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Attribution of meteorological, hydrological and agricultural drought propagation in different climatic regions of China

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  • Ding, Yibo
  • Gong, Xinglong
  • Xing, Zhenxiang
  • Cai, Huanjie
  • Zhou, Zhaoqiang
  • Zhang, Doudou
  • Sun, Peng
  • Shi, Haiyun

Abstract

Drought propagation describes the changes in a drought signal as it moves from one major type of drought to another. It is important to investigate the propagation among meteorological, agricultural and hydrological drought, as well as their major impacting factors, to improve understanding of the drought propagation relationship, monitor agricultural drought and reduce crop losses. This study presents the first exploration of the interplay between multiple droughts among different climate zones and seasons in China. The standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI) and self-calibrating Palmer drought severity index (scPDSI) were used to represent meteorological, agricultural and hydrological drought, respectively. The Pearson correlation coefficient was used to analyze the propagation relationships among different droughts and identify the most sensitive season for drought propagation. The Lindeman–Merenda–Gold (LMG) method was used to quantify the relative importance of PRE (precipitation), PET (potential evapotranspiration) and SM (soil moisture) to hydrological and agricultural drought. The propagation from meteorological to agricultural drought was prominent in different seasons at the annual scale over China. In general, the propagation relationship from agricultural to hydrological drought was weaker than that from meteorological to agricultural drought. In Northern China (arid and semi-arid areas), there was a stronger propagation relationship from agricultural to hydrological drought in summer and autumn than in spring. There was also stronger propagation from agricultural to hydrological drought in eastern China than in western China. Different climate regions had different major factors driving hydrological drought because of the different climate characteristics. However, SM was generally the most important driving factor for agricultural drought in all climate regions. Mulching plastic film might be an effective and feasible method to reduce PET from soil evaporation in sub-regions that apply high irrigation levels. These findings may also be applied to strengthen the study of artificial regulation of water resources, which could be an approach to reducing crop losses from drought.

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  • 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).
    • Handle: RePEc:eee:agiwat:v:255:y:2021:i:c:s0378377421002614
    DOI: 10.1016/j.agwat.2021.106996
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    3. Jiangtao Yu & Hangnan Yu & Lan Li & Weihong Zhu, 2024. "Spatial and Temporal Changes in Soil Freeze-Thaw State and Freezing Depth of Northeast China and Their Driving Factors," Land, MDPI, vol. 13(3), pages 1-21, March.
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    5. Yang, Yueting & Li, Kaiwei & Wei, Sicheng & Guga, Suri & Zhang, Jiquan & Wang, Chunyi, 2022. "Spatial-temporal distribution characteristics and hazard assessment of millet drought disaster in Northern China under climate change," Agricultural Water Management, Elsevier, vol. 272(C).
    6. 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).
    7. Amogh Gyaneshwar & Anirudh Mishra & Utkarsh Chadha & P. M. Durai Raj Vincent & Venkatesan Rajinikanth & Ganapathy Pattukandan Ganapathy & Kathiravan Srinivasan, 2023. "A Contemporary Review on Deep Learning Models for Drought Prediction," Sustainability, MDPI, vol. 15(7), pages 1-31, April.
    8. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Hao, Fanghua, 2022. "Changes and driving factors of compound agricultural droughts and hot events in eastern China," Agricultural Water Management, Elsevier, vol. 263(C).
    9. Yang, Beibei & Cui, Qian & Meng, Yizhuo & Zhang, Zhen & Hong, Zhiming & Hu, Fengmin & Li, Junjie & Tao, Chongxin & Wang, Zhe & Zhang, Wen, 2023. "Combined multivariate drought index for drought assessment in China from 2003 to 2020," Agricultural Water Management, Elsevier, vol. 281(C).
    10. Huang, Wenhuan & Wang, Hailong, 2021. "Drought and intensified agriculture enhanced vegetation growth in the central Pearl River Basin of China," Agricultural Water Management, Elsevier, vol. 256(C).

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