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气候变化对关中地区粮食产量的影响及趋势分析

本站小编 Free考研考试/2022-01-01
赵茹欣,
王会肖,,
董宇轩
北京师范大学水科学研究院/城市水循环及海绵城市技术北京市重点实验室 北京 100875
基金项目: 国家自然科学基金项目41371043
国家自然科学基金项目51779009

详细信息
作者简介:赵茹欣, 研究方向为水文水资源及气候变化。E-mail:zhaorx324@163.com
通讯作者:王会肖, 主要研究方向为农业水文水资源。E-mail:huixiaowang@bnu.edu.cn
中图分类号:S162.5+3

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收稿日期:2019-10-25
录用日期:2020-02-01
刊出日期:2020-04-01

Impact of climate change on grain yield and its trend across Guanzhong region

ZHAO Ruxin,
WANG Huixiao,,
DONG Yuxuan
College of Water Sciences, Beijing Normal University/Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China
Funds: the National Natural Science Foundation of China41371043
the National Natural Science Foundation of China51779009

More Information
Corresponding author:WANG Huixiao, E-mail:huixiaowang@bnu.edu.cn


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摘要
摘要:以增温为主的气候变化对粮食产量具有显著影响。本文利用关中地区1983—2016年的站点气象要素、粮食产量统计数据和跨部门影响模型比较计划（Intersectoral Impact Model Intercomparison Project，ISIMIP）中4个全球气候模式2021—2050年降水、气温输出结果，采用突变分析、趋势分析和敏感性分析等方法，从粮食单产、气候产量和气候生产潜力等方面系统分析了我国主要粮食产地之一的陕西关中粮食产量对气候变化的响应特征。结果表明：1）1983—2016年，关中地区年平均气温呈显著上升趋势，升温速率为0.05℃·a-1（P < 0.01），其中，最高气温的上升起主要作用；年降水量则以-1 mm·a-1的速率呈下降趋势，但不显著。2）关中地区多年平均粮食单产为3 599 kg·hm-2，且逐年波动上升，速率为57.17 kg·hm-2·a-1（P < 0.001）。关中多地的气候产量与气温呈正相关，气温的升高一定程度上促进了关中气候产量的增加，但并不显著（平均增加率为0.85 kg·hm-2·a-1）。渭河关中地区多年以来的气候生产潜力为7 000~12 000 kg·hm-2，受气温波动的影响，1995年后的平均气候生产潜力高于1995年之前，是整个研究时段气候生产潜力呈现增加趋势的主要时期。3）未来30年里（2021—2050年），关中地区在RCP2.6情景下的平均气候生产潜力略高于RCP6.0情景，但前者的生产潜力呈逐年下降趋势，后者则表现出逐年上升趋势。关中地区的作物对气候资源的利用空间还很大，且气候变化对关中粮食产量具有促进作用，但此正向作用并不是持续不变的。
关键词:气候变化/
粮食产量/
气候生产潜力/
全球气候模式/
关中地区
Abstract:Climate change dominated by warming has a significant impact on grain yield. From an examination of grain yield, climatic yield and climate potential productivity (CPP), this paper systematically analyzed the response of grain yield to climate change in Guanzhong, Shaanxi, one of China's main food-producing areas. Datasets were climate variables at 8 meteorological stations, grain yield statistics from Guanzhong region during 1983-2016, and the precipitation and temperature simulation results from 4 global climate models of the Intersectoral Impact Model Intercomparison Project for 2021-2050. Mutation analysis, trend analysis, and sensitivity analysis were all used in the study. The results showed that the annual average temperature of Guanzhong region was increasing significantly at the rate of 0.05 ℃·a-1, and a significant increase in the maximum temperature was contributing most to this trend. Meanwhile, annual average precipitation showed a decreasing trend at the rate of -1 mm·a-1 but was not significant. During 1983-2016, the average annual grain yield of Guanzhong region was 3 599 kg·hm-2. Although showing fluctuations, it increased at the rate of 57.17 kg·hm-2·a-1 (P < 0.001). There was a positive correlation between the climatic yield and temperature in many parts of Guanzhong. The increase in temperature had promoted an increase in climatic yield in Guanzhong to a certain extent, but not significantly (the increase was 0.85 kg·hm-2·a-1 and P>0.05). The CPP of Guanzhong region ranged between 7 000-12 000 kg·hm-2 over 34 years. Due to the fluctuations in temperature, the average CPP after 1995 was higher than that before 1995, which meant that the change in CPP after 1995 was the main driving source of the increasing trend of CPP during the whole study period. During 2021-2050, the average CPP of Guanzhong region under RCP 2.6 scenario will be higher than that of RCP 6.0. However, the CPP decreases under the RCP 2.6 scenario but increases under the RCP 6.0 scenario. There is a plenty room for promotion of climate resources used by crops in Guanzhong region, and climate change has had a positive effect on the grain yield in Guanzhong, but this effect will not persist.
Key words:Climate change/
Grain yield/
Climate potential productivity/
Global climate model/
Guanzhong region

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图1关中地区及气象站点和格点地理位置
Figure1.Location of Guanzhong region, weather stations and grids


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图21983—2016年关中地区气候要素随时间变化特征
Figure2.Changes of climate variables of Guanzhong region from 1983 to 2016


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图31983—2016年关中地区粮食单产及气候产量随时间变化曲线
Figure3.Variation curves of grain yield and climate yield in Guanzhong region from 1983 to 2016


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图4关中地区各市气候要素与气候产量的相关性
Figure4.Correlation between climate variables and climate yield in each city of Guanzhong region


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图51983—2016年关中气候生产潜力及气候资源利用率的变化
Figure5.Changes of climate potential productivity and climate resource utilization rate in Guanzhong region from 1983 to 2016


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图6关中地区各市气候生产潜力对气温和降雨的敏感性及其相互关系
St:对气温的敏感系数; Sp:对降雨的敏感系数。
Figure6.Sensitivity of climate potential productivity to temperature and precipitation and their correlation in each city of Guanzhong region
St: sensitivity coefficient to temperature; Sp: sensitivity coefficient to precipitation.


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图7关中地区气温(a, b)和降水(c, d)的不同气候模式历史模拟序列与观测数据的比较
图a和图c为一元线性回归拟合系数。
Figure7.Comparison between historical simulation results by different climate models and observed data of temperature (a, b) and precipitation (c, d) in Guanzhong region
Figure a and c show fitting coefficients of linear equations.


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图8RCP2.6和RCP6.0情景下关中地区未来气候生产潜力的空间分布
Figure8.Spatial distribution of future climate potential productivity in Guanzhong region under RCP2.6 and RCP6.0 scenarios


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图9RCP2.6和RCP6.0情景下关中地区未来气候生产潜力的时间变化
Figure9.Time variation of future climate potential productivity in Guanzhong region under RCP2.6 and RCP6.0 scenarios


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表1关中地区气象站点信息
Table1.Information of weather stations of Guanzhong region
序号
No.		站台号
Station number		站名
Station name		纬度
Latitude (°N)		经度
Longitude (°E)		高程
Elevation (m)
S153929长武Changwu35.20107.801 206.5
S253948蒲城Pucheng34.95109.58499.2
S357025凤翔Fengxiang34.52107.38781.1
S457028太白Taibai34.03107.321 543.6
S557030永寿Yongshou34.70108.15994.6
S657034武功Wugong34.25108.22447.8
S757037耀县Yaoxian34.93108.98710.0
S857048秦都Qindu34.40108.72472.8


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表24个全球气候模式的相关信息统计表
Table2.Descriptions of the 4 global circulation models used in this study
模式名称
Model name		机构缩写
Institute acronyms		机构全称
Institute full name
GFDL-ESM2MNOAA GFDL美国国家海洋与大气管理局和美国地球物理流体动力学实验室
National Oceanic and Atmospheric Administration, U.S. Department of Commerce; U.S. Geophysical Fluid Dynamics Laboratory
HadGEM2-ESMOHC (additional realizations by INPE)英国气象局哈德利中心和西班牙国家气象局
Met Office Hadley Centre and Instituto Nacional de Pesquisas Espaciais
IPSL-CAM5-LRIPSL法国皮埃尔西蒙拉普拉斯研究所
Institute Pierre-Simon Laplace
MIROC5MIROC日本海洋与地球科学技术厅、大气和海洋研究所(东京大学)和国家环境研究所
Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (University of Tokyo), and National Institute for Environmental Studies


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表31983—2016年关中地区各气象要素的变化趋势及显著性
Table3.Trends and significance of climate variables of Guanzhong region from 1983 to 2016
平均气温
Mean temperature
(℃?a–1)		降水
Precipitation
(mm?a–1)		最高气温
Maximum temperature
(℃?a–1)		最低气温
Minimum temperature
(℃?a–1)		日照时数
Sunshine duration
(h?a–1)		积温(≥10 ℃)
Accumulated temperature
(≥10 ℃) (℃?a–1)
趋势Trend0.046**–1.0110.055**0.048**1.1416.00**
**表示通过P < 0.01显著性检验。** represents significance at P < 0.01


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表41983—2016年关中地区各市气候要素变化特征
Table4.Spatial characteristics of climate variables in each city of Guanzhong region from 1983 to 2016
城市City平均气温Mean temperature降水Precipitation日照时数Sunshine duration
平均值
Mean (℃)		趋势
Trend (℃?a–1)		突变年份
Abrupt year		平均值
Mean (mm)		趋势
Trend (mm?a–1)		突变年份
Abrupt year		平均值
Mean (h)		趋势
Trend (h?a–1)		突变年份
Abrupt year
西安Xi’an13.570.03**1992589.65-0.5820051 744.94-1.321997
铜川Tongchuan12.830.04**1993537.68-1.1120062 203.120.68
宝鸡Baoji10.470.05**1995626.61-0.4220031 925.531.071999
咸阳Xianyang11.940.04**1994563.57-0.5920092 011.744.001990
渭南Weinan14.020.07**1995511.58-2.352 199.821.27
**表示通过P < 0.01显著性检验。** represents significance at P < 0.01


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表51983—2016年关中地区各市的作物产量变化趋势
Table5.Trend of grain yield in each city of Guanzhong region from 1983 to 2016
城市City粮食单产Grain yield气候产量Climate yield
均值
Mean (kg?hm–2)		趋势
Trend (kg?hm–2?a–1)		均值
Mean (kg?hm–2)		趋势
Trend (kg?hm–2?a–1)
西安Xi’an4 21763.15***7.321.67
铜川Tongchuan2 96169.21***321.978.98*
宝鸡Baoji3 50565.84***-13.981.60
咸阳Xianyang3 94965.82***428.889.51*
渭南Weinan3 37253.99***166.625.81
*和***分别表示趋势在P < 0.05和P < 0.001水平显著。* and *** represent significant trends at P < 0.05 and P < 0.001 levels, respectively.


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表61983—2016年关中地区各市气候生产潜力在不同时间段的变化趋势及显著性
Table6.Trend and significance of climate potential productivity in each city of Guanzhong region at different periods from 1983 to 2016
城市
City		1983—19951996—20161983—2016
均值
Mean (kg·hm-2)		趋势
Trend (kg·hm-2·a-1)		均值
Mean (kg·hm-2)		趋势
Trend (kg·hm-2·a-1)		均值
Mean (kg·hm-2)		趋势
Trend (kg·hm-2·a-1)
关中Guanzhong9 809-143.38*10 02530.429 9428.16
西安Xi’an10 036-199.87*10 23153.2110 1569.55
铜川Tongchuan9 769-156.289 9568.459 8841.11
宝鸡Baoji9 932-68.6810 14030.1110 06011.94
咸阳Xianyang9 753-173.33*10 01939.689 91710.78
渭南Weinan9 830-160.079 88715.979 865-2.80
*表示趋势在P < 0.05水平显著。* represents significant trend at P < 0.05 level.


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