Characterization of meteorological droughts across South Australia

Rashid, M. M.; Beecham, Simon

doi:10.1002/met.1783

Cited by 17 publications

(9 citation statements)

References 49 publications

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“…At present, most of the research studies hydrological and meteorological drought using copula function, and seldom combine the research results with crop data [44,45]. The annual drought disaster in China leads to severe grain production, so it is urgent to further study regional agricultural drought [46].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Wang

Rong

et al. 2021

Water

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Precipitation is low and drought occurs frequently in Northern Shaanxi. To study the characteristics and occurrence and development of drought events in Northern Shaanxi is beneficial to the prevention and control of drought disasters. Based on the monthly rainfall data of 10 meteorological stations in Northern Shaanxi from 1960 to 2019, the characteristic variables of drought events at each meteorological station in Northern Shaanxi were extracted by using run theory and copula function. The joint probability distribution and recurrence period were obtained by combining the duration and intensity of drought, and the relationship between drought characteristics and crop drought affected area was studied. The results show that (1) from 1960 to 2019, drought events mainly occurred in Northern Shaanxi with long duration and low severity, short duration and high severity, or short duration and low severity, among which the frequency of drought events that occurred in Yuyang and Baota districts was higher. The frequency of light drought and extreme drought was more in the south and less in the north, while the frequency of moderate drought and severe drought was more in the north and less in the south. (2) The optimal edge distribution of drought intensity and drought duration in Northern Shaanxi is generalized Pareto distribution, and the optimal fitting function is Frank copula function. The greater the duration and intensity of drought, the greater the cumulative probability and return period. (3) The actual recurrence interval and the theoretical recurrence interval of drought events in Northern Shaanxi were close, and the error was only 0.1–0.3a. The results of the joint return period can accurately reflect the actual situation, and this study can provide effective guidance for the prevention and management of agricultural dryland in Northern Shaanxi.

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Section: Discussionmentioning

confidence: 99%

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Wang

Rong

et al. 2021

Water

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“…Rainfall station density is estimated as number of selected stations (45 in our case) divided by the study area (1,028,790 km 2 ). Some other studies used similar data point density as follows: rainfall stations density was used by Bari Abarghouei et al (2011) as '0.25' in Iran, Li et al (2011) as '0.28' in China, Zhang et al (2015 as '0.48' in China, Akinsanola andOgunjobi (2017) as '0.25' in Nigeria, andRashid andBeecham (2019) as '0.47' in South Australia per 10.000 km 2 .…”

Section: Study Area and Datamentioning

confidence: 99%

“…They stated that south-eastern Australia experienced an exceptional drought in this period, particularly New South Wales, Victoria, and Queensland with insufficient rainfall, decreased soil moisture, and increased temperature and evapotranspiration. In another study, Rashid and Beecham (2019) focused drought characterization of meteorological drought in South Australia by using monthly rainfall data of 46 rainfall stations (during the period 1960-2010) at 3-, 6-, 12-, and 24-month durations SPI, and they found that 23 of 46 rainfall stations had a negative trend for longterm drought (24-month SPI).…”

Section: Introductionmentioning

confidence: 99%

“…In another study, Deo et al (2017) investigated the suitability of EDI for drought monitoring in Australia at 7 stations using daily rainfall data. Rashid and Beecham (2019) studied meteorological drought characterisation in South Australia at 3-, 6-, 12-, and 24-month SPIs using data from 46 stations covering between 1960 and 2010. It can be seen that previous studies used limited data, SPIs of few time scales, and little/no spatial analysis to evaluate droughts in south-east Australia.…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal meteorological drought assessment: a case study in south-east Australia

Yıldırım

Rahman

2021

Nat Hazards

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An understanding on different aspects of droughts is crucial for effective water resources management. Australia has experienced notable droughts in recent years. The present study utilises Effective Drought Index (EDI) and Standardized Precipitation Index (SPI) based on six time horizons (3, 6, 9, 12, 24, and 36 months) to evaluate drought parameters such as magnitude, duration, and intensity with their onset and end in south-east Australia using data from 45 rainfall stations. Maximum drought quantities determined using SPI and EDI, with average data length of 125 years, have been mapped by spline interpolation technique. Furthermore, average drought parameters for each of the SPIs and EDI have been investigated and spatial distributions of drought quantities have been exhibited. In the study area, SPIs based on different time scales (either short term or long term) have detected the maximum drought severity, duration, and/or intensity (at least one of the parameters) between 2013 and 2019. It has been found that south-east Australia had faced one of the most intense droughts during 2013 to 2019. It has also been found that the longest duration of drought has been in southern and eastern coasts of the study area. Generated maps based on average EDI values have depicted that the north-western and central parts of the study area have experienced the longest and strongest drought, whereas higher-intensity drought has been found to be dominating the eastern and southern parts of the study area. Higher frequency of the number of droughts has been found mostly in the east and south of the study area in terms of moderate, severe, and extreme droughts. The generated spatial maps of SPIs and EDI in this study help to identify the most drought-prone and vulnerable parts within south-east Australia. The drought maps developed for south-eastern Australia by this spatiotemporal analysis can be a key tool to policymakers for mitigation, risk assessment, and drought preparedness planning.

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“…Drought will potentially cause drastic consequences for global water resources management [1] agriculture production [2], ecological protection [3], as well as economic and social development [4]. Detecting and understanding the characteristics of the previous droughts are the preconditions to predict drought and of great importance for water resource management [5].…”

Section: Introductionmentioning

confidence: 99%

Two Severe Prolonged Hydrological Droughts Analysis over Mainland Australia Using GRACE Satellite Data

et al. 2021

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In recent years, many droughts have happened over mainland Australia, especially the two severe prolonged droughts, from 2006 to 2009 and 2018 to 2020, resulting in serious water scarcity. Therefore, using the Total Storage Deficit Index (TSDI) from the Gravity Recovery and Climate Experiment (GRACE), we analyzed the two severe prolonged droughts from the perspective of the affected area, spatial evolution, frequency, severity and drought driving factors. The results show that the affected area of Drought 2006–2009 ranged from 57% to 95%, and that of Drought 2018–2020 ranged from 45% to 95%. Drought 2006–2009 took its rise in southeastern Australia and gradually spread to the central part. Drought 2018–2020 originated in the southwest corner of the Northern Territory and northern New South Wales, and gradually expanded to Western Australia and the whole New South Wales respectively. During Drought 2006–2009, Victoria suffered drought all months, including 59% mild drought and 41% moderate drought, North Territory had the highest drought severity of 44.26 and Victoria ranked the second high with the severity of 35.51 (cm months). For Drought 2018–2020, Northern Territory was also dominated by drought all months, including 92% mild drought and 8% moderate drought, the drought severities were in North Territory and Western Australia with 52.19 and 31.44 (cm months), respectively. Finally, the correlation coefficients between the two droughts and Indo-Pacific climate variability including El Niño-Southern Oscillation and Indian Ocean Dipole (IOD) are computed. By comparing the correlation coefficients of Drought 2018–2020 with Drought 2006–2009, we find that the impact of the El Niño on the hydrological drought becomes weaker while IOD is stronger, and the role of Southern Oscillation on droughts is diverse with the quite different spatial patterns. The results from Fourier analysis confirm that the two hydrological droughts are all related to Indo-Pacific climate variability but with slightly different driving mechanisms.

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Characterization of meteorological droughts across South Australia

Cited by 17 publications

References 49 publications

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Spatiotemporal meteorological drought assessment: a case study in south-east Australia

Two Severe Prolonged Hydrological Droughts Analysis over Mainland Australia Using GRACE Satellite Data

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