IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v35y2015i2d10.1007_s10669-015-9545-6.html
   My bibliography  Save this article

Developing resilience to naturally triggered disasters

Author

Listed:
  • Timothy Davies

    (University of Canterbury
    Durham University)

Abstract

Naturally triggered disasters are serious disruptions to society resulting from complex interactions between natural and human systems. Probabilistically based risk management is intrinsically unreliable for planning local (or community) resilience to naturally triggered disasters, because the number of such events that will affect a given community in any realistic planning time frame is very small, so event occurrence is unlikely to reliably match probability, and because even with small discrepancies between probability and occurrence, utility optimisation compounds these to yield optima with very large imprecisions. Thus, probabilistically based risk management is only applicable reliably to disaster reduction that considers large numbers of events, for example, when governments are performing their mandated duties around regional or national public safety and when insurance companies are analysing disaster statistics across large areas. This leaves a methodology gap for disaster reduction at local scale, which puts in question the validity of larger-scale strategies to reduce disaster impacts. Complex system science suggests that disasters are fundamentally unpredictable; certainly, they are often unexpected when they occur. Disaster risk reduction/management identifies the need to “Identify, assess and monitor disaster risks…”; but because disaster triggers are generally poorly quantified, or unexpected in type or magnitude, this is an unrealistic aspiration. An alternative strategy, for developing community resilience to disaster effects scenarios, is suggested herein, as a complement to conventional risk management applied over larger areas. Communities can increase their resilience by engaging with scientists and officials to develop realistic disaster event and effects scenarios and then to plan how the effects scenarios can be reduced, by adapting community behaviour and structure as opportunities arise. This can then underpin and link to larger-scale disaster reduction strategies. Systems that exhibit resilience to system shocks have structures and behaviours that appear to correspond to the characteristics of complex dynamic systems. However, modern societal behaviours deviate from these, and strategies for improving resilience to naturally triggered disasters may be indicated by complex system behaviour.

Suggested Citation

  • Timothy Davies, 2015. "Developing resilience to naturally triggered disasters," Environment Systems and Decisions, Springer, vol. 35(2), pages 237-251, June.
  • Handle: RePEc:spr:envsyd:v:35:y:2015:i:2:d:10.1007_s10669-015-9545-6
    DOI: 10.1007/s10669-015-9545-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-015-9545-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10669-015-9545-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fabian Barthel & Eric Neumayer, 2012. "A trend analysis of normalized insured damage from natural disasters," Climatic Change, Springer, vol. 113(2), pages 215-237, July.
    2. Aban, Inmaculada B. & Meerschaert, Mark M. & Panorska, Anna K., 2006. "Parameter Estimation for the Truncated Pareto Distribution," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 270-277, March.
    3. D. Sornette, "undated". "Dragon-Kings, Black Swans and the Prediction of Crises," Working Papers CCSS-09-005, ETH Zurich, Chair of Systems Design.
    4. N. Nirupama & Amanda Maula, 2013. "Engaging public for building resilient communities to reduce disaster impact," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 66(1), pages 51-59, March.
    5. Didier Sornette & Guy Ouillon, "undated". "Dragon-kings: Mechanisms, statistical methods and empirical evidence," Working Papers ETH-RC-12-004, ETH Zurich, Chair of Systems Design.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jesse M. Keenan, 2018. "Regional resilience trust funds: an exploratory analysis for leveraging insurance surcharges," Environment Systems and Decisions, Springer, vol. 38(1), pages 118-139, March.
    2. Maraña, Patricia & Labaka, Leire & Sarriegi, Jose Mari, 2020. "We need them all: development of a public private people partnership to support a city resilience building process," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    3. Jonathan Pearson & G. Punzo & M. Mayfield & G. Brighty & A. Parsons & P. Collins & S. Jeavons & A. Tagg, 2018. "Flood resilience: consolidating knowledge between and within critical infrastructure sectors," Environment Systems and Decisions, Springer, vol. 38(3), pages 318-329, September.
    4. Igor Linkov & Sabrina Larkin & James H. Lambert, 2015. "Concepts and approaches to resilience in a variety of governance and regulatory domains," Environment Systems and Decisions, Springer, vol. 35(2), pages 183-184, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sinha, Amit & Horvath, Philip A. & Beason, Tyler & Roos, Kelly R., 2019. "Simulation of a financial market: The possibility of catastrophic disequilibrium," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 13-16.
    2. Rebecca Westphal & Didier Sornette, 2020. "How market intervention can prevent bubbles and crashes," Swiss Finance Institute Research Paper Series 20-74, Swiss Finance Institute.
    3. Sergey Bredikhin & Jonathan Linton & Thais Matoszko, 2017. "Why and How the Value of Science-Based Firms Violates Financial Theory: Implications for Policy and Governance," Foresight-Russia Форсайт, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 11(1 (eng)), pages 24-30.
    4. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    5. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    6. Glette-Iversen, Ingrid & Aven, Terje, 2021. "On the meaning of and relationship between dragon-kings, black swans and related concepts," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    7. Vladimir Filimonov & Didier Sornette, 2014. "Power law scaling and "Dragon-Kings" in distributions of intraday financial drawdowns," Papers 1407.5037, arXiv.org, revised Apr 2015.
    8. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    9. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman, 2018. "Optimal threshold for Pareto tail modelling in the presence of outliers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 169-180.
    10. Jerome L Kreuser & Didier Sornette, 2017. "Super-Exponential RE Bubble Model with Efficient Crashes," Swiss Finance Institute Research Paper Series 17-33, Swiss Finance Institute.
    11. Filimonov, Vladimir & Sornette, Didier, 2015. "Power law scaling and “Dragon-Kings” in distributions of intraday financial drawdowns," Chaos, Solitons & Fractals, Elsevier, vol. 74(C), pages 27-45.
    12. Castillo, Joan del & Serra, Isabel, 2015. "Likelihood inference for generalized Pareto distribution," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 116-128.
    13. Shahzad Hussain & Sajjad Haider Bhatti & Tanvir Ahmad & Muhammad Ahmed Shehzad, 2021. "Parameter estimation of the Pareto distribution using least squares approaches blended with different rank methods and its applications in modeling natural catastrophes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(2), pages 1693-1708, June.
    14. Blázquez de Paz, Mario, 2018. "Electricity auctions in the presence of transmission constraints and transmission costs," Energy Economics, Elsevier, vol. 74(C), pages 605-627.
    15. J. Park & T. P. Seager & P. S. C. Rao & M. Convertino & I. Linkov, 2013. "Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems," Risk Analysis, John Wiley & Sons, vol. 33(3), pages 356-367, March.
    16. Kwame Boamah‐Addo & Tomasz J. Kozubowski & Anna K. Panorska, 2023. "A discrete truncated Zipf distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 156-187, May.
    17. Yulong Wang & Zhijie Xiao, 2020. "Estimation and Inference about Tail Features with Tail Censored Data," Boston College Working Papers in Economics 994, Boston College Department of Economics.
    18. Darrell Jiajie Tay & Chung-I Chou & Sai-Ping Li & Shang You Tee & Siew Ann Cheong, 2016. "Bubbles Are Departures from Equilibrium Housing Markets: Evidence from Singapore and Taiwan," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-13, November.
    19. Matteo Coronese & Francesco Lamperti & Francesca Chiaromonte & Andrea Roventini, 2018. "Natural Disaster Risk and the Distributional Dynamics of Damages," LEM Papers Series 2018/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    20. Marek Arendarczyk & Tomasz J. Kozubowski & Anna K. Panorska, 2022. "The Greenwood statistic, stochastic dominance, clustering and heavy tails," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 331-352, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:35:y:2015:i:2:d:10.1007_s10669-015-9545-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.