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基于葉綠素?zé)晒膺b感的江西省稻田總初級(jí)生產(chǎn)力估算及其氣象驅(qū)動(dòng)因素研究
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國(guó)家自然科學(xué)基金長(zhǎng)江水科學(xué)研究聯(lián)合基金項(xiàng)目(U2040213)、江西省水利科技項(xiàng)目(202426ZDKT21、202223TGKT08)和江蘇省高等學(xué)校基礎(chǔ)科學(xué)(自然科學(xué))研究面上項(xiàng)目(21KJB210021)


Estimation of Gross Primary Production of Paddy Field in Jiangxi Province Based on Remote Sensing Measured Sun-induced Chlorophyll Fluorescence and Its Correlation with Meteorological Factors
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    摘要:

    總初級(jí)生產(chǎn)力(Gross primary production, GPP)是表征作物在光合作用中吸收大氣CO2的指標(biāo),也是作物產(chǎn)量形成的重要起點(diǎn)。本研究以江西省稻田為研究對(duì)象,基于日光誘導(dǎo)葉綠素?zé)晒猓⊿un-induced chlorophyll fluorescence, SIF)遙感數(shù)據(jù)和地面通量觀測(cè)數(shù)據(jù),構(gòu)建了基于SIF的稻田GPP非線性估算模型,進(jìn)而對(duì)江西省2001—2020年稻田GPP進(jìn)行模擬。結(jié)果表明:相較于MOD17 GPP和GOSIF GPP,基于SIF的非線性模型模擬精度更高,可以更好地捕捉水稻季和非水稻季GPP的季節(jié)變化,但對(duì)早稻-晚稻交替期模擬效果較差。2001—2020年江西省稻田多年平均GPP為(2082.8±143.2)g/(m2·a),空間上呈現(xiàn)北側(cè)低、南側(cè)高的特點(diǎn),稻田GPP低值主要位于南昌市及其周邊,高值位于贛州市和景德鎮(zhèn)市。2001—2020年江西省稻田GPP總體呈波動(dòng)上升趨勢(shì),趨勢(shì)率為24.3g/(m2·a),上升趨勢(shì)最大的區(qū)域位于江西省南部,上升趨勢(shì)最小或存在下降趨勢(shì)的區(qū)域主要位于南昌市和九江市,可能與該地區(qū)水稻“雙改單”現(xiàn)象有關(guān)。江西省各市稻田GPP年際變化的主要影響因素為氣溫,貢獻(xiàn)率在28.3%~44.2%之間,太陽(yáng)輻射對(duì)稻田GPP為負(fù)貢獻(xiàn),風(fēng)速在部分區(qū)域?qū)Φ咎颎PP為正貢獻(xiàn),降水量和相對(duì)濕度對(duì)稻田GPP年際變化的影響最弱。研究可為模擬江西省稻田GPP以及評(píng)估氣候變化背景下稻田固碳能力和產(chǎn)量估算提供理論依據(jù)。

    Abstract:

    Gross primary productivity (GPP) is an indicator that reflects the absorption of atmospheric CO2 by crops through photosynthesis and serves as an important starting point for crop yield formation. The remote sensing measured sun-induced chlorophyll fluorescence (SIF) had highly advantages in GPP estimation. However, there were few studies in estimating rice GPP using remote sensing measured SIF. The paddy field in Jiangxi Province was taken as research object, a non-linear model for estimating rice GPP was constructed based on remote sensing measured SIF and ground flux observation data, and then the GPP over paddy field in Jiangxi Province during 2001—2020 was estimated. The results showed that compared with MOD17 GPP and GOSIF GPP, the SIF-based non-linear model had higher GPP estimation accuracy. The model can better capture the seasonal variations of rice GPP in both the rice seasons and non-rice seasons, but it performed poorly during the period of early rice to late rice transition. During 2001—2020, the annual average rice GPP for the Jiangxi Province was (2082.8±143.2)g/(m2·a), and generally exhibited lower values in the north and higher values in the south. The areas with low GPP values were mainly located in the Nanchang City and its surrounding areas, while high values were found in Ganzhou City and Jingdezhen City. During 2001—2020, the rice GPP in Jiangxi Province showed an overall increasing trend with an increasing rate of 24.3g/(m2·a). The regions with the largest increasing trend were located in the southern part of the Jiangxi Province, while areas with the smallest increasing or decreasing trend mainly located in Nanchang City and Jiujiang City, possibly related to the transition of “double cropping rice to single cropping rice”. The main influencing factor for interannual variations in rice GPP in Jiangxi Province was temperature, with contribution rate ranging from 28.3% to 44.2%. Solar radiation had a negative contribution to rice GPP, the wind speed had a positive contribution to rice GPP in some regions, while precipitation and relative humidity had little impact on rice GPP. The research findings can provide a theoretical basis for estimating rice GPP, as well as for assessing the carbon sequestration capacity and yield estimation of rice under climate change in Jiangxi Province.

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劉博,徐濤,徐強(qiáng)強(qiáng),李啟龍,劉方平,侯佳佳,崔遠(yuǎn)來(lái).基于葉綠素?zé)晒膺b感的江西省稻田總初級(jí)生產(chǎn)力估算及其氣象驅(qū)動(dòng)因素研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2024,55(8):391-400. LIU Bo, XU Tao, XU Qiangqiang, LI Qilong, LIU Fangping, HOU Jiajia, CUI Yuanlai. Estimation of Gross Primary Production of Paddy Field in Jiangxi Province Based on Remote Sensing Measured Sun-induced Chlorophyll Fluorescence and Its Correlation with Meteorological Factors[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(8):391-400.

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  • 收稿日期:2024-03-17
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  • 在線發(fā)布日期: 2024-08-10
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