县域尺度下关中地区农作物水足迹时空特征及影响因素

doi:10.13866/j.azr.2024.02.16

摘要/Abstract

摘要：

探讨区域农作物水足迹与其时空分布规律及驱动因素，可以提高农业生产效率和水资源利用效益。本研究量化并分析关中地区54个县（区）2000—2020年冬小麦和夏玉米水足迹，并借助通径分析方法探究影响其绿水足迹、蓝水足迹及灰水足迹时空变化的驱动因素。结果表明：（1）关中地区农作物总水足迹从2000年2.232×10⁸m³下降到2020年2.003×10⁸m³,其中，蓝水是最主要的水资源使用形式，其次是灰水，绿水使用量最少，三者占比分别为37.261%、36.254%和26.485%；（2）农作物总水足迹空间上差异显著，呈现出东高西低和相似地区（高-高、低-低）集聚分布的特征；（3）单位面积产量、平均风速和化肥施用量分别为影响绿水足迹、蓝水足迹和灰水足迹最显著的因素。本研究的结果有利于帮助关中地区节约水资源和提高用水效率，拓展农业水资源可持续利用思路。

关键词: 农作物, 水足迹, 影响因素, 时空分布, 关中地区

Abstract:

Exploring the regional crop water footprint and its spatial and temporal distribution patterns and driving factors can help optimize agricultural production layouts, improve agricultural production and water use efficiency, and achieve sustainable agricultural development. This study quantified and analyzed the water footprint of major crops in 54 counties and districts in the Guanzhong region from 2000 to 2020. Pathway analysis was used to explore the driving factors influencing temporal and spatial changes in crop water footprint. Key findings revealed that: (1) The total water footprint of crops in the Guanzhong region decreased from 2.232 × 10⁸m³in 2000 to 2.003 × 10⁸m³ in 2020. Blue water use was the most dominant, followed by gray water use, with green water use being the lowest, accounting for 37.261%, 36.254%, and 26.485%, respectively. (2) Significant spatial variations existed in the total crop water footprint, showing a high eastern and low western profile. Regions with similar crop water footprints (high-high or low-low) demonstrated an agglomeration distribution. (3) The crops’ green water footprint was primarily influenced by yield per unit area, while the blue water footprint was mainly affected by average wind speed, followed by pesticide use and relative humidity. Additionally, fertilizer application had the greatest impact on the gray water footprint. This finding suggests that agricultural input factors significantly outweigh meteorological factors in influencing the crop water footprint. Consequently, production level and agricultural inputs were primarily responsible for regional water footprint variability. Potential strategies for regulating crop water footprint include: (1) implementing reasonable allocation of precipitation to improve green water utilization to achieve optimal allocation and use of water resources; (2) enhancing irrigation practices by improving irrigation facilities, increasing irrigation efficiency, and reducing irrigation water resource consumption, particularly as irrigation is a significant contributor to the blue water footprint in agricultural water consumption; (3) reducing fertilizer application and pesticide use while ensuring crop yield to minimize water consumption caused by water environment pollution, thereby controlling agricultural water consumption and alleviating pressure on water resources. These study results are beneficial for conserving water resources and improving water use efficiency in the Guanzhong region. They provide crucial support for facilitating sustainable agricultural water management practices.

Key words: crop, water footprint, influencing factors, spatiotemporal distribution, Guanzhong region

聂汉林, 樊良新, 郭琎, 张梦可, 王志君. 县域尺度下关中地区农作物水足迹时空特征及影响因素[J]. 干旱区研究, 2024, 41(2): 339-352.

NIE Hanlin, FAN Liangxin, GUO Jin, ZHANG Mengke, WANG Zhijun. Spatial and temporal characteristics of crop water footprint and influencing factors in Guanzhong region at the county scale[J]. Arid Zone Research, 2024, 41(2): 339-352.

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农作物	年份	Moran’s I
农作物	年份	Moran’s I	P值	Z(I)
冬小麦	2000	0.229	0.003	3.006
	2004	0.253	0.001	3.316
	2008	0.266	0.001	3.455
	2012	0.264	0.001	3.443
	2016	0.259	0.001	3.400
	2020	0.382	0.000	4.651
夏玉米	2000	0.176	0.019	2.338
	2004	0.206	0.007	2.703
	2008	0.102	0.148	1.447
	2012	0.223	0.003	2.995
	2016	0.227	0.002	3.032
	2020	0.417	0.000	5.255

影响因子	蓝水足迹	绿水足迹	灰水足迹
平均气温	0.152	0.168	-0.031
相对湿度	-0.791^**	0.578^**	0.387
平均风速	0.844^**	-0.433	-0.248
日照时数	0.326	-0.047	-0.359
单位面积产量	-0.746^**	0.704^**	0.473^*
化肥施用量	-0.718^**	0.422	0.732^**
农业塑料薄膜使用量	0.018	0.342	0.476^*
农药使用量	-0.727^**	0.471^*	0.677^**