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Spatio-temporal characteristics of drought structure across China using an integrated drought index

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  • Huang, Shengzhi
  • Wang, Lu
  • Wang, Hao
  • Huang, Qiang
  • Leng, Guoyong
  • Fang, Wei
  • Zhang, Ying

Abstract

Previous studies have focused on drought duration, intensity and frequency without explicitly investigating the timing of droughts, such as the drought onset and demise, as well as their transition periods, which is of importance for agricultural production. Furthermore, large discrepancies exist for those studies using a single-variable based drought index. In this study, a nonparametric multivariate standardized drought index (NMSDI) that combines information about precipitation and streamflow was applied to investigate the spatial and temporal features of the drought structure in China. Subsequently, the relationships between El Niño-Southern Oscillation (ENSO) events and NMSDI variations were examined. The results indicate that: the NMSDI exhibited comparable performance when compared to the corresponding Standardized Precipitation Index and Standardized Streamflow Index, and importantly, it is more sensitive to capturing the onset, persistence, and termination of droughts; the preferred season of drought onset is in summer, with drought demise occurring in winter; the average drought duration in China is nearly 6 months, which is longer than the transition periods of drought onset (3 months) and demise (3 months); ENSO events have a strong influence on drought variations, with the effects depending on climate zones across China. Our results on the timing of droughts have important implications for drought mitigation and adaptation in China, which is helpful for agricultural production under the context of climate warming.

Suggested Citation

  • Huang, Shengzhi & Wang, Lu & Wang, Hao & Huang, Qiang & Leng, Guoyong & Fang, Wei & Zhang, Ying, 2019. "Spatio-temporal characteristics of drought structure across China using an integrated drought index," Agricultural Water Management, Elsevier, vol. 218(C), pages 182-192.
    • Handle: RePEc:eee:agiwat:v:218:y:2019:i:c:p:182-192
    DOI: 10.1016/j.agwat.2019.03.053
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    References listed on IDEAS

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    1. Saiyan Liu & Shengzhi Huang & Yangyang Xie & Hao Wang & Guoyong Leng & Qiang Huang & Xiaoting Wei & Lu Wang, 2019. "Identification of the Non-stationarity of Floods: Changing Patterns, Causes, and Implications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 939-953, February.
    2. Lu, Shibao & Bai, Xiao & Li, Wei & Wang, Ning, 2019. "Impacts of climate change on water resources and grain production," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 76-84.
    3. Shengzhi Huang & Jianxia Chang & Qiang Huang & Yutong Chen, 2014. "Spatio-temporal Changes and Frequency Analysis of Drought in the Wei River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3095-3110, August.
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    Cited by:

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    2. Wang, Fei & Lai, Hexin & Li, Yanbin & Feng, Kai & Zhang, Zezhong & Tian, Qingqing & Zhu, Xiaomeng & Yang, Haibo, 2022. "Dynamic variation of meteorological drought and its relationships with agricultural drought across China," Agricultural Water Management, Elsevier, vol. 261(C).
    3. Lu, Shibao & Sun, Huaping & Sun, Dongying & Guo, Min & Bai, Xiao, 2020. "Assessment on reservoir flood resources utilization of Ankang Reservoir, China," Resources Policy, Elsevier, vol. 68(C).
    4. Yanqun Ren & Jinping Liu & Patrick Willems & Tie Liu & Quoc Bao Pham, 2023. "Detection and Assessment of Changing Drought Events in China in the Context of Climate Change Based on the Intensity–Area–Duration Algorithm," Land, MDPI, vol. 12(10), pages 1-18, September.
    5. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).
    6. Mondol, Md Anarul Haque & Zhu, Xuan & Dunkerley, David & Henley, Benjamin J., 2021. "Observed meteorological drought trends in Bangladesh identified with the Effective Drought Index (EDI)," Agricultural Water Management, Elsevier, vol. 255(C).
    7. Dai, Meng & Huang, Shengzhi & Huang, Qiang & Leng, Guoyong & Guo, Yi & Wang, Lu & Fang, Wei & Li, Pei & Zheng, Xudong, 2020. "Assessing agricultural drought risk and its dynamic evolution characteristics," Agricultural Water Management, Elsevier, vol. 231(C).

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