts. An analysis of the response of Louisiana’s economy to the landfall of Hurricane Katrina concluded that the disruption of economic processes substantially aggravated direct tangible impacts. The total costs were estimated at 149 billion US dollars, of which 42 billion were associated with indirect losses (Hallegatte, 2008).
When large parts of Thailand were hit by a severe flood in 2011, this event had large implications for supply chains in the manufacturing industry, such as the automotive industry and the production of hard disk drives. Thailand is one of the main producers of hard disk drives (HDD). Before the flood event, about 43% of the world’s HDDs were produced in Thailand. During the flood in 2011, important manufacturing places belonging to Toshiba and Western Digital were inundated and needed up to 114 days to recover (Haraguchi & Lall, 2015). As a result, HDD shipments of the five largest producers in Thailand declined by 30%, leading to a global price increase of 80 to 190% for desktop and mobile HDDs (Haraguchi & Lall, 2015). Even half a year after the flood event, the majority of prices of HDD remained higher compared with pre-flood levels. This illustration demonstrates the close interconnectedness of the world economy and the vulnerability of global supply chains, especially due to increasing just-in-time production.
Another important example of indirect tangible impacts of floods is the disruption of transportation networks. In Germany, a large-scale flood event in 2013 had a severe effect on railway operations. During the event itself, 75 railway routes had to be temporarily closed, or interferences were reported. The flood also destroyed parts of high-speed railway tracks that connect the German capital Berlin with other important cities such as Frankfurt and Cologne. The high-speed connection was closed for almost 5 months, resulting in diverting approximately 10,000 passenger trains and more than 3000 freight trains (Thieken et al., 2016b).
The severity of indirect economic impacts depends on various aspects, such as the amount of direct losses (Hallegatte, 2008), the adaptability and flexibility of the production system to compensate for unavailable inputs, and the size of the economy; developing economies also seem to be more vulnerable than industrialized ones (Noy, 2009). Findings regarding the impact of natural disasters on the overall economy are still inconclusive. While some studies report a negative impact in terms of reduced growth rates, others even find a positive long-term effect at the national scale, probably because of the stimulus effect of reconstruction and improved productivity following the reconstruction process (Przyluski & Hallegatte, 2011; Koks & Thissen, 2016). Moreover, flood events in one region can lead to positive indirect economic impacts in other areas—for instance, as a result of extra exports. An assessment of the indirect economic effects of a potential flood in the south of Holland at a pan-European scale found that several regions in Europe would experience positive indirect effects (Koks & Thissen, 2016).
In contrast to direct economic losses, indirect tangible impacts are not systematically registered in international databases such as EM-DAT. Research on this type of flood impact was long neglected compared with direct losses. However, a growing body of literature has recently addressed this topic (e.g., Koks et al., 2015; Haraguchi & Lall, 2015; In den Bäumen et al., 2015). Existing approaches to assess indirect tangible economic impacts due to floods are input–output models, computable general equilibrium (CGE) models, or a combination of both (Meyer et al., 2013; Koks & Thissen, 2016). The U.S. Federal Emergency Management Agency (FEMA, 2011) provides a tool for estimating losses caused by the disruption of business processes at the company level. Subject to inundation depth and economic sector, the tool specifies relocation expenses, capital-related income losses, wage losses, and rental income losses. Little knowledge currently exists on how to mitigate the indirect tangible impacts of floods—for instance, how to increase the resilience of global supply chains (Haraguchi & Lall, 2015) and businesses (e.g., Runyan, 2006). Also, indirect tangible effects—beyond business interruption—are often not included in traditional cost-benefit analyses, potentially leading to biased and suboptimal risk mitigation decisions (Kreibich et al., 2014).
What Are the Indirect Intangible Impacts of Flood Impacts?
Floods can cause societal impacts that occur outside the flooded area or following the flooding. While many health problems occur directly during the flood situation (e.g., as a result of injuries or of contaminated water), there are also delayed physical and mental complaints, which only become apparent after some length of time (Alderman et al., 2012) and therefore count as indirect impacts. Long-term health effects as well as negatively perceived changes in social life cannot easily be monetized, and so they are categorized as indirect intangible effects. In many cases, causal relations to the respective flood event are difficult to prove owing to process complexity (Hajat et al., 2005). Moreover, effects such as malnutrition, displacement, contamination, and disruption of social environments may reinforce each other (Du et al., 2010; Menne & Murray, 2013).
Frequently, indirect intangible impacts only surface at a time when emergency situations are already settled and clearing work and reconstruction is ongoing. Therefore, these impacts are rather unrecognized compared to more obvious direct impacts. Scientific knowledge on indirect intangible impacts is more limited compared to, for instance, direct costs (Meyer et al., 2013). Although flood exposure has been systematically related to physical and psychological health impacts (Hajat et al., 2005; Carroll et al., 2010; Fernandez et al., 2015) and the relevant body of literature has increased, this field still remains underresearched (Menne & Murray, 2013; Lamond et al., 2015). The specific relation between flooding and different health consequences and their severity are not well understood yet, and there are no data bases collecting quantitative information on the broader health impacts of flooding. Nevertheless, impacts on health and social life are of high importance since they are frequently long lasting, may entail further serious consequences, and might be perceived by affected people as more significant than financial losses (Tapsell & Tunstall, 2008).
Physical complaints related to floods are manifold and include, for example, injuries during cleanup and reconstruction work (Ahern et al., 2005; Du et al., 2010) and diseases caused at a later time by contaminated water or food, such as diarrhea, cholera, hepatitis A and E, or sickness triggered by the rotavirus (Du et al., 2010; Alderman et al., 2012). These infectious diseases occur to a great extent in low-income countries, while outbreaks are uncommon in developed, temperate countries (Ahern et al., 2005; Hajat et al., 2005; Menne & Murray, 2013). Remaining bodies of floodwater can also spur mosquito-borne diseases, such as malaria, dengue, or West Nile fever, and rodent-borne infections can increase in many world regions following floods (Ahern et al., 2005).
In the long term, health effects and malnutrition can lead to morbidity (Lowe et al., 2013). However, there are little data on indirect, flood-related deaths (Alderman et al., 2012). In general, vulnerability to health impairments increases if people are displaced, hygiene or water quality is of low standard (Ahern et al., 2005; Alderman et al., 2012), and health care is insufficient (Hajat et al., 2005). Thus, the health impacts of flooding differ profoundly between low- and high-income countries: developed countries are often affected less since their relevant infrastructure meets a high standard and many infectious diseases are not endemic in temperate regions (Du et al., 2010). Vulnerability to physical health impacts might be higher for certain social groups, such as the elderly, the disabled, children, women, ethnic minorities, and those with few financial resources (Hajat et al., 2005, p. 185).
The majority of physical health effects are present in the weeks and months after flooding, whereas the psychological impacts can last for years (Tapsell & Tunstall, 2008; Fernandez et al., 2015; Isaranuwatchai et al., 2017) and be perceived as grievous not only for the people directly affected by the flood but also for support workers, relatives, and friends (Fewtrell & Kay, 2008; Carroll et al., 2010). Many factors and complex processes influence the grievance and duration of mental complaints—for instance, flood severity, the implementation of emergency measures, personality characteristics, demographic and socioeconomic aspects (Lamond et al., 2015), the importance of personal and material losses, displacement and disruption of homes and social life, long repair work, and fear of flood recurrence (Hajat et al., 2005; Tapsell & Tunstall, 2008; Du et al., 2010). Isaranuwatchai et al. (2017) analyzed the mental effects of the 2004 tsunami in Thailand one and two years after the event and found that the loss of family members has the most severe and most long-lasting effect on mental health.
Anxiety and depressive illness are the most common mental disorders that are reported to increase after flooding. Further complaints include panic attacks, stress, mood swings, flashbacks, and suicidal thoughts (Carroll et al., 2009; Mason et al., 2010; Alderman et al., 2012; Fernandez et al., 2015; Lamond et al., 2015). Some authors describe mental illnesses in the context of posttraumatic stress disorder (PTSD), which combines different symptoms (Hajat et al., 2005). Fernandez et al. (2015), in their literature review, conclude that certain persons are reported to be more vulnerable to psychological health issues. These include people who have only low income, were highly exposed to the flood, showed preexisting mental health problems, and had to cope with postdisaster stressors such as relocation, financial losses, or unemployment (Fernandez et al., 2015). Various studies state that women are more vulnerable to mental disorders than men (Tapsell & Tunstall, 2008, Mason et al., 2010; Alderman et al., 2012), but findings are not consistent (Lowe et al., 2013; Fernandez et al., 2015). Similarly, correlations between mental complaints and factors such as age, social support, socioeconomic status, and education are not coherent (Lowe et al., 2013), and there are different views, for example, on relocation, as living in another surrounding can also minimize memories of the event and enhance social support (Isaranuwatchai et al., 2017).
Floods assuredly have adverse impacts on the well-being and mental health of the affected population (Hajat et al., 2005; Menne & Murray, 2013). However, Alderman et al. (2012) point out that studies report quite different numbers of mental disorders. Two years after a flood event, numbers range from 8.6% of people with a PTSD in a Chinese case study and 53% of people with mild depression in a Korean case (Alderman et al., 2012). The comparison of such figures is problematic since robust findings on the mental impacts of flooding are rare. There is a need to undertake research and set up datasets on health impacts after flooding. Furthermore, it is crucial to enhance methodological approaches, identify and assess high-risk groups, understand the secondary causes and stressors of health risks, and implement long-term studies, especially on mental health effects (Ahern et al., 2005; Neria et al., 2009; Alderman et al., 2012; Menne & Murray, 2013; Fernandez et al., 2015; Isaranuwatchai et al., 2017).Mental health effects and the way of expressing these effects might differ profoundly on account of the different cultures and context-specific settings (Norris et al., 2002; Ahern et al., 2005; Menne & Murray, 2013; Fernandez et al., 2015). Crabtree (2012, p. 27) concludes that “[t]he diversity of results suggests that culture and context are of great importance. However, it must be said that too few cases have been studied, too few disorders investigated, and too few variables have been analyzed to make many strong claims beyond these generalizations.” Also needing more consideration are cost estimates of health-related impacts in order to reach a more comprehensive picture of flood losses. Different approaches exist to estimate costs in a monetary or nonmonetary way—for example, the investigation of people’s willingness to pay (contingent valuation method) (Markantonis et al., 2012; Meyer et al., 2013) and the concept of human life years, which indicates development setbacks in years due to flooding (UNISDR, 2015b). However, these approaches need to be further developed and applied more consistently.
At the same time, health impacts require more attention in disaster preparedness, and people might need more support to cope with traumatic experiences, recovery, and daily life after flooding (Neria et al., 2009; Alderman et al., 2012; Fernandez et al., 2015; Lamond et al., 2015; Isaranuwatchai et al., 2017). In case of risk management, the way authorities and operating forces respond to the event, as well as individual flood awareness and preparation, can significantly impact psychological health (Ahern et al., 2005; Carroll et al., 2010), and physical and psychological complaints can reinforce and prolong each other (Tapsell & Tunstall, 2008; Isaranuwatchai et al., 2017).
Floods can also have impacts on social life that some people might perceive as negative. These effects include changed perceptions of place and home, impairment of social cohesion, and destruction of relationships in families and in affected communities (Tapsell & Tunstall, 2008; Fernandez et al., 2015). These changes might be triggered by displacement or migration, time-consuming and exhaustive recovery processes, economic decline, (mental) health effects, and nonaffected persons’ lack of understanding of the flood victims’ situation (Tapsell & Tunstall, 2008; Fernandez et al., 2015; Lamond et al., 2015). Severe flood events can also lead to growing public mistrust of authorities and to accusations of certain people, groups, or institutions for causing the severe impacts of flooding (Tapsell & Tunstall, 2008; Kuhlicke et al., 2016).
In the aftermath of flood events, the existing flood risk management is usually revisited and reanalyzed. As a result, structural flood protection measures are often repaired, modified, enlarged, or newly planned and implemented. These construction projects can trigger public conflicts in which questions of equity and participation are raised, and negative impacts for certain economic interests as well as for landscape and nature protection are debated on (Warner et al., 2013; Otto et al., 2016). In cases of large-scale dams, for instance, conflicts can include issues such as the disturbance of livelihood practices and social life, as well as resettlement plans (Tilt et al., 2009). The different consequences for social life can be long-lasting and far-reaching not only on a local level, but also beyond, which gives them importance but makes them hard to grasp and be assessed. Thus, these effects are mentioned but hardly included in flood impact assessments.
What Are the Positive Societal Impacts of Floods?
Although flooding can be devastating to people in terms of their health and economic assets, it has always been an essential part of nature’s renewal process, providing several beneficial societal impacts (Tockner & Stanford, 2002). Many countries depend on groundwater and underground aquifers for freshwater, and floods are an intermittent source of freshwater supply. Floodwaters absorb into the ground and recharge the underground aquifers that supply natural springs, wells, rivers, and lakes with freshwater. Moreover, a variety of physical, chemical, and biological changes occur in floodwater that positively impact ecosystems. For instance, floods carry and deposit nutrient-rich sediments that support both the plant and animal life of wetlands, one of the most productive ecosystems in the world (Arias et al., 2014). Because of high currents, flooding reduces waste accumulation by hydrodynamic spreading and replenishes anoxic or hypoxia water with oxygen-rich water. Furthermore, floods flush out accumulated organic substances introduced by untreated drainage water from farmlands, factories, and domestic use, as well as contaminants caused by the intensive use of pesticides and fertilizers. The variable sediment and flow regimes (i.e., floods) support the biodiversity in rivers and floodplains; wetlands, in turn, serve as natural buffer zones for excessive flood flows.
Related to the positive effects of recharging groundwater and improving soil fertility are the beneficial impacts of flooding for agriculture. Especially in less and least developed countries with a high percentage of people working in the agricultural sector, floods are both a great threat and a resource for the livelihood of millions of people (Tockner & Stanford, 2002). Farming communities in or near floodplains rely on regular floodwaters that carry nutrients and sediments, enriching the soil and making it very fertile for cultivation. Historically, many civilizations developed along the fertile floodplains of rivers such as the Tigris and Euphrates (known as Mesopotamia, “the land between the rivers”), the Huang He, the Nile, and the Indus (e.g., Hughes, 1992). For the population, a lack of seasonal flooding had severe consequences in terms of food production. In the early 21st century, particularly rice farmers take advantage of the natural fertilization process. The Mekong Delta is an illustrative example: the so-called rice bowl of Southeast Asia sustains the livelihood and food security of millions of people in Vietnam and Cambodia. As a result of the annual flood pulse and large amount of suspended sediments transported by the Mekong River to its extensive floodplains, agricultural production and economic growth have been continuously increasing (Käkönen, 2008).
The Mekong River exemplifies the beneficial impacts of flooding with regard to fishery livelihoods and the recovery of the fish stock, respectively. In the river basin, fish is a central social, economic, and cultural resource and an important foundation of food security (Ziv et al., 2012). As part of one of the world’s largest inland fisheries, Mekong fishery is a relevant source of income for numerous people (Sarkkula et al., 2009). With the variable flow regimes and the provision of freshwater, waste, nutrients, and larva, floods are a trigger for both the spawning and migration of certain species and essential for various stages of the life cycle of species (Stone, 2016). A healthy river ecosystem is also relevant for supplementary livelihoods in the form of recreational and ecotourist activities, which are of increasing importance for many regions.
The example also illustrates that many of the benefits of flooding cannot be discounted easily. In particular, when industrialized societies think of flooding, they think of it in terms of having water where they do not want it. However, in many regions, the beneficial effects are critical, and flooding is not primarily considered a hazard but rather a basic necessity for planting crops and increasing fishery resources, destroying varmints and killing insects, cleaning stagnant water, and delivering fertile sediments, thus maintaining livelihoods. In countries such as China, India, and Vietnam, to name only three examples, structural measures for flood defense and power generation are a threat to the livelihood of many people (e.g., Ziv et al., 2012). In these three countries, large deltas are densely populated and heavily farmed. For the inhabitants of the Changjiang, Indus, and Mekong river deltas, floods are not only a threat but also a source of freshwater for irrigation and domestic use, improving navigation of transport, washing out acid water, pushing saltwater toward the sea, and preventing erosion by depositing soil.
In the Mekong Delta, large-scale flood-control structures are challenging both the social equity and environmental sustainability. Hydropower development has impacts on water quantity and quality, and, consequently, on fish habitats (Ziv et al., 2012). In addition to the so-called barrier effect of dams on fish migration, flood protection structures change the natural flood pulse and the hydrograph, directly undermining the productivity of the system by reducing inundated habitats, delaying the onset of flooding, and shortening growth periods for aquatic organisms, with negative impacts uon fisheries productivity, nutritional security, and economic income (Sarkkula et al., 2009; Ziv et al., 2012). Also in other countries, such as Bangladesh, Indonesia, Japan, Egypt, the United States, Thailand, and the Philippines, water-control measures that prevent topsoil-replenishing sediments from being deposited in the delta are largely responsible for the increasing vulnerability of the delta’s population. The rapid sinking of deltas is a result of sediment compaction from the removal of oil, gas, and water from the delta’s underlying sediments, the trapping of sediment in reservoirs upstream, and floodplain engineering in combination with the rising global sea level (Chaussard et al., 2013).
The negative and positive impacts of flooding frequently result in social tension between people depending on floods for their livelihoods and people desiring to prevent the floods; this discord recurrently leads to the neglect of those depending on floods. As illustrated, flood prevention creates both winners and losers, and any kind of measure can shift the distribution of benefits or involuntary risks from one group to another. While the taxpayer usually bears the expensive structural flood protection, the benefits of the investment (i.e., reduced flood risk) are often enjoyed by a relatively small group of people living in floodprone areas (Penning-Rowsell & Pardoe, 2012). It is a difficult task to identify those benefiting from flood risk reduction policies and how they should compensate those who are disadvantaged by it. Scientific approaches such as cost-benefit analysis cannot easily resolve conflicts and strong differences in value judgments that are often present in flood risk policies (Mechler, 2016). Thus, the distribution of costs and benefits remains a key challenge in flood risk management.
Conclusion
Each year, flood events have a tremendous impact on societies around the world, resulting in loss of life, damage to or destruction of economic assets, ecosystems, and cultural heritage, as well as long-term health effects. At the same time, floods are an important source of living for millions of people in developing countries, especially for those directly depending on natural resources.
In natural hazards research, negative flood impacts have been commonly categorized into direct and indirect impacts. Both are further distinguished as tangible and intangible losses. Our current understanding of these various impacts and the complex cause–effect relations and feedbacks differs. While a rather large body of literature exists chronicling direct economic damage and loss of human life, less is known about the more indirect and intangible effects of flooding. This is despite the fact that these types of impacts can also be severe for human societies. In recent years, however, a growing body of literature has addressed the indirect and intangible effects of flooding. To gain a more comprehensive understanding of the negative impacts of flooding, future research should further expand into these areas. A better understanding could contribute to improved flood risk management policies that integrate the different aspects.
Countries significantly differ regarding political tradition, economic status, societal milieu, and flood risk. All these factors influence the social perception of both flood risk and flood risk management (Bubeck et al., 2015). Also, the degree to which an individual or community is vulnerable to the impacts of flooding or resilient is never distributed homogeneously within and between social groups. To fairly address the challenges posed by floods, issues of governance, social justice, and power are therefore critical. Since the way people think about flooding influences where they look for solutions, as well as the shape and character of the means they use to attain those solutions, a starting point lies in integrating different kinds of knowledge and expertise. This requires that scientists, the public, and decision makers in policy and practice collaborate when they are designing context-appropriate flood management policies.
The dynamic nature of both floods and the human system exposed to them requires a continuous process of monitoring and adjustment because future conditions will most likely change. In the European Union, the Floods Directive innovatively takes this into account, requiring member states to review their flood risk and their management periodically (European Commission, 2007).
References
- Ahern, M., Kovats, R. S., Wilkinson, P., Few, R., & Matthies, F. (2005). Global health impacts of floods: epidemiologic evidence. Epidemiologic Reviews, 27(1), 36–46.
- Alderman, K., Turner, L. R., & Tong, S. (2012). Floods and human health: A systematic review. Environment International, 47, 37–47.
- Arias, M. E., Cochrane, T. A., Kummu, M., Lauri, H., Holtgrieve, G. W., Koponen, J., & Piman, T. (2014). Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia’s most important wetland. Ecological Modelling, 272, 252–263.
- Barredo, J. I. (2009). Normalised flood losses in Europe: 1970–2006. Natural Hazards and Earth System Sciences, 9(1), 97–104.
- Below, R., Wirtz, A., & Guha-Sapir, D. (2009). Disaster category classification and peril terminology for operational purposes. Working Paper No. 264. Universite catholique de Louvain, Brussels.
- Bouwer, L. M. (2010). Have disaster losses increased due to anthropogenic climate change? Bulletin of the American Meteorological Society, 92(1), 39–46.
- Bubeck, P., Kreibich, H., Penning-Rowsell, E., Botzen, W. J.W., de Moel, H., & Klijn, F. (2015). Explaining differences in flood management approaches in Europe and the USA: A comparative analysis. Journal of Flood Risk Management
- Carroll, B., Balogh, R., & Morbey, H. (2010). Health and social impacts of a flood disaster: Responding to needs and implications for practice. Disasters, 34(4), 1045–1063.
- Carroll, B., Morbey, H., Balogh, R., & Araoz, G. (2009). Flooded homes, broken bonds, the meaning of home, psychological processes and their impact on psychological health in a disaster. Health and Place, 15(2), 540–547.
- Chaussard, E., Amelung, F., Abidin, H., & Hong, S. H. (2013). Sinking cities in Indonesia: ALOS PALSAR detects rapid subsidence due to groundwater and gas extraction. Remote Sensing of Environment, 128, 150–161
- Crabtree, A. (2012). Climate change and mental health following flood disasters in developing countries, a review of the epidemiological literature: What do we know, what is being recommended? Australasian Journal of Disaster and Trauma Studies, 12(1), 21–30.
- Du, W., Fitzgerald, G. J., Clark, M., & Hou, X. (2010). Health impacts of floods. Prehospital and Disaster Medicine, 25(3), 265–272.
- European Commission. (2007). Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks (Floods Directive). Brussels: European Commission.
- European Commission. (2013). Recording disaster losses: Recommendations for a European approach. JRC Scientific and Policy Reports EUR 26111 EN, Luxembourg, European Commission.
- FEMA. (2011). Multi-hazard loss estimation methodology. Hazus®-mh mr5. Technical manual. Washington, DC: Federal Emergency Management Agency.
- Fernandez, A., Black, J., Jones, M., Wilson, L., Salvador-Carulla, L., Astell-Burt, T., & Black, D. (2015). Flooding and mental health: A systematic mapping review. Plos One, 10(4), e0119929.
- Fewtrell, L., & Kay, D. (2008). An attempt to quantify the health impacts of flooding in the UK using an urban case study. Public Health, 122, 446–451.
- FGG Elbe. (2015). Hochwasserrisikomanagementplan gem. § 75 WHG bzw. Artikel 7 der Richtlinie 2007/60/EG über die Bewertung und das Management von Hochwasserrisiken für den deutschen Teil der Flussgebietseinheit Elbe. Flussgebietsgemeinschaft Elbe. [In German.]
- Gall, M., Borden, K. A., & Cutter, S. L. (2009). When do losses count? Bulletin of the American Meteorological Society, 90(6), 799–809.
- Gerl, T., Kreibich, H., Franco, G., Marechal, D., & Schröter, K. (2016). A review of flood loss models as basis for harmonization and benchmarking. Plos One, 11(7), 1–22.
- Grames, J., Prskawetz, A., Grass, D., Viglione, A., & Blöschl, G. (2016). Modeling the interaction between flooding events and economic growth. Ecological Economics, 129, 193–209.
- Guha-Sapir, D., & Below, R. (2002). The quality and accuracy of disaster data: A comparative analysis of three global data sets. Geneva, Switzerland: Provention Consortium.
- Hajat, S., Ebi, K. L., Kovats, R. S., Menne, B., Edwards, S., & Haines, A. (2005). The human health consequences of flooding in Europe: A review. In W. Kirch, B. Menne, & R. Bertollini (Eds.), Extreme weather events and public health responses (pp. 185–186). New York: Springer.
- Hallegatte, S. (2008). An adaptive regional input‐output model and its application to the assessment of the economic cost of Katrina. Risk Analysis, 28(3), 779–799.
- Hallegatte, S. (2012). A cost effective solution to reduce disaster losses: Hydro-meteorological services, early warning, and evacuation. Policy Research Working Paper No. 6058. Washington, DC: World Bank.
- Haraguchi, M., & Lall, U. (2015). Flood risks and impacts: A case study of Thailand’s floods in 2011 and research questions for supply chain decision making. International Journal of Disaster Risk Reduction, 14(Part 3), 256–272.
- Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., & Kanae, S. (2013). Global flood risk under climate change. Nature Climate Change, 3(9), 816–821.
- Hughes, J. D. (1992). Sustainable agriculture in ancient Egypt. Agricultural History, 66(2), 12–22.
- In den Bäumen, H. S., Többen, J., & Lenzen, M. (2015). Labour forced impacts and production losses due to the 2013 flood in Germany. Journal of Hydrology, 527, 142–150.
- IPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
- IPCC. (2013). Climate change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
- Isaranuwatchai, W., Coyte, P. C., McKenzie, K., & Noh, S. (2017). The 2004 tsunami and mental health in Thailand: A longitudinal analysis of one-and two-year post-disaster data. Disasters, 41(1), 150–170.
- Jonkman, S. N. (2005). Global perspectives on loss of human life caused by floods. Natural Hazards, 34(2), 151–175.
- Jonkman, S. N., & Kelman, I. (2005). An analysis of the causes and circumstances of flood disaster deaths. Disasters, 29(1), 75–97.
- Jonkman, S. N., Maaskant, B., Boyd, E., & Levitan, M. L. (2009). Loss of life caused by the flooding of New Orleans after Hurricane Katrina: Analysis of the relationship between flood characteristics and mortality. Risk Analysis, 29(5), 676–698.
- Käkönen, M. (2008). Mekong Delta at the crossroads: More control or adaptation? Ambio, 37(3), 205–212.
- Kellermann, P., Schöbel, A., Kundela, G., & Thieken, A. H. (2015). Estimating flood damage to railway infrastructure: The case study of the March River flood in 2006 at the Austrian Northern Railway. Natural Hazards and Earth System Sciences, 15(11), 2485–2496.
- Koks, E., Bockarjova, M., de Moel, H., & Aerts, J. C. J. H. (2015). Integrated direct and indirect flood risk modeling: development and sensitivity analysis. Risk Analysis, 35(5), 882–900.
- Koks, E., & Thissen, M. (2016). A multiregional impact assessment model for disaster analysis. Economic Systems Research, 28(4), 429–449.
- Kreibich, H., Bubeck, P., Van Vliet, M., & de Moel, H. (2015). A review of damage-reducing measures to manage fluvial flood risks in a changing climate. Mitigation and Adaptation Strategies for Global Change, 20(6), 967–989.
- Kreibich, H., van den Bergh, J. C. J. M., Bouwer, L. M., Bubeck, P., Ciavola, P., Green, C., . . . Thieken, A. H. (2014). Costing natural hazards. Nature Climate Change, 4(5), 303–306.
- Kuhlicke, C., Callsen, I., & Begg, C. (2016). Reputational risks and participation in flood risk management and the public debate about the 2013 flood in Germany. Environmental Science and Policy, 55(Part 2), 318–325.
- Kummu, M., de Moel, H., Ward, P. J., & Varis, O. (2011). How close do we live to water? A global analysis of population distance to freshwater bodies. Plos One, 6(6), e20578.
- Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., . . . Mach, K. (2014). Flood risk and climate change: Global and regional perspectives. Hydrological Sciences Journal, 59(1), 1–28.
- Lamond, J. E., Rotimi, J. D., & Proverbs, D. G. (2015). An exploration of factors affecting the long term psychological impact and deterioration of mental health in flooded households. Environmental Research, 140, 325–334.
- Lanza, S. G. (2003). Flood hazard threat on cultural heritage in the town of Genoa (Italy). Journal of Cultural Heritage, 4(3), 159–167.
- Lowe, D., Ebi, K. L., & Forsberg, B. (2013). Factors increasing vulnerability to health effects before, during and after floods. International Journal of Environmental Research and Public Health, 10(12), 7015–7067.
- Maaskant, B., Jonkman, S. N., & Bouwer, L. M. (2009). Future risk of flooding: An analysis of changes in potential loss of life in South Holland (The Netherlands). Environmental Science and Policy, 12(2), 157–169.
- Markantonis, V., Meyer, V., & Schwarze, R. (2012). Valuating the intangible effects of natural hazards: Review and analysis of the costing methods. Natural Hazards and Earth System Science, 12(5), 1633–1640.
- Mason, V., Andrews, H., & Upton, D. (2010). The psychological impact of exposure to floods. Psychology, Health and Medicine, 15(1), 61–73.
- Mechler, R. (2016). Reviewing estimates of the economic efficiency of disaster risk management: Opportunities and limitations of using risk-based cost-benefit analysis. Natural Hazards, 81(3), 2121–2147.
- Menne, B., & Murray, V. (Eds.). (2013). Floods in the WHO European region: Health effects and their prevention. Copenhagen: World Health Organization, Regional Office for Europe.
- Merz, B., Kreibich, H., Schwarze, R., & Thieken, A. H. (2010). Review article: Assessment of economic flood damage. Natural Hazards and Earth System Sciences, 10(8), 1697–1724.
- Meyer, V., Becker, N., Markantonis, V., Schwarze, R., van den Bergh, J. C. J., Bouwer, L.M., . . . Viavattene, C. (2013). Review article: Assessing the costs of natural hazards: state of the art and knowledge gaps. Natural Hazards and Earth System Sciences, 13(5), 1351–1373.
- Munich Re. (2015). Topics geo. natural catastrophes 2015: Analyses, assessments, positions. Munich: Munich Reinsurance.
- Neria, Y., Galea, S., & Norris, F. H. (2009). Disaster mental health research: Current state, gaps in knowledge, and future directions. In Y. Neria, S. Galea, & F. H. Norris (Eds.), Mental health and disasters (pp. 594–610). New York: Cambridge University Press.
- Newton, A., & Weichselgartner, J. (2014). Hotspots of coastal vulnerability: A DPSIR analysis to find societal pathways and responses. Estuarine, Coastal and Shelf Science, 140, 123–133.
- Norris, F. H., Kaniasty, K., Conrad, M. L., Inman, G. L., & Murphy, A. D. (2002). Placing age differences in cultural context: A comparison of the effects of age on PTSD after disasters in the United States, Mexico, and Poland. Journal of Clinical Geropsychology, 8(3), 153–173.
- Noy, I. (2009). The macroeconomic consequences of disasters. Journal of Development economics, 88(2), 221–231.
- Otto, A., Hornberg, A., & Thieken, A. H. (2016). Local controversies of flood risk reduction measures in Germany: An explorative overview and recent insights. Journal of Flood Risk Management.
- Penning-Rowsell, E. C., & Fordham, M. (1994). Floods across Europe: Flood hazard assessment, modelling and management. London: Middlesex University Press.
- Penning-Rowsell, E. C., Johnson, C., Tunstall, S., Tapsell, S. M., Morris, J. Chatterton, J. B., Coker, A., & Green, C. (2003). The benefits of flood and coastal defence: Techniques and data for 2003. London: Flood Hazard Research Centre, Middlesex University.
- Penning-Rowsell, E. C., & Pardoe, J. (2012). Who benefits and who loses from flood risk reduction? Environment and Planning C: Politics and Space, 30(3), 448–466.
- Penning-Rowsell, E. C., Priest, S., Parker, D., Morris, J., Tunstall, S., Viavattene, C., Chatterton, J. B., & Owen, D. (2014). Flood and coastal erosion risk management: A manual for economic appraisal. Abingdon, U.K.: Routledge.
- Penning-Rowsell, E. C., Tunstall, S. M., Tapsell, S. M., & Parker, D. J. (2000). The benefits of flood warnings: real but elusive, and politically significant. Water and Environment Journal, 14(1), 7–14.
- Przyluski, V., & Hallegatte, S. (2011). Indirect costs of natural hazards: Costs of natural hazards. (CONHAZ/FP7) Project Report.
- Runyan, R. C. (2006). Small business in the face of crisis: Identifying barriers to recovery from a natural disaster. Journal of Contingencies and Crisis Management, 14(1), 12–26.
- Sarkkula, J., Keskinen, M., Koponen, J., Kummu, M., Richey, J. E., & Varis, O. (2009). Hydropower in the Mekong region: What are the likely impacts upon fisheries? In F. Molle, T. Foran, & M. Käkönen (Eds.), Contested waterscapes in the Mekong region: Hydropower, livelihoods and governance (pp. 227–249). London: Earthscan.
- Smith, K., & Ward, R. (1998). Floods: Physical processes and human impacts. Chichester, U.K.: John Wiley & Sons.
- Stone, R. (2016). Dam-building threatens Mekong fisheries. Science, 354(6316), 1084–1085.
- Stovel, H. (1998). Risk preparedness: A management manual for world cultural heritage. Rome: International Centre for the Study of the Preservation and Restoration of Cultural Property.
- Taboroff, J. (2003). Natural disasters and urban cultural heritage: A reassessment. In A. Kreimer, M. Arnold, & A. Carlin (Eds.), Building safer cities: The future of disaster risk (pp. 233–240). Washington, DC: World Bank.
- Tapsell, S. M., & Tunstall, S. M. (2008). “I wish I’d never heard of Banbury”: The relationship between “place” and the health impacts from flooding. Health and Place, 14(2), 133–154.
- Thieken, A. H. (2016b). The flood of June 2013 in Germany: How much do we know about its impacts? Natural Hazards and Earth System Sciences, 16(6), 1519.
- Thieken, A. H., Kienzler, S., Kreibich, H., Kuhlicke, K., Kunz, M., Mühr, B., Müller, M., . . . Schröter, K. (2016a). Review of the flood risk management system in Germany after the major flood in 2013. Ecology and Society, 21(2), 51.
- Thieken, A. H., Müller, M., Kreibich, H., & Merz, B. (2005). Flood damage and influencing factors: New insights from the August 2002 flood in Germany. Water Resources Research, 41(12), W12430.
- Tilt, B., Braun, Y., & He, D. (2009). Social impacts of large dam projects: A comparison of international case studies and implications for best practice. Journal of Environmental Management, 90(Suppl. 3), S249–S257.
- Tockner, K., & Stanford, J. A. (2002). Riverine flood plains: present state and future trends. Environmental conservation, 29(3), 308–330.
- UNISDR. (2011). Revealing risk, redefining development. Global assessment report on disaster risk reduction 2011. Geneva, Switzerland: United Nations International Strategy for Disaster Risk Reduction.
- UNISDR (2015a). Indicators to monitor global targets of the Sendai Framework for Disaster Risk Reduction 2015–2030: A technical review. Geneva, Switzerland: United Nations Office for Disaster Risk Reduction.
- UNISDR (2015b). Making development sustainable: The future of disaster risk management. Global assessment report on disaster risk reduction 2015. Geneva, Switzerland: United Nations Office for Disaster Risk Reduction.
- Warner, J. F., Van Buuren, A., & Edelenbos, J. (Eds.). (2013). Making space for the river: Governance experiences with multifunctional river flood management in the US and Europe. London: IWA Publishing.
- Wieczorek, G. F., Larsen, M. C., Eaton, L. S., Morgan, B. A., & Blair, J. L. (2001). Debris-flow and flooding hazards associated with the December 1999 storm in coastal Venezuela and strategies for mitigation. Reston, VA: U.S. Geological Survey.
- Winsemius, H. C., Aerts, J. C. J. H., Van Beek, L. P., Bierkens, M. F., Bouwman, A., Jongman, B., . . . Van Vuuren, D. P. (2016). Global drivers of future river flood risk. Nature Climate Change, 6(4), 381–385.
- Ziv, G., Baran, E., Nam, S., Rodríguez-Iturbe, I., & Levin, S. A. (2012). Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin. Proceedings of the National Academy of Sciences, 109(15), 5609–5614.
Notes
1. Mortality refers to the number of fatalities in relation to the exposed population.