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A novel composite drought index combining precipitation, temperature and evapotranspiration used for drought monitoring in the Huang-Huai-Hai Plain

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  • Li, Jiale
  • Li, Yu
  • Yin, Lei
  • Zhao, Quanhua

Abstract

Single drought index such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Evapotranspiration Condition Index (ETCI) and so on, has a limited capability to indicate drought state. It has been proved that the composite drought index proposed by integrating multiple single drought indices can indicate and predict drought state more efficiently and accurately. This paper presents the Precipitation Temperature Evapotranspiration Drought Index (PTEDI) combining the PCI, TCI and ETCI. The three-dimensional Euclidean PCI-TCI-ETCI space is built, and the PTEDI is defined as the magnitude of the vector in the PCI-TCI-ETCI space. To verify the rationality and effectiveness of the PTEDI as a desired drought index in the Huang-Huai-Hai Plain, it is compared with the PCI, TCI, ETCI and PCACDI (Principal Component Analysis Combined Drought Index), and is evaluated with the Drought Affected/Disaster Area (DAA/DDA) and Net Primary Productivity (NPP). The results indicate that the PTEDI outperforms the PCI, TCI, ETCI and PCACDI, and is highly correlated with the Standardized Precipitation Index (SPI-1) (R = 0.61), Soil Moisture Condition Index (SMCI) (R= 0.56), and NPP (R = 0.56). The time series of the PTEDI and four indices (SPI-1, SMCI, Crop Water Stress Index (CWSI) and Temperature Vegetation Drought Index (TVDI)) exhibits good spatial consistency. The PTEDI has a negative correlation with the DAA/DDA (R < −0.6). Furthermore, to illustrate the applicability of the PTEDI, the drought spatiotemporal variation is analyzed by taking it as a drought index. At the monthly scale, moderate drought occurs most frequently in March and July. At the annual scale, the PTEDI fluctuates between 0.34 and 0.60 without obvious periodicity, and the study area is mainly characterized by mild drought. Moreover, the drought evolution is analyzed by using the timing analysis methods. In conclusion, the PTEDI can be applied to monitor drought effectively.

Suggested Citation

  • Li, Jiale & Li, Yu & Yin, Lei & Zhao, Quanhua, 2024. "A novel composite drought index combining precipitation, temperature and evapotranspiration used for drought monitoring in the Huang-Huai-Hai Plain," Agricultural Water Management, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:agiwat:v:291:y:2024:i:c:s0378377423004912
    DOI: 10.1016/j.agwat.2023.108626
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    1. Yang Li & Wen Zhang & Christopher R. Schwalm & Pierre Gentine & William K. Smith & Philippe Ciais & John S. Kimball & Antonio Gazol & Steven A. Kannenberg & Anping Chen & Shilong Piao & Hongyan Liu & , 2023. "Widespread spring phenology effects on drought recovery of Northern Hemisphere ecosystems," Nature Climate Change, Nature, vol. 13(2), pages 182-188, February.
    2. S. Asseng & F. Ewert & C. Rosenzweig & J. W. Jones & J. L. Hatfield & A. C. Ruane & K. J. Boote & P. J. Thorburn & R. P. Rötter & D. Cammarano & N. Brisson & B. Basso & P. Martre & P. K. Aggarwal & C., 2013. "Uncertainty in simulating wheat yields under climate change," Nature Climate Change, Nature, vol. 3(9), pages 827-832, September.
    3. Zhang, Xiying & Chen, Suying & Sun, Hongyong & Shao, Liwei & Wang, Yanzhe, 2011. "Changes in evapotranspiration over irrigated winter wheat and maize in North China Plain over three decades," Agricultural Water Management, Elsevier, vol. 98(6), pages 1097-1104, April.
    4. Ren, Pinpin & Huang, Feng & Li, Baoguo, 2022. "Spatiotemporal patterns of water consumption and irrigation requirements of wheat-maize in the Huang-Huai-Hai Plain, China and options of their reduction," Agricultural Water Management, Elsevier, vol. 263(C).
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    1. Xiao, Xin & Ming, Wenting & Luo, Xuan & Yang, Luyi & Li, Meng & Yang, Pengwu & Ji, Xuan & Li, Yungang, 2024. "Leveraging multisource data for accurate agricultural drought monitoring: A hybrid deep learning model," Agricultural Water Management, Elsevier, vol. 293(C).

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