Show simple item record

Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios

dc.contributor.authorTonn, Gina
dc.contributor.authorGuikema, Seth
dc.contributor.authorZaitchik, Benjamin
dc.date.accessioned2020-05-05T19:36:07Z
dc.date.availableWITHHELD_12_MONTHS
dc.date.available2020-05-05T19:36:07Z
dc.date.issued2020-04
dc.identifier.citationTonn, Gina; Guikema, Seth; Zaitchik, Benjamin (2020). "Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios." Risk Analysis 40(4): 884-898.
dc.identifier.issn0272-4332
dc.identifier.issn1539-6924
dc.identifier.urihttps://hdl.handle.net/2027.42/154949
dc.description.abstractFlood risk is a function of both climate and human behavior, including individual and societal actions. For this reason, there is a need to incorporate both human and climatic components in models of flood risk. This study simulates behavioral influences on the evolution of community flood risk under different future climate scenarios using an agent‐based model (ABM). The objective is to understand better the ways, sometimes unexpected, that human behavior, stochastic floods, and community interventions interact to influence the evolution of flood risk. One historic climate scenario and three future climate scenarios are simulated using a case study location in Fargo, North Dakota. Individual agents can mitigate flood risk via household mitigation or by moving, based on decision rules that consider risk perception and coping perception. The community can mitigate or disseminate information to reduce flood risk. Results show that agent behavior and community action have a significant impact on the evolution of flood risk under different climate scenarios. In all scenarios, individual and community action generally result in a decline in damages over time. In a lower flood risk scenario, the decline is primarily due to agent mitigation, while in a high flood risk scenario, community mitigation and agent relocation are primary drivers of the decline. Adaptive behaviors offset some of the increase in flood risk associated with climate change, and under an extreme climate scenario, our model indicates that many agents relocate.
dc.publisherGuilford
dc.publisherWiley Periodicals, Inc.
dc.subject.otherAgent‐based model
dc.subject.othermitigation
dc.subject.otherflood risk
dc.subject.otherclimate change
dc.subject.otherbehavioral influences
dc.titleSimulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBusiness (General)
dc.subject.hlbtoplevelBusiness and Economics
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154949/1/risa13428_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/154949/2/risa13428.pdf
dc.identifier.doi10.1111/risa.13428
dc.identifier.sourceRisk Analysis
dc.identifier.citedreferenceKick, E. L., Fraser, J. C., Fulkerson, G. M., McKinney, L. A., & DeVries, D. H. ( 2011 ). Repetitive flood victims and acceptance of FEMA mitigation offers: An analysis with community–system policy implications. Disasters, 35 ( 3 ), 510 – 539.
dc.identifier.citedreferenceDillon, R. L., & Tinsley, C. H. ( 2008 ). How near‐misses influence decision making under risk: A missed opportunity for learning. Management Science, 54 ( 8 ), 1425 – 1440.
dc.identifier.citedreferenceDillon, R. L., Tinsley, C. H., & Cronin, M. ( 2011 ). Why near‐miss events can decrease an individual’s protective response to hurricanes. Risk Analysis, 31 ( 3 ), 440 – 449.
dc.identifier.citedreferenceEpstein, J. M. ( 2006 ). Generative social science: Studies in agent‐based computational modeling. Princeton, NJ: Princeton University Press.
dc.identifier.citedreferenceEvans, T. P., & Kelley, H. ( 2004 ). Multi‐scale analysis of a household level agent‐based model of landcover change. Journal of Environmental Management, 72 ( 1 ), 57 – 72.
dc.identifier.citedreferenceFox‐Rogers, L., Devitt, C., O’Neill, E., Brereton, F., & Clinch, J. P. ( 2016 ). Is there really “nothing you can do”? Pathways to enhanced flood‐risk preparedness. Journal of Hydrology, 543, 330 – 343.
dc.identifier.citedreferenceHaer, T., Botzen, W. J. W., & Aerts, J. C. ( 2016 ). The effectiveness of flood risk communication strategies and the influence of social networks—Insights from an agent‐based model. Environmental Science & Policy, 60, 44 – 52.
dc.identifier.citedreferenceHaer, T., Botzen, W. J. W., & Aerts, J. C. ( 2019 ). Advancing disaster policies by integrating dynamic adaptive behavior in risk assessments using an agent‐based modeling approach. Environmental Research Letters, 14, 044022
dc.identifier.citedreferenceHaer, T., Botzen, W. J. W., Moel, H., & Aerts, J. C. ( 2017 ). Integrating household risk mitigation behavior in flood risk analysis: An agent‐based model approach. Risk Analysis, 37 ( 10 ), 1977 – 1992.
dc.identifier.citedreferenceHino, M., Field, C. B., & Mach, K. J. ( 2017 ). Managed retreat as a response to natural hazard risk. Nature Climate Change, 7 ( 5 ), 364 – 370.
dc.identifier.citedreferenceHudson, P., Botzen, W. W., Poussin, J., & Aerts, J. C. ( 2017 ). Impacts of flooding and flood preparedness on subjective well‐being: A monetisation of the tangible and intangible impacts. Journal of Happiness Studies, 20 ( 2 ), 665 – 682.
dc.identifier.citedreferenceJanssen, E., Wuebbles, D. J., Kunkel, K. E., Olsen, S. C., & Goodman, A. ( 2014 ). Observational‐and model‐based trends and projections of extreme precipitation over the contiguous United States. Earth’s Future, 2 ( 2 ), 99 – 113.
dc.identifier.citedreferenceKates, R. W., Travis, W. R., & Wilbanks, T. J. ( 2012 ). Transformational adaptation when incremental adaptations to climate change are insufficient. Proceedings of the National Academy of Sciences, 109 ( 19 ), 7156 – 7161.
dc.identifier.citedreferenceKundzewicz, Z. W. ( 2002 ). Non‐structural flood protection and sustainability, Water International, 27 ( 1 ), 3 – 13.
dc.identifier.citedreferenceKundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., … Muir‐Wood, R. ( 2014 ). Flood risk and climate change: Global and regional perspectives. Hydrological Sciences Journal, 59 ( 1 ), 1 – 28.
dc.identifier.citedreferenceLin, S., Shaw, D., & Ho, M. C. ( 2008 ). Why are flood and landslide victims less willing to take mitigation measures than the public? Natural Hazards, 44 ( 2 ), 305 – 314.
dc.identifier.citedreferenceLindell, M. K., & Hwang, S. N. ( 2008 ). Households’ perceived personal risk and responses in a multihazard environment. Risk Analysis, 28 ( 2 ), 539 – 556.
dc.identifier.citedreferenceLudy, J., & Kondolf, G. M. ( 2012 ). Flood risk perception in lands “protected” by 100‐year levees. Natural Hazards, 61 ( 2 ), 829 – 842.
dc.identifier.citedreferencePalmer, P. I., & Smith, M. J. ( 2014 ). Model human adaptation to climate change. Nature, 512 ( 7515 ), 365 – 366.
dc.identifier.citedreferencePoussin, J. K., Botzen, W. W., & Aerts, J. C. ( 2014 ). Factors of influence on flood damage mitigation behaviour by households. Environmental Science & Policy, 40, 69 – 77.
dc.identifier.citedreferenceSiegrist, M., & Gutscher, H. ( 2008 ). Natural hazards and motivation for mitigation behavior: People cannot predict the affect evoked by a severe flood. Risk Analysis, 28 ( 3 ), 771 – 778.
dc.identifier.citedreferenceTinsley, C. H., Dillon, R. L., & Cronin, M. A. ( 2012 ). How near‐miss events amplify or attenuate risky decision making. Management Science, 58 ( 9 ), 1596 – 1613.
dc.identifier.citedreferenceTonn, G. L., & Guikema, S. D. ( 2018 ). An agent‐based model of community flood risk. Risk Analysis, 38 ( 6 ), 1258 – 1278.
dc.identifier.citedreferenceVillarini, G., Serinaldi, F., Smith, J. A., & Krajewski, W. F. ( 2009 ). On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resources Research, 45 ( 8 ), https://doi.org/10.1029/2008WR007645
dc.identifier.citedreferenceAdger, W. N., Dessai, S., Goulden, M., Hulme, M., Lorenzoni, I., Nelson, D. R., … Wreford, A. ( 2009 ). Are there social limits to adaptation to climate change? Climatic Change, 93 ( 3 ), 335 – 354.
dc.identifier.citedreferenceAlberto, B., Banitt, A., Faber, B., Fleming, M., & Foley, P. ( 2015 ). Red River of the North at Fargo, North Dakota, pilot study, impact of climate change on flood frequency curve. U.S. Army Corps of Engineers.
dc.identifier.citedreferenceAlfieri, L., Feyen, L., & Di Baldassarre, G. ( 2016 ). Increasing flood risk under climate change: A pan‐European assessment of the benefits of four adaptation strategies. Climatic Change, 136 ( 3–4 ), 507 – 521.
dc.identifier.citedreferenceBerglund, E. Z. ( 2015 ). Using agent‐based modeling for Water resources planning and management. Journal of Water Resources Planning and Management, 141 ( 11 ), 04015025.
dc.identifier.citedreferenceBirkholz, S., Muro, M., Jeffrey, P., & Smith, H. M. ( 2014 ). Rethinking the relationship between flood risk perception and flood management. Science of the Total Environment, 478, 12 – 20.
dc.identifier.citedreferenceBonabeau, E. ( 2002 ). Agent‐based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences, 99 ( Suppl 3 ), 7280 – 7287.
dc.identifier.citedreferenceBubeck, P., Botzen, W. J., & Aerts, J. C. ( 2012 ). A review of risk perceptions and other factors that influence flood mitigation behavior. Risk Analysis, 32 ( 9 ), 1481 – 1495.
dc.identifier.citedreferenceBubeck, P., Botzen, W. J. W., Kreibich, H., & Aerts, J. C. J. H. ( 2013 ). Detailed insights into the influence of flood‐coping appraisals on mitigation behaviour. Global Environmental Change, 23 ( 5 ), 1327 – 1338.
dc.identifier.citedreferenceBurton, I., Kates, R. W., & White, G. F. ( 1993 ). The environment as hazard ( 2nd ed. ). New York: Guilford.
dc.identifier.citedreferenceBuss, L. S. ( 2005 ). Nonstructural flood damage reduction within the US Army Corps of Engineers. Journal of Contemporary Water Research & Education, 130 ( 1 ), 26 – 30.
dc.identifier.citedreferenceCheong, S. M. ( 2011 ). Policy solutions in the US. Climatic Change, 106 ( 1 ), 57 – 70.
dc.identifier.citedreferenceCrooks, A. T., & Heppenstall, A. J. ( 2012 ). Introduction to agent‐based modelling. In A.T. Crooks, L. M. See, & M. Batty (Eds.), Agent‐based models of geographical systems (pp. 85 – 105 ). The Netherlands: Springer.
dc.identifier.citedreferenceCummings, C.A., Todhunter, P. E., & Rundquist, B. C. ( 2012 ). Using the Hazus‐MH flood model to evaluate community relocation as a flood mitigation response to terminal lake flooding: The case of Minnewaukan, North Dakota, USA. Applied Geography, 32 ( 2 ), 889 – 895.
dc.identifier.citedreferenceDawson, R. J., Peppe, R., & Wang, M. ( 2011 ). An agent‐based model for risk‐based flood incident management. Natural Hazards, 59 ( 1 ), 167 – 189.
dc.identifier.citedreferenceDeBruin, W. B., Wong‐Parodi, G., & Morgan, M. G. ( 2014 ). Public perceptions of local flood risk and the role of climate change. Environment Systems and Decisions, 34 ( 4 ), 591 – 599.
dc.identifier.citedreferenceDilling, L., Daly, M. E., Travis, W. R., Wilhelmi, O. V., & Klein, R. A. ( 2015 ). The dynamics of vulnerability: Why adapting to climate variability will not always prepare us for climate change. Wiley Interdisciplinary Reviews: Climate Change, 6 ( 4 ), 413 – 425.
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.