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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)

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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
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