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High-resolution propagation time from meteorological to agricultural drought at multiple levels and spatiotemporal scales

Author

Listed:
  • Li, Yifei
  • Huang, Shengzhi
  • Wang, Hanye
  • Zheng, Xudong
  • Huang, Qiang
  • Deng, Mingjiang
  • Peng, Jian

Abstract

Meteorological drought (MD) is the source of agricultural drought (AD), and in-depth understanding of the propagation process from MD to AD can help AD early warning. However, previous studies primarily focused on average state of propagation time (PT) rather than from the perspective of various drought levels, and had coarse spatiotemporal resolutions (monthly and basin scales), and also ignored the PT during critical stages of crop water demand. To fill the knowledge gap, this study used the standardized precipitation index (SPI) and standardized soil moisture index (SSMI) to characterize MD and AD. Then, a framework for high-resolution PT identification under different drought levels based on Copula theory and conditional probability was proposed. Taking the rain-fed agricultural region of Loess Plateau (RFLP) as an example, the PT of the critical stages of water demand for local crops (spring maize, winter wheat) was calculated respectively. Result showed that: (1) PT in summer and autumn is shorter than those in winter and spring, and the higher drought level, the faster the spreading rate, in which the PT in spring, summer, autumn, and winter under extreme MD conditions were 3–15, 1–6, 1–8 and 4–16 ten days, respectively; (2) it should be noted that the central part of RFLP is a hotspot, with a shorter PT than any surrounding area; (3) PT is mainly related to local water and heat characteristics, and high potential evapotranspiration tends to accelerate the propagation process, while sufficient soil moisture has a good buffering effect on MD and can slow down the propagation; (4) it was observed that PT in the jointing-heading stage of wheat was significantly shortened, which should be of great concern to the local agricultural authorities. In general, this study sheds new insights into high spatiotemporal resolution drought propagation, which is helpful for AD risk management.

Suggested Citation

  • Li, Yifei & Huang, Shengzhi & Wang, Hanye & Zheng, Xudong & Huang, Qiang & Deng, Mingjiang & Peng, Jian, 2022. "High-resolution propagation time from meteorological to agricultural drought at multiple levels and spatiotemporal scales," Agricultural Water Management, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:agiwat:v:262:y:2022:i:c:s0378377421007058
    DOI: 10.1016/j.agwat.2021.107428
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    References listed on IDEAS

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    1. Kalisa, Wilson & Zhang, Jiahua & Igbawua, Tertsea & Ujoh, Fanan & Ebohon, Obas John & Namugize, Jean Nepomuscene & Yao, Fengmei, 2020. "Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Zhou, Keke & Li, Jianzhu & Zhang, Ting & Kang, Aiqing, 2021. "The use of combined soil moisture data to characterize agricultural drought conditions and the relationship among different drought types in China," Agricultural Water Management, Elsevier, vol. 243(C).
    3. Chen, Shichao & Du, Taisheng & Wang, Sufen & Parsons, David & Wu, Di & Guo, Xiuwei & Li, Donghao, 2021. "Quantifying the effects of spatial-temporal variability of soil properties on crop growth in management zones within an irrigated maize field in Northwest China," Agricultural Water Management, Elsevier, vol. 244(C).
    4. Zhang, Yu & Hao, Zengchao & Feng, Sifang & Zhang, Xuan & Xu, Yang & Hao, Fanghua, 2021. "Agricultural drought prediction in China based on drought propagation and large-scale drivers," Agricultural Water Management, Elsevier, vol. 255(C).
    5. Eltazarov, Sarvarbek & Bobojonov, Ihtiyor & Kuhn, Lena & Glauben, Thomas, 2021. "Mapping weather risk – A multi-indicator analysis of satellite-based weather data for agricultural index insurance development in semi-arid and arid zones of Central Asia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 23.
    6. Huang, Shengzhi & Huang, Qiang & Chang, Jianxia & Leng, Guoyong & Xing, Li, 2015. "The response of agricultural drought to meteorological drought and the influencing factors: A case study in the Wei River Basin, China," Agricultural Water Management, Elsevier, vol. 159(C), pages 45-54.
    7. Han, Zhiming & Huang, Qiang & Huang, Shengzhi & Leng, Guoyong & Bai, Qingjun & Liang, Hao & Wang, Lu & Zhao, Jing & Fang, Wei, 2021. "Spatial-temporal dynamics of agricultural drought in the Loess Plateau under a changing environment: Characteristics and potential influencing factors," Agricultural Water Management, Elsevier, vol. 244(C).
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