欢迎访问作物学报,今天是

作物学报 ›› 2022, Vol. 48 ›› Issue (6): 1537-1545.doi: 10.3724/SP.J.1006.2022.03061

• 研究简报 • 上一篇    下一篇

气候变化背景下农业气象灾害对东北地区春玉米产量影响

李祎君(), 吕厚荃*()   

  1. 国家气象中心, 北京 100081
  • 收稿日期:2020-10-19 接受日期:2021-10-20 出版日期:2022-06-12 网络出版日期:2021-11-18
  • 通讯作者: 吕厚荃
  • 作者简介:E-mail: duoshaoduo151@163.com, Tel: 010-68407040
  • 基金资助:
    国家重点基础研究发展计划(973计划)项目(2013CB430205);“十三五”国家重点研发计划项目(2019YFD1002201)

Effect of agricultural meteorological disasters on the production corn in the Northeast China

LI Yi-Jun(), LYU Hou-Quan*()   

  1. National Meteorological Centre of China, Beijing 100081, China
  • Received:2020-10-19 Accepted:2021-10-20 Published:2022-06-12 Published online:2021-11-18
  • Contact: LYU Hou-Quan
  • Supported by:
    National Key Basic Research Program(2013CB430205);National Key Research and Development Program of China(2019YFD1002201)

摘要:

随着气候变化, 中国重要商品粮基地—东北地区的农业气象灾害呈现出多发和频发的态势, 为了解这种变化对当地春玉米生产的影响, 本文引入通径分析法, 探讨该地区的主要农业气象灾害对春玉米产量的直接影响或协同影响及其程度, 进而在实际生产中更好的趋利避害以确保粮食生产安全。结果发现, 农业气象灾害可以解释50%左右东北地区春玉米产量的波动, 且影响春玉米生产的主要农业气象灾害已经从过去的冷害转变为干旱; 在气候变暖的大背景下, 影响春玉米生产的主要因子由热量条件转换为水分条件, 干旱已成为威胁春玉米产量的首要灾害。分省来看, 影响辽宁春玉米产量的农业气象灾害, 按照影响程度排序为干旱、洪涝和风灾; 影响吉林春玉米产量的农业气象灾害主要为干旱和洪涝; 影响黑龙江春玉米产量的农业气象灾害, 按照影响程度排序为干旱、洪涝和风灾。由此可见, 东北三省由于地理位置差异, 影响其玉米生产的主要农业气象灾害也有所差异, 黑龙江除风雹灾害影响大于其他两省外, 水旱灾害的影响均弱于辽吉, 风雹灾害局地性强, 影响范围有限, 因而其对玉米生产的影响远不及水旱灾害, 黑龙江玉米生产稳定性较高, 受农业气象灾害影响相对较小, 对东北地区在具体研究中不能一概而论。

关键词: 农业气象灾害, 干旱, 洪涝, 冷害, 产量

Abstract:

Agricultural meteorological disasters are the main natural disasters that threaten grain output. In recent years, with climate change, agricultural meteorological disasters are more and more frequent, and their impact on northeast China is also increasing. In this paper, to make better use of advantages and avoid disadvantages in actual production to ensure food production safety, spring corn in three provinces of northeast China was taken as the research object to discuss the impact of major agricultural meteorological disasters in this region on spring corn yield and its degree. The results showed that agricultural meteorological disasters could explain about 50% of the fluctuation of spring corn yield in Northeast China, and the main agricultural meteorological disasters that affected spring corn production had changed from cold damage in the traditional sense to drought. Under the background of climate warming, the main factor affecting spring corn production was changed from thermal condition to water condition, and drought had become the primary disaster threatening spring corn production. The agricultural meteorological disasters that affected the spring corn yield in Liaoning province were drought, flood, and wind in order of the degree of influence. The agricultural meteorological disaster that affected spring corn yield in Jilin province was only drought. The agricultural meteorological disasters affecting the yield of spring corn in Heilongjiang province were ranked as flood, drought, and cold damage according to the degree of impact. In conclusion, due to geographical differences, the main agro-meteorological disasters affecting the corn production in the three provinces of Northeast China were also different, and their complexity was not the same, which cannot be generalized in the specific study.

Key words: agricultural meteorological disasters, drought, flood, cold damage, corn yield

图1

1971-2018年研究区域年平均气温与距平(a)和研究区域气温突变检验(b)"

图2

1971-2018年研究区域降水量变化"

图3

1971-2018年研究区农业气象灾害成灾面积"

图4

1971-2018年研究区各类农业气象灾害成灾面积变化"

附表1

研究区域各类农业气象灾害成灾率与气象要素关系"

省份
Province
气象要素
Meteorological elements
实际产量
Actual output
气象产量滑5a relative weather yield 总成灾率
Total hazard rate
旱灾成灾率
Drought disaster rate
水灾成灾率
Flood disaster rate
风灾成灾率
Wind disaster rate
冷害成灾率
Chilling damage disaster rate
其他成灾率
Other disaster rate
黑龙江
Heilongjiang
≥10℃积温 ≥10℃ accumulated temperature 0.593** 0.593** 0.593** 0.180 0.015 -0.190 -0.238 0.146
5-6月气温 Temperature of May and June 0 0 0 0.220 -0.005 -0.210 -0.174 0.140
5-6月日照 Sunshine of May and June 0.459** 0.459** 0.459** 0.171 -0.005 -0.140 0.026 -0.021
5-6月降水 Precipitation of May and June 0.001 0.001 0.001 0.244 0.148 -0.011 -0.099 -0.016
7-8月气温 Temperature of July and August -0.441** -0.441** -0.441** 0.189 -0.125 -0.271 -0.338* 0.011
7-8月日照 Sunshine of July and August 0.002 0.002 0.002 0.197 -0.600** 0.002 0.027 0.082
7-8月降水 Precipitation of July and August 0.357* 0.357* 0.357* -0.392** 0.693** -0.104 -0.110 -0.059
9月气温 Temperature of September 0.013 0.013 0.013 0.006 -0.037 -0.083 -0.087 0.171
9月日照 Sunshine of September 0.453** 0.453** 0.453** 0.168 -0.134 0.178 0.001 -0.168
9月降水 Precipitation of September 0.001 0.001 0.001 0.253 0.125 -0.194 -0.157 0.255
生长季气温 Temperature in growing season -0.396** -0.396** -0.396** 0.399** -0.068 -0.269 -0.277 0.137
生长季降水 Precipitation in growing season 0.005 0.005 0.005 0.005 0.638** -0.153 -0.182 0.039
生长季日照 Sunshine in growing season 0.125 0.125 0.125 -0.327* -0.372** -.011 0.029 -0.019
吉林
Jilin
≥10℃积温 ≥10℃ accumulated temperature 0.502** -0.203 0.056 0.224 -0.120 -0.258 -0.331* 0.031
5-6月气温 Temperature of May and June 0.409** -0.349* 0.181 0.288* -0.040 -0.066 -0.443** 0.052
5-6月日照 Sunshine of May and June -0.353* -0.059 0.328* 0.261 0.156 0.088 -0.117 0.038
5-6月降水 Precipitation of May and June 0.131 0.250 -0.410** -0.510** 0.034 0.136 0.035 -0.095
7-8月气温 Temperature of July and August 0.315* -0.295* 0.013 0.222 -0.167 -0.414** -0.230 0.076
7-8月日照 Sunshine of July and August -0.409** -0.125 0.022 0.361* -0.482** -0.096 0 0.078
7-8月降水 Precipitation of July and August 0.189 0.116 0.089 -0.275 0.624** -0.132 -0.135 -0.104
9月气温 Temperature of September 0. 480** 0.043 -0.117 0.002 -0.145 -0.154 -0.101 0.050
9月日照 Sunshine of September -0.105 -0.114 0.017 0.145 -0.190 0.047 -.102 0.118
9月降水 Precipitation of September -0.076 0.123 0.087 -0.005 0.156 -0.043 0.081 -0.064
辽宁
Liaoning
≥10℃积温 ≥10℃ accumulated temperature 0.265 -0.276 0.404** 0.477** -0.088 -0.014 0.023 -0.074
5-6月气温 Temperature of May and June 0.386** -0.273 0.333* 0.435** -0.172 -0.005 -0.007 0.122
5-6月日照 Sunshine of May and June -0.416** -0.119 0.281 0.354* -0.116 0.130 -0.106 -0.013
5-6月降水 Precipitation of May and June 0.135 0.115 -0.265 -0.359* 0.114 0.033 0.075 0.077
7-8月气温 Temperature of July and August 0.178 -0.381** 0.239 0.243 0.023 -0.124 0.021 0.058
7-8月日照 Sunshine of July and August -0.347* -0.074 0.302* 0.514** -0.358* 0.005 0.163 -0.035
7-8月降水 Precipitation of July and August -0.025 -0.049 -0.198 -0.626** 0.714** 0.015 -0.090 -0.029
9月气温 Temperature of September 0.553** 0.161 -0.130 0.064 -0.297* -0.045 -0.070 -0.114
9月日照 Sunshine of September -0.199 0.016 0.191 0.254 -0.176 0.263 0.163 0.028
9月降水 Precipitation of September -0.228 0.192 -0.218 -0.353* 0.185 0.077 0.083 -0.010

表1

辽宁省主要农业气象灾害对玉米气象产量的直接作用和间接作用"

成灾率
Disaster rates
决策系数
Decision coefficient
通径系数
Path
coefficient
间接通径系数Indirect path coefficient 合计
Total
旱灾成灾率Dr 洪涝成灾率Fr 风灾成灾率Wr 冷冻害成灾率Cr 其他成灾率Or
旱灾成灾率
Drought disaster rates (Dr)
-0.220 -0.735 0.195 -0.016 0.007 0.029 0.215
洪涝成灾率
Flood disaster rate (Fr)
-0.160 -0.731 0.195 0.036 0 0.029 0.260
风灾成灾率
Wind disaster rate (Wr)
-0.011 -0.183 0.064 -0.146 0.003 -0.043 -0.122
冷冻害成灾率
Cold disaster rate (Cr)
-0.004 -0.067 -0.088 0.005 0.009 0.011 -0.069
其他成灾率
Other disaster rates (Or)
-0.066 -0.057 0.115 0.116 0.042 -0.003 0.063

表2

吉林省主要农业气象灾害对玉米气象产量的直接作用和间接作用"

成灾率
Disaster rates
决策系数
Decision coefficient
通径系数
Path
coefficient
间接通径系数Indirect-path coefficient 合计
Total
Dr Fr Wr Cr Or
旱灾成灾率 Dr -0.389 -0.646 0.019 -0.007 0.003 0.006 0.022
洪涝成灾率 Fr -0.009 -0.134 0.019 0.004 -0.004 0.007 0.027
风灾成灾率 Wr -0.010 -0.061 0.073 -0.009 -0.004 -0.009 0.050
冷冻害成灾率 Cr -0.001 -0.043 0.043 -0.012 0.006 0 0.037
其他成灾率 Or -0.007 -0.062 0.066 0.015 0.009 0 0.090

表3

黑龙江省主要农业气象灾害对气象产量的直接作用和间接作用"

成灾率
Disaster rates
决策系数
Decision coefficient
通径系数
Path
coefficient
间接通径系数Indirect path coefficient 合计
Total
Dr Fr Wr Cr Or
旱灾成灾率 Dr -0.300 -0.570 0.033 -0.017 0.010 -0.004 0.039
洪涝成灾率 Fr -0.021 -0.127 0.033 0.022 0 -0.013 0.041
风灾成灾率 Wr -0.031 -0.174 -0.055 0.016 0.003 -0.001 -0.038
冷冻害成灾率 Cr -0.018 0.075 -0.073 0.013 -0.089 -0.008 -0.157
其他成灾率 Or -0.014 0.081 0.027 0.021 0.003 -0.007 0.044
[1] 马建勇, 许吟隆, 潘婕. 东北地区农业气象灾害的趋势变化及其对粮食产量的影响. 中国农业气象, 2012, 33: 283-288.
Ma J Y, Xu Y L, Pan J. Analysis of agro-meteorological disasters tendency variation and the impacts on grain yield over Northeast China. Chin J Agron, 2012, 33: 283-288 (in Chinese with English abstract).
[2] 崔一鸣, 张明哲, 王禄禄, 宋佳, 毕伊红, 辛得, 李明鉴. 1966-2013年东北地区玉米低温冷害指数分析. 现代农业科技, 2018, (15):8-10.
Cui Y M, Zhang M Z, Wang L L, Song J, Bi Y H, Xin D, Li M J. Analysis on low temperature and chilling injury index of corn in Northeast China from 1966 to 2013. Mod Agric Sci Technol, 2018, (15):8-10 (in Chinese with English abstract).
[3] 郭建平, 马树庆. 农作物低温冷害监测预测理论和实践. 北京: 气象出版社, 2009. pp 26-27.
Guo J P, Ma S Q. Theory and Practice of Monitoring and Forecasting Crop Cold Damage. Beijing: Meteorological Press, 2009. pp 26-27(in Chinese).
[4] 王春乙, 毛飞. 东北地区低温冷害的分布特征. 见: 王春乙, 郭建平. 农作物低温冷害综合防御技术研究. 北京: 气象出版社, 1999. pp 9-15.
Wang C Y, Mao F. Distribution characteristics of low temperature and chilling damage in Northeast China. In: Wang C Y, Guo J P, eds. Research on Comprehensive Defense Technology of Crops Low Temperature and Chilling Injury. Beijing: Meteorological Press, 1999. pp 9-15(in Chinese).
[5] 马树庆, 刘玉英, 王琪. 玉米低温冷害动态评估和预测方法. 应用生态学报, 2006, 17: 1905-1910.
Ma S Q, Liu Y Y, Wang Q. Dynamic prediction and evaluation method of maize chilling damage. Chin J Appl Ecol, 2006, 17: 1905-1910 (in Chinese with English abstract).
[6] 李帅, 王晾晾, 陈莉, 姜丽霞, 张洪杰, 覃雪. 黑龙江省玉米低温冷害风险综合评估模型研究. 自然资源学报, 2013, 28: 635-645.
Li S, Wang L L, Chen L, Jiang L X, Zhang H J, Qin X. The comprehensive risk evaluation model of chilling injury to maize in Heilongjiang province. J Nat Res, 2013, 28: 635-645 (in Chinese with English abstract).
[7] 张方亮, 杨晓光. 东北三省春玉米生长季主要农业气象灾害特征分析. 见: 第十五届全国玉米栽培学术研讨会会议论文集. 北京: 中国作物学会, 2017. pp 115-117.
Zhang F L, Yang X G. Analysis on the characteristics of main agro-meteorological disasters in spring corn growing season in the three Northeast provinces. In: Proceedings of the 15th National Corn Cultivation Symposium. Beijing: Crop Science Society of China, 2017. pp 115-117(in Chinese).
[8] 陈振林, 张建平, 王春乙, 郑江平. 应用WOFOST模型模拟低温与干旱对玉米产量的综合影响. 中国农业气象, 2007, 28: 440-442.
Chen Z L, Zhang J P, Wang C Y, Zheng J P. Application of WOFOST model in simulation of integrated impacts of low temperature and drought on maize yield. Chin J Agrometeorol, 2007, 28: 440-442 (in Chinese with English abstract).
[9] 高晓容. 东北地区玉米主要气象灾害风险评估研究. 南京信息工程大学硕士论文, 江苏南京, 2012.
Gao X R. Study on the Risk Assessment of the Main Meteorological Disasters for Maize in Northeast China. MS Thesis of Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China, 2012 (in Chinese with English abstract).
[10] 杨若子, 周广胜. 东北三省玉米主要农业气象灾害综合危险性评估. 气象学报, 2015, 73: 1141-1153.
Yang R Z, Zhou G S. Comprehensive risk assessment of the main maize agro-meteorological disasters in the three provinces of Northeast China. Acta Meteorol Sin, 2015, 73: 1141-1153 (in Chinese with English abstract).
[11] 杨若子. 东北玉米主要农业气象灾害的时空特征与风险综合评估. 南京信息工程大学硕士论文, 江苏南京, 2015.
Yang R Z. Northeast China Maize Trend Yield Agrometeorological Disasters Risk Assessment. MS Thesis of Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China, 2015 (in Chinese with English abstract).
[12] 张琪, 丛鹏, 彭励. 通径分析在Excel和SPSS中的实现. 农业网络信息, 2007, (3):109-110.
Zhang Q, Cong P, Peng L. The realization of path analysis in Excel and SPSS. Agric Netw Inf, 2007, (3):109-110 (in Chinese with English abstract).
[13] 杜家菊, 陈志伟. 使用SPSS线性回归实现通径分析的方法. 生物学通报, 2010, 45(2):4-6.
Du J J, Chen Z W. Using SPSS linear regression to realize path analysis. Bull Biol, 2010, 45(2):4-6 (in Chinese with English abstract).
[14] 林德光. 通径分析法在腰果播种巾的应用——兼论通径分析的SAS实施. 热带作物学报, 2001, 22(3):34-39.
Lin D G. The application of path analysis method in cashew nut sowing towels and the SAS implementation of path analysis. Chin J Trop Crop, 2001, 22(3):34-39 (in Chinese with English abstract).
[15] 黄大辉, 彭懿紫, 黄天进, 蔡巨广, 莫永生, 曾超珍. 杂交水稻主要性状的多重逐步回归和通径分析. 广西农业生物科学, 2004, 23(2):100-103.
Huang D H, Peng Y Z, Huang T J, Cai J G, Mo Y S, Zeng C Z. Multiple stepwise regression and path analysis of the main characters of hybrid rice. Guangxi Agric Biol Sci, 2004, 23(2):100-103 (in Chinese with English abstract).
[16] 刘美含, 史海滨, 李仙岳, 闫建文, 孙伟, 窦旭. 河套灌区玉米农田蒸散动态变化及其影响因子的通径分析. 排灌机械工程学报, 2018, 36: 1081-1086.
Liu M H, Shi H B, Li X Y, Yan J W, Sun W, Dou X. Path analysis of dynamic changes of corn farmland evapotranspiration and its influencing factors in Hetao irrigation area. J Dra Irri Mach Eng, 2018, 36: 1081-1086 (in Chinese with English abstract).
[17] 袁志发, 周静芋, 郭满才, 雷雪芹, 解小莉. 决策系数——通径分析中的决策指标. 西北农林科技大学学报(自然科学版), 2001, 29(5):131-133.
Yuan Z F, Zhou J W, Guo M C, Lei X Q, Xie X L. Decision coefficient—the decision index in path analysis. J Northwest A&F Univ (Nat Sci Edn), 2001, 29(5):131-133 (in Chinese with English abstract).
[18] 王春乙, 张建平. 东北农作物冷害干旱并发影响评估. 见: 王春乙. 东北地区农作物低温冷害研究. 北京: 气象出版社, 2008. pp 163-173.
Wang C Y, Zhang J P. Evaluation on the concurrent effects of crop chilling injury and drought in Northeast China. In: Wang C Y, ed. Study on Chilling Injury of Crops in Northeast China. Beijing: Meteorological Press, 2008. pp 163-173(in Chinese).
[19] 张星, 郑有飞, 周乐照. 农业气象灾害灾情等级划分与年景评估. 生态学杂志, 2007, 26: 418-421.
Zhang X, Zheng Y F, Zhou L Z. Grade classification and annual case assessment of agro-meteorological disasters in Fujian province. Chin J Ecol, 2007, 26: 418-421 (in Chinese with English abstract).
[1] 陈松余, 丁一娟, 孙峻溟, 黄登文, 杨楠, 代雨涵, 万华方, 钱伟. 甘蓝型油菜BnCNGC基因家族鉴定及其在核盘菌侵染和PEG处理下的表达特性分析[J]. 作物学报, 2022, 48(6): 1357-1371.
[2] 王丹, 周宝元, 马玮, 葛均筑, 丁在松, 李从锋, 赵明. 长江中游双季玉米种植模式周年气候资源分配与利用特征[J]. 作物学报, 2022, 48(6): 1437-1450.
[3] 王旺年, 葛均筑, 杨海昌, 阴法庭, 黄太利, 蒯婕, 王晶, 汪波, 周广生, 傅廷栋. 大田作物在不同盐碱地的饲料价值评价[J]. 作物学报, 2022, 48(6): 1451-1462.
[4] 颜佳倩, 顾逸彪, 薛张逸, 周天阳, 葛芊芊, 张耗, 刘立军, 王志琴, 顾骏飞, 杨建昌, 周振玲, 徐大勇. 耐盐性不同水稻品种对盐胁迫的响应差异及其机制[J]. 作物学报, 2022, 48(6): 1463-1475.
[5] 杨欢, 周颖, 陈平, 杜青, 郑本川, 蒲甜, 温晶, 杨文钰, 雍太文. 玉米-豆科作物带状间套作对养分吸收利用及产量优势的影响[J]. 作物学报, 2022, 48(6): 1476-1487.
[6] 陈静, 任佰朝, 赵斌, 刘鹏, 张吉旺. 叶面喷施甜菜碱对不同播期夏玉米产量形成及抗氧化能力的调控[J]. 作物学报, 2022, 48(6): 1502-1515.
[7] 石艳艳, 马志花, 吴春花, 周永瑾, 李荣. 垄作沟覆地膜对旱地马铃薯光合特性及产量形成的影响[J]. 作物学报, 2022, 48(5): 1288-1297.
[8] 李阿立, 冯雅楠, 李萍, 张东升, 宗毓铮, 林文, 郝兴宇. 大豆叶片响应CO2浓度升高、干旱及其交互作用的转录组分析[J]. 作物学报, 2022, 48(5): 1103-1118.
[9] 王霞, 尹晓雨, 于晓明, 刘晓丹. 干旱锻炼对B73自交后代当代干旱胁迫记忆基因表达及其启动子区DNA甲基化的影响[J]. 作物学报, 2022, 48(5): 1191-1198.
[10] 闫晓宇, 郭文君, 秦都林, 王双磊, 聂军军, 赵娜, 祁杰, 宋宪亮, 毛丽丽, 孙学振. 滨海盐碱地棉花秸秆还田和深松对棉花干物质积累、养分吸收及产量的影响[J]. 作物学报, 2022, 48(5): 1235-1247.
[11] 柯健, 陈婷婷, 吴周, 朱铁忠, 孙杰, 何海兵, 尤翠翠, 朱德泉, 武立权. 沿江双季稻北缘区晚稻适宜品种类型及高产群体特征[J]. 作物学报, 2022, 48(4): 1005-1016.
[12] 李瑞东, 尹阳阳, 宋雯雯, 武婷婷, 孙石, 韩天富, 徐彩龙, 吴存祥, 胡水秀. 增密对不同分枝类型大豆品种同化物积累和产量的影响[J]. 作物学报, 2022, 48(4): 942-951.
[13] 王吕, 崔月贞, 吴玉红, 郝兴顺, 张春辉, 王俊义, 刘怡欣, 李小刚, 秦宇航. 绿肥稻秆协同还田下氮肥减量的增产和培肥短期效应[J]. 作物学报, 2022, 48(4): 952-961.
[14] 杜浩, 程玉汉, 李泰, 侯智红, 黎永力, 南海洋, 董利东, 刘宝辉, 程群. 利用Ln位点进行分子设计提高大豆单荚粒数[J]. 作物学报, 2022, 48(3): 565-571.
[15] 陈云, 李思宇, 朱安, 刘昆, 张亚军, 张耗, 顾骏飞, 张伟杨, 刘立军, 杨建昌. 播种量和穗肥施氮量对优质食味直播水稻产量和品质的影响[J]. 作物学报, 2022, 48(3): 656-666.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!