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

Kavina S. Dayal, Ravinesh C. Deo () and Armando A. Apan
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Kavina S. Dayal: Institute of Agriculture and Environment, University of Southern Queensland
Ravinesh C. Deo: Institute of Agriculture and Environment, University of Southern Queensland
Armando A. Apan: Institute of Agriculture and Environment, University of Southern Queensland

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 2, No 13, 823-847

Abstract: 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.

Keywords: Drought risk; Hazard/exposure/vulnerability index; Fuzzy logic; Geographic information system (GIS) (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3326-8

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