Show simple item record

An Agent‐Based Model of Evolving Community Flood Risk

dc.contributor.authorTonn, Gina L.
dc.contributor.authorGuikema, Seth D.
dc.date.accessioned2018-06-11T17:59:11Z
dc.date.available2019-08-01T19:53:23Zen
dc.date.issued2018-06
dc.identifier.citationTonn, Gina L.; Guikema, Seth D. (2018). "An Agent‐Based Model of Evolving Community Flood Risk." Risk Analysis 38(6): 1258-1278.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/144235
dc.description.abstractAlthough individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent‐based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near‐miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high‐risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in‐depth behavioral and decision rules at the individual and community level.
dc.publisherJoseph Henry Press
dc.publisherWiley Periodicals, Inc.
dc.subject.otherflood mitigation
dc.subject.otherAgent‐based model
dc.subject.otherflood risk
dc.titleAn Agent‐Based Model of Evolving Community Flood Risk
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/144235/1/risa12939.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/144235/2/risa12939_am.pdf
dc.identifier.doi10.1111/risa.12939
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferenceEpstein JM. Generative Social Science: Studies in Agent‐Based Computational Modeling. Princeton, NJ: Princeton University Press, 2006.
dc.identifier.citedreferenceKoks EE, Jongman B, Husby TG, Botzen WJW. Combining hazard, exposure and social vulnerability to provide lessons for flood risk management. Environmental Science & Policy, 2015; 47: 42 – 52.
dc.identifier.citedreferenceBirkholz S, Muro M, Jeffrey P, Smith HM. Rethinking the relationship between flood risk perception and flood management. Science of the Total Environment, 2015; 478: 12 – 20.
dc.identifier.citedreferenceBubeck P, Botzen WJW, Kreibich H, Aerts JCJH. Detailed insights into the influence of flood‐coping appraisals on mitigation behaviour. Global Environmental Change, 2013; 23 ( 5 ): 1327 – 1338.
dc.identifier.citedreferenceBrody SD, Kang JE, Bernhardt S. Identifying factors influencing flood mitigation at the local level in Texas and Florida: The role of organizational capacity. Natural Hazards, 2010; 52 ( 1 ): 167 – 184.
dc.identifier.citedreferenceO’Connell PE, O’Donnell G. Towards modelling flood protection investment as a coupled human and natural system. Hydrol. Earth Syst. Sci. 2014; 18: 155 – 171.
dc.identifier.citedreferenceTerpstra T. Emotions, trust, and perceived risk: Affective and cognitive routes to flood preparedness behavior. Risk Analysis, 2011; 31 ( 10 ): 1658 – 1675.
dc.identifier.citedreferenceBonabeau E. Agent‐based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 2002; 99 ( suppl 3 ): 7280 – 7287.
dc.identifier.citedreferenceEvans TP, Kelley H. Multi‐scale analysis of a household level agent‐based model of landcover change. Journal of Environmental Management, 2004; 72 ( 1 ): 57 – 72.
dc.identifier.citedreferenceCrooks AT, Heppenstall AJ. Introduction to agent‐based modelling. Pp. 85 – 105 in Heppenstall A, Crooks A, See L, Batty M (eds). Agent‐Based Models of Geographical Systems. Dordrecht, The Netherlands: Springer, 2012.
dc.identifier.citedreferenceBerglund EZ. Using agent‐based modeling for water resources planning and management. Journal of Water Resources Planning and Management, 2015; 04015025.
dc.identifier.citedreferenceEpstein JM. Modeling civil violence: An agent‐based computational approach. Proceedings of the National Academy of Sciences, 2002; 99 ( suppl 3 ): 7243 – 7250.
dc.identifier.citedreferenceMagliocca N, Safirova E, McConnell V, Walls M. An economic agent‐based model of coupled housing and land markets (CHALMS). Computers, Environment and Urban Systems, 2011; 35 ( 3 ): 183 – 191.
dc.identifier.citedreferenceNg TL et al. An agent‐based model of farmer decision‐making and water quality impacts at the watershed scale under markets for carbon allowances and a second‐generation biofuel crop. Water Resources Research, 2011; 47, W09519.
dc.identifier.citedreferenceZechman EM. Agent‐based modeling to simulate contamination events and evaluate threat management strategies in water distribution systems. Risk Analysis, 2011; 31 ( 5 ): 758 – 772.
dc.identifier.citedreferenceDawson RJ, Peppe R, Wang M. An agent‐based model for risk‐based flood incident management. Natural Hazards, 2011; 59 ( 1 ): 167 – 189.
dc.identifier.citedreferenceKelton WD, Law AM. Simulation Modeling and Analysis. Boston: McGraw Hill, 2000.
dc.identifier.citedreferenceVillarini G, Serinaldi F, Smith JA, Krajewski WF. On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resources Research, 2009; 45 ( 8 ).
dc.identifier.citedreferenceLin S, Shaw D, Ho MC. Why are flood and landslide victims less willing to take mitigation measures than the public? Natural Hazards, 2008; 44 ( 2 ): 305 – 314.
dc.identifier.citedreferencePoussin JK, Botzen WW, Aerts JC. Factors of influence on flood damage mitigation behaviour by households. Environmental Science & Policy, 2014; 40: 69 – 77.
dc.identifier.citedreferenceLindell MK, Hwang SN. Households′ perceived personal risk and responses in a multihazard environment. Risk Analysis, 2008; 28 ( 2 ): 539 – 556.
dc.identifier.citedreferenceLindell MK, Perry RW. The protective action decision model: Theoretical modifications and additional evidence. Risk Analysis, 2012; 32 ( 4 ): 616 – 632.
dc.identifier.citedreferenceBotzen WJW, Aerts JCJH, van den Bergh JCJM. Willingness of homeowners to mitigate climate risk through insurance. Ecological Economics, 2009; 68 ( 8 ): 2265 – 2277.
dc.identifier.citedreferenceWilby RL, Keenan R. Adapting to flood risk under climate change. Progress in Physical Geography, 2012; 36 ( 3 ): 348 – 378.
dc.identifier.citedreferenceKron W. Flood risk = hazard• values• vulnerability. Water International, 2005; 30 ( 1 ): 58 – 68.
dc.identifier.citedreferenceCriss RE, Everett L. Shock. Flood enhancement through flood control. Geology, 2001; 29 ( 10 ): 875 – 878.
dc.identifier.citedreferenceBirkland TA et al. River ecology and flood hazard mitigation. Natural Hazards Review, 2003; 4 ( 1 ): 46 – 54.
dc.identifier.citedreferenceBurn DH. Perceptions of flood risk: A case study of the Red River flood of 1997. Water Resources Research, 1999; 35 ( 11 ): 3451 – 3458.
dc.identifier.citedreferenceSiegrist M, Gutscher H. Natural hazards and motivation for mitigation behavior: People cannot predict the affect evoked by a severe flood. Risk Analysis, 2008; 28 ( 3 ): 771 – 778.
dc.identifier.citedreferenceBubeck P, Botzen WJ, Aerts JC. A review of risk perceptions and other factors that influence flood mitigation behavior. Risk Analysis, 2012; 32 ( 9 ): 1481 – 1495.
dc.identifier.citedreferenceLudy J, Kondolf GM. Flood risk perception in lands “protected” by 100‐year levees. Natural Hazards, 2012; 61 ( 2 ): 829 – 842.
dc.identifier.citedreferenceWenger DE, James TF, Faupel CE. Disaster beliefs and emergency planning, University of Delaware Disaster Research Project, 1980.
dc.identifier.citedreferenceDooley D, Catalano R, Mishra, S, Serxner S. Earthquake preparedness: Predictors in a community survey. Journal of Applied Social Psychology, 1992; 22: 451 – 470.
dc.identifier.citedreferenceLindell MK, Perry RW. Household adjustment to earthquake hazard: A review of research. Environment and Behavior, 2000; 32: 590 – 630.
dc.identifier.citedreferenceTierney K, Lindell M, Perry, R. Facing the Unexpected: Disaster Preparedness and Response in the United States. Washington, DC: Joseph Henry Press, 2001.
dc.identifier.citedreferenceMileti DS, O’Brien P. Warnings during disaster: Normalizing communicated risk. Social Problems, 1992; 39 ( 1 ): 40 – 57.
dc.identifier.citedreferenceDow K, Cutter SL. Crying wolf: Repeat responses to hurricane evacuation orders. Coastal Management, 1998; 26: 237 – 252.
dc.identifier.citedreferenceDillon RL, Tinsley CH. How near‐misses influence decision making under risk: A missed opportunity for learning. Management Science, 2008; 54 ( 8 ): 1425 – 1440.
dc.identifier.citedreferenceDillon RL, Tinsley CH, Cronin M. Why near‐miss events can decrease an individual’s protective response to hurricanes. Risk Analysis, 2011; 31 ( 3 ): 440 – 449.
dc.identifier.citedreferenceTinsley CH, Dillon RL, Cronin MA. How near‐miss events amplify or attenuate risky decision making. Management Science, 2012; 58 ( 9 ): 1596 – 1613.
dc.identifier.citedreferenceCollmann J, Cooper T. Breaching the security of the Kaiser Permanente Internet patient portal: The organizational foundations of information security. Journal of the American Medical Informatics Association, 2007; 14 ( 2 ): 239 – 243.
dc.identifier.citedreferenceCooper T, Collmann J, Neidermeier H. Organizational repertoires and rites in health information security. Cambridge Quarterly of Healthcare Ethics, 2008; 17 ( 04 ): 441 – 452.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.