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干旱对太行山山前平原雨养农田产量影响的模拟研究
引用本文:王亚凯,刘孟雨,董宝娣,乔匀周,张明明,杨红,靳乐乐.干旱对太行山山前平原雨养农田产量影响的模拟研究[J].干旱地区农业研究,2019,37(2):185-194.
作者姓名:王亚凯  刘孟雨  董宝娣  乔匀周  张明明  杨红  靳乐乐
作者单位:中国科学院遗传与发育生物学研究所农业资源研究中心/河北省节水农业重点实验室/中国科学院农业水资源重点实验室,河北 石家庄050021;中国科学院大学,北京100049;中国科学院遗传与发育生物学研究所农业资源研究中心/河北省节水农业重点实验室/中国科学院农业水资源重点实验室,河北 石家庄,050021
基金项目:国家重点研发计划项目(2016YFD0300808);中国科学院科技服务网络计划(STS)项目(KFJ-STS-ZDTP-001);河北省重点研发计划项目(17227006D,18226419D)
摘    要:以多时间尺度标准化降水蒸散指数(SPEI)作为干旱指标,利用APSIM模型(农业生产系统模拟模型)模拟太行山山前平原雨养旱作农田冬小麦-夏玉米近30 a产量变化,分析干旱对作物产量的影响。结果显示:APSIM模型对模拟雨养条件下作物产量具有良好的适用性,玉米产量年际波动较大、变异系数为51.2%,易受降雨因素影响;小麦产量波动相对较为稳定,变异系数为26.4%。干旱指数与作物产量极显著相关(P<0.01),其中小麦产量与SPEI-3-Apr相关系数达0.79,玉米产量与SPEI-3-Sep相关系数达0.88,适宜干湿状态在0~2之间;所建立的回归方程分别可以解释61.8%的小麦产量变异和87.7%的玉米产量变异。研究表明,SPEI-3-Apr、SPEI-3-Sep可分别作为该地区雨养农田小麦、玉米产量的估计指标。

关 键 词:雨养农田  冬小麦-夏玉米产量模拟  标准化降水蒸散指数(SPEI)  APSIM模型

Simulation of drought impact on yield of rainfed wheat and maize in the Piedmont Plain of Mt. Taihang, China
WANG Ya-kai,LIU Meng-yu,DONG Bao-di,QIAO Yun-zhou,ZHANG Ming-ming,YANG Hong,JIN Le-le.Simulation of drought impact on yield of rainfed wheat and maize in the Piedmont Plain of Mt. Taihang, China[J].Agricultural Research in the Arid Areas,2019,37(2):185-194.
Authors:WANG Ya-kai  LIU Meng-yu  DONG Bao-di  QIAO Yun-zhou  ZHANG Ming-ming  YANG Hong  JIN Le-le
Institution:Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China; University of Chinese Academy of Sciences, Beijing 101400, China,Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China,Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China,Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China,Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China; University of Chinese Academy of Sciences, Beijing 101400, China,Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China; University of Chinese Academy of Sciences, Beijing 101400, China and Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/ Hebei Laboratory of Agricultural Water-Saving/Key Laboratory of Agricultural Water Resources, Shijiazhuang, Hebei 050021, China; University of Chinese Academy of Sciences, Beijing 101400, China
Abstract:The drought impacts on crop yield were analyzed through calculating multi-time scale standardized precipitation evapotranspiration index (SPEI). APSIM (Agricultural Production Systems Simulator) model was used to simulate about thirty-year yield data of winter wheat-summer maize in the double cropping system under rainfed conditions in Piedmont Plain of Mt. Taihang. The results showed that the APSIM model could reliably simulate wheat and maize yield under rainfed conditions. The maize yield was easily affected by rainfall, and yield fluctuation was relatively large with a variation coefficient of 51.2%. The fluctuation of wheat yield was relatively small with a variation coefficient of 26.4%. High correlation between SPEI and crop yield (P<0.01) was observed that the correlation coefficient was 0.79 between wheat yield and SPEI-3-Apr and 0.88 between maize yield and SPEI-3-Sep. The optimum SPEI values were between 0~2. The established regression equations could describe 61.8% and 87.7% of yield variability of winter wheat and summer maize, respectively. This study indicated that SPEI-3-Apr and SPEI-3-Sep could be optimal drought indices to estimate yields of winter wheat and summer maize under rainfed conditions in Piedmont Plain of Mt. Taihang China, respectively.
Keywords:rainfed farming  yield simulation of winter wheat-summer maize  SPEI  APSIM model
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