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基于机器学习和未来气候变化模式的埃塞俄比亚粮食产量预测

徐宁 李发东 张秋英 艾治频 冷佩芳 舒旺 田超 李兆 陈刚 乔云峰

徐宁, 李发东, 张秋英, 艾治频, 冷佩芳, 舒旺, 田超, 李兆, 陈刚, 乔云峰. 基于机器学习和未来气候变化模式的埃塞俄比亚粮食产量预测[J]. 中国生态农业学报 (中英文), 2023, 31(0): 1−16 doi: 10.12357/cjea.20230257
引用本文: 徐宁, 李发东, 张秋英, 艾治频, 冷佩芳, 舒旺, 田超, 李兆, 陈刚, 乔云峰. 基于机器学习和未来气候变化模式的埃塞俄比亚粮食产量预测[J]. 中国生态农业学报 (中英文), 2023, 31(0): 1−16 doi: 10.12357/cjea.20230257
Xu N, Li F D, Zhang Q Y, Ai Z P, Leng P F, Shu W, Tian C, Li Z, Chen G, Qiao Y F. Crop yield prediction in Ethiopia based on machine learning under future climate scenarios[J]. Chinese Journal of Eco-Agriculture, 2023, 31(0): 1−16 doi: 10.12357/cjea.20230257
Citation: Xu N, Li F D, Zhang Q Y, Ai Z P, Leng P F, Shu W, Tian C, Li Z, Chen G, Qiao Y F. Crop yield prediction in Ethiopia based on machine learning under future climate scenarios[J]. Chinese Journal of Eco-Agriculture, 2023, 31(0): 1−16 doi: 10.12357/cjea.20230257

基于机器学习和未来气候变化模式的埃塞俄比亚粮食产量预测

doi: 10.12357/cjea.20230257
基金项目: 国家自然科学基金国际(地区)合作与交流项目(Y88X0100AE)
详细信息
    作者简介:

    徐宁, 研究方向为农业生态系统碳循环。E-mail: 18348271232@163.com

    通讯作者:

    乔云峰, 研究方向为水资源与水文学。E-mail: qiaoyf@igsnrr.ac.cn

  • 中图分类号: S562; S162.54

Crop yield prediction in Ethiopia based on machine learning under future climate scenarios

Funds: This study was supported by Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (Y88X0100AE).
More Information
  • 摘要: 对于以农业产业为支柱的埃塞俄比亚, 粮食供应和安全对国家安全和人民的生计尤为重要。由于作物生长和气候因素之间的复杂耦合关系, 预测气候变化对农作物产量影响具有较大难度, 机器学习技术则为预测这种复杂系统的变化提供了一种有效途径。本研究利用37个全球气候模式(GCM)的数据以及土壤数据, 基于机器学习模型, 预测了埃塞俄比亚2021年至2050年5种粮食作物在SSP126、SSP245和SSP585情景下的产量变化。在经过GCM和变量的筛选后, 利用梅赫季和贝尔格季中5种作物共10个产量数据对直方图梯度提升决策树、极端梯度提升随机森林、轻梯度提升决策树、随机森林、极限树以及K近邻6种机器学习模型进行训练。经过模型评估, 选择表现良好的3个模型并采用线性回归算法进行堆叠, 然后使用模型进行预测。研究结果表明, 埃塞俄比亚在未来30年间, 梅赫季各个作物的产量变化都以增产少于2 t·hm−2为主, 而在SSP126情景下的贝尔格季将出现更明显的产量减少, 这可能是由于温室效应的减缓降低了CO2的施肥效应。随着社会矛盾加剧和人类活动造成的生态环境恶化, 研究区的农业对改变粮食农业结构和重新分配生产力的需求不断增长, 导致农作物生产力向新的适宜地区转移。在SSP126和SSP585情景下, 研究区域将分别因为干旱情况的和温室效应加剧而获得更高的粮食作物生产力。
  • 图  1  埃塞俄比亚行政区划

    Figure  1.  Administrative division of Ethiopia

    图  2  37个GCM近地面气压变量(a)和近地面气温变量(b)的泰勒图

    ps 和tas分别表示近地面气压和近地面气温。ps and tas represent surface air pressure and near-surface air temperature, respectively. AE5: ACCESS-ESM1-5; AC11M: AWI-CM-1-1-MRAE11L: AWI-ESM-1-1-LR; BCM: BCC-CSM2-MR; BE: BCC-ESM1; CC0: CAMS-CSM1-0; CE: CanESM5; CE0: CAS-ESM2-0; CWF: CESM2-WACCM-FV2; C: CIESM; CCH: CMCC-CM2-HR4; CCS: CMCC-CM2-SR5; E11E: E3SM-1-1-ECA; EE: EC-Earth3; EEV: EC-Earth3-Veg; EEVL: EC-Earth3-Veg-LR; FE20: FIO-ESM-2-0; GE: GFDL-ESM4; GE1G: GISS-E2-1-G; GE1H: GISS-E2-1-H: ; IE: IITM-ESM; IC8: INM-CM4-8; IC0: INM-CM5-0; ICL: IPSL-CM6A-LR; K10G: KACE-1-0-G; M: MIROC6; ME12H: MPI-ESM-1-2-HAM; ME2H: MPI-ESM1-2-HR; ME2L: MPI-ESM1-2-LR; ME0: MRI-ESM2-0; N: NESM3; NC: NorCPM1; NL: NorESM2-LM; NM: NorESM2-MM; S U: SAM0-UNICON; TE: TaiESM1)

    Figure  2.  Taylor diagram of surface air pressure (a) and near-surface air temperature (b) for 37 GCM

    图  3  14个变量和5种梅赫季作物产量的斯皮尔曼相关性热图

    huss: 近地面比湿度 Near-Surface specific humidity; pr: 降水量 Precipitation; ps: 近地面气压 Surface air pressure; rsds: 地面下行短波辐射量 Surface downwelling shortwave radiation; tas: 近地面气温 Near-Surface air temperature; tasmax: 近地面日最高气温 Daily maximum near-Surface air temperature; tasmin: 近地面日最低气温 Daily minimum near-Surface air temperature; uas: 近地面东向风速 Eastward near-Surface wind; vas: 近地面北向风速 Northward near-Surface wind; tn: 总氮 Total nitrogen; bd: 容重 Bulk density; cec: 阳离子交换量 Cation exchange capacity; soc: 土壤有机碳 Soil organic content; ph: pH; b_m: 大麦(梅赫季) Barley (Meher Season); w_m: 小麦(梅赫季) Wheat (Meher Season); m_m: 玉米(梅赫季) Maize (Meher Season); s_m: 高粱(梅赫季) Sorghum (Meher Season); t_m: 苔麸(梅赫季) Teff (Meher Season)。

    Figure  3.  Spearman correlation heat map with 14 variables and yield of 5 crops in Meher season

    图  4  埃塞俄比亚5种粮食作物2020年产量(统计数据)

    Figure  4.  Yield of 5 staple crops in 2020 in Ethiopia (statistical data)

    图  5  埃塞俄比亚五种作物1995~2020年间产量变化(统计数据)

    Figure  5.  Changes of yield of 5 crops in Ethiopia from 1995 to 2020 (statistical data)

    图  6  2021—2050年SSP126、SSP245、SSP585情景下梅赫季粮食作物产量变化量

    Figure  6.  Yield changes of 5 crops under SSP126, SSP245 and SSP585 scenarios in Meher season from 2021 to 2050

    图  7  2021-2050年SSP126、SSP245、SSP585情景下贝尔格季粮食作物产量变化量

    Figure  7.  Yield changes of 4 crops under SSP126, SSP245 and SSP585 scenarios in Belg season from 2021 to 2050

    表  1  研究初步选用的未来气候变化模式气候参数列表及信息

    Table  1.   List and information of preliminarily selected GCM variables

    名称 Variable name代号 Alias单位Unit
    近地面比湿度 Near-Surface specific humidityhuss1
    降水量 Precipitationprkg∙m−2∙s−1
    近地面气压 Surface air pressurepsPa
    地面下行短波辐射量 Surface downwelling shortwave radiationrsdsW∙m−2
    近地面气温 Near-Surface air temperaturetasK
    近地面日最高气温 Daily maximum near-Surface air temperaturetasmaxK
    近地面日最低气温 Daily minimum near-Surface air temperaturetasminK
    近地面东向风速 Eastward near-Surface winduasm∙s−1
    近地面北向风速 Northward near-Surface windvasm∙s−1
    下载: 导出CSV

    表  2  6种模型的模拟表现

    Table  2.   Prediction performance of 6 different models

    模型名称
    Model name
    判决系数
    Coefficient of Determination, R2
    平均绝对误差
    Mean Absolute Error, MAE
    解释方差评分
    Explained Variance Score, EVS
    直方图梯度提升
    Histogram Gradient Boosting (HGB)
    0.512.330.38
    极端梯度提升随机森林
    Extreme Gradient Boosting Random Forest (XGBRF)
    0.743.020.69
    轻梯度提升
    Light Gradient Boosting Machine (LGBM)
    0.648.240.68
    随机森林 Random Forest (RF)0.693.640.65
    极限树 Extra Trees (ET)0.671.650.59
    K近邻 K-Neighbors0.555.650.42
    下载: 导出CSV

    表  3  最终模型对不同作物的模拟表现

    Table  3.   Prediction performance of the stacked model for different crops

    作物种类
    Crop type
    判决系数
    (Coefficient of Determination, R2)
    平均绝对误差
    (Mean Absolute Error, MAE)
    解释方差评分
    (Explained Variance Score, EVS)
    苔麸(梅赫季)
    Teff (Meher Season)
    0.762.350.64
    玉米(梅赫季)
    Maize (Meher Season)
    0.881.220.91
    小麦(梅赫季)
    Wheat (Meher Season)
    0.822.460.71
    大麦(梅赫季)
    Barley (Meher Season)
    0.733.150.72
    高粱(梅赫季)
    Sorghum (Meher Season)
    0.714.30.75
    苔麸(贝尔格季)
    Teff (Belg Season)
    0.604.570.55
    玉米(贝尔格季)
    Maize (Belg Season)
    0.674.690.56
    小麦(贝尔格季)
    Wheat (Belg Season)
    0.624.250.60
    大麦(贝尔格季)
    Barley (Belg Season)
    0.3119.530.12
    高粱(贝尔格季)
    Sorghun (Belg Season)
    0.595.800.58
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-05-11
  • 录用日期:  2023-07-08
  • 修回日期:  2023-08-12
  • 网络出版日期:  2023-08-14

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