中国农业气象 ›› 2022, Vol. 43 ›› Issue (09): 732-748.doi: 10.3969/j.issn.1000-6362.2022.09.005

• 农业生物气象栏目 • 上一篇    下一篇

基于多因素模型重构陕西苹果主要物候数据序列

张晓男,刘布春,刘园,贺金娜,刘珊珊   

  1. 1. 中国农业科学院农业环境与可持续发展研究所/作物高效用水与抗灾减损国家工程实验室/农业部农业环境重点实验室,北京 100081;2. 沈阳农业大学农学院,沈阳 110161;3. 抚顺市气象局,抚顺 113006
  • 收稿日期:2021-11-30 出版日期:2022-09-20 发布日期:2022-09-19
  • 通讯作者: 刘布春,研究员,从事农业气象及灾害风险评估研究. E-mail:liubuchun@caas.cn
  • 作者简介:张晓男,E-mail:1185351493@qq.com
  • 基金资助:
    国家重点研发计划“重大自然灾害监测预警与防范”重点专项(2017YFC1502804)

Reconstruct the Main Phenological Periods of Shaanxi Apple by Constructing the Multi-factor Models

ZHANG Xiao-nan, LIU Bu-chun, LIU Yuan, HE Jin-na, LIU Shan-shan   

  1. 1. Institute of Environment and Sustainable Development in Agriculture, CAAS/National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction/Key Laboratory of Agricultural Environment, MOA, Beijing 100081, China; 2. College of Agronomy, Shenyang Agricultural University, Shenyang 110161;3.Fushun Meteorological Bureau, Fushun 113006
  • Received:2021-11-30 Online:2022-09-20 Published:2022-09-19

摘要: 苹果生长发育受气象因素影响较大,陕西高低温灾害发生频率的增加对苹果的产量和品质有很大影响。物候期的确定是指导果业生产、进行灾害风险管理的重要依据。目前,物候期观测数据十分匮乏,通过构建物候模型可对历史物候期进行重构。在陕西的四个果区,分别选取物候资料记录相对全面的两个代表站点,礼泉和凤翔(关中果区)、旬邑和长武(渭北西部果区)、铜川和白水(渭北东部果区)、延长和洛川(延安果区)。在各果区的两个代表站点中,选取历史物候期记录时间序列更长的站点,利用SPSS软件对该站点物候期日序与所选气象指标进行逐步回归分析,建立多个单项或多项物候期预测模型,再通过回代检验和预测检验两种方法选取最优模型。采用平均绝对误差(MAE)、物候期模拟值与实际值相差0~3d的相对准确率(RA)评估检验结果,并选择最优模型。结果表明:(1)萌芽期模型MAE为0.8~2.4d,RA为84.6%~100%;花期模型MAE为2.5~3.4d,RA为55.6%~75%;果实发育期模型MAE为0.9~2.8d,RA为63.2%~100%;成熟期模型MAE为2.2~3.2d,RA为69.2%~72.2%;模型模拟效果由好到差依次为萌芽期、果实发育期、成熟期和花期。(2)重构1981−2019年延安果区、渭北东部果区、渭北西部果区和关中果区苹果萌芽期年日序分别为72−98、70−88、73−98和71−85,花期年日序分别为102−116、86−107、100−125和84−115;1981−2019年延安果区、渭北东部果区和关中果区苹果果实发育期年日序分别为114−122、89−118和87−117,成熟期年日序为260−301、276−297和224−348。(3)重构物候期的空间分布,1981−2019年延安果区和渭北东部果区萌芽期由东南向西北逐渐推迟,关中果区和渭北西部果区自西向东推迟;花期整体自南向北越来越晚;果实发育期从南向北逐步推迟;延安果区和渭北东部果区成熟期从东向西逐步推迟,关中果区和渭北西部果区自西向东逐步推迟。本研究构建的物候模型的模拟效果总体较好,所重构的苹果物候期数据序列可为苹果生产管理和灾害风险防范提供基础性支撑,对果树物候期模型的研发具有借鉴意义。

关键词: 陕西苹果, 萌芽期, 花期, 果实发育期, 成熟期, 物候模型

Abstract: The growth of apple is greatly affected by meteorological factors. The increasing frequency of high and low temperature disasters in Shaanxi province can greatly influence the yield and quality of apple. Phenological period is helpful to guide fruit production and manage disaster risk. At present, phenological data are very scarce. The historical phenological period can be reconstructed by constructing phenological model. There were four main apple producing areas in Shaanxi province. Two representative stations with comprehensive phenological data were selected for each area. These representative stations were Liquan and Fengxiang (Guanzhong area), Xunyi and Changwu(Western area of Weibei), Tongchuan and Baishui (Eastern area of Weibei), Yanchang and Luochuan(Yan'an area). Firstly, the station with longer historical phenological data record among the two representative stations was selected. Then, the relationship between day of year(DOY) of phenological period and meteorological indexes was analyzed by using SPSS. Several single-index or multiple-index phenological prediction models were established through stepwise regression analysis. Finally, the optimal model was selected by back substitution test and prediction test. The test results were evaluated by the mean absolute error (MAE) and the relative accuracy (RA) with a difference of 0−3 days between the simulated value and the observed value. Considered both and chose the optimal model. The results showed that (1) the mean absolute errors (MAE) of sprouting time models were 0.8−2.4 days and the RA were 84.6%−100%. The MAE of flowering date models were 2.5−3.4 days and the RA were 55.6%−75%. The MAE of fruit development period models were 0.9−2.8 days and the RA were 63.2%−100%. The MAE of harvest period models were 2.2−3.2 days and the RA were 69.2%−72.2%. The sprouting time models had the best simulation effect. The fruit development period models were the second. The harvest period models were the third. The flowering date model had the worst simulation effect. (2) From 1981 to 2019, the reconstructed DOY of sprouting time in Yan'an area, Eastern area of Weibei, Western area of Weibei and Guanzhong area were between 72−98, 70−88, 73−98 and 71−85. And the reconstructed DOY of flowering date in these areas were between 102−116, 86−107, 100−125 and 84−115. The reconstructed DOY of fruit development period in Yan'an area, Eastern area of Weibei and Guanzhong area were between 114−122, 89−118 and 87−117. And the reconstructed DOY of harvest period in these three areas were between 260−301, 276−297 and 224−348. (3) The spatial distribution of reconstructed phenological periods showed that: from 1981 to 2019, the sprouting time of Yan'an area and Eastern area of Weibei was gradually delayed from southeast to northwest, while that of Guanzhong area and western area of Weibei was delayed from west to east. The flowering date and fruit development period were both later and later in north of whole study area. The harvest period of Yan'an area and eastern area of Weibei was delayed from east to west , while that of Guanzhong area and western area of Weibei was gradually delayed from west to east. The simulation effect of these models was generally good. The reconstructed apple phenological data can provide basic support for apple production management and disaster risk prevention. This study can be used as a reference for the development of fruit tree phenological period model.

Key words: Shaanxi apple, Sprouting time, Flowering date, Fruit development period, Harvest period, Phenological period model