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Spatio-temporal quantitative links between climatic extremes and population flows: a case study in the Murray-Darling Basin, Australia

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  • K. Shuvo Bakar

    (Australian National University
    Data 61, CSIRO)

  • Huidong Jin

    (Data 61, CSIRO)

Abstract

A growing body of research shows that extreme climatic events, e.g. heatwave, rainstorms and droughts, are becoming more frequent and intensified across various regions of the world. Australia is not isolated from these changes with marked increase in both rainfall and temperature extremes. Inherently, we understand that exposure to these extreme events could encourage decisions about population flow, and quantifying this linkage is challenging, especially for communities in small areas with an average of 10,000 people. Using spatio-temporal statistical techniques, this paper examines the possible environmental and socio-economic drivers associated with population flows of small communities as well as the possible predictive scenarios due to the effects introduced by climatic extremes. The analysis has been undertaken for a case-study region in the Murray-Darling Basin, Australia, where the economy is underpinned by agriculture and is sensitive to climate variability and extremes. The analysis reveals that in addition to the socio-economic factors, the environmental variables have a statistically significant association on shaping the distribution of the population flows in the study area. This statistical analysis can direct further data collection and causality analysis and be beneficial for policy makers, stakeholders and local communities to work together to adapt the Basin to climate extremes and changes.

Suggested Citation

  • K. Shuvo Bakar & Huidong Jin, 2018. "Spatio-temporal quantitative links between climatic extremes and population flows: a case study in the Murray-Darling Basin, Australia," Climatic Change, Springer, vol. 148(1), pages 139-153, May.
    • Handle: RePEc:spr:climat:v:148:y:2018:i:1:d:10.1007_s10584-018-2182-6
    DOI: 10.1007/s10584-018-2182-6
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    References listed on IDEAS

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    Cited by:

    1. K. Shuvo Bakar & Nicholas Biddle & Philip Kokic & Huidong Jin, 2020. "A Bayesian spatial categorical model for prediction to overlapping geographical areas in sample surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 535-563, February.
    2. Barbora Šedová & Lucia Čizmaziová & Athene Cook, 2021. "A meta-analysis of climate migration literature," CEPA Discussion Papers 29, Center for Economic Policy Analysis.
    3. Sarah Ann Wheeler & Ying Xu & Alec Zuo, 2020. "Modelling the climate, water and socio-economic drivers of farmer exit in the Murray-Darling Basin," Climatic Change, Springer, vol. 158(3), pages 551-574, February.

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