Natural Hazards

, Volume 91, Issue 1, pp 353–374 | Cite as

A comparative frequency analysis of three standardized drought indices in the Poyang Lake basin, China

  • Guixia Yan
  • Zhiyong Wu
  • Denghua Li
  • Heng Xiao
Original Paper


Regional drought frequency analysis was carried out in the Poyang Lake basin (PLB) from 1960–2014 based on three standardized drought indices: the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI) and the standardized Palmer drought index (SPDI). Drought events and characteristics were extracted. A Gumbel–Hougaard (GH) copula was selected to construct the bivariate probability distribution of drought duration and severity, and the joint return periods (T a ) were calculated. Results showed that there were 50 (50 and 40) drought events in the past 55 years based on the SPI (SPEI and SPDI), and 9 (8 and 10) of them were severe with T a more than 10 years, occurred in the 1960s, the 1970s and the 2000s. Overall, the three drought indices could detect the onset of droughts and performed similarly with regard to drought identification. However, for the SPDI, moisture scarcity was less frequent, but it showed more severe droughts with substantially higher severity and longer duration droughts. The conditional return period (Ts|d) was calculated for the spring drought in 2011, and it was 66a and 54a, respectively, based on the SPI and SPDI, which was consistent with the record. Overall, the SPI, only considering the precipitation, can as effectively as the SPEI and SPDI identify the drought process over the PLB under the present changing climate. However, drought is affected by climate and land-cover changes; thus, it is necessary to integrate the results of drought frequency analysis based on different drought indices to improve the drought risk management.


Drought Standardized drought index Copulas Return period Poyang Lake basin 



This study was financially supported by the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20140998), the National Natural Science Foundation of China (Grant Nos. 41401016, 51579065 and 51779071), National key Research and Development Program of China (Grant No. 2016YFC0401407) and the Scientific Research Foundation of Higher Education Institutions of Henan Province (Grant No. 16A570003), Jiangsu Overseas Research & Training Program for University Prominent Young and Middle-aged Teachers and Presidents.


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of HydrometeorologyNanjing University of Information Science and TechnologyNanjingPeople’s Republic of China
  2. 2.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water ResourcesHohai UniversityNanjingPeople’s Republic of China
  3. 3.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringNanjing Hydraulic Research InstituteNanjingPeople’s Republic of China
  4. 4.Yellow River Institute of Science, North China University of Water Resources and Electric PowerZhengzhouPeople’s Republic of China

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