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Drought Risk Analysis Using Spi For Effective Agricultural Projects’ And Water Resource Management Over Victoria State, Australia

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  • Bernard Moeketsi Hlalele

    (Human Sciences Research Council Developmental, Capable & Ethical State Division Sustainable Human Security 134 Pretorius Street, Pretoria, 0002, South Africa)

Abstract

Drought is a gradual and persistent hazard resulting from below-average precipitation, which poses a threat to various economic sectors and human life as a whole. This external and insurable risk predominantly affects agriculture and water resource management projects, causing a ripple effect across related sectors and operations. The objective of this study was to analyse drought risk in the Victoria State of Australia using the Standardized Precipitation Index (SPI) to monitor and characterize drought occurrences, with the aim of safeguarding and enhancing agricultural and water resource management initiatives. The SPI methodology was employed, computing four temporal scales (SPI-3, 6, 12, and 24) for assessing both agricultural and hydrological drought. The findings indicate a consistent pattern across most stations, revealing significant declines in SPI values on various time scales, suggesting an escalation in drought severity in the near future. Although there is some optimism for agriculture and related projects in the region, caution is warranted due to the decreasing trends observed in SPI-3 and 6. On the other hand, SPI-12 and 24 clearly demonstrate that severe droughts have already affected all stations, with the potential for even more severe episodes in the future. Consequently, it is imperative for the government and relevant stakeholders to exercise extreme caution in water usage, as irresponsible or excessive consumption could have adverse effects on water-intensive projects and activities in the area.

Suggested Citation

  • Bernard Moeketsi Hlalele, 2024. "Drought Risk Analysis Using Spi For Effective Agricultural Projects’ And Water Resource Management Over Victoria State, Australia," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 6(1), pages 21-35, May.
  • Handle: RePEc:zib:zbnbda:v:6:y:2024:i:1:p:21-35
    DOI: 10.26480/bda.01.2024.21.35
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