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Public perceptions of local flood risk and the role of climate change

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Abstract

The IPCC reports that climate change will pose increased risks of heatwaves and flooding. Although survey-based studies have examined links between public perceptions of hot weather and climate change beliefs, relatively little is known about people’s perceptions of changes in flood risks, the extent to which climate change is perceived to contribute to changes in flood risks, or how such perceptions vary by political affiliation. We discuss findings from a survey of long-time residents of Pittsburgh, Pennsylvania, USA, a region that has experienced regular flooding. Our participants perceived local flood risks as having increased and expected further increase in the future; expected higher future flood risks if they believed more in the contribution of climate change; interpreted projections of future increases in flooding as evidence for climate change; and perceived similar increases in flood risks independent of their political affiliation despite disagreeing about climate change. Overall, these findings suggest that communications about climate change adaptation will be more effective if they focus more on protection against local flood risks, especially when targeting audiences of potential climate sceptics.

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Notes

  1. A total of 23 of these 200 (11.5 %) had missing values on at least one of the questions analyzed here. Missing values therefore differ across analyses. The 23 incomplete responders showed no significant differences from the 177 complete responders in terms of demographic characteristics, flood experience, or political affiliation (p > .05).

  2. We computed average population age from the age categories reported in the 2000 Pittsburgh Census data (downloaded from http://www.city-data.com/us-cities/The-Northeast/Pittsburgh-Population-Profile.html). Specifically, we multiplied the proportion of individuals in each age category by the mid-point of that age category and then computed the overall sum.

  3. One of our nine focal measures (i.e., those listed in Table 1) showed a marginal difference, suggesting that participants with a college education were marginally less likely to interpret the stable flood trend prediction as resulting from climate change (M = 3.33, SD = 1.77 vs. M = 3.86, SD = 1.97), t(191) = 1.98, p = .05.

  4. Floods were defined as involving “water covering some normally useful dry land, where there are several houses or other buildings; water that is more than one foot deep; and water that stays around for a day or more.” Extreme floods were defined as “water covering some useful normally dry land, where there are several houses or other buildings; water that is more than 1 foot deep; and water that stays around days or even weeks.” We followed with a description of the Western Pennsylvania Flood of 2004, which, in pilot interviews, appeared to be well remembered by Pittsburgh residents: “On September 9, 2004, at the tail end of hurricane season, the Pittsburgh region had record-breaking rainfall of 3.6 inches with 5.95 inches falling 9 days later. On September 19, 2004, the rivers crested at 31 feet, 6 feet over flood levels. Extreme flooding and mud slides damaged or destroyed numerous bridges and closed hundreds of roads. Thousands of homes and businesses in Allegheny County and the surrounding counties of Armstrong, Beaver, Butler, Indiana, Washington, and Westmoreland were severely damaged or destroyed by this extreme flooding.”

  5. We started by asking about the present, because it is a natural reference point against which to compare changes from the past and into the future. People are willing and able to report probabilities for future events (Bruine de Bruin et al. 2007; Hurd and McGarry 2002). People are also willing and able to report perceived probabilities for past events, although in hindsight they may be overconfident about how much they knew about the likelihood of events happening (Fischhoff 1975). Yet, our sample showed no significant correlation of older age with reported flood risks for 1963 (r = .05, p > .05 for typical floods; r = .00, p > .05 for extreme floods). Nor were perceived changes in flood risk from 1963 to 2013 correlated with age (r = −.04, p > .05 for typical floods; r = −.03, p > .05 for extreme floods).

  6. We also asked participants direct questions about perceived changes in flood risks, in terms of whether typical and extreme floods would be ‘more likely,’ ‘less likely,’ or ‘about as likely’ in the year 2063 as compared to 2013, and in the year 1963 as compared to 2013. We found significant Spearman rank correlations between these direct responses and the differences between reported flood risks (ranging from .31 to .44, all p<.001).

  7. Because the three graphs were initially presented together, we did not counterbalance the order in which graphs were subsequently presented again. Our goal was to examine the perceived role of climate change in the presented flood projections, and not to test whether people could accurately identify the presented trends. Yet, we did assess participants’ ability to recognize the trends in the presented flood trend predications and found that the graph of the stable flood trend (Fig. 1a) was correctly identified by 67.2 % as stable, graph of the increasing flood trend prediction (Fig. 1b) was correctly identified by 89.0 % as increasing, the graph of the decreasing flood trend (Fig. 1c) was correctly identified by 82.5 % as decreasing. Limiting analyses to those participants who correctly perceived all three trends had no effect on the reported findings regarding the perceived role of climate change.

  8. As might be expected, the specific role of climate change differed by the type of flood trend prediction. A separate ANOVA on agreement with the statements of specific consequences of climate change (more vs. less rain) by flood trend predictions (increasing vs. stable vs. decreasing), F(1, 182) = 77.02, p < .001 found that the perceived contribution of more rain due to climate change was highest for the increasing flood trend prediction, showing a linear decline over the three type of flood trend predictions (M = 5.08, SD = 1.70 vs. M = 3.65, SD = 1.87 vs. M = 2.74, SD = 1.68) with the opposite linearly decreasing pattern being found for the perceived contribution of less rain due to climate change (M = 2.39, SD = 1.57 vs. M = 3.05, SD = 1.72 vs. M = 4.35, SD = 1.85). Again, Democrats showed systematically stronger climate change beliefs than did non-Democrats across these questions, F(1, 182) = 9.63, p < .01, with no additional main effects or interactions for flood experience (yes vs. no) or type of climate change beliefs (more vs. less rain).

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Acknowledgments

This work was supported by the center for Climate and Energy Decision Making (SES-0949710), through a cooperative agreement between the National Science Foundation and Carnegie Mellon University. We thank Carmen Lefevre, Kelly Klima, and Andrea Taylor for their comments and insights.

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Authors and Affiliations

  1. Centre for Decision Research, Leeds University Business School, Maurice Keyworth Building, Leeds, LS2 9JT, UK

    Wändi Bruine de Bruin

  2. Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

    Wändi Bruine de Bruin, Gabrielle Wong-Parodi & M. Granger Morgan

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  1. Wändi Bruine de Bruin
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  2. Gabrielle Wong-Parodi
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  3. M. Granger Morgan
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Correspondence to Wändi Bruine de Bruin.

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Bruine de Bruin, W., Wong-Parodi, G. & Morgan, M.G. Public perceptions of local flood risk and the role of climate change. Environ Syst Decis 34, 591–599 (2014). https://doi.org/10.1007/s10669-014-9513-6

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