赵俊芳2,,,
徐慧2,
徐精文1
1.四川农业大学资源学院 成都 611130
2.中国气象科学研究院灾害天气国家重点实验室 北京 100081
基金项目: 中国气象科学研究院基本科研业务费专项2017R001
国家重点研发计划项目2017YFA0603004
详细信息
作者简介:孔祥娜, 主要从事农业气象、病虫害识别等研究。E-mail:1263321300@qq.com
通讯作者:赵俊芳, 主要从事农业气象、全球变化、碳循环等研究。E-mail:zhaojfcams@163.com
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出版历程
收稿日期:2018-12-10
录用日期:2019-03-13
刊出日期:2019-07-01
Assessment of the direct radiation effect of atmospheric aerosol on maize yield in China by using APSIM model
KONG Xiangna1, 2,,ZHAO Junfang2,,,
XU Hui2,
XU Jingwen1
1. College of Resources, Sichuan Agricultural University, Chengdu 611130, China
2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
Funds: the Basic Research Funds-regular of Chinese Academy of Meteorological Sciences2017R001
the National Key Research and Development Program of China2017YFA0603004
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Corresponding author:ZHAO Junfang, E-mail: zhaojfcams@163.com
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摘要
摘要:在大气气溶胶污染日益严重的时代背景下，气溶胶对农作物生长发育的影响越来越不可忽视。本文以全球气溶胶监测网（AErosol RObotic NETwork，AERONET）中具有常年观测数据的我国北京、香河和太湖为研究站点，利用AERONET多年观测资料以及MODIS地表反照率数据，借助6S（Second Simulation of a Satellite Signal in the Solar Spectrum）辐射传输模式，计算出2001-2014年研究站点的气溶胶直接辐射效应，评估了APSIM（Agricultural Production Systems Simulator）作物模型的适用性，运用验证适用的APSIM模型分析了气溶胶直接辐射效应对我国玉米产量的影响。结果表明：1）验证后的APSIM玉米模型在我国北京、香河和太湖玉米产区具有较好的适用性。APSIM模型在模拟玉米的发育期以及产量中的模拟结果较好，其中各站点产量的相对均方根误差（NRMSE）为1.55%~6.24%，一致性指标（D）为0.80~0.99，决定系数（R2）为0.75~1.00。2）气溶胶使得太阳直接辐射降低；降低的趋势主要受气溶胶的净辐射通量的影响。2001-2014年期间北京、香河和太湖总辐射量分别降低31.95%、14.74%和28.30%。3）气溶胶直接辐射效应造成玉米减产。2001-2014年期间气溶胶直接辐射效应使得北京、香河和太湖玉米产量分别减少28.44%、14.89%和13.43%。总体来说，2001-2014年期间大气气溶胶直接辐射效应使得我国北京、香河和太湖3个高污染区的玉米产量减少13.43%~28.44%。
关键词:气溶胶/
直接辐射效应/
玉米产量/
APSIM模型/
6S辐射传输模式
Abstract:Owing to the increasingly serious atmospheric aerosol pollution, the impact of aerosols on the growth and development of crops can no longer be ignored. In this paper, the Beijing, Xianghe, and Taihu stations in China with perennial observation data in global aerosol monitoring network (AErosol RObotic NETwork, AERONET) were used as the research stations. Based on the AERONET data, MODIS surface albedo data and the 6S (Second Simulation of a Satellite Signal in the Solar Spectrum) radiation transfer model, the effects of aerosol direct radiation at three research stations from 2001 to 2014 were calculated. Then, the applicability of the APSIM (Agricultural Production Systems Simulator) model was evaluated, and the impacts of direct aerosol radiation on maize yield in China were analyzed by using the APSIM model. The results showed that:1) the verified APSIM maize model had good applicability in the maize producing areas of Beijing, Xianghe, and Taihu in China. The results of APSIM model were a better simulation of the developmental stages and the yield of maize, in which normalized root mean square error (NRMSE), coincidence indicator (D), and determinate coefficient (R2) were 1.55%-6.24%, 0.80-0.99, and 0.75-1.00, respectively. 2) Aerosols reduced direct solar radiation, and the decreasing trend was mainly affected by the net radiation flux of aerosols. The total solar radiation of Beijing, Xianghe, and Taihu stations reduced by 31.95%, 14.74% and 28.30%, respectively, from 2001 to 2014. 3) The direct radiation effect of aerosols caused a reduction in maize yield. The maize yields of the Beijing, Xianghe, and Taihu stations, caused by the direct radiation effect of aerosols, were reduced by 28.44%, 14.89%, and 13.43%, respectively, from 2001 to 2014. In general, because of the direct radiation effects of atmospheric aerosols, the maize yields from 2001 to 2014 were reduced by 13.43%-28.44% in three highly polluted areas (Beijing, Xianghe, and Taihu) in China.
Key words:Aerosol/
Direct radiation effect/
Maize yield/
APSIM model/
6S radiation transfer model
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图1研究站点分布
Figure1.Locations of the research stations
下载: 全尺寸图片幻灯片
图23个研究站点玉米发育期、产量实测值和模拟值结果对比
Figure2.Comparison between measured and simulated phenology and yield of maize at three stations
下载: 全尺寸图片幻灯片
图3北京(a)、香河(b)和太湖(c)研究站点的气溶胶直接辐射效应
Figure3.Direct radiation effects of aerosol in stations of Beijing (a), Xianghe (b) and Taihu (c)
下载: 全尺寸图片幻灯片
图4北京(a)、香河(b)和太湖(c)研究站点有无气溶胶直接辐射效应下玉米产量的变化
Figure4.Changes in maize yield with or without effect of direct aerosol radiation at stations of Beijing (a), Xianghe (b) and Taihu (c)
下载: 全尺寸图片幻灯片表1研究区域相关的全球气溶胶监测网(AERONET)站点信息
Table1.Information of stations of AErosol RObotic NETwork relative to the study areas
| 站点 Station | 经度 Longitude | 纬度 Latitude | 海拔 Altitude (m) | 观测时段(年-月) Observation period (year-month) |
| 北京 Beijing | 116.38°E | 39.98°N | 92 | 2001-03—2016-12 |
| 香河 Xianghe | 116.96°E | 39.75°N | 36 | 2001-03—2016-12 |
| 太湖 Taihu | 120.22°E | 31.42°N | 20 | 2005-09—2016-08 |
下载: 导出CSV表23个研究站点玉米的APSIM参数
Table2.Parameters of APSIM for maize at the three stations
| 站点 Station | 出苗到营养生长期结束所需积温 Accumulated temperature from emergence to end of vegetative growth period (℃·d) | 开花到成熟所需积温 Accumulated temperature from flowering to maturity (℃·d) | 最大穗粒数 Maximum grain numbers per head | 灌浆速率 Grain filling rate (g·d-1) | 光周期斜率 Photoperiods slope (℃·h-1) |
| 北京 Beijing | 130 | 625 | 800 | 10.5 | 5 |
| 香河 Xianghe | 145 | 600 | 850 | 9.5 | 5 |
| 太湖 Taihu | 180 | 1 000 | 850 | 9.4 | 7 |
下载: 导出CSV表3APSIM模型在3个研究站点对玉米生育期和产量模拟的验证结果
Table3.Verification results of APSIM model for maize growth period and yield at three stations
| 站点 Station | 项目 Item | 验证评价指标 Validation index | ||||
| RMSE | D | MAE | NRMSE (%) | R2 | ||
| 北京 Beijing | 播种到出苗天数 Days from sowing to emergence | 1.15 | 0.65 | 0.67 | 15.06 | 0.57 |
| 播种到开花天数 Days from sowing to flowering | 1.83 | 0.70 | 1.33 | 3.49 | 0.99 | |
| 播种到成熟天数 Days from sowing to maturity | 0.82 | 0.88 | 0.67 | 0.90 | 0.89 | |
| 产量 Yield | 226.48 | 0.80 | 216.68 | 3.62 | 0.75 | |
| 香河 Xianghe | 播种到出苗天数 Days from sowing to emergence | 0.00 | 1.00 | 0.00 | 0.00 | 1.00 |
| 播种到开花天数 Days from sowing to flowering | 1.73 | 0.66 | 1.67 | 3.37 | 1.00 | |
| 播种到成熟天数 Days from sowing to maturity | 1.91 | 0.74 | 1.67 | 1.95 | 0.43 | |
| 产量 Yield | 479.15 | 0.85 | 379.00 | 6.24 | 0.90 | |
| 太湖 Taihu | 播种到出苗天数 Days from sowing to emergence | 1.83 | 0.91 | 1.33 | 10.33 | 0.96 |
| 播种到开花天数 Days from sowing to flowering | 1.73 | 0.83 | 1.67 | 2.11 | 0.62 | |
| 播种到成熟天数 Days from sowing to maturity | 2.94 | 0.52 | 2.67 | 2.31 | 0.85 | |
| 产量 Yield | 113.37 | 0.99 | 79.07 | 1.55 | 1.00 | |
| RMSE:均方根误差; D:一致性指标; MAE:平均绝对误差; NRMSE:相对均方根误差; R2:决定系数。RMSE: root mean square error; D: coincidence indicator; MAE: mean absolute error; NRMSE: normalized root mean square error; R2: determinate coefficient. | ||||||
下载: 导出CSV表43个研究站点在气溶胶影响下的太阳辐射和玉米产量变化
Table4.Changes in solar radiation and maize yield caused by aerosols in three stations
| 站点 Station | 年份 Year | 气溶胶直接辐射变化 Change of aerosol direct radiation | 玉米产量变化 Change of maize yield | |||
| 辐射量 Radiation (W·m-2) | 变化率 Change rate (%) | 产量 Yield (kg·hm-2) | 变化率 Change rate (%) | |||
| 北京 Beijing | 2002 | -194.11 | -29.65 | -2 089.80 | -23.02 | |
| 2003 | -238.46 | -36.34 | -2 497.70 | -31.10 | ||
| 2004 | -167.53 | -25.45 | -1 274.50 | -15.02 | ||
| 2005 | -96.00 | -14.29 | -1 486.70 | -18.56 | ||
| 2006 | -249.97 | -38.07 | -3 307.40 | -35.39 | ||
| 2007 | -265.52 | -40.56 | -3 376.70 | -36.63 | ||
| 2008 | -216.07 | -32.95 | -2 211.30 | -27.91 | ||
| 2009 | -217.95 | -33.21 | -3 371.20 | -34.71 | ||
| 2010 | -226.00 | -34.44 | -2 843.80 | -33.12 | ||
| 2011 | -229.14 | -34.91 | -3 262.80 | -33.58 | ||
| 2012 | -199.42 | -30.63 | -474.70 | -26.80 | ||
| 2013 | -220.67 | -3.63 | -2 760.00 | -31.45 | ||
| 2014 | -204.29 | -31.22 | -1 627.50 | -22.38 | ||
| 香河 Xianghe | 2005 | -204.91 | -32.96 | -2 253.20 | -23.26 | |
| 2006 | -126.33 | -20.32 | -111.30 | -1.46 | ||
| 2007 | -37.75 | -6.08 | -1 118.50 | -13.54 | ||
| 2008 | -180.26 | -28.99 | -3 284.30 | -32.36 | ||
| 2009 | -131.95 | -21.22 | -711.90 | -8.53 | ||
| 2010 | -75.46 | -12.13 | -650.20 | -8.11 | ||
| 2011 | -53.47 | -8.60 | -1 097.00 | -11.29 | ||
| 2012 | -43.03 | -6.92 | -834.60 | -9.46 | ||
| 2013 | -48.29 | -7.77 | -1 354.50 | -15.87 | ||
| 2014 | -18.23 | -2.93 | -591.20 | -8.13 | ||
| 太湖 Taihu | 2006 | -232.74 | -27.06 | -918.80 | -11.81 | |
| 2007 | -275.19 | -31.94 | -1 479.90 | -17.33 | ||
| 2008 | -255.10 | -29.60 | -1 286.70 | -15.16 | ||
| 2009 | -257.43 | -29.73 | -1 385.30 | -15.08 | ||
| 2010 | -193.26 | -22.63 | -1 741.90 | -18.99 | ||
| 2011 | -271.09 | -1.72 | -1 558.00 | -17.00 | ||
| 2012 | -218.83 | -25.45 | -770.30 | -8.84 | ||
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