Bolter, Keren Prize

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Sea Level Rise Misconceptions in Broward County, FL

University of New Orleans

University of New Orleans ScholarWorks@UNO Coastal Resilience Workshop Sea Level Rise Misconceptions in Broward County, FL Keren Prize Bolter Florida Atlantic University, Boca Raton, FL Follow this and additional works at: https://scholarworks.uno.edu/resilience Bolter, Keren Prize, "Sea Level Rise Misconceptions in Broward County, FL" (2015). Coastal Resilience Workshop. 4. https://scholarworks.uno.edu/resilience/2015/posters/4 This Event is brought to you for free and open access by ScholarWorks@UNO. It has been accepted for inclusion in Coastal Resilience Workshop by an authorized administrator of ScholarWorks@UNO. For more information, please contact scholarworks@uno.edu. Sea Level Rise Misconceptions in Broward County, FLDr. Keren Prize Bolter, Department of Geosciences, Florida Atlantic University, Boca Raton, FL   e-mail: kbolter@fau.eduMethodologyIn the study area, Broward County, FL, perceived risk data was collected via28-question online surveys (N = 487) distributed via snowballing (Streeton etal., 2004). Questions included, “What is the elevation where you live?” and“How far would you have to dig in the ground to get to water?” Actual riskwas determined by obtaining true values and indexing vulnerability to stormsurge, residential property loss, and groundwater storage. A preliminarystatistical analysis was conducted to identify spatial trends in terms ofperceived risk being underestimated, realistic, or overestimated.Survey Geocoding – Respondents were given the option to provide theirstreet; zip code was required (there were 475 street level responses). Forthe county street layer, vectors with the same street name same zip codewere dissolved and input to an Address Locator. Respondents locationswere geocoded to street/zip code midpoints. Multiple data sources for streets(US census, Broward county GIS, Florida Department of Transportation(FDOT), ESRI) were used to verify locations.Determining actual elevation, depth to water table (DTW), hurricaneevacuation zone, and flood zone – These are the indicators for propertyloss, groundwater storage, storm surge, and flooding, respectively.Comparing actual risk values to estimations from survey responses requiresdownscaling data to the smallest area in which the respondent can possiblyreside. Data was clipped to residential areas as designated by FDOT landuse. Streets within the same zip code were concatenated, and a 200 ft bufferwas created around each. The mean, standard deviation, and range ofelevation, DTW, and surge zone were calculated for each street buffer usinga zonal statistics tool. Values for all data were extracted to respondent pointsand evaluated against survey answers.Indexing indicators for relative risk – Respondents were asked in Likert scaleformat to estimate personal risk to property loss, storm surge (SS), andflooding, in comparison to the rest of the county. To compare actual data tothe survey answers, indexes were created for each of the three indicators.For SS, two feet of SLR were added to a category 5 Sea, Lake, andOverland Surges from Hurricanes (SLOSH) model and interpolated. The SSheight was subtracted from elevation to calculate depth of surge as a rastersurface. For the SS and elevation rasters, standard deviations were takenfrom the mean to create 5 categories of risk. For the DTW, there were only 5categories, so these were used. Respondents were classified by each index.Other Survey Answers – Answers related to demographics andopinions/concerns about SLR were aggregated and coded. A frequencyanalysis and contingency tables were used to assess the responses.IntroductionGlobal climate change stressors downscale to specific local vulnerabilities,thus requiring unique local adaptation strategies. In southeast Florida, sealevel rise (SLR) is of specific concern, both as a present and as animpending threat, that requires a localized planning approach (Parkinson,2009). Zhang (2010) estimated that 79% of Broward County’s land area willbe inundated between 1.5 and 3 m (4.9 to 9.8 ft) of SLR. Coastal populationsare particularly at risk due to erosion, inundation and storm surge, but interiorpopulations are also susceptible to rising water tables. Groundwater storageis reduced in the wet season, and SLR permanently limits storage capacityby lifting the aquifer closer to the ground surface.Robust SLR adaptation options require significant economic costs that manypeople may not be willing to pay for if they do not perceive an actual risk.While actual risk can be calculated from physical data and statisticalprobabilities (Kaplan & Garrick, 2006), perceived risk differs becauseindividual views are skewed by political, cultural, emotional, and timing filters(Leiserowitz, 2005). If perceived risk does not adequately line up with actualrisk, the necessary strategies may not be implemented due to lack of publicsupport (Raaijmakers et al., 2008).The objectives of this study are to 1) Identify perceived risk to influences ofSLR on storm surge, inundation, flooding, and society 2) Determine actualrisk based on an index of physical vulnerability data and 3) Compareperceived risk to actual risk both spatially and socioeconomically todetermine how closely residents’ perception of risk matches their actual risk.Discussion & ConclusionInitial results indicate misconceptions and an overall lack of awareness interms of source and magnitude of risk. While 80% of respondents werehomeowners, 72% did not know their flood zone. Several respondentsanswered open response questions with statements such as “Florida will beunderwater.” The amount of property loss that will be seen in the next 50years is minimal. The biggest short term threat from SLR is increased floodingdue to compromised drainage and decreased aquifer storage. A higher stormsurge that moves further inland is the next main SLR impact. For elevationrisk bias, there was an even number of respondents that overestimated andunderestimated their risk, but nearly all underestimated risk for DTW. Therewas a statistically significant trend moving south from overestimation tounderestimation. For DTW, this trend went from east to west.In terms of climate change impacts, effective communication is lagging behindscientific knowledge (Moser, 2010). Inconsistencies between perceived andactual risk may hinder public support for costly SLR mitigation strategies.Results can pinpoint areas in which to focus on increasing awareness. Furtherresearch will include risk bias assessment methods including principalcomponent analysis and multivariate analysis.ReferencesLeiserowitz, A. A. 2005. American Risk Perceptions: Is Climate Change Dangerous? Risk Analysis 25, 1433–1442.Kaplan, S., and B. J. Garrick. 2006. On the Quantitative Definition of Risk. Risk Analysis 1 (1): 11–27. Moser, S. C. 2010. Now More Than Ever: The Need for More Societally Relevant Research on Vulnerability and Adaptation to Climate Change.” Applied Geography 30 (4): 464–474.Parkinson, R. W. 2009. “Adapting to Rising Sea Level: a Florida Perspective.” In AIP Conference Proceedings, 1157:19–25. Raaijmakers, R., Krywkow, J, and van der Veen, A. 2008. Flood risk perceptions and spatial multicriteriaanalysis: An exploratory research for hazard mitigation, Natural Hazards 46 (3): 307-322.Streeton, R., Cooke, M., & Campbell, J. 2004. Researching the researchers: Using a snowballing technique. Nurse Researcher, 12(1), 35-46.Zhang, K. 2010. Analysis of Non-linear Inundation from Sea-level Rise Using LIDAR Data: a Case Study for South Florida. Climatic Change 106 (4): 537–565.Selected Survey Demographic ResultsLiDAR Elevation IndexStudy AreaSurge Depth IndexGroundwater Index11.7%15.6,%17.7%19.9%34.3%Age18 - 2526 - 3536 - 4546 - 55Over 5559%41%Gender% Female% Male14%6%11%16%19%32%2%Annual Household Income<$30k$30k - $39,999$40k - $49,999$50k - $74,999$75k - $100k> $100kblank71%13%11%5%Race/EthnicityWhite, non-HispanicHispanicBlack, non-HispanicOther18%51%20%11%SLR KnowledgeNot at all familiarSomewhat familiarVery familiarExtremely familiar11%89%Is SLR occurring?NoYes4%26%34%22%14%How much SLR by 2030?Not at allUp to 3 inches3 to 7 inches7 to 12 inchesOver 12 inches5%23%17%33%22%How much SLR by 2050?Not at allUp to 9 inches9 to 12 inches12 to 24 inchesOver 24 inches17%16%50%17%Which Evacuation Zone?Yes, Zone AYes, Zone BNoI don't know72%10%10%5%1%1%1%Which Flood Zone?I don't knowXAHAEVE12.826.941.513.25.621.230.827.414.36.413.028.436.815.66.2VERY LOW LOW AVERAGE HIGH VERY HIGHRelative Perceived Risk  Property loss risk storm surge risk flooding riskSelected Survey Perception ResultsSelected Comparison Results5.218.826.527.122.40.0 5.0 10.0 15.0 20.0 25.0 30.0NONELOWMEDIUMHIGHVERY HIGHOverall SLR concern?4134155114806810683 841100 - 3 FT 3.1 - 6 FT 6.1 - 9 FT 9.1 - 12 FT > 12 FTLand Elevations HistogramActual Percieved8421312113 61295144841020 - 1 FT 1.1 - 4 FT 4.1 - 8 FT 8.1 - 12 FT > 12 FTDepth to Water Table HistogramActual Percieved59%31%10%Depth to Water Table Risk PerceptionunderestimateRealisticOverestimatePerceived Risk for Inundation Perceived Risk for GroundwaterInundation Cluster Analysis Groundwater Cluster AnalysisActual: 3-7 inches Actual: 9-24 inchesActualX 5%AH 24%AE 45%VE 26%ActualZone A 6%Zone B 12%No 82%

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Sea Level Rise Misconceptions in Broward County, FL

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