Spatial modelling of natural disaster risk reduction policies with Markov decision processes

Espada Jr., Rodolfo and Apan, Armando and McDougall, Kevin (2014) Spatial modelling of natural disaster risk reduction policies with Markov decision processes. Applied Geography, 53. pp. 284-298. ISSN 0143-6228


The 2010/2011 floods in Queensland, Australia inflicted significant damages to government's critical infrastructures, private properties and businesses reaching an estimated amount of AU$16 billion. Mitigating the devastating effects of floods to the community and critical infrastructures entails competing financial requirements at the different levels of government. Hence, the main objective of this study was to examine the financial optimality of disaster risk reduction measures by integrating Markov decision processes (MDP for short) with geographic information system (GIS). Conducted in the core suburbs of Brisbane City, we organised the MDP variables using the following: 1) flood risk levels as the states of the urban system; 2) Queensland's disaster risk reduction measures as the action variables; 3) percentage of government expenditures by disaster risk reduction category as the state transition probabilities; 4) total lost earnings to businesses affected by the flood events as the reward variables; and 5) the weighted average riskless rate of return, the weighted average rate of return, and rate of return for a riskier asset as discounting factors. We analysed 36 MDP scenarios at four-level iteration and then calculated the expectimax values to find the optimal policy. The results from the analyses revealed that the Commonwealth government optimised the use of its natural disaster risk reduction expenditures to recovery while the State government focused on mitigation. When both government expenditures combined, the mitigation measure was identified as the optimum natural disaster risk reduction policy. The methodology presented in this study allowed a spatial representation and computationally feasible integration of complex flood disaster risk model with government expenditures and business earnings. The insights from this integrated approach emphasise the viability of finding optimum expenditures, and re-examine if necessary, in implementing natural disaster risk reduction policies and climate adaptation strategies.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2014 Elsevier Ltd. Permanent restricted access to published version in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 07 Aug 2014 05:50
Last Modified: 04 Jul 2016 06:18
Uncontrolled Keywords: flood; natural disaster risk reduction; optimum policy; Markov decision processes; geographic information system
Fields of Research : 04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040604 Natural Hazards
09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010303 Optimisation
Socio-Economic Objective: D Environment > 96 Environment > 9603 Climate and Climate Change > 960302 Climate Change Mitigation Strategies
D Environment > 96 Environment > 9610 Natural Hazards > 961010 Natural Hazards in Urban and Industrial Environments
Identification Number or DOI: 10.1016/j.apgeog.2014.06.021

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