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Assessing Illinois’s flood vulnerability using Hazus-MH

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Abstract

In this study, we developed a flood vulnerability index to help planners screen the relative flood vulnerability across the entire state of Illinois at the county, jurisdictional, and census block scales. Our flood vulnerability index was comprised of a deterministic flood loss assessment using the Federal Emergency Management Agency’s Hazus-MH multi-hazard loss estimation software, coupled with a parametric social vulnerability index developed from US Census data. The flood-vulnerability screening revealed that approximately half (46 %; 8500 km2) of Illinois’s 18,500 km2 special flood hazard areas (i.e., 100-year floodplain) had low flood vulnerability (i.e., few people affected, with little or no flood losses). This finding substantially reduces the area that Illinois planners may need to focus their mitigation efforts. The relative flood vulnerability across the three spatial scales evaluated in this study generally mirrored each other (i.e., counties with high flood vulnerability had a substantial number of its jurisdictions and census blocks with high flood vulnerability). However, the census block-level analysis revealed that counties and a substantial number of jurisdictions with moderate-to-low relative flood vulnerability often had pockets (one to a few census blocks) of high relative flood vulnerability. This suggests flood-vulnerability screening should be performed to at least the census block scale to ensure pockets of vulnerability are not overlooked. Jurisdictional flood loss ratios (flood losses proportional to total floodplain exposure) in Illinois were generally largest in rural and relatively unprotected floodplain communities located along the state’s large rivers. This suggests the economic impacts related to riverine flooding would be more severe in these rural jurisdictions, relative to their economic base, and likely exceed the economic resources these communities could assemble for flood recovery. The jurisdiction flood-vulnerability screening results indicated the primary driver of flood vulnerability was different between urban and rural communities. In urban jurisdictions, social vulnerability was the main driver in flood vulnerability where in the rural jurisdictions flood losses tended to be the primary driver. This suggests different mitigation strategies will likely need to be employed in urban versus rural jurisdictions in order to reduce flood vulnerability.

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References

  • Association of State Floodplain Mangers (ASFPM) (2009) Hazus-MH flood model validation. http://www.floods.org/ace-files/Projects/ASFPM_2009_HAZUS_Validation_Final.pdf Accessed 11 Oct 2014

  • Association of State Floodplain Mangers (ASFPM) (2010a) Comparing Hazus-MH flood loss estimates across hazard identification methods and building stock inventory data Albion Township Dane County, WI. http://www.floods.org/ace-files/Projects/ASFPM_2010_HAZUS_UDF_MultiMethod_Comp_Final.pdf Accessed 11 Oct 2014

  • Association of State Floodplain Mangers (ASFPM) (2010b) Structure level flood damage. Analysis: NFIP and Hazus-MH midwest flooding 2008 Albion Township, Dane County, WI. http://www.floods.org/ace-files/Projects/ASFPM_2010_HAZUS_UDF_NFIP_Comp_Final.pdf Accessed 11 Oct 2014

  • Balica SF, Douben N, Wrigth NG (2009) Flood vulnerability indices at varying spatial scales. Water Sci Technol 60(10):2571–2580. doi:10.2166/wst.2009.183

    Article  Google Scholar 

  • Balica SF, Popescu I, Beevers L, Wright NG (2013) Parametric and physically based modelling techniques for flood risk and vulnerability assessment: a comparison. Environ Model Softw 41:84–92. doi:10.1016/j.envsoft.2012.11.002

    Article  Google Scholar 

  • Berke P, Godschalk D (2009) Searching for the good plan. J Plan Lit 23(3):227–240

    Article  Google Scholar 

  • Borden KA, Schmidtlein MC, Emrich CT, Piegorsch WW, Cutter SL (2007) Vulnerability of US cities to environmental hazards. J Homel Secur Emerg Manag 4(2):1–21

    Google Scholar 

  • Burton CG (2010) Social vulnerability and hurricane impact modeling. Nat Hazards Rev 11(2):58–68

    Article  Google Scholar 

  • Burton CG (2015) A validation for community resilience to natural hazard disasters using the recovery from Hurricane Katrina as a case study. Annu As Am Geogr 105(1):67–86

    Article  Google Scholar 

  • Burton C, Cutter SL (2008) Levee failures and social vulnerability in the Sacramento-San Joquin Delta Area, California. Nat Hazards Rev 3:136–149

    Article  Google Scholar 

  • Chakraborty J, Tobin GA, Montz BE (2005) Population evacuation: assessing spatial variability in geophysical risk and social vulnerability to natural hazards. Nat Hazards Rev 6(1):23–33

    Article  Google Scholar 

  • Clark JR, Moul D (2003) Coverage improvement in Census 2000 Enumeration. US Census Bureau, Census 2000 testing, experimentation and evaluation program, Topic 10 Report, Washington D.C. US Census Bureau. https://www.census.gov/pred/www/rpts/TR10.pdf. Accessed 11 Oct 2014

  • Collins TW, Grineski SE, Aguilar M (2009) Vulnerability to environmental hazards in the Ciudad Juárez (Mexico)-El Paso (USA) metropolis: a model for spatial risk assessment in transnational context. Appl Geogr 29(3):448–461

    Article  Google Scholar 

  • Conner RF, Hiroki K (2005) Development of a method for assessing flood vulnerability. Water Sci Technol 51(5):61–67

    Google Scholar 

  • Cross JA (2001) Megacities and small towns: different perspectives on hazard vulnerability. Environ Hazards 3:63–80. doi:10.3763/ehaz.2001.0307

    Google Scholar 

  • Cutter SL (2010) Social science perspectives on hazard and vulnerability science. In: Beer T (ed) Geophysical hazard: minimizing risk, maximizing awareness. Springer, Dordrecht, pp 17–30. ISBN: 978-90-481-323-5

  • Cutter SL, Finch C (2007) Temporal and spatial changes in social vulnerability to natural hazards. Proc Natl Acad Sci USA 105(7):2301–2306

    Article  Google Scholar 

  • Cutter SL, Mitchell JT, Scott MS (2000) Revealing the vulnerability of people and places: a case study of Georgetown County, South Carolina. Annu As Am Geogr 90(4):713–737

    Article  Google Scholar 

  • Cutter SL, Boruff BJ, Shirley WL (2003) Social vulnerability to environmental hazards. Soc Sci Q 84(1):242–261

    Article  Google Scholar 

  • Cutter SL, Emrich CT, Morath DP, Dunning CM (2013) Integrating social vulnerability into federal flood risk management planning. J Flood Risk Manag. doi:10.1111/jfr3.12018

    Google Scholar 

  • Ding A, White JF, Ullman PW, Fashokun AO (2008) Evaluation of HAZUS-MH flood model with local data and other program. Nat Hazards Rev 9(1):20–28. doi:10.1061/(ASCE)1527-6988(2008)9:1(20)

    Article  Google Scholar 

  • Dun and Bradstreet (2006) Market Analysis Profile aggregated by Standard Industrial Classification (SIC) Code Clusters, Database. July

  • Elliot JR, Pais J (2006) Race, class, and Hurricane Katrina: social differences in human responses to disaster. Soc Sci Res 335(2):295–321

    Article  Google Scholar 

  • Executive Order 11988, Floodplain Management (1977) 42 CFR 26951, 3CFR 1977

  • Federal Emergency Management Agency (FEMA) (2011) Local multi-hazard mitigation planning guidance. U.S. Department of Homeland Security https://www.fema.gov/media-library/assets/documents/23194?fromSearch=fromsearch&id=4859 Accessed 15 Jan 2015

  • Federal Emergency Management Agency (FEMA) (2012a) Flood insurance community rating system participation. U.S. Department of Homeland Security http://www.fema.gov/media-library/assets/documents/27808 Accessed 3 Sept 2015

  • Federal Emergency Management Agency (FEMA) (2015) Community Status Book Report, Illinois. U.S. Department of Homeland Security https://www.fema.gov/cis/IL.pdf. Accessed 3 Sept 2015

  • Federal Emergency Management Agency (FEMA) Mitigation Division (2012b) Multi-hazard loss estimation methodology flood model HAZUS-MH 2.1 technical manual. http://www.fema.gov/library/viewRecord.do?id=5120. Accessed 28 June 2013

  • Fekete A (2009) Validation of a social vulnerability index in context to river-floods in Germany. Nat Hazards Earth Syst Sci 9(2):393–403

    Article  Google Scholar 

  • Fekete A (2011) Spatial disaster vulnerability and risk assessments: challenges in their quality and acceptance. Nat Hazards 61(3):1161–1178

    Article  Google Scholar 

  • Finch C, Emrich CT, Cutter SL (2010) Disaster disparities and differential recovery in New Orleans. Popul Environ 31(4):179–202

    Article  Google Scholar 

  • Flanagan BE, Gregory EW, Hallisey EJ, Heitgerd JL, Lewis B (2011) A social vulnerability index for disaster management. J Homel Secur Emerg Manag 8(1):1–22

    Google Scholar 

  • Frazier TG, Wood N, Yarnal B, Bauer DH (2010) Influence of potential sea level rise on societal vulnerability to hurricane storm-surge hazards, Sarasota County, Florida. Appl Geogr 30(4):490–505

    Article  Google Scholar 

  • Frazier TG, Walker MH, Kumari A, Thomspon CM (2013) Opportunities and constraints to hazard mitigation planning. Appl Geogr 40:52–60

    Article  Google Scholar 

  • Godschalk D (2003) Urban hazard mitigation: creating resilient cities. Nat Hazards Rev 4(3):136–143. http://webra.cas.sc.edu/hvri/products/sovi2010_data.aspx Accessed 7 July 2013

  • H. John Heinz III Center for Science, Economics and the Environment [Heinz Center] (2000) The hidden costs of coastal hazards: implications for risk assessment and mitigation. Island Press, Washington

    Google Scholar 

  • Hall JW, Tarantola S, Bates PD, Horritt MS (2005) Distributed sensitivity analysis of flood inundation model calibration. J Hydraul Eng. doi:10.1061/(ASCE)0733-9429(2005)131:2(117),117-126

    Google Scholar 

  • Hannah MG (2001) Sampling and the politics of representation in US Census 2000. Environ Plan D Soc Space 19:515–534

    Article  Google Scholar 

  • Hazards and Vulnerability Research Institute (HVRI) (2012) Social Vulnerability Index (SoVI) for the United States—2006–2010 Data

  • Illinois State Water Survey (ISWS) (1996) One-hundred and five-hundred year flood zones for unincorporated areas in Illinois. http://www.isgs.uiuc.edu/nsdihome/outmeta/IL_Flood_Zones_1986_Py.html Accessed 26 June 2013

  • Jolliffe IT (2002) Principal components analysis, 2nd edn. Springer, New York

    Google Scholar 

  • Karmakar S, Slobodan P, Peck A, Black J (2010) An information system for risk-vulnerability assessment to flood. J Geogr Inf Syst 2:129–146. doi:10.4236/jgis.2010.23020

    Google Scholar 

  • Lein JK, Abel LE (2010) Hazard vulnerability assessment: How well does nature follow our rules? Environ Hazards 9(2):147–166

    Article  Google Scholar 

  • Masozera M, Bailey M, Kerchner C (2007) Distribution of impacts of natural disasters across income groups: a case study of New Orleans. Ecol Econ 63:299–306

    Article  Google Scholar 

  • Mennis J (2009) Dasymetric mapping for estimating population in small areas. Geogr Compass 3(2):727–745

    Article  Google Scholar 

  • Montz BE, Evans TA (2001) GIS and social vulnerability analysis. In: Gruntfest E, Handmer J (eds) Coping with flash floods. Kluwer Academic Publishers, Netherlands, pp 37–48

    Chapter  Google Scholar 

  • Mustafa D, Ahmed S, Saroch E, Bell H (2011) Pinning down vulnerability: from narratives to numbers. Disasters 35(1):62–86

    Article  Google Scholar 

  • Myers CA, Slack T, Singelmann J (2008) Social vulnerability and migration in the wake of disaster: the case of Hurricanes Katrina and Rita. Popul Environ 29(6):271–291

    Article  Google Scholar 

  • National Oceanic and Atmospheric (NOAA) (2014) National oceanic and atmosphere administration’s storm event database. http://www.ncdc.noaa.gov/stormevents/choosedates.jsp?statefips=17%2CILLINOIS. Accessed 15 Jan 2015

  • National Research Council (NRC) (2006) Facing hazards and disasters: understanding human dimensions. National Academy Press. Washington. http://www.nap.edu/catalog/11671. Accessed 17 Dec 2014

  • National Research Council (NRC) (2009) Mapping the zone, improving flood map accuracy. The National Academies Press, Washington. http://www.nap.edu/catalog/12573. Accessed 17 Dec 2014

  • Ngo EB (2001) When disasters and age collide: reviewing vulnerability of the elderly. Nat Hazards Rev 2(2):80–89

    Article  Google Scholar 

  • Passel JS (2005) Estimates of the size and characteristics of the undocumented population. Pew Hispanic Center, Washington

    Google Scholar 

  • Phillips BD, Metz WC, Nieves LA (2005) Disaster threat: preparedness and potential response of the lowest income quartile. Glob Environ Change B Environ Hazards 6(3):123–133

    Google Scholar 

  • Polsky C, Neff R, Yarnal B (2007) Building comparable global change vulnerability assessments: the vulnerability scoping diagram. Glob Environ Change 17(3–4):472–485

    Article  Google Scholar 

  • Remo JWF, Carlson M, Pinter N (2012) Hydraulic and flood-loss modeling of levee, floodplain, and river management strategies, Middle Mississippi River, USA. Nat Hazards 61:551–575. doi:10.10007/s11069-011-9938-x

    Article  Google Scholar 

  • Remo JWF, Pinter N, Ellison B, Mahoub M (2013) Illinois statewide flood hazard assessment. In: Illinois Emergency Management Agency, 2013 Illinois Natural Hazard Mitigation Plan. http://www.illinois.gov/iema/Mitigation/documents/Plan_IllMitigationPlan.pdf. Accessed 19 Jan 2015

  • Rygel L, O’Sullivan D, Yarnal B (2006) A Method for constructing a social vulnerability index: an application to hurricane storm surges in a developed country. Mitig Adapt Strateg Glob Change 11(3):741–764

    Article  Google Scholar 

  • Scawthorn C, Flores P, Balis N, Seligson H, Tate E, Cahng S, Mifflin E, Thomas W, Murphy J, Jones C, Larence M (2006) HAZUS-MH flood loss estimation methodology II. Damage and loss assessment. Nat Hazards Rev. doi:10.1061/(ASCE)1527-6988(2006)7:2(72

    Google Scholar 

  • Schmidtlein MC, Shafer JM, Berry M, Cutter SL (2010) Modeled earthquake losses and social vulnerability in Charleston, South Carolina. Appl Geogr 31(1):269–281

    Article  Google Scholar 

  • Schneider PJ, Schauer BA (2006) HAZUS—its development and its future. Nat Hazards Rev 7:40–44. doi:10.1061/(ASCE)1527-6988(2006)7:2(40)

    Article  Google Scholar 

  • Sleeter R (2008) A new method for mapping population distribution: fact sheet 2008–3010, U.S. Geological Survey, Reston, VA. http://pubs.usgs.gov/fs/2008/3010/. Accessed 8 Jan 2015

  • Tate E (2012) Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis. Nat Hazards 63:325–347. doi:10.1007/s11069-012-0152-2

    Article  Google Scholar 

  • Tate E (2013) Uncertainty analysis for a social vulnerability index. Annu As Am Geogr 10(3):526–543

    Article  Google Scholar 

  • Tate E (2014) Uncertainty and sensitivity analysis of the Hazus-MH flood model. Nat Hazards Rev. doi:10.1061/(ASCE)NH.1527-6996.0000167

    Google Scholar 

  • Tate E, Cutter SL, Berry M (2010) Integrated multihazard mapping. Environ Plan B Plan Des 37(4):646–663

    Article  Google Scholar 

  • Tierney K (2006) Social inequality, hazards and disasters. In: Daniels RJ, Kettle DF, Kunreuther H (eds) Risk and disasters: lessons from Hurricane Katrina. University of Pennsylvania Press, Philadelphia, pp 109–128

    Google Scholar 

  • URS Group (2007) Hazus-MH riverine flood validation study. Washington County, Utah. Federal Emergency Management Agency (FEMA), U.S. Department of Homeland Security. Washington. http://www.fema.gov/media-library-data/20130726-1620-20490-4869/hz_ut_fld_val.pdf. Accessed 30 Sept 2014

  • U.S. Census Bureau (2000) Census of population and housing, 2000: summary tape file 1B. Extract on CD-ROM/prepared by the Bureau of Census

  • U.S. Census Bureau (2014) Illinois quick facts from the U.S. Census Bureau. http://quickfacts.census.gov/qfd/states/17/17003.html. Accessed 30 Sept 2014

  • U.S. Geologic Survey (USGS) (2013) National elevation dataset. http://viewer.nationalmap.gov/viewer/ Accessed 01 June 2013

  • van der Veen A, Logtmeijer C (2005) Economic hotspots: visualizing vulnerability to flooding. Nat Hazards 36(1–2):65–80

    Article  Google Scholar 

  • Vincent K (2004) Creating an index of social vulnerability to climate change in Africa. Working paper 56. Tyndall Centre for Climate Change Research, London

  • Wilks DS (2006) Statistical methods in the atmospheric sciences. Elsevier, Oxford

    Google Scholar 

  • Wisner B, Blaikie P, Cannon T, Davis I (2004) At risk: natural hazards. People’s vulnerability and disasters. Routledge, New York

    Google Scholar 

  • Wood NJ, Burton CG, Cutter SL (2010) Community variations in social vulnerability to Cascadia-related tsunamis in the US Pacific Northwest. Nat Hazards 52(2):369–389

    Article  Google Scholar 

  • Wu SY, Yarnal B, Fisher A (2002) Vulnerability of coastal communities to sea level rise: a case study of Cape May County, New Jersey, USA. Clim Res 22:255–270

    Article  Google Scholar 

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Acknowledgments

We thank Mr. Ross Guida and the three anonymous reviewers for their helpful reviews of this manuscript. In addition, we would like to thank Ms. Amanda Damptz for assistance with the figures. This research was carried out with support from the Illinois Emergency Management Agency and US National Science Foundation, award #1235317 (Infrastructure Management for Extreme Events).

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Authors and Affiliations

  1. Department of Geography and Environmental Resources, Southern Illinois University Carbondale, Carbondale, IL, 62901-4323, USA

    Jonathan W. F. Remo & Moe Mahgoub

  2. The Department of Earth and Planatery Sciences, University of California Davis, Davis, CA, 95616, USA

    Nicholas Pinter

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  1. Jonathan W. F. Remo
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Correspondence to Jonathan W. F. Remo.

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This research was carried out with support from the Illinois Emergency Management Agency and US National Science Foundation, award #1235317 (Infrastructure Management for Extreme Events). The contributing authors have no conflict of interest, including specific financial interests, relationships, or affiliations relevant to the subject matter or materials contained within this manuscript.

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Nicholas Pinter was formally affiliated with Department of Geology, Southern Illinois University Carbondale, Carbondale, IL 62901-4323, USA during his study.

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Remo, J.W.F., Pinter, N. & Mahgoub, M. Assessing Illinois’s flood vulnerability using Hazus-MH. Nat Hazards 81, 265–287 (2016). https://doi.org/10.1007/s11069-015-2077-z

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