陈帅, 侯孟阳, 李园园, 邓元杰, 姚顺波. 黄河流域水资源、能源与粮食生产的时空匹配及阻尼效应[J]. 农业工程学报, 2022, 38(18): 246-254. DOI: 10.11975/j.issn.1002-6819.2022.18.027
    引用本文: 陈帅, 侯孟阳, 李园园, 邓元杰, 姚顺波. 黄河流域水资源、能源与粮食生产的时空匹配及阻尼效应[J]. 农业工程学报, 2022, 38(18): 246-254. DOI: 10.11975/j.issn.1002-6819.2022.18.027
    Chen Shuai, Hou Mengyang, Li Yuanyuan, Deng Yuanjie, Yao Shunbo. Spatial-temporal matching patterns for grain production using water and energy resources and damping effect in the Yellow River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(18): 246-254. DOI: 10.11975/j.issn.1002-6819.2022.18.027
    Citation: Chen Shuai, Hou Mengyang, Li Yuanyuan, Deng Yuanjie, Yao Shunbo. Spatial-temporal matching patterns for grain production using water and energy resources and damping effect in the Yellow River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(18): 246-254. DOI: 10.11975/j.issn.1002-6819.2022.18.027

    黄河流域水资源、能源与粮食生产的时空匹配及阻尼效应

    Spatial-temporal matching patterns for grain production using water and energy resources and damping effect in the Yellow River Basin

    • 摘要: 水、能源与粮食是人类生活与可持续发展的重要保障,探究水资源、能源对粮食生产作用对于优化资源配置与保障粮食安全有着重要的意义。该研究运用洛伦兹曲线与基尼系数评估黄河流域上中下游水资源、能源与粮食生产之间的匹配度,并基于柯布-道格拉斯函数引入粮食增长阻尼模型测算出黄河流域水资源与能源对于粮食生产的制约程度。结果表明:1)黄河流域水资源、能源对粮食的基尼指数呈现出先减小后增大情形,黄河下游区域的匹配度要比上中游区域更为合理,2019年,下游区域水资源、能源对粮食都呈现出高度匹配状态情形。2)黄河流域水资源对于粮食生产的阻尼系数波动较大,阻尼系数变化范围为0.005~0.032,且水资源对粮食增长阻尼作用呈现出6 a一周期情形。能源对于粮食生产的阻尼作用呈现出稳步上升情形,且在2015后上增较快。在水资源与能源约束条件下,2019年黄河流域粮食产量增长要比上一年分别降低0.76%与5.28%。3)黄河流域水资源阻尼系数呈现出西部小东部大情形,能源阻尼效应呈中高约束状态集中在黄河上游东部区域与下游区域,低约束状态集中于黄河中游区域。另外,黄河流域水资源与能源阻尼系数具有典型的空间集聚特征,水资源阻尼效应高-高集聚区主要分布在黄河下游区域,能源阻尼效应低-低集聚区分布在中游北部区域。研究结论可为黄河流域粮食的稳定增长与资源有效配置提供科学依据。

       

      Abstract: Abstract: Shortage and matching dislocation of water resources and energy can pose a serious risk to the growth rate of food production. Particularly, water, energy and food are the indispensable resources in the human life and development. In this study, the Lorentz curve and Gini coefficient were used to evaluate the matching degree between the water-grain and energy-grain in the Yellow River Basin. Cobb-Douglas function was also applied for the grain growth damping model, in order to calculate the restriction degree of water resources and energy on the grain production. The results show that: 1) The Gini index of water resources and energy to the grain decreased first and then increased, the matching degree of which was more reasonable in the lower reaches of the Yellow River than that of the upper and middle reaches. In 2019, the Gini index values of water resources to grain in the Yellow River and the upper, middle and lower reaches were 0.365, 0.379, 0.336, and 0.122, respectively, while the Gini index values of energy to grain were 0.194, 0.218, 0.206, and 0.118, respectively, indicating the high matching in the lower reaches. The water resources and energy in the upper and middle reaches were generally matched with the grain. 2) The damping coefficient of water resources to grain production was fluctuated greatly, where the variation range of damping coefficient was 0.005~0.032. Besides, the damping effect of water resources on the grain growth basically presented a six-year cycle with a decrease-increase-decrease situation. By contrast, there was a steady increase in the damping effect of energy on the grain, the energy damping coefficient increased rapidly after 2015. Under the constraints of water resources and energy in 2019, the annual grain output growth was reduced by 0.76%, and 5.28%, respectively, compared with the previous year. 3) There was a certain degree of agglomeration in the damping effect of water resources and energy. The damping coefficient of water resources presented the pattern of small in the West and large in the East. A medium and high constraint state was obtained in the energy damping effect, which was concentrated in the eastern and lower reaches of the upper reaches, whereas, the low constraint state was concentrated in the middle reaches of the Yellow River. In addition, there was the typical spatial agglomeration in the damping coefficient of water resources and energy. The H(High)-H(High) agglomeration area of water resources damping effect was mainly distributed in the lower reaches of the Yellow River, whereas, the L(Low)-L(Low) agglomeration area of energy damping effect was distributed in the northern part of the middle reaches. The finding can provide a strong reference for the stable growth of grain and the effective allocation of resources in the Yellow River Basin.

       

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