Multi-timescale Performance of Groundwater Drought in Connection with Climate

Ruirui Zhu (), Hongxing Zheng, Anthony J. Jakeman and Francis H.S. Chiew
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Ruirui Zhu: Australian National University
Hongxing Zheng: CSIRO Environment
Anthony J. Jakeman: Australian National University
Francis H.S. Chiew: CSIRO Environment

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2023, vol. 37, issue 9, No 13, 3599-3614

Abstract: Abstract The Millennium drought which occurred around 1997–2009 throughout southeastern Australia has led to recorded low groundwater levels causing considerable economical losses. Improving the drought resilience of at-risk groundwater systems has been recognized as a priority for sustainable water resources management in the region. This study introduces the standardized groundwater discharge index (SGDI) based on groundwater discharge to river to assess groundwater drought performance at multi-timescales for catchments in the southeastern Murray-Darling Basin. The response time of groundwater drought to precipitation drought is found to be above 12 months according to the relationships between SGDI and the standardized precipitation index. The performance of groundwater drought, indicated by resilience and resistance, overall shows that catchments with higher drought resilience are often accompanied by lower drought resistance and vulnerability. Groundwater drought is found to be less resilient but more resistant than precipitation drought due to the buffer capacity of the groundwater system. The determinants of groundwater drought performance at different timescales are identified by a machine learning approach. The relationships between groundwater drought performance metrics and their determinants are found to be highly nonlinear and distinctly different among the timescales. Climate factors and catchment physical properties can explain up to 60% of the spatial variance in drought resilience and resistance across the region at the 12-month scale. Our findings provide crucial insight into groundwater drought management and open potential pathways for improving groundwater drought resilience and resistance to mitigate the drought impacts potentially driven by a changing climate.

Keywords: Groundwater drought; Resilience and resistance; Multi-timescale; Machine learning; Murray-Darling Basin (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11269-023-03515-y

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