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生态学杂志 ›› 2021, Vol. 40 ›› Issue (4): 1146-1153.doi: 10.13292/j.1000-4890.202104.031

• 研究报告 • 上一篇    下一篇

基于灾害指数的奉化水蜜桃气象产量模拟

丁烨毅1,杨栋1*,朱佳敏2,陈妙金3,李从初1,魏莎莎4,徐红霞5   

  1. 1宁波市气象局, 浙江宁波 315012; 2北仑区气象局, 浙江北仑 315211; 3奉化区水蜜桃研究所, 浙江奉化 315500;4慈溪市农业技术推广中心, 浙江慈溪 315300; 5浙江省农业科学院, 杭州 310021)
  • 出版日期:2021-04-10 发布日期:2021-04-14

Climate yield simulation of juicy peach in Fenghua based on disaster index.

DING Ye-yi1, YANG Dong1*, ZHU Jia-min2, CHEN Miao-jin3, LI Cong-chu1, WEI Sha-sha4, XU Hong-xia5   

  1. (1Ningbo Bureau of Meteorology, Ningbo 315012, Zhejiang, China; 2Beilun DistrictMeteorological Bureau, Ningbo 315211, Zhejiang, China; 3Institute of Fenghua Honeypeach, Fenghua 315500, Zhejiang, China; 4Cixi Agricultural Technology Extension Center, Cixi 315300, Zhejiang, China; 5Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China).
  • Online:2021-04-10 Published:2021-04-14

摘要: 气象产量模拟是保险产品设计及气象为农服务效益评估的重要环节。基于1995—2018年奉化水蜜桃单产数据,采用傅里叶变换、滑动平均、Logistic、HP滤波和指数法对水蜜桃趋势产量和气象产量进行分离;建立水蜜桃常见气象灾害指数,并利用气象灾害指数对5种产量分离结果进行验证和筛选;以灾害指数为输入因子,利用基于遗传算法的BP神经网络(BP neural network based on genetic algorithm,GA-BP)方法建立水蜜桃气象产量模型。结果表明:受气候变化影响,1995—2018年奉化水蜜桃开花—成熟期连阴雨和硬核—成熟期强降水呈先降后升,近年来极端性降水概率增强,大风出现频率增大;气候变暖一定程度缓解开花坐果期低温,但成熟期高温风险加大;3阶傅里叶分离的趋势产量模拟效果佳,对典型灾害年和低灾害年模拟准确率为88%,相关系数为-0.8,综合指数为0.85;基于灾害指数建立的GABP模型对3阶傅里叶方法分离的相对气象产量模拟效果最佳;回代检验的绝对误差和均方根误差分别为0.02和0.03,相关系数为0.95;预报检验的绝对误差和均方根误差分别为0.03和0.04,相关系数为0.92。综上可见,3阶傅里叶方法适用于奉化地区水蜜桃产量分离,基于灾害指数构建的特色作物产量模拟精度和稳定性较高,且模型物理意义明确。

关键词: 水蜜桃, 灾害指数, 产量分离, GA-BP, 产量模拟

Abstract: Climate yield simulation is critical to the insurance design and benefit evaluation of meteorological service for agriculture. Based on the peach yield data in Fenghua from 1995 to 2018, Fourier transform, moving average, Logistic, HP filter and exponent methods were used to separate the trend yield and climate yield of juicy peach. The common meteorological disaster index of juicy peach was established, which was used to verify and screen the yield separation results with five different methods. With the disaster index as the input factor, the climate yield model of peach was established by BP neural network based on genetic algorithm (GA-BP). The results showed that, from 1995 to 2018, the continuous rain during blossommature period and heavy precipitation during stone hardeningmature stage of Fenghua juicy peach decreased first and then increased. In recent years, the frequency of extreme precipitation and gale increased. Climate warming alleviated the chilling damage in flowering and fruit setting stage, but increased the risk of high temperature in mature stage. The simulation effect of trend yield by the third-order Fourier separation was good. The simulation accuracy of typical disaster years and low disaster years was as high as 88%, with a correlation coefficient of -0.8 and a comprehensive index of0.85. The GABP model based on the disaster index had the best simulation effect on the relative climate yield separated by the thirdorder Fourier method. The absolute error and root mean square error of the back-testing were 0.02 and 0.03, respectively, with the correlation coefficient being as high as 0.95. The absolute error and root mean square error of prediction test were 0.03 and 0.04, respectively, with the correlation coefficient being as high as 0.92. In conclusion, the thirdorder Fourier method was suitable for peach yield separation in Fenghua. The simulation accuracy and stability of characteristic crop yield based on disaster index were higher, with clear physical meaning of the model.

Key words: juicy peach, disaster index, yield separation, GA-BP method, yield simulation.