CAJ | 학술논문

以北京地区玉渊潭公园杭州早樱（1998-2012年）、密云农业气象试验站白玉兰（1996-2012年）及颐和园公园山桃（1981-2012年）物候观测资料和海淀、密云气象站的1981-2012年逐日平均气温观测资料为基础，分别应用国际通用的3种物候模型（SW 模型、UniChill 模型和统计模型）对以上植物的始花期和盛花期建模，并评估模型适用性。结果表明：SW 模型在北京地区3种观赏植物开花期预测中适用性最高，其交叉检验的均方根误差仅为1．93～3．58 d，其次为 UniChill 模型（均方根误差为2．49～3．79 d），统计模型效果最差（均方根误差为2．36～4．24 d）。因此，推荐在观赏植物开花期预测业务中采用 SW 模型。
이북경지구옥연담공완항주조앵（1998-2012년）、밀운농업기상시험참백옥란（1996-2012년）급이화완공완산도（1981-2012년）물후관측자료화해정、밀운기상참적1981-2012년축일평균기온관측자료위기출，분별응용국제통용적3충물후모형（SW 모형、UniChill 모형화통계모형）대이상식물적시화기화성화기건모，병평고모형괄용성。결과표명：SW 모형재북경지구3충관상식물개화기예측중괄용성최고，기교차검험적균방근오차부위1．93～3．58 d，기차위 UniChill 모형（균방근오차위2．49～3．79 d），통계모형효과최차（균방근오차위2．36～4．24 d）。인차，추천재관상식물개화기예측업무중채용 SW 모형。
In recent years,with the tourism booming and the increasing demands for flower-appreciation,the prediction of flowering date of ornamentals plants becomes more and more important.For a long time, phenological models are widely used in agriculture field,but rarely applied in predicting flowering time of ornamental plants. <br> Based on phenological data of three ornamentals plants (Prunus discoidea ,Magnolia denudata and Amygdalus davidiana )in Beijing Area,corresponding meteorological data during the period of 1981 -2012 at Haidian and Miyun meteorological stations,three phenological models (SW Model,UniChill Mod-el and Statistical Model)for simulating the first flowering date and the full flowering date of the above three plants are developed.In the experimental process,the least square fitting is introduced in computing parameters,including linear least square fitting in Statistical Model and nonlinear least square fitting in SW Model and UniChill Model.Moreover,the simulating annealing approach is used to obtain the analytic so-lutions for SW Model and UniChill Model.Results show that SW Model performs well in simulating the first flowering date and the full flowering date of Prunus discoidea ,the full flowering date of Magnolia denudata ,and the first flowering date and the full flowering date of Amygdalus davidiana .Besides,SW Model is the most applicable model with the root mean square error (RMSE)of external verification be-tween 1.93-3.58 days.UniChill Model ranks the second with the RMSE of 2.49-3.89 days,and Statis-tical Model has the largest uncertainty with the RMSE of 2.37-4.24 days.As far as prediction accuracy is concerned,SW Model also ranks the first,and for more than 85% of years,the prediction error is within 3 days. <br> Above all,SW Model is recommended for predicting the flowering dates of the ornamental plants in Beijing Area.But Statistical Model based on daily average temperature,considering the comprehensive effect of light and moisture and plant physiological processes,may perform better.With the increasing ur-ban heat island effect in Beijing Area,the deviation caused by urban heat island effect should be removed during the application of SW Model.