PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (10): 1746-1760.doi: 10.18306/dlkxjz.2021.10.011

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A review of studies on the impacts of extreme precipitation on rice yields

JIAN Yiwei1,2(), FU Jin1,2, ZHOU Feng1,2,*()   

  1. 1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
    2. Laboratory for Earth Surface Process, Peking University, Beijing 100871, China
  • Received:2020-11-01 Revised:2021-06-24 Online:2021-10-28 Published:2021-12-28
  • Contact: ZHOU Feng;
  • Supported by:
    National Natural Science Foundation of China(41977082);National Key Research and Development Program of China(2016YFD0800501)


The increasing trend of extreme precipitation has become stronger globally, and is expected to have detrimental impact on agricultural ecosystems. Rice is one of the staple foods, and the inter-annual fluctuation of rice yield is highly affected by extreme precipitation. However, the mechanisms and spatiotemporal sensitivity of rice yield to extreme precipitation have not been clarified. This review summarized the temporal and spatial patterns of extreme precipitation in the main rice-producing regions of the world and its impact on rice yield, and explored the mechanism of extreme precipitation impact on rice growth and yield from the perspective of physiological, chemical, and physical processes. The input data and advantages and disadvantages in application of the main research methods, including statistical model and crop model, were evaluated and compared. The results indicate that an increase of 1% in extreme precipitation led to a decrease in rice yield by 0.02%-0.5%, mainly through increased nutrient loss and flooding. Yet, large uncertainties still exist in rice yield prediction of current studies, because it is difficult to clarify how rice yield responds to different characteristics (intensity, frequency, and duration) of extreme precipitation and its spatiotemporal sensitivity, and the mechanisms of extreme precipitation affecting rice yield components are not well understood. In addition, lacking the integration of crop models and statistical models also introduces uncertainties. We recommend to promote the integration of multi-methods, especially field observation, controlled experiment, and model improvement, to quantitatively analyze the mechanism of extreme precipitation impact on yield components, and to improve data accuracy to better simulate rice yields under extreme precipitation events in the future. Achieving these progresses will lay a foundation for optimizing the current rice cropping system and agricultural management to mitigate the impact of extreme precipitation.

Key words: extreme precipitation, rice yield, climate change, statistical model, crop model