基于不同空間尺度的作物產(chǎn)量集成預(yù)報(bào)——以江蘇一季稻為例

doi:10.12306/2020jms.0041

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基于不同空間尺度的作物產(chǎn)量集成預(yù)報(bào)——以江蘇一季稻為例
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                        10.12306/2020jms.0041
                    
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中圖分類號(hào):S161
基金項(xiàng)目:2019年國內(nèi)外作物產(chǎn)量預(yù)報(bào)專項(xiàng)；國家氣象中心預(yù)報(bào)員專項(xiàng)（Y201912）

Comparative analysis of different regional scales integration yield prediction ——a case study of single rice in Jiangsu

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摘要:

基于1981-2016年江蘇省不同區(qū)域一季稻產(chǎn)量序列,計(jì)算站點(diǎn)尺度的氣溫、降水、日照適宜度以及綜合氣候適宜度,在此基礎(chǔ)上構(gòu)建基于氣候適宜指數(shù)的作物產(chǎn)量預(yù)報(bào)模型,開展不同空間尺度的一季稻產(chǎn)量精細(xì)化預(yù)報(bào)。同時(shí),以各主產(chǎn)地市、縣一季稻種植面積百分比為權(quán)重,加權(quán)集成省級(jí)產(chǎn)量,開展基于不同空間尺度一季稻產(chǎn)量序列的大區(qū)域尺度產(chǎn)量預(yù)測。結(jié)果表明:(1)江蘇省不同區(qū)域一季稻氣象產(chǎn)量與不同時(shí)段氣候適宜指數(shù)之間存在較高的相關(guān)性,基于氣候適宜指數(shù)的預(yù)報(bào)方法適用于江蘇省不同區(qū)域一季稻單產(chǎn)預(yù)報(bào)。(2)2012-2016年省級(jí)尺度模型預(yù)報(bào)平均準(zhǔn)確率高于97.5%,主產(chǎn)地市、縣模型平均預(yù)報(bào)準(zhǔn)確率低于省級(jí)尺度預(yù)報(bào)模型,主產(chǎn)縣預(yù)報(bào)準(zhǔn)確率年際間波動(dòng)較大,表明預(yù)報(bào)區(qū)域越小,預(yù)報(bào)的難度提升。(3)基于氣候適宜指數(shù)模型的江蘇省級(jí)、主產(chǎn)地市集成,主產(chǎn)縣集成模型預(yù)報(bào)準(zhǔn)確率大部在95%以上,整體上看主產(chǎn)縣集成優(yōu)于主產(chǎn)地市集成,主產(chǎn)地市集成優(yōu)于省級(jí)尺度模型。由此,開展地市級(jí)和縣級(jí)尺度的精細(xì)化產(chǎn)量預(yù)報(bào)可提升省級(jí)尺度預(yù)報(bào)準(zhǔn)確率,同時(shí)提高縣級(jí)作物產(chǎn)量預(yù)報(bào)能力。

Abstract:

Based on the yield series of single rice in different regions of Jiangsu Province from 1981 to 2016, the temperature, precipitation, sunshine hours and comprehensive climate suitability at station scale were calculated. On this basis, the crop yield prediction model based on climate suitability index was constructed to carry out the fine prediction of single rice yield at different spatial scales. At the same time, with the percentage of planting area of single rice in each major producing area city and county as the weight, the provincial yield was weighted and integrated to carry out large regional scale yield prediction based on different spatial scale single rice yield series. Results show that: (1)there is a high correlation between the meteorological yield of single rice in different regions of Jiangsu Province and the climate suitability index of different time periods. The prediction method based on the climate suitability index is suitable for the yield prediction of single rice in different regions of Jiangsu Province. (2)The average forecast accuracy of the provincial scale model from 2012 to 2016 is higher than 97.5%. The average forecast accuracy of the city scale model and the county scale model is lower than the provincial scale model. The accuracy of the county scale model has a large fluctuation in different years, which indicate that the smaller the forecast area, the more difficult the forecast accuracy. (3)Based on the climate suitability index model, the prediction accuracy integrate by province, integrate by city and integrate by county is mostly above 95%.On the whole, the integrated model of main producing area counties is better than the integrated model of main producing area cities, and the integrated model of main producing area cities is better than the provincial scale model. Therefore, to carry out the refined yield forecast at prefecture level and county level can improve the accuracy of provincial scale forecast, and improve the ability of meteorological crop yield forecast at county level.

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劉維,宋迎波.基于不同空間尺度的作物產(chǎn)量集成預(yù)報(bào)——以江蘇一季稻為例.氣象科學(xué),2021,41(6):828-834 LIU Wei, SONG Yingbo. Comparative analysis of different regional scales integration yield prediction ——a case study of single rice in Jiangsu. Journal of the Meteorological Sciences,2021,41(6):828-834

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收稿日期:2020-04-09
最后修改日期:2020-05-10
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在線發(fā)布日期: 2022-01-10
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