地球科学进展

地球科学进展 ›› 2016, Vol. 31 ›› Issue (5): 515 -528. doi: 10.11867/j.issn.1001-8166.2016.05.0515.

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未来气候变化背景下高温热害对中国水稻产量的可能影响分析
熊伟 1( ), 冯灵芝 2, 居辉 1, 杨笛 1   
  1. 1.中国农业科学院农业环境与可持续发展研究所,北京 100081
    2.陕西省榆林市气象局,陕西 榆林 719000
  • 收稿日期:2016-03-05 修回日期:2016-05-01 出版日期:2016-05-20
  • 基金资助:
    *国家自然科学基金项目“气候变化下我国粮食产量增速放缓的驱动机制及适应潜力研究”(编号:41471074)和“我国麦—玉轮作复种体系对气候变化的适应机制及适应技术集成的模拟研究”(编号:41171093)资助

Possible Impacts of High Temperatures on China’s Rice Yield under Climate Change

Wei Xiong 1( ), Lingzhi Feng 2, Hui Ju 1, Di Yang 1   

  1. 1.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    2.Meteorological Administration of Yulin City, Shaanxi Province, Yulin 719000,China
  • Received:2016-03-05 Revised:2016-05-01 Online:2016-05-20 Published:2016-05-10
  • About author:

    First author:Xiong Wei(1974-), male, Xiaogan City, Hubei Provinces, Professor. Research areas include climate change impacts and adaptation.E-mail:xiongw@ami.ac.cn

  • Supported by:
    Project supported by the National Natural Science Foundation of China Projects “A research on the reasons of the recent slowing of crop yield growth in China and the potential of adaptation”(No.41471074) and “The adaptation mechanism of summer maize and winter wheat cropping system in China and an integrated simulation of adaptation”(No.41171093)
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研究分析了RCP2.6和RCP8.5气候情景下2021—2050年我国水稻高温敏感期(孕穗期—乳熟期)高温事件的变化趋势(较基准时段1961—1990年),并利用1981—2009年水稻田间观测资料,明确了水稻高温减产的主导因子,构建了主导因子与水稻减产率之间的经验回归关系式,在此基础上预估了未来RCP2.6和RCP8.5气候情景下我国水稻发生高温热害的风险变化。结果表明:①RCP2.6和RCP8.5气候情景下2021—2050年,全国各水稻种植区,水稻高温事件均有增加趋势,高温日数(HSD)、高温积温(HDD)都呈现增加趋势,高温持续日数(CHD)有延长趋势,其中华南双季稻区、长江流域单季稻区和东北单季稻区的HSD和HDD的变化幅度较为明显。②中国水稻高温中心在1961—2000年主要集中于湖南北部,与湖北省交界处附近,2种情景下2021—2050年均出现了向东北方向移动的趋势。③除东北区外,我国其余水稻种植区,孕穗—乳熟阶段的日最高气温连续3 d超过35 ℃以上的有效积温HDD2是导致水稻减产的第一大要素,两者之间具有显著线性负相关关系;而东北区水稻产量更易受到孕穗—乳熟阶段的单日日最高气温超过32 ℃的有效积温SDD2的影响,且两者呈现出显著一元二次曲线关系。④与1961—1990年相比,2种气候情景下2021—2050年我国水稻发生高温热害的概率增加较大的地区,主要集中在长江流域单季稻区的湖北和安徽的大部分地区,华南双季稻区的广东、广西、海南省的大部分地区以及东北单季稻区的南部。

关键词: 水稻, 高温事件, 高温热害概率, 产量, RCP情景

This study investigated the changes of high temperature events during important growing period of rice (graining filling to maturity) of 2021-2050 due to climate change. Future climate scenarios were HadGEM2-ES simulation with RCP2.6 and RCP8.5 emission pathways. Relationship between high temperature and yield change was established from historical weather and field observations during 1981-2009 period. The impacts of high temperatures on China’s rice production up to 2050 were assessed by applying deduced regression models to climate scenarios. Key messages drawn from this exercise include: ①High temperature event exhibited gradual increase from 2021 to 2050 under both RCP2.6 and RCP8.5 scenarios, characterized by increased number of high temperature days (HSD), rising accumulated temperature with Tmax greater than 35 ℃ (HDD), and increased lasting days of high temperature (CHD). The HSD and HDD increased substantially in double rice cropping system of South China, single rice cropping system of Yangtze River Basin and rice area of Northeast China. ②High temperature hotspot was located near the border between Hunan and Hubei during 1961-2000, and might move towards northeast in the period of 2021-2050. ③Except the Northeast, China’s rice production suffered most from increased HDD during grain filling to maturity, indicated by significant negative and linear relationship between yield and HDD, whereas rice in Northeast China was subject to the increase of SDD during grain filling to maturity, with a significant and quadratic relationship between the yield and SDD. ④Compared to the high temperature risks during 1961-1990, climate change would increase the risks in majority of the rice area, especially in Hubei and Anhui-the central portion of Yangtze River Basin rice area, Guangdong, Guangxi and Hainan-south China double rice area, and south part of Northeast China single rice area.

Key words: Rice, High temperature event, Possibility of heat stress, Yield, RCP scenario.

中图分类号: 

图1 中国水稻种植区和农业气象站点、气象站点的空间分布
Fig.1 Rice planting zone, and locations of agro-meteorological and meteorological stations
表1 1981—2009年各水稻种植区水稻孕穗、乳熟的平均日期
Table 1 Average date of booting, anthesis and milking in each agrometeorological station in China from 1981 to 2009
区域 区域 熟制 孕穗 乳熟 平均持续
天数/d
Ⅰ 长江流域 单季稻 7月下旬 8月中旬 26
Ⅱ 江南 早稻 6月下旬 7月中旬 22
Ⅲ 华南 早稻 6月中旬 7月上旬 23
Ⅳ 云贵 单季稻 7月下旬 8月下旬 31
Ⅴ 东北 单季稻 7月下旬 8月下旬 30
表2 RCP2.6,RCP8.5情景下2021—2050年中国水稻高温敏感期HSD和HDD较基准时段(1961—1990年)的平均变化
Table 2 Changes of HSD and HDD during high temperature sensitive period of rice in 2021-2050 under RCP2.6 and RCP8.5 (relative to baseline 1961-1990)
情景 Baseline RCP2.6 RCP8.5 Baseline RCP2.6 RCP8.5
HSD/d ΔHSD/d HDD/(℃·d) ΔHDD/(℃·d)
区

域		 长江流域单季稻(I) 2.59 1.15 2.00 4.39 4.74 7.74
江南双季稻区(II) 1.73 0.47 0.92 2.22 2.20 2.94
华南双季稻区(III) 0.70 1.71 3.21 0.78 5.29 9.57
云贵高原单季稻区(IV) 0.49 0.18 0.21 0.66 0.10 0.07
东北单季稻区(V) 0.02 0.92 1.59 0.02 2.44 5.75
全国 1.27 1.08 1.49 1.91 3.89 4.81
图2 基准时段(1961—1990年)我国及各水稻种植区水稻高温敏感期高温持续日数的频次
Fig.2 Occurrence frequency and lasting days of the high temperature events during rice high temperature sensitive period under baseline
表3 RCP2.6,RCP8.5情景下2021—2050年中国水稻高温敏感期高温持续日数(CHD)较基准时段的平均频次变化
Table 3 Changes of CHD during high temperature sensitive period of rice in 2021-2050 under RCP2.6 and RCP 8.5 (relative to baseline)
高温持续日数 1~2 d 3~5 d 6~8 d >8 d
RCP2.6 RCP8.5 RCP2.6 RCP8.5 RCP2.6 RCP8.5 RCP2.6 RCP8.5
长江流域单季稻区(I) -0.03 -0.08 0.08 0.06 0.01 0.05 0.06 0.11
江南双季稻区(II) 0.01 -0.14 -0.02 0.05 0.01 0.04 0.03 0.03
华南双季稻区(III) 0.08 0.29 0.13 0.35 0.06 0.10 0.06 0.11
云贵高原单季稻区(IV) -0.08 -0.09 -0.02 -0.03 0.00 0.00 0.00 0.00
东北单季稻区(V) 0.13 0.19 0.14 0.12 0.03 0.04 0.06 0.02
全国 0.02 0.06 0.07 0.12 0.03 0.05 0.06 0.06
图3 1961—2000年和RCP2.6和RCP8.5情景下2021—2050年中国水稻高温中心的年代际移动情况
Fig.3 Movement of the weighted central point of high temperature risk in 1961-2000 and 2021-2050 under RCP2.6 and RCP8.5 scenarios
表4 影响水稻产量距平百分率(D)的主导因子
Table 4 Main factors affecting the inter-variability of rice yield and their statistics (D)
区域 第一因子 站点比例
/%		 相关性
(+/-)		 第二因子 站点比例
/%		 相关性
(+/-)		 第三因子 站点比例
/%		 相关性
(+/-)
长江流域单季稻区(I) HDD2 52.2 - ADD2 8.7 - R2 15.2 -
江南双季稻区(II) HDD2 28.6 - ADD3 21.4 - R2 14.3 -
华南双季稻区(III) HDD2 27.3 - ADD2 13.6 - P2 9.1 -
云贵高原单季稻区(IV) HDD2 20.0 - T 13.3 + HDD3 6.7 -
东北单季稻区(V) SDD2 12.5 +- SDD0 12.5 +- P1 6.3 -
全国 HDD2 37.1 - HDD0 8.8 - P0 10.2 -
表5 各区域水稻产量距平百分率D与减产的最主导因子之间回归方程、减产速率和减产的高温阈值
Table 5 Regression models and the statistics of yield loss and high temperature indices
区域 省 拟合方程 自由度
(n-2)		 R2 减产速率H
/(%/(℃·d))		 M
/(℃·d)
长江流域单季稻区(I) 江苏 D=-0.6498 HDD+5.9305 7 0.81** 0.65 9.13
安徽 D=-0.6019 HDD+5.4426 39 0.12* 0.60 9.04
湖北 D=-0.3335 HDD+2.914 58 0.19** 0.33 8.74
四川 D=-0.4813 HDD+6.847 51 0.39** 0.48 14.23
重庆 D=-0.5473 HDD+11.241 30 0.45** 0.55 20.54
江南早稻区(II) 湖南 D=-0.4319 HDD+3.9005 34 0.55** 0.43 9.03
江西 D=-0.5503 HDD+4.0608 55 0.36** 0.55 7.38
浙江 D=-0.3694 HDD+4.697 29 0.43* 0.37 12.72
福建 D=-0.4022 HDD+2.1586 26 0.38* 0.40 5.37
华南早稻区(III) 广东、海南 D=-0.3839 HDD+3.2418 25 0.50** 0.38 8.44
广西 D=-0.9218 HDD+6.5073 19 0.19* 0.92 7.06
云贵稻区(IV) D=-0.3043 HDD+2.0233 13 0.50** 0.30 6.65
东北稻区(V) D=-0.182SDD2+2.4513SDD
-2.8966		 79 0.20** --- 12.16
图4 RCP2.6(a)和RCP8.5(b)情景下2021—2050年中国水稻发生高温热害的概率变化情况(较基准时段1961—1990年)
Fig.4 Change in probability of high temperature events during rice growth period in 2021-2050 under scenario RCP 2.6 (a) and RCP 8.5 (b) (compared to baseline 1961-1990)
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