基于资源环境承载力的泰州市耕地保有量预测研究

发布时间：2018-02-26 08:16

本文关键词： 资源环境泰州市人口承载力耕地保有量　出处：《地理与地理信息科学》2016年04期 　论文类型：期刊论文

【摘要】：以泰州市为例,利用灰色系统模型和ARIMA模型,分别从土地资源、水资源及环境负荷角度对泰州市人口承载力进行评价和预测,并根据"木桶原理",确定泰州市资源环境的最大人口承载规模,最终测算规划期内的最低耕地保有量。研究结果表明:泰州市粮食生产与水资源供给充足,土地资源、水资源不会限制人口增长,环境负荷将是未来人口增长最主要的制约因素;在保证资源环境均不超载的情况下,泰州市2020年最大人口规模541.61万人,2030年567.00万人;基于最大人口规模的最低耕地保有量2020年26.19万hm2,2030年28.26万hm2,均低于规划耕地保有量,表明泰州市粮食供给已达到自给水平。该文揭示了影响泰州市资源环境人口承载能力的短板与制约要素,确定了基于粮食安全的耕地资源最低警戒规模,为泰州市耕地资源保护与合理利用提供了科学依据。
[Abstract]:Taking Taizhou city as an example, using grey system model and ARIMA model, the population carrying capacity of Taizhou city is evaluated and forecasted from the angle of land resources, water resources and environmental load, respectively. According to the "wooden bucket principle", the maximum population carrying scale of Taizhou city's resources and environment is determined, and the minimum cultivated land quantity in the planning period is finally calculated. The results show that the grain production and water resources in Taizhou are sufficient and the land resources are sufficient. Water resources will not limit population growth, and environmental load will be the main restriction factor of population growth in the future. Under the condition that resources and environment are not overloaded, the largest population scale in Taizhou is five million four hundred and sixteen thousand and one hundred in 2020 and 5.67 million in 2030. The minimum cultivated land holdings based on the maximum population size were 261,900 hm2in 2020 and 282,600 hm2in 2030, all of which were lower than the planned cultivated land holdings. The results show that the grain supply in Taizhou has reached the self-sufficiency level. This paper reveals the short board and restriction factors that affect the carrying capacity of the population of resources and environment in Taizhou, and determines the minimum alert scale of cultivated land resources based on food security. It provides scientific basis for the protection and rational utilization of cultivated land resources in Taizhou City.
【作者单位】：中国科学院流域地理学重点实验室中国科学院南京地理与湖泊研究所;泰州市国土资源局;南京大学地理与海洋科学学院;
【分类号】：F323.211

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