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Detection and Assessment of Changing Drought Events in China in the Context of Climate Change Based on the Intensity–Area–Duration Algorithm

Author

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  • Yanqun Ren

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jinping Liu

    (College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    Hydraulics and Geotechnics Section, KU Leuven, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium
    The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing 210098, China)

  • Patrick Willems

    (Hydraulics and Geotechnics Section, KU Leuven, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium)

  • Tie Liu

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Quoc Bao Pham

    (Faculty of Natural Sciences, Institute of Earth Sciences, University of Silesia in Katowice, Będzińska Street 60, 41-200 Sosnowiec, Poland)

Abstract

Drought can have a significant impact on both society and the economy, resulting in issues such as scarcity of water and shortages of food and energy, as well as elevated health risks. However, as global temperatures continue to rise, the impact of drought events is increasingly exacerbated, manifested by an increase in the frequency, intensity, duration, and spatial extent of their effects. Therefore, studying the changing characteristics of drought events with the background of climate change is of great significance. Based on the high-precision and high-resolution CN05.1 dataset, this study obtained the monthly Standardized Precipitation Evapotranspiration Index (SPEI) dataset from 1961 to 2020, and then identified regional drought events in China using the Intensity–Area–Duration (IAD) method, which considers both temporal continuity and spatial dynamics. On this basis, the spatiotemporal variations in frequency, intensity, duration, and affected area of drought events in China and its seven subregions were analyzed. The results showed that the subregions located in the northern region of China generally have lower mean, maximum, and minimum temperatures than those located in the southern region, but the associated interannual change rate of the subregions in the north is higher than that in the south. As for the annual total precipitation, results show a clear pattern of decreasing southeast–northwest gradient, with an increasing trend in the northern subregions and a decreasing trend in the southern subregions except for the subregion south China (SC). The northeast of China (NE), SC, the southwest of China (SW) and north China (NC) are the regions with a high frequency of drought events in China, while the frequency of drought events in NW and Qinghai–Tibetan Plateau (QTP), although lower, is on a significantly increasing trend, and the increasing rate is higher than for the other regions. For drought intensity, Xinjiang (XJ) and QTP had greater drought intensity, and the change rate of these regions with greater drought intensity was also greater. The drought impact area in China showed a significant increasing trend, mainly concentrated in QTP, NW and NE. Particular attention needs to be focused on the southwest of QTP, where drought events in this region show a significant increase in frequency, intensity, duration and impact area.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:10:p:1820-:d:1246308
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    References listed on IDEAS

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    1. Jinping Liu & Junchao Wu & Sk Ajim Ali & Nguyen Thi Thuy Linh & Yanqun Ren & Masoud Jafari Shalamzari, 2024. "Unraveling Projected Changes in Spatiotemporal Patterns and Drought Events across Mainland China Using CMIP6 Models and an Intensity–Area–Duration Algorithm," Land, MDPI, vol. 13(10), pages 1-23, September.
    2. Yuchen Zhong & Jun Sun & Qi Wang & Dinghua Ou & Zhaonan Tian & Wuhaomiao Yu & Peixin Li & Xuesong Gao, 2024. "Spatiotemporal Distribution and Driving Mechanisms of Cropland Long-Term Stability in China from 1990 to 2018," Land, MDPI, vol. 13(7), pages 1-17, July.

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