基于WOFOST模型的冬小麥長勢評估和產(chǎn)量預報——以2021年度冬小麥為例

doi:10.12306/2023jms.0016

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基于WOFOST模型的冬小麥長勢評估和產(chǎn)量預報——以2021年度冬小麥為例
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                        10.12306/2023jms.0016
                    
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中圖分類號:P49
基金項目:中國氣象局創(chuàng)新發(fā)展專項(CXF2021J065;CXF2023J060)

Winter wheat growth evaluation and yield prediction based on WOFOST model: a case study of the growth of winter wheat in 2021

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為實現(xiàn)世界糧食研究模型(World Food Studies,WOFOST)在氣象業(yè)務服務中的應用,利用WOFOST模型模擬的冬小麥逐日生育進程、葉面積指數(shù)和地上總生物量,運用模糊數(shù)學方法構建冬小麥長勢評估指數(shù),基于模擬的地上總生物量和穗干重采用對比法構建冬小麥單產(chǎn)預報模型。在對2015—2020年度歷史檢驗的基礎上,開展2021年度全國和各主產(chǎn)區(qū)冬小麥長勢評估和單產(chǎn)預報。結果表明:(1)基于WOFOST模型,2015—2020年度冬小麥動態(tài)長勢評估結果與冬小麥生育期內(nèi)氣象條件影響和單產(chǎn)增減趨勢基本一致,全國和各主產(chǎn)區(qū)冬小麥單產(chǎn)預報平均準確率為90.2%~98.5%;江淮江漢基于WOFOST模型的冬小麥單產(chǎn)平均預報準確率高于統(tǒng)計模型,全國和華北黃淮區(qū)比統(tǒng)計模型偏低1.0~2.2個百分點。(2)基于WOFOST模型的2021年度全國和各主產(chǎn)區(qū)冬小麥長勢評價指數(shù)均為前期低后期高,其中2—3月指數(shù)呈明顯上升趨勢,與實際氣象條件的變化一致。(3)基于地上總生物量、穗干重,2021年度全國冬小麥單產(chǎn)預報平均準確率分別為98.7%、99.0%,各主產(chǎn)區(qū)冬小麥單產(chǎn)預報平均準確率分別為92.3%~99.4%、89.3%~99.7%;基于WOFOST模型的全國和華北黃淮冬小麥單產(chǎn)預報效果略好于統(tǒng)計模型,其它主產(chǎn)區(qū)預報效果接近或差于統(tǒng)計模型。

Abstract:

As to achieve the application of World Food Studies (WOFOST) model in meteorological service, the growth evaluation index for winter wheat was constructed by usage of fuzzy mathematics method based on the development stage, leaf area index and total aboveground production simulated from WOFOST model, and yield prediction model was proposed by year-to-year comparative method based on total above ground production and dry weight of living organs. The growth evaluation index and yield prediction model were tested in 2015-2020 and further used to assess winter wheat growth and yield at national and regional scales in 2021. It was clear that the results of dynamic growth evaluation for winter wheat based on WOFOST model in 2015-2020 were in line with the influence of meteorological conditions within winter wheat growing season and trend in yield. The average accuracy of yield predictionin China and major producing areas was 90.2%-98.5%. In the perspective of yield prediction, the average accuracy based on WOFOST model was higher than that derived from statistical mode in Jianghuai and Jianghan while the accuracy based on WOFOST model was 1.0-2.2 percentage points lower than that derived from statistical model in China, North China and Huanghuai. Based on WOFOST model,the growth evaluation index for winter wheat in China and all major production areas was low in the early stage and high in the late stage in 2021 during which it significantly increased from February to March, keeping with the change of meteorological conditions.Using the yield prediction model constructed on simulated total aboveground production and dry weight of living organs, the national average accuracy in 2021 was 98.7% and 99.0%, and the average accuracy in main production areas was 92.3%-99.4% and 89.3%-99.7%, respectively. The performance of yield prediction based on WOFOST model was slightly better than that derived from statistical model in China, North China and Huanghuai, while it was close to or worse than that derived from statistical model in other main producing areas.

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鄭昌玲,魏瑞江,張蕾.基于WOFOST模型的冬小麥長勢評估和產(chǎn)量預報——以2021年度冬小麥為例.氣象科學,2025,45(2):284-292 ZHENG Changling, WEI Ruijiang, ZHANG Lei. Winter wheat growth evaluation and yield prediction based on WOFOST model: a case study of the growth of winter wheat in 2021. Journal of the Meteorological Sciences,2025,45(2):284-292

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收稿日期:2022-07-08
最后修改日期:2023-03-10
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在線發(fā)布日期: 2025-07-03
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