How Perceptions of Risks Affect Responses to Climate Change: Implications for Water Resource Planning
How Perceptions of Risks Affect Responses to Climate Change: Implications for Water Resource Planning
- Sonia AkterSonia AkterSonia Akter is Assistant Professor at the Lee Kuan Yew (LKY) School of Public Policy at the National University of Singapore. She graduated with a PhD in Environmental Management and Development from the Australian National University in 2010, and holds a MS degree in Economics from York University, Toronto, Canada. Her three key research interests are climate change mitigation and adaptation policy, agriculture and food security, gender equity and women empowerment. Web profile: https://lkyspp.nus.edu.sg/our-people/faculty/sonia-akter
- and Shaleen KhanalShaleen KhanalShaleen Khanal is a PhD student at the Lee Kwan Yew School of Public Policy in National University of Singapore. His research focuses on the spatial dimensions of inequality at both household and national level. His research particularly focuses on understanding how government policies might exacerbating such outcomes. Previously, he worked as a researcher for SAWTEE – a non-governmental thinktank working in areas of international trade and climate change.
The link between risk perception and risk response is not straightforward. There are several individual, community, and national factors that determine how climate change risk is perceived and how much of the perception translates to response. The nexus between risk perception and risk response in the context of water resource management at the individual, household, community, and institutional level has been subject of a large body of theoretical and empirical studies from around the globe. At the individual level, vulnerability, exposure, and cognitive factors are important determinants of climate change risk perception and response. At the community level, risk perception is determined by culture, social pressure, and group identity. Responses to risk vary depending on the level of social cohesion and collective action. At the national level, public support is a key determinant of institutional response to climate change, particularly for democratic nations. The level of global cooperation and major polluting countries’ willingness to curb their fair share of greenhouse gas emissions also deeply influence policymakers’ decisions to respond to climate change risk.
- Disaster Preparation & Response
Climate change (CC) is one of the most important threats to natural and human systems (Intergovernmental Panel on Climate Change [IPCC], 2018), and it is especially relevant for the ongoing and impending changes in hydrological systems, human uses of water, and the frequency and intensity of extreme weather events. More specifically, climate change is projected to reduce surface water and groundwater availability, streamflow, and water quality; to increase the frequency and intensity of natural calamities, such as floods, cyclones, and droughts; and to increase the intensity and variability of rainfall in some parts of the world (IPCC, 2014). Additionally, sea-level rise and tidal changes are expected to increase soil and water salinization (IPCC, 2019), leading to a massive loss of land and livelihood for rural communities, especially in developing countries. The magnitude and severity of these risks vary widely across countries and regions. Perceptions of these risks and responses to them are also highly variable.
Risk is a multidimensional concept. Social scientists, psychologists, and natural scientists define risk differently. The IPCC defines risk as the probability that an adverse event will occur and its expected outcome (Oppenheimer, Little, & Cooke, 2016). Psychologists define risk perception as “feelings” that correspond to one’s “instinctive and intuitive reactions to danger” (Slovic & Peters, 2016). Risk perception not only depends on the nature and magnitude of the risk, but also is influenced by a number of cognitive, social, cultural, and political factors (Marris, Langford, & O’Riordan, 1998; West, Bailey, & Winter, 2010). Perception of risk varies among individuals, households, communities, and institutions. At the individual level, risk perception is a function of demographic characteristics (e.g., age, gender), psychological factors (e.g., risk preference; Kahneman & Tversky, 1979; Sjöberg, 2000; Slovic, Fischhoff, & Lichtenstein, 1980), experience with risk (Wachinger, Renn, Begg, & Kuhlicke, 2013), ideological beliefs (Mayer, Shelly, Chiricos, & Gertz, 2017), and sociocultural factors (Douglas & Wildavsky, 1983; Johnson & Covello, 1987). At the household level, factors like ethnicity, race, household composition, socioeconomic status, and poverty influence risk perception (Ndamani & Watanabe, 2017; Riad, Norris, & Ruback, 2006). Communities, too, perceive risk differently. Factors like cross-cultural differences (Bontempo, Bottom, & Weber, 1997; Weber & Hsee, 1998), proximity to the source of risk (Akter & Mallik, 2013; Brouwer, Akter, Brander, & Haque, 2009), institutional trust (Schmidt, Gomes, Guerreiro, & O’Riordan, 2014), social norms (Lo, 2013), and place attachment (Raymond & Brown, 2010) determine community risk perceptions. Finally, institutions responsible for developing and implementing adaptation and mitigation measures, such as governmental agencies, policymakers, and development organizations, are subject to various internal and external influences, such as political ideologies, trust in scientific information, geopolitics, and global power dynamics, etc., that shape their risk perceptions.
The interlinkage among risk, risk perception, and risk response is poorly understood. While some scholars found that risk perception is a strong predictor of behavioral intention when it comes to either taking individual actions or supporting government policies (O’Connor, Bard, & Fisher, 1999), many studies reveal a weak or no link between risk perception and risk response (Barnes, Islam, & Toma, 2013; Carlton et al., 2016). From a policy perspective, it is important to know how various actors in a society perceive CC risks and how they respond to them. This article summarizes what is known about the determinants of CC risk perception and the link between CC risk perception and CC response across multiple actors (Taylor, Dessai, & Bruine de Bruin, 2014), with a particular focus on the water-related CC risks. The article reviews a large number of theoretical and empirical studies from a variety of disciplines, including psychology, anthropology, development studies, international politics, geography, health, and cultural studies. Experiences of both developed and developing countries are included in the review to highlight divergence and commonalities in the pattern. Studies were located via a literature search in the Web of Science database, ProQuest database, and Google Scholar using a combination of keywords (climate change, risk perception, adaptation, and mitigation).
The article discusses the findings of the study at the individual/household level, community level, and organizational/national level, respectively, and then it concludes the study and offers recommendations for future research.
Individual/Household Level Determinants of CC Risk Perception and Response
Most studies on CC risk perception and response focus on individuals or households. The findings have three themes: disadvantaged groups, exposure and experience, and ideology and cognition.
Risk perception of CC and its effects on adaptation is comparatively high among vulnerable populations. The poor, the marginalized, and women appear to have a higher water-related CC risk perception compared to the nonmarginalized, nonpoor groups and men. The highest levels of risk perception and response are found among the poorest and the most vulnerable people because they are directly and most severely affected by events like flooding, storm surge, rainfall variability, and water scarcity (Lazrus, 2015; Smith, 2017). The coping and adaptive measures undertaken by these groups are reactive (Klein, 2003). For example, poor households use temporary or permanent migration and rely on postdisaster relief and rehabilitation assistance, informal credi,t or private transfers (Akter & Mallik, 2013; Lazrus, 2015; Mozumder, Bohara, Berrens, & Halim, 2009).
Financial constraints are a major barrier to adopting proactive CC response measures for disadvantaged households. In Bangladesh and Pakistan, poor households at risk of flooding, of tropical cyclone, and of drought refuse to buy hypothetical index insurance or to pay for the construction of a flood protection embankment due to lack of financial resources (Akter, Brouwer, Choudhury, & Aziz, 2009; Akter, Krupnik, Rossi, & Khanam, 2016; Brouwer et al., 2009; Fahad & Wang, 2018). There are cases where a vulnerable population makes riskier decisions for a higher return. For instance, lowlands are often occupied by the poor due to their low price and high soil fertility even though they are highly susceptible to inundation and crop failure (Brouwer et al., 2009; Chowdhury, 2003; Leong, 2018). Studies in Central America and Africa show that lack of access to land and poor credit, instead of perception of risk, are key determinants of farmers’ choice of adaptation measures to extreme weather events (Bryan et al., 2013; Tucker, Eakin, & Castellanos, 2010). Banerjee (2015) found similar results in the states of Maharashtra and Andhra Pradesh, India. She found that farmers’ ability to live with CC-induced water stress or to respond to it by adopting a water conservation technology depends on their financial status and access to credit.
Gender is a common denominator in determining water-related CC risk perceptions in both developing and developed countries. Studies consistently found that women have more knowledge about CC, and, consequently, they are more concerned about CC, than men (Cullen, Anderson, Biscaye, & Reynolds, 2018; Safi, Smith, & Liu, 2012; van der Linden, 2015). Shao, Xian, Lin, and Small (2017) found that risk perception of flooding is higher among women in the United States. Raphael et al. (2009) found, in New South Wales, Australia, women were significantly more likely than men to believe that the Millennium Drought (2001–2009) would continue for a much longer period. Despite possessing relatively higher risk perception than men, women are less likely to respond to CC risk, partly because they face gender-specific adaptation barriers. For example, female farmers in a coastal district of Bangladesh are significantly less likely than their male counterparts to buy weather index insurance designed to protect them against heavy rainfall (Akter et al., 2016). The low demand by women farmers is partly due to their lack of financial literacy. Owusu, Nursey-Bray, and Rudd (2019) found that, in Ghana, women have to travel long distances to collect drinking water as the nearby water collection points become unusable due to salinity intrusion and sea erosion. As a result, women experience a higher burden of domestic work, which limits their ability to participate in CC adaptation measures like disaster preparedness training or information-sharing sessions. In tropical cyclone-prone southwest coastal Bangladesh, women are less likely to evacuate before a cyclone due to lack of transportation, inadequate privacy at the cyclone shelters, and their responsibility for taking care of children, elders, and livestock (Akter & Mallik, 2013).
Racial and ethnic minorities comprise another important disadvantaged subgroup. Research shows that risk perception is consistently higher among ethnic and racial minorities (Pearson, Ballew, Naiman, & Schuldt, 2019). There is widespread evidence of “White male effect” in CC denial. White male effect is a tendency to embrace CC skepticism that is predominantly and overwhelmingly observed among White males in developed nations (Jylhä, Cantal, Akrami, & Milfont, 2016; McCright & Dunlap, 2011). Mayer et al. (2017) found that being a male, politically conservative, White, or rich substantially reduces CC risk perception. Similar results were reported in other studies (Frondel, Simora, & Sommer, 2017; Li, Juhasz-Horvath, Harrison, Pinter, & Rounsevell, 2017; Linnekamp, Koedam, & Baud, 2011). However, risk response does not closely correspond to risk perception. During Hurricane Katrina, Blacks were less inclined than Whites to evacuate before the storm (Elliott & Pais, 2006). In some societies, for the racial and ethnic minorities, responding to CC risk is often constrained by social limits. Banerjee (2015) found that, in India, adaptation measures, such as water conservation infrastructure, are not accessible by members of the lower castes. In a study conducted in Western Nepal, Jones and Boyd (2011) found that physical and financial capital are not the only barriers to CC adaptation; the households that belong to lower castes (e.g., Dalit, Janajatis, and Chhetris) have access to fewer opportunities to respond to CC than households that belong to upper castes.
Exposure and Experience
Past experience with CC and CC-related hazards influences risk perception and response. Fahad and Wang (2018) found that, in Pakistan, farmers’ experience with changes in climatic conditions is a key determinant of their CC risk perception. Kais and Islam (2019) observed a similar pattern among shrimp farmers in Bangladesh. In coastal areas where the risk of sea-level rise is high, CC risk perception is higher among shrimp farmers. In Tanzania, Quinn, Huby, Kiwasila, and Lovett (2003) found that risk perception varies across occupation; while pastoralists ranked water shortage as the most important problem, crop farmers were more concerned about changes in weather patterns. Economic, physical, and structural damage caused by past climatic events significantly increases people’s willingness to pay for flood insurance and flood protection embankment (Akter et al., 2016; Akter & Mallik, 2013; Brouwer et al., 2009). Likewise, prior experience of a catastrophic cyclone or hurricane increases people’s tendency to evacuate, to attend disaster preparedness training, and to follow weather updates and early warnings (Burnside, Miller, & Rivera, 2007; Demuth, Morss, Lazo, & Trumbo, 2016). Demski et al. (2017) found that the winter flooding of 2013/2014 in the United Kingdom led to a higher risk perception and increased support for CC mitigation policies, as well as a greater desire for CC adaptation, among flood victims.
Another set of studies revealed that past experience and exposure do not lead to an increase in CC risk responses if people believe that they are adequately prepared. In Assam (India), Leong (2018) found that a flood protection embankment might even increase vulnerability because people tend to become overconfident about their safety. This phenomenon, known as “risk compensation,” often leads to lower response to CC risks (Hedlund, 2000). Similar results are found in developed nations. For example, in the United Kingdom, despite a high degree of information, CC adaptation is low even in areas that are highly vulnerable to flooding (Taylor et al., 2014; Whitmarsh, 2008). Likewise, availability of technology means that risk perception among farmers is low primarily due to risk compensation in many developed nations (Barnes et al., 2013; Prokopy et al., 2015). Prokopy et al. (2015) found that, in the United States, the presence of crop insurance distorts the risk signal, resulting in very low CC risk perception.
The weak correlation between risk perception and risk response is also explained by the complex nature of CC risk. CC science is very intricate, scientific debate surrounding the validity of the scientific conclusions is intense, and CC impacts are expected to be felt over a long time horizon. Also, CC threats are not homogenously distributed across geography, people, or economic activities (Dietz, Ostrom, & Stern, 2003; Leiserowitz, 2006). Most importantly, CC creates winners and losers. Some countries and occupation groups are likely to benefit from CC, while some countries and occupation groups are expected to bear its brunt. All these factors together make it hard for the general public to grasp the nuances of various CC risks and to fathom their implications for their households or community (Etkin & Ho, 2007; Taylor et al., 2014; Whitmarsh, 2008).
Another important reason for the weak correlation between CC risk perception and response is the normalization of CC risk. Some people believe that CC is too big to be solved by one person, household, or country (O’Neill & Nicholson-Cole, 2009; Takahashi, Burnham, Terracina-Hartman, Sopchak, & Selfa, 2016; Taylor et al., 2014), or that it is the responsibility of the government to solve CC (Taylor et al., 2014). Such normalization is true in both developed and developing nations. For instance, in Australia, farmers have relied on the federal government for drought compensation for centuries (Downing, Jones, & Singley, 2016).
Ideology and Cognition
Risk perceptions vary across ideologies. Douglas and Wildavsky (1983) classified people in four categories based on their ideologies: fatalists, individualists, hierarchists, and egalitarians. Egalitarians and nonfatalists have higher risk perceptions and an inclination to adapt and to support mitigation responses to CC (Libarkin, Gold, Harris, McNeal, & Bowles, 2018; Marris et al., 1998; West et al., 2010; Xue, Hine, Marks, Phillips, & Zhao, 2016). Conversely, individualists tend to downplay CC risk and are less likely to support CC mitigation responses (Xue et al., 2016). Fatalists believe that natural disasters are ordained by God and humans have no power to control the climate. Hence, they believe that preventive actions to mitigate disaster-induced losses are a futile investment. Akter, Krupnik, and Khanam (2017) studied a coastal district of Bangladesh with a history of cyclones, waterlogging, and hailstorms, and they showed that fatalists, although they believed that water-related CC risks were real and were likely to adversely impact their lives and livelihoods, were averse to adopting adaptation measures. Leong (2018) found that people assess their current risks based on the adequateness of their existing safeguard mechanisms. In her study in a flood-prone region in India, she found that “engineers” and “hardened preparers” tend to believe in the effectiveness of existing flood embankments and other coping mechanisms and thereby reduce their risk assessment, which make them more vulnerable. Meanwhile, “discontents” and “pessimists” have high risk perceptions but low responses because they display an inability to diagnose their problems or an unwillingness to cope. Related to the case is another stream of literature that focuses on the extent of adaptation measures. Studies on adaptation measures show that individuals differentiate between partial adaptation measures and complete adaptation measures. In the Netherlands, Botzen, Aerts, and van den Bergh (2013) showed that, despite their higher costs, measures that fully eliminated flood risk received higher public support than those that partially reduced flood risk.
A strand of empirical studies focuses on the rate of discount to use to evaluate future climate threats. The most severe effects of CC are likely to occur in the future, but the costs of adaptation are accrued in the present. Many people heavily discount future CC consequences, preferring to deal with more immediate risks (O’Donoghue & Rabin, 1999; Read, Loewenstein, & Kalyanaraman, 1999; for a review, see Pahl, Sheppard, Boomsa, & Groves, 2014). People also tend to be more optimistic about finding solutions to CC in the future and defer solving it at present (Pahl et al., 2014; Read et al., 1999). A high discount rate can also be a barrier to CC adaptation. Cole et al. (2013) found that farmers discount future returns at an exceptionally high rate; therefore, they recommended that the insurance pay-out for drought index insurance should be delivered immediately. Di Falco et al. (2019) showed that the discount rate in fact can be affected by weather anomalies. The authors found that, in Ethiopia, a 10% negative rainfall anomaly increases the discount rate by 20%, implying that farmers prefer a small immediate payment compared to a large deferred payment when they are hit by a negative weather shock.
Community-Level Determinants of CC Risk Perception and Response
There are studies that show how risk perceptions vary at the community level (Below, Schmid, & Sieber, 2015; Bontempo et al., 1997; Scherer & Cho, 2003). Studies of indigenous communities in semi-arid and arid Africa, small Pacific islands, and the Arctic, for instance, demonstrate that community-level adaptations are necessary to counter climate risks (Derry, 2011; Lazrus, 2015). Empirical studies on community-level determinants of risk perception and risk response are summarized in the following four subsections.
Social Amplification of Risk
Discussion of the effect of cognition on risk assessment and adaptation cannot be complete without discussion of the effect of communities and societies on individuals. Risks and responses are motivated and operationalized in a social setting, and social interactions can amplify or attenuate risk perceptions (Kasperson et al., 1988). Threats and perceptions of risks are generated and transmitted by knowledge communities, media, and interpersonal networks and are codified by the values, attributes, and identities of individuals living in communities (Kasperson et al., 1988; Renn, 2011).1 The importance of media in communicating risks of CC has been well documented. In Japan, Sampei and Aoyagi-Usui (2009) demonstrated that the increase in public concern coincided with a rapid rise in media reporting on threats of global warming. Similarly, Leiserowitz’s (2006) study highlighted the importance of imagery in forming perceptions of CC risk among Americans. The results on the importance of accurate risk communication are supported by findings on communication of flooding risk in Canada (Lieske, Wade, & Roness, 2014). Fischer’s (2019) study validated this logic with evidence from Bangladesh showing that the media’s framing of issues related to water safety and security was crucial in defining narratives of water-relates issues. Similar findings were reported by Mason and Triplett (2016) in their study of media reporting on algae outbreak in Grand Lake in Oklahoma.
The influence of social networks and social pressures on CC risk perception and response has also been documented by many empirical studies (Scherer & Cho, 2003). In Australia, researchers found that threat perception of flooding and sea-level rise is socially and spatially amplified due to prevailing social norms and relations with nature (Raymond & Brown, 2010). Research in developing countries shows similar results. A study conducted in Malaysia found that social trust and environmental knowledge are the key predictors of CC risk perception and participation in conservation-related activities (Choon, Ong, & Tan, 2018). Similar results were observed in China, where Tang, Folmer, and Xue (2013) found that social network played a crucial role in raising awareness and perception of water shortages and prices. In terms of response as well, in Ethiopia, Wossen et al. (2013) showed that households operating in networks were better at water conservation. Similarly, Samaddar, Murase, and Okada (2014) found that communication networks were important for learning new technologies related to water conservation and rainwater harvesting in Bangladesh. Such behaviors are also observed in more nonrelational community forms, like CC activists, water-related professionals, and organizations whose social and group identities are defined by tackling CC (Douglas & Wildavsky, 1983; Perera & Hewege, 2013; Trogrlić et al., 2017).
Cohesive communities are more likely to engage in collective actions to respond to CC risks, while socially less cohesive communities exhibit poor collective actions and thus fail to adapt (Adger, Barnett, Brown, Marshall, & O’brien, 2013; Akter, 2020). For instance, Lo (2013) found that the decision to buy flood insurance in Australia was not correlated with individuals’ risk perception or flood damage experience; rather, it was strongly influenced by their family’s or their friends’ desire for them to buy flood insurance and whether other people with similar characteristics had purchased flood insurance. Comparable results were observed among farmers in Scotland, New Zealand, and the United States, even among farmers who did not believe in anthropogenic CC (Barnes et al., 2013; Prokopy et al., 2015). There is ample evidence in the literature to show that in low-income countries, in the absence of a strong social safety net and formal risk-mitigation arrangements (e.g., insurance), households in vulnerable areas rely on their informal social networks as risk coping mechanisms. Akter and Mallik (2013) showed that poor households utilize social security networks when exposed to cyclones and floods. In Thailand, Allaire (2016) found that use of social networks and online media meant that households experienced significantly lower (37%) flood damage on average during the 2011 Bangkok flooding.
In addition to the drivers of community-based responses, the nature of responses and their effects on future risks on communities also require a closer examination. This is because in certain circumstances, community measures can in fact have unintended consequences. For instance, social networks can act as de-escalating mechanisms that reduce risk perceptions and the willingness to respond among individuals with already low risk perceptions, thus increasing vulnerability (Wolf, Adger, Lorenzoni, Abrahamson, & Raine, 2010). This phenomenon can also explain consistent CC denial as a political identity among conservatives in the United States (Leiserowitz, 2006). In Fiji, Brown, Daigneault, Tjenstrom, and Zou (2018) showed that belonging to one ethnic and social group led to low risk perception of future natural disasters (cyclone). While these examples show people actively participating in communities that perpetuate their existing beliefs, other community-based effects can in fact be unintentional. This is because most independent responses taken by vulnerable individuals and communities aim at reducing the consequences of short-term shocks, rather than being strategic adaptations (Bates, Kundzewicz, Wu, & Palutikof, 2008; Gentle, Thwaites, Race, Alexander, & Maraseni, 2018). Such short-term responses can be maladaptative, leading to negative consequences in the long run (Bates et al., 2008; Brooks, Grist, & Brown, 2009). While some evidence exists on responses to water-related risks and maladaptation (see Christian-Smith, Levy, & Gleick, 2015), more research needs to be done to understand the mechanisms behind successful adaptation and maladaptation practices (McMullan, 2018).
Another important area for consideration is the role of social networks in exacerbating or abating risk perception among vulnerable populations. Evidence suggests that participation in, and utilization of, social networks can differ according to gender, ethnicity, and resources (Brown et al., 2018; Moore, 1990). Brown et al. (2018) found that social norms on land rights and collective damage mitigation from Cyclone Evans were unequal among two ethnicities in a network and therefore affected them differently. There is also some evidence that social networks can reinforce existing socioeconomic order, increasing the marginalization of the vulnerable (Craveiro, 2017). However, more research needs to be conducted to understand the role of social networks in terms of CC risk and responses and their differentiated effects on vulnerable populations.
The role of traditional knowledge in shaping CC risk perception has been well documented. Pacific Island communities, for example, have observed changes in weather and precipitation patterns (Lazrus, 2015; Lefale, 2010), fish spawning and migration behaviors (Levine & Sauafea-Leau, 2013), and coastal landscape (Nunn, 2013). Because traditional knowledge is dependent upon the worldviews of the communities, the CC risks perceived by the communities tend to be strongly correlated with their worldviews. For example, Inuits in Canada believe that the increasing unpredictability of hunting and the rise in popularity of wage work threaten the social fabric of their community (Collings, 2009). Similarly, Lazrus (2015) found that unpredictable rainfall and the rising sea level in Tuvalu threaten community norms and principles. Therefore, communities perceive threats from climate change as threats to their culture and way of life.
Traditional knowledge is also extensively used across rural or isolated communities to adapt to CC risk (Ignatowski & Rosales, 2013; Ingty, 2017; Lazrus, 2015). Such adaptation measures take various forms, including prediction of weather and river basin water changes (Withanachchi, Köpke, Withanachchi, Pathiranage, & Ploeger, 2014), collective water resource management and sharing (Ingty, 2017), local irrigation, water harvesting and recycling (Rivera-Ferre et al., 2016), and predicting changes in water level and fish population (Sanderson et al., 2015).
Traditional knowledge is often overlooked during the adaptation/mitigation policymaking processes at the national and international levels (Ignatowski & Rosales, 2013). Leonard et al. (2013) found that traditional knowledge of the Miriwoong indigenous community in Australia helped scientists gain a deeper understanding of certain ecological functions, hydrological cycles, and seasonality of surface water flow of the East Kimberley region of Northern Australia. This, development organizations and multilateral agencies highlight the importance of incorporation of traditional knowledge in adaptation and mitigation strategies (IPCC, 2018). Rakib et al. (2019) found the predictive power of traditional knowledge in forecasting coastal hazards and salinity intrusion useful for devising effective mitigation and adaptive measures. Yet there are some indications to suggest that in times of rapid changes in climatic conditions, traditional knowledge might not be an adequate predictor of, or response to, CC (CBD & UNEP, 2007; Derry, 2011).
National and Global Level Determinants of CC Risk Perception and Response
The link between CC risk perception and response to CC by policymakers requires investigation. This includes understanding how government officials and policymakers perceive CC risks and the process through which the perceived risk translates into national level policies and regulations.
Public support is considered as an important determinant of risk perception by government officials and the consequent policy actions (Burstein, 2003). Evidence from developed countries shows that public support for adaptation and mitigation policies strongly influences the architecture and fate of the national CC policy (Akter, Bennett, & Ward, 2012; Dietz, Dan, & Shwom, 2007; Leiserowitz, 2006; Singh, Zwickle, Bruskotter, & Wilson, 2017). The conservative movement in the United States played an important role in deterring the government’s effort to ratify the Kyoto Protocol (Brechin, 2003; McCright & Dunlap, 2003). Akter and Bennett (2011) estimated mean household willingness to pay for the Australian Carbon Pollution Reduction Scheme (CPRS) and identified determinants of public support for the CPRS. Their findings revealed a zero mean willingness to pay and strikingly low public support for the CPRS. These findings help explain the actual fate of the CPRS, which was shelved by the Labour Government in 2010 in the face of fierce public opposition. When the policy was resurrected in the form of a carbon tax in 2011, it prompted severe public outcry, which eventually led to the demise of the Labour Government and ended Australia’s endeavor to curb carbon emissions using a carbon pricing mechanism. Germany decided to phase out nuclear energy in the wake of vigorous public opposition following the Fukushima accident in Japan in 2011 (Jahn & Korolczuk, 2012). In France as well, the government suspended its plan to introduce a fuel tax, the centerpiece of France’s CC mitigation policy, in the wake of the so-called yellow vest movement (New York Times, 2018).
Studies have also examined the role of nongovernmental agencies in affecting water-related CC policies. For instance, a study in China found that advocacy by environmental nongovernmental organizations that aligned their strategies with government’s priorities helped in shaping policy on construction of a dam on the Nu River (Zeng, Dai, & Javed, 2018). Other studies have pointed to the role of policy entrepreneurs and interest groups in formulating water policies (Horne, 2013; Huitema & Meijerink, 2010; Renner & Meijerink, 2018).
However, studies of such direct evidence for effects of public support on public policy on CC are rare, especially in developing countries, where the extent of knowledge and climate activism is inadequate. Furthermore, the public policy literature acknowledges that public support is neither a necessary nor a sufficient condition for adoption and implementation of policies (Cobb, Ross, & Ross, 1976; Howlett, Ramesh, & Perl, 2009). CC risk perception in the United States, for example, has been rising steadily over the years (Leiserowitz et al., 2018), yet the Trump administration has had “a seriously debilitating” impact on CC response (Bomberg, 2017). The case of Australia is similar (Pietsch & McAllister, 2010). Part of the problem lies in the fact that, for reasons described above, perceptions of risks and preferences for policies among the general population are not clear (Carson, Louviere, & Wei, 2010). To better understand the dynamics of climate policy formulation and implementation, more research needs to be done to understand the interlinkage between risk perception and adaptation strategies of national and local governments.
International organizations like the IPCC and the United Nations Framework Convention on Climate Change (UNFCCC) are crucial for producing scientific information on CC risks and catalyzing national frameworks for CC risk adaptation and mitigation. These global organizations exercise substantial “epistemic and political authority” (Beck et al., 2014). Water and CC have received high priority in the United Nation’s Sustainable Development Goals (SDG), the blueprint for the world’s current and future economic prosperity and well-being. Goal 6 of the SDG aims to achieve universal and sustainable access to safe and affordable drinking water by 2030 and Goal 13 promises to take urgent actions to combat CC and its impacts.
One limitation of the global CC risk narratives adopted by these organizations is their lack of disciplinary representation. The organizations rely heavily on the natural sciences, particularly the earth sciences, for their reports, syntheses, and policy briefs on CC risk (Bjurström & Polk, 2011; Grothmann, Grecksch, Winges, & Siebenhüner, 2013). Among the social science disciplines, research by economists is overrepresented. Despite the strong relevance of political science, behavioral science, and sociology, research from these fields is rarely cited by the IPCC and other global organizations. For example, flood risk reduction in Bangladesh relies not only on CC mitigation and adaptation measures taken by its government, but also on Bangladesh’s ability to reach an effective and enforceable transboundary water-sharing plan with India (Thomas, 2017). The tendency to overrely on certain disciplines invokes a bias in the public policy sphere and impedes the development of a comprehensive CC risk reduction framework that is accepted by all disciplines.
Fairness and equity in global governance of CC and water policies also posit important questions (Fehr & Schmidt, 1999). The risks of water-related disasters and water insecurity arising from CC are disproportionately skewed toward developing, low-income, and small island nations (Burke, Hsiang, & Miguel, 2015; Garrick & Hall, 2014; Nicholls et al., 2007). However, developed nations are the largest contributors to global greenhouse gas emissions (Boden, Marland, & Andres, 2013). Accordingly, there is a mismatch between risk perception and response, because nations with relatively low risk perceptions are the ones that should be taking necessary responses. Additionally, developing nations face a trade-off between economic growth and CC adaptation, because some CC risk-reduction measures (such as reducing the rate of land clearing or banning the use of cheap but highly polluting fuel) mean a loss of income and livelihood for a majority of their populations (Ma & Jiang, 2019; Tampubolon & Setyoko, 2019).
Discussion and Conclusions
This article presents an overview of the determinants of CC risk perception and the link between CC risk perception and risk response, and some of the implications for water resource planning. The synthesis reveals that risks are perceived and responded to differently at different levels. Women and poorer households exhibit higher CC risk perception than men and nonpoor households. Risk responses, however, are more complex. For many vulnerable communities, despite high risk perception, high costs and lack of access to resources severely constrain their ability to respond to CC risk.
Risk perceptions and responses vary across communities. Cultural relationships with nature and social networks play important roles in determining CC risk perception and response. Networks and communities amplify risk perception and have the power to either accelerate or decelerate risk response. Due to social pressures, people in such networks can respond to water-related CC threat without even perceiving it as a risk. Finally, traditional knowledge plays an important role in shaping risk perception and adaptation behavior among indigenous communities. There is an increasing realization that empowering local communities and integrating traditional adaptive methods with modern mitigation measures are an important pathway for reducing CC vulnerability.
Finally, at national and international levels, public perception and support shape national adaptation and mitigation policies. Issues like inequality and migration have been de-politicized under the umbrella of CC, and solutions to address CC are sought in areas of technology and markets. Debate on political reasons and solutions behind CC needs to take place. At the same time, policy risks of CC, and the impact of policies on CC has not received much scholarly attention. While there is a reasonable body of literature on organizational responses to policy risks, effects of policies on people and communities need more investigation.
An important gap in research is the possible positive effects of CC for people in certain climatic conditions. While such gains are likely to be highly limited, CC can bring favorable outcomes in certain regions, especially in terms of agriculture production. Danish farmers perceive the possibility of a longer summer to be beneficial because it offers increased farming opportunities and higher income for them (Woods, Nielsen, Pedersen, & Kristofersson, 2017). More research is needed to understand regional and local variations in CC benefits in low-temperature climates and how these benefits can be leveraged through effective CC mitigation or adaptation policies. At the same time, increased economic opportunities can also accrue in activities that exacerbate the effects of CC, as is the case with oil production in the Arctic (Petrick et al., 2017). Policy responses in such cases not only should take economic gain into account, but also should be based on moral and ethical considerations.
Traditional knowledge, its role in adapting to climate change, and potential threats to traditional knowledge from changing weather, changing hydrology, and national mitigation measures need better understanding. This should be complemented by studies on national strategies that have incorporated traditional knowledge in their adaptation and mitigation frameworks. Understanding the role of cultural differences within and between societies and the effect of such differences in risk perception and responses is necessary. There is evidence that cultural roots of communities can lead to differential risks and response strategies. For policy measures to be effective, understanding cultural differences and their effects on risk perception and response is imperative.
Another important research gap is the climate policy implications for actors at different levels. There is a growing body of evidence on the effect of CC policy risks on organizations (especially private-sector bodies). The existing studies found that, despite realizing the importance of CC, most firms consider regulatory risks to play the most important role in their adaptive responses. A study of 126 European firms found that regulatory risks are more important for firms than physical risks posed by CC, and firms exposed to regulations had higher responses to CC risk compared to non-exposed firms (Sakhel, 2017). Similar results were echoed by mining firms in Canada, although their responses to CC risk mitigation were low because of costs and uncertainty (Ford et al., 2010, 2011). Other studies indicate that costs of adaptation are an important component of adaptation measures against policy risks (Niles, Lubell, & Haden, 2013). However, research on policy risks has been largely conducted at the organizational level in developed economies. Policy risks should conceptually be important for other economic sectors, most notably farming, where emission regulations and subsidies are important determinants of profitability. Beyond economics, these policies can have important spatial and social consequences that can impact livelihoods. Yet very few studies have been conducted to understand this nexus. Clearly, more attention needs to be paid in the future to how policy risks and responses affect the behavior of households, communities, economic agents, and organizations.
The author’s study is funded by the Start-up Research Grant of the Lee Kuan Yew School of Public Policy, the National University of Singapore (Grant ID# R-603-000-216-133).
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1. The role of knowledge communities is explored in the next section.