“双碳”目标下黄河流域九省区农业水资源利用效率评价及时空分异研究

Evaluation and spatiotemporal heterogeneity of agricultural water resource utilization efficiency in nine provinces and regions of Yellow River Basin under “dual-carbon” goal

摘要

【目的】面向水资源高效可持续利用的需求，为揭示碳中和背景下农业水资源利用效率时空演变规律及驱动机理，【方法】基于投入产出视角，整合“水-土-人-肥-机”投入要素，构建涵盖农业产值、碳汇、碳排放量、农业面源污染产出的农业水资源利用效率评价指标体系。通过耦合超效率SBM模型、Malmquist指数模型和标准差椭圆方法系统揭示黄河流域九省区2011—2023年农业水资源利用效率时空演变规律，运用地理探测器定量解析驱动机制，明晰其对效率的影响程度。【结果】结果显示：(1)2011—2023年，黄河流域九省区农业水资源利用效率均值从0.54升至1.03,重心先向东北扩张后向西南回调。(2)技术进步指数高于技术效率指数(TC=1.049>EC=1.001)。(3)2011年农业水资源利用效率由人均水资源量主导(q=0.98),2015年政策干预为核心(财政支农q=0.94,环保投入q=0.94),2019年资源-环境-生产多维耦合，2023年进一步向政策-生态聚集。【结论】黄河流域九省区农业水资源利用效率呈现“低效集聚-区域突破-协同优化”三阶段特征，区域差距缩小协同发展效果显著。技术进步指数是效率提升核心动力，松弛变量分析精准定位冗余要素，为优化资源配置提供科学依据。“双碳”战略下，黄河流域九省区农业水资源利用效率的演进凸显水资源高效利用与农业低碳转型的协同强化态势，驱动机制实现从自然禀赋单核主导向资源-经济-生产-政策-生态多维度调控的系统性转型。

Abstract

[Objective] To meet the demand for efficient and sustainable water resource utilization and to reveal the spatiotemporal evolution patterns and driving mechanisms of agricultural water resource utilization efficiency(AWRUE) in the context of carbon neutrality. [Methods] From an input-output perspective, an evaluation indicator system for AWRUE was constructed by integrating the “water-land-labor-fertilizer-machinery” input factors, covering agricultural output value, carbon sink, carbon emissions, and agricultural non-point source pollution. By coupling the super-efficiency SBM model, Malmquist index model, and standard deviational ellipse method, the spatiotemporal evolution patterns of AWRUE in nine provinces and regions of the Yellow River Basin from 2011 to 2023 were systematically revealed. The geodetector method was employed to quantitatively analyze the driving mechanisms and clarify their degree of influence on efficiency. [Results] The result showed that:(1) from 2011 to 2023, the average AWRUE in the nine provinces and regions of the Yellow River Basin increased from 0.54 to 1.03, and its center of gravity initially expanded northeastward and then shifted back southwestward.(2) The technological progress index was higher than the technical efficiency index(TC=1.049 > EC=1.001).(3) In 2011, AWRUE was predominantly driven by per capita water resources(q=0.98). Policy interventions became the core driving factor(fiscal support for agriculture, q=0.94; environmental protection investment, q=0.94) in 2015. In 2019, efficiency was driven by multidimensional coupling of resources, environment, and production. It further converged towards a policy-ecology nexus in 2023. [Conclusion] The AWRUE in the nine provinces and regions of the Yellow River Basin exhibits a three-phase pattern of “low-efficiency clustering—regional breakthrough—coordinated optimization”, with regional disparities narrowing and significant effects achieved in coordinated development. Technological progress(TC) serves as the core driver for efficiency enhancement. Slack variable analysis precisely identifies redundant factors, providing a scientific basis for optimizing resource allocation. Under the “dual-carbon” strategy, the evolution of AWRUE in the nine provinces and regions of the Yellow River Basin highlights a trend of strengthened coordination between efficient water resource utilization and low-carbon agricultural transformation. The driving mechanism undergoes a systematic transition from being dominated solely by natural endowments to multidimensional regulation integrating resources, economy, production, policy, and ecology.

关键词

农业水资源利用效率 / 农业碳排放 / 碳汇 / 时空分异 / 地理探测器 / 超效率SBM模型 / 影响因素 / 资源优化配置

Key words

agricultural water resource utilization efficiency / agricultural carbon emissions / carbon sink / spatiotemporal heterogeneity / geodetector / super-efficiency SBM model / influencing factors / optimal allocation of resources

基金资助

国家自然科学基金项目(U24A20615)

国家自然科学基金项目(52179001)

国家重点研发计划项目(2017YFC0506603)