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Accuracy of agricultural drought indices and analysis of agricultural drought characteristics in China between 2000 and 2019

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Listed:
  • Pan, Ying
  • Zhu, Yonghua
  • Lü, Haishen
  • Yagci, Ali Levent
  • Fu, Xiaolei
  • Liu, En
  • Xu, Haiting
  • Ding, Zhenzhou
  • Liu, Ruoyu

Abstract

Agricultural drought threatens global water security, food security, and natural ecosystems. Accurate identification of agricultural drought is a crucial task to mitigate its consequences. However, it is challenging to achieve reliable and accurate regional agricultural drought assessment in both wet and dry climates at the same time. Therefore, the objective of this study is to identify a reliable and accurate agricultural drought index that performs well in both dry and wet climates. Drought indices such as the Standardized Precipitation Index (SPI), the Vegetation Condition Index (VCI), the Soil Moisture Anomaly index (SMA), and the Drought Severity Index (DSI) were calculated and compared against in situ drought information devised by official sources in China. The results showed that: (1) DSI based on the Global Land Data Assimilation System (GLDAS) products performed the best in identifying agricultural drought in both dry and wet climate regions of China. (2) Agricultural regions such as Northern arid and semiarid regions, Northeast China Plain, Huang-Huai-Hai Plain, and Loess Plateau, experienced moderate and severe agricultural droughts with a frequency of 20%. (3) The frequency of agricultural droughts observed in Northern arid and semi-arid regions and Northeast China Plain has slowed significantly over the last two decades with a significance level of 0.01. On the other hand, the number of agricultural droughts has increased in Yunnan-Guizhou Plateau since 2002.

Suggested Citation

  • Pan, Ying & Zhu, Yonghua & Lü, Haishen & Yagci, Ali Levent & Fu, Xiaolei & Liu, En & Xu, Haiting & Ding, Zhenzhou & Liu, Ruoyu, 2023. "Accuracy of agricultural drought indices and analysis of agricultural drought characteristics in China between 2000 and 2019," Agricultural Water Management, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:agiwat:v:283:y:2023:i:c:s0378377423001701
    DOI: 10.1016/j.agwat.2023.108305
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    1. 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).
    2. 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).
    3. Ding, Yibo & Gong, Xinglong & Xing, Zhenxiang & Cai, Huanjie & Zhou, Zhaoqiang & Zhang, Doudou & Sun, Peng & Shi, Haiyun, 2021. "Attribution of meteorological, hydrological and agricultural drought propagation in different climatic regions of China," Agricultural Water Management, Elsevier, vol. 255(C).
    4. Jordan I. Christian & Jeffrey B. Basara & Eric D. Hunt & Jason A. Otkin & Jason C. Furtado & Vimal Mishra & Xiangming Xiao & Robb M. Randall, 2021. "Global distribution, trends, and drivers of flash drought occurrence," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    5. Shilong Piao & Philippe Ciais & Yao Huang & Zehao Shen & Shushi Peng & Junsheng Li & Liping Zhou & Hongyan Liu & Yuecun Ma & Yihui Ding & Pierre Friedlingstein & Chunzhen Liu & Kun Tan & Yongqiang Yu , 2010. "The impacts of climate change on water resources and agriculture in China," Nature, Nature, vol. 467(7311), pages 43-51, September.
    6. Zhiyong Wu & Huihui Feng & Hai He & Jianhong Zhou & Yuliang Zhang, 2021. "Evaluation of Soil Moisture Climatology and Anomaly Components Derived From ERA5-Land and GLDAS-2.1 in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 629-643, January.
    7. Prashant K. Srivastava, 2017. "Satellite Soil Moisture: Review of Theory and Applications in Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3161-3176, August.
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    2. Zhang, Q. & Li, Y.P. & Huang, G.H. & Wang, H. & Li, Y.F. & Shen, Z.Y., 2024. "Multivariate time series convolutional neural networks for long-term agricultural drought prediction under global warming," Agricultural Water Management, Elsevier, vol. 292(C).

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