Characteristics of meteorological drought pattern and risk analysis for maize production in Xinjiang, Northwest China

Abstract

Xinjiang is an important maize cultivation area in Northwest China. Investigating the relationship between meteorological drought and climate-driven maize yield can help to mitigate the negative impacts of drought on agricultural production in Xinjiang. In this study, multi-source data, including meteorological, agricultural, and socio-economic data, are collected to analyze the spatiotemporal patterns of drought and assess drought disaster risk. The standardized precipitation evapotranspiration index is calculated to classify different drought grades in the study area. The main results are as follows: (1) the relationship between drought and climate-driven maize yield is determined using a stepwise regression analysis, which indicates that drought conditions occurring from May to July are crucial for the yield in Xinjiang; (2) the modified Mann-Kendall test detects that the frequency-intensity-coverage of drought from May to July shows a decreasing tendency as a whole in the study area; (3) the correlation analysis shows that the multivariate ENSO index may be the dominant force in regional drought evolution; and (4) a drought disaster risk assessment system is constructed based on principles of natural disaster management. The drought disaster risk is higher in southwestern and northwestern Xinjiang, areas that should deserve more attention.

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Acknowledgements

Four scientific funds [the National Key Technology R&D Program of China (No. 2012BAD16B0305, 2012BAC23B01), the Clean Development Mechanism Fund of China (No. 2013013), and the Postgraduates Innovation Program of Jiangsu (KYLX15_0871)] and two data centers of science [http://midasia.data.ac.cn/ and http://www.resdc.cn] supported our work.

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Correspondence to Cheng Li.

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Li, C., Wang, R., Ning, H. et al. Characteristics of meteorological drought pattern and risk analysis for maize production in Xinjiang, Northwest China. Theor Appl Climatol 133, 1269–1278 (2018). https://doi.org/10.1007/s00704-017-2259-6

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