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Spatiotemporal Trends and Attribution of Drought across China from 1901–2100

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  • Yongxia Ding

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710169, China)

  • Shouzhang Peng

    (State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China)

Abstract

Investigating long-term drought trends is of great importance in coping with the adverse effects of global warming. However, little attention has been focused on studying the detailed spatial variability and attribution of drought variation in China. In this study, we first generated a 1 km resolution monthly climate dataset for the period 1901–2100 across China using the delta spatial downscaling method to assess the variability of the Standardized Precipitation Evaporation Index (SPEI). We then developed a simple approach to quantifying the contributions of water supply (precipitation) and demand (potential evapotranspiration, PET) on SPEI variability, according to the meaning of the differentiating SPEI equation. The results indicated that the delta framework could accurately downscale and correct low-spatial-resolution monthly temperatures and precipitation from the Climatic Research Unit and general circulation models (GCMs). Of the 27 GCMs analyzed, the BNU-ESM, CESM1-CAM5, and GFDL-ESM2M were found to be the most accurate in modeling future temperatures and precipitation. We also found that, compared with the past (1901–2017), the climate in the future (2018–2100) will tend toward significant droughts, although both periods showed a high spatial heterogeneity across China. Moreover, the proportion of areas with significantly decreasing SPEI trends was far greater than the proportion of those with increasing trends in most cases, especially for northwestern and northern China. Finally, the proposed approach to quantifying precipitation and PET contributions performed well according to logical evaluations. The percentage contributions of precipitation and PET on SPEI variability varied with study periods, representative concentration pathway scenarios, trend directions, and geographic spaces. In the past, PET contributions for significant downward trends and precipitation contributions for significantly upward trends accounted for 95% and 72%, while their future contributions were 57 ± 22%–149 ± 20% and 95 ± 27%–190 ± 58%, respectively. Overall, our results provide detailed insights for planning flexible adaptation and mitigation strategies to cope with the adverse effects of climate drought across China.

Suggested Citation

  • Yongxia Ding & Shouzhang Peng, 2020. "Spatiotemporal Trends and Attribution of Drought across China from 1901–2100," Sustainability, MDPI, vol. 12(2), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:477-:d:306395
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    1. 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.
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    2. Zhen Chen & Xiaohong Gao & Zhifeng Liu & Kelong Chen, 2023. "Spatiotemporal Variation of Soil Erosion Characteristics in the Qinghai Lake Basin Based on the InVEST Model," IJERPH, MDPI, vol. 20(6), pages 1-21, March.
    3. Azimatjan Mamattursun & Han Yang & Kamila Ablikim & Nurbiya Obulhasan, 2022. "Spatiotemporal Evolution and Driving Forces of Vegetation Cover in the Urumqi River Basin," IJERPH, MDPI, vol. 19(22), pages 1-25, November.
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    5. Monia Santini & Sergio Noce & Marco Mancini & Luca Caporaso, 2023. "A Global Multiscale SPEI Dataset under an Ensemble Approach," Data, MDPI, vol. 8(2), pages 1-14, February.
    6. Jincai Zhao & Qianqian Liu & Heli Lu & Zheng Wang & Ke Zhang & Pan Wang, 2021. "Future droughts in China using the standardized precipitation evapotranspiration index (SPEI) under multi-spatial scales," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 615-636, October.
    7. Ruixin Zhang & Yuke Zhou & Tianyang Hu & Wenbin Sun & Shuhui Zhang & Jiapei Wu & Han Wang, 2023. "Detecting the Spatiotemporal Variation of Vegetation Phenology in Northeastern China Based on MODIS NDVI and Solar-Induced Chlorophyll Fluorescence Dataset," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
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    9. Mengyao Ci & Lu Ye & Changhao Liao & Li Yao & Zhiqin Tu & Qiao Xing & Xuguang Tang & Zhi Ding, 2023. "Long-Term Dynamics of Ecosystem Services and Their Influencing Factors in Ecologically Fragile Southwest China," Sustainability, MDPI, vol. 15(16), pages 1-22, August.
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    11. 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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