极端降水对水稻产量的影响研究综述

doi:10.18306/dlkxjz.2021.10.011

Abstract

Abstract:

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

JIAN Yiwei, FU Jin, ZHOU Feng. A review of studies on the impacts of extreme precipitation on rice yields[J].PROGRESS IN GEOGRAPHY, 2021, 40(10): 1746-1760.

Figures/Tables 4

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名称	研究内容	数据	优点	缺点	典型方法
统计模型	作物生育期内气候因素对作物产量的影响	长期历史观测数据(气候变量、作物产量)	模型简单,运行成本小;隐含农民适应性行为及作物生理响应	模型共线性问题;模型缺乏解释,不便外推	相关分析;线性回归;面板回归
作物机理模型	不同气候情景下作物产量的预测	基于田间实验的参数率定,特定点位的输入数据(气候变量、生理指标等)	模拟作物生长生理机制;在更精细的空间尺度上评估气候因素及适应性措施的影响	模型复杂,参数率定难;未考虑适应性行为,不能反映社会经济反馈;模拟极端降水条件弱	ORYZA2000; CERES-rice; DSSAT
控制实验	作物生长对气候因子的响应及敏感性	实验观测数据(作物生长性状、产量组成等)	对作物响应过程及影响途径进行分析	数据获取难;结果稳定性差;难排除协变量	梯度增温;人工气候室;人工降水
计量经济模型	气候因素与生产要素投入对作物产量的影响	长期历史观测数据(气候变量、作物产量、生产要素投入)	考虑社会经济反馈	遗漏变量偏误;前提假设过多,难以构建符合实际的生产函数	生产函数法;经济气候模型

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

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