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

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

Agricultural Water Management, 2023, vol. 283, issue C

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.

Keywords: Agricultural drought; Soil moisture; GLDAS; Drought severity index; Drought frequency; China (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:283:y:2023:i:c:s0378377423001701

DOI: 10.1016/j.agwat.2023.108305

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