食物、能源和水（Food，Energy and Water，FEW）是支撑人类生存和社会经济发展不可或缺的基础性资源，且相互之间存在密切的关联关系。我国FEW 资源空间错位严重，水资源的稀缺性及其对食物和能源的强烈支撑作用决定了其在 FEW 系统中的核心地位，也使资源安全面临严峻挑战。本文通过核算 2017 年我国大陆 30 省（自治区、直辖市）粮食、能源（原煤、原油、天然气、火电）生产的蓝水足迹并构建 FEW 压力指数，采用空间自相关分析、洛伦茨曲线和基尼系数计算方法展开 FEW 资源空间冲突与协调性研究。结果表明：1）2017 年我国粮食生产蓝水足迹总量为 2209.4 亿 m 3 ，高值区除新疆外主要分布在东北及中部以南地区；2）能源生产蓝水足迹总量为 126.97 亿m 3 ，其中原煤和火电分别贡献了 8.9%和 85.9%，高值区集中在华北地区及东部沿海城市；3）除北京和上海外，FEW 压力指数呈河北独大、其他省份由北到南波动降低的空间格局；4）空间自相关分析结果表明 FEW 压力指数具有显著的空间正相关性，HH 集聚特征明显；5）水资源与粮食、能源以及粮能生产蓝水足迹在空间上都呈现不匹配的格局，其中除水资源和能源生产蓝水足迹的空间分布较不匹配外，另外两对表现为一般不匹配状态。

Food, Energy and Water (FEW) are indispensable resources for human survival as well as social and economic development, and among which exists intricate and close relationships. In the FEW-nexus relationship, water resource, as the core element of sustainable development, has the most significant support for food and energy. The scarcity of water resource and its extreme mismatch with food and energy production in china make it an enormous challenge for resources’ security. Therefore, this study calculated the blue water footprint of food and main water- consuming energy products (raw coal, crude oil, natural gas and thermal power generation) in the 30 provinces of mainland china in 2017, generated FEW pressure index (WSI EF ) , then used spatial autocorrelation analysis, Lorenz curve and Gini coefficient to systematically analyze the conflict and coordination of FEW from a spatial perspective. The results showed that: 1) the total blue water footprint of food production reached 2209.4 billion m 3 in 2017, and the high value areas mainly distributed in the northeast and south of the central region except for Xinjiang; 2) the total blue water footprint of energy production attained 126.97 billion m 3 , of which raw coal and thermal power generation accounted for 8.9% and 85.9% respectively, and the high value areas concentrated in the north and eastern coastal cities; 3) except for Beijing and Shanghai, WSI EF generally demonstrated a spatial pattern in which Hebei is seriously huge and other provinces decreased fluctuatingly from north to south; 4) spatial autocorrelation analysis indicated that WSI EF owned a significant spatial positive correlation and obvious HH agglomeration characteristics; 5) the amount of water resource and the blue water footprint of food and energy as well as the sum of them were spatially mismatched. In addition to the spatial distribution of the amount of water resource and the blue water footprint of energy, which was relatively unmatched, the other two demonstrated a general mismatch.