Spatio-temporal drought risk mapping approach and its application in the drought-prone region of south-east Queensland, Australia

Dayal, Kavina S. and Deo, Ravinesh C. and Apan, Armando A. (2018) Spatio-temporal drought risk mapping approach and its application in the drought-prone region of south-east Queensland, Australia. Natural Hazards. ISSN 0921-030X

Abstract

Strategic management of water resources in drought-vulnerable regions can be greatly hampered by frequent, severe and long-lasting droughts. To enable better drought relief policy and amicable solutions and proactive actions for preparedness and mitigation of drought impacts, this study adopts a spatio-temporal methodology for the assessment of drought risk of drought-prone areas in south-east Queensland, Australia. In this study, the spatially representative depiction of the drought risk in a drought-prone region with multiple vulnerability, exposure and drought hazard indicators is considered in order to develop a geographic information systems-based drought risk mapping tool. Spatial indicators of drought are categorised into various subclasses, and the conditional joint probability of each indicator is the determined in accordance with the Bayes theorem. The fuzzy logic approach is then embraced as a new approach in this study to standardise the different drought factors on a range of 0–1 followed by an aggregation of drought vulnerability, exposure and hazard indices using the fuzzy GAMMA overlay operation in ArcGIS 10.5 to produce the optimal drought risk map for the case study region. The analysis of drought’s different phases shows varying vulnerability levels in different austral seasons (summer, autumn and spring of 2007) and annually (2007, 2009 and 2013) that is well represented by drought hazard index, i.e. rainfall departure. The application of the fuzzy set to incorporate and classify drought factors reveals its useful implications for handling of spatial drought-related data and the development of the drought risk index. The validation of the method performed with upper and lower layer soil moisture data reveals significant correlation with the drought risk index. The study has implications for drought risk mapping, particularly in utilising the ability of the fuzzy logic-based analytical technique integrated with GIS-based mapping tools for spatio-temporal drought risk studies. The approach in this paper can be considered as a practical mapping tool for drought studies, to better enable drought management, drought mitigation and relief-planning actions that need to be implemented by different decision-makers in water resources, agriculture and other socio-economic areas.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published online 25 April 2018. Permanent restricted access to ArticleFirst version, in accordance with the copyright policy of the publisher. This project, supervised by Dr Ravinesh Deo, was funded by University of Southern Queensland Office of Research and Graduate Studies Postgraduate Research Scholarship, USQPRS (2015–2017) and the School of Agricultural, Computational and Environmental Science.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 30 Apr 2018 01:37
Last Modified: 16 May 2018 01:49
Uncontrolled Keywords: drought risk hazard; exposure; drought vulnerability index; fuzzy logic; geographic information system (GIS)
Fields of Research : 05 Environmental Sciences > 0502 Environmental Science and Management > 050204 Environmental Impact Assessment
04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040608 Surfacewater Hydrology
04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040604 Natural Hazards
05 Environmental Sciences > 0502 Environmental Science and Management > 050206 Environmental Monitoring
Socio-Economic Objective: D Environment > 96 Environment > 9610 Natural Hazards > 961003 Natural Hazards in Farmland, Arable Cropland and Permanent Cropland Environments
E Expanding Knowledge > 97 Expanding Knowledge > 970104 Expanding Knowledge in the Earth Sciences
Identification Number or DOI: 10.1007/s11069-018-3326-8
URI: http://eprints.usq.edu.au/id/eprint/34056

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