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Climate-induced rice yield anomalies linked to large-scale atmospheric circulation in Bangladesh using multi-statistical modeling

机译:使用多统计建模,气候诱导的水稻产量与孟加拉国大规模大气循环相关联

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Connecting climate-induced yield anomalies to the key climatic variables (KCVs) and large-scale atmospheric circulation index (LACI) is crucial to developing a strategic policy for food security in developing countries including Bangladesh. However, the effects of the KCVs and LACI on rice yield are still less explored in Bangladesh. This study aims to investigate daily climatic datasets from 18 sites and five LACIs during 1980-2017 to explore climate-induced yield anomalies to the KCVs and LACIs in different sub-zones of Bangladesh using the decoupling model and ensemble empirical mode decomposition (EEMD). We demarcated four sub-zones (northern, southwestern, south-central, and western) with different climate-induced yield index (CIYI) of winter Boro rice oscillations by employing principal component analysis. The CIYI time series in the northern zone was dominated by a 2-4-year oscillation, whereas the CIYI in the western zone demonstrated a prominent 6.5-year oscillation. Among the four sub-zones, south-central and northern zones had the most notable CIYI-KCV and CIYI-LACI associations, while the potential evapotranspiration (PET) in March and multivariate ENSO indices (MEI) in January were identified as the best yield prediction indicator. Wavelet coherence analysis indicated significant in-phase and out-phase coherences between KCVs and CIYI fluctuations at different time-frequency bands in these sub-zones. The random forest model also confirmed the MEI as the key driver influencing the rice yield fluctuation in Bangladesh. The isotopic signature of rainwater also demonstrated that the temperature variation is the main driver for event-based precipitation change in the south-central rice-growing zone. These outcomes can provide a scientific basis to take adaptive measures to mitigate the reduction in rice yield in western and northern Bangladesh for associated decision-makers and practitioners.
机译:将气候诱导的产量异常连接到关键气候变量(KCV)和大规模的大气流通指数(LACI)至关重要,在包括孟加拉国在内的发展中国家制定粮食安全战略政策至关重要。然而,孟加拉国探讨了KCVS和LACI对水稻产量的影响。本研究旨在在1980 - 2017年期间调查来自18个站点的每日气候数据集和五个LaCIS,以探讨使用去耦模型和集合经验模式分解(EEMD)的孟加拉国不同子区域的气候诱导的产量异常。通过采用主成分分析,我们用不同的气候诱导的冬季硼米振荡的不同气候诱导的产量指数(CIYI)划定了四个子地区(北部,西南,南部和西部)。北方地区的CIYI时间序列占据了2-4年振荡的主导,而西方地区的CIYI展示了突出的6.5年振荡。在四个子地区,南部和北部地区具有最值得注意的Ciyi-KCV和Ciyi-Laci协会,而3月份的潜在蒸散(PET)和1月份的多元ENSO指数(MEI)被确定为最佳产量预测指标。小波相干性分析表明了这些子区域不同时频带的KCV和CIYI波动之间的显着同相和超相结合。随机森林模型还确认了MEI作为影响孟加拉国水稻产量波动的关键驾驶员。雨水的同位素特征也表明,温度变化是南中西水稻种植区的事件沉淀变化的主要驱动器。这些结果可以为采取自适应措施,以减轻西部和北孟加拉国的水稻产量减少,以获得相关决策者和从业人员。

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  • 来源
    《Theoretical and applied climatology》 |2021年第4期|1077-1099|共23页
  • 作者单位

    Begum Rokeya Univ Dept Disaster Management Rangpur 5400 Bangladesh;

    Begum Rokeya Univ Dept Disaster Management Rangpur 5400 Bangladesh;

    Bangladesh Rice Res Inst Gazipur 1701 Bangladesh;

    Atom Energy Res Estab Inst Nucl Sci & Technol Isotope Hydrol Div Dhaka Bangladesh;

    Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Forecast & Evaluat Meteoro Jiangsu Key Lab Agr Meteorol Sch Appl Meteorol Nanjing 210044 Peoples R China;

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