黄河流域粮食生产韧性与水资源承载力时空耦合、演变轨迹及驱动因素

doi:10.12118/j.issn.1000-6060.2025.643

Abstract

Abstract:

Investigating the intrinsic relationship and driving factors between grain production resilience and water resource carrying capacity in the Yellow River Basin of China has significant implications for the basin’s high-quality development. This study examines nine provinces and autonomous regions in the Yellow River Basin, constructing a grain production resilience and water resource carrying capacity evaluation index system and comprehensively applying entropy value analysis, coupling coordination degree models, and random forest algorithms to systematically analyze these systems’ integrated development, spatiotemporal coupling evolution characteristics, and driving factors from 2014 to 2023. The relevant results are fourfold. (1) In the period under study, grain production resilience in the Yellow River Basin showed a steady upward trend, while water resource carrying capacity exhibited an increase-fluctuation-adjustment pattern. (2) The two systems’ coupling coordination degree improved from barely coordinated (0.534) to preliminarily coordinated (0.610), although at a slow pace. Over time, fluctuating characteristics of overall divergence, individual sectors leading, and lagging sectors undergoing optimization transpired. (3) Spatially, the coupling coordination level exhibited a gradient distribution pattern of higher in the east than in the west and higher in the lower reaches than in the upper reaches. The upper, middle, and lower reaches formed distinct local patterns, respectively encompassing a low-value cluster zone, a high-value C-shaped pattern encircling Shanxi, and another high-value cluster zone. (4) Effective irrigated area is the primary driver, jointly influencing both systems’ coordination alongside the water production modulus, water consumption per 10000 yuan of GDP, number of agricultural researchers, and cropping index.

Key words: food security, water resource carrying capacity, Yellow River Basin, resilience, random forest

XU Qingdi, YANG Qing. Spatiotemporal coupling, evolutionary trajectories, and driving factors of grain production resilience and water resources carrying capacity in the Yellow River Basin[J].Arid Land Geography, 2026, 49(9): 1940-1950.

Figures/Tables 11

Fig. 1

Fig. 2

Tab. 1

Indicator system for grain production resilience and water resource carrying capacity"

目标层	一级指标	二级指标	单位	指标计算方法	指标性质
水资源承载力	资源环境系统	人均水资源量（X₁）	m³·人^-1	区域水资源总量/区域人口总量	+
		产水模数（X₂）	m³·hm^-2	区域水资源总量/区域总面积	+
		水资源开发利用率（X₃）	%	区域供水总量/区域水资源总量	-
		建成区绿化覆盖率（X₄）	%	统计数据	+
		森林覆盖率（X₅）	%	统计数据	+
		生态用水量（X₆）	m³	统计数据	+
	经济社会系统	人均GDP（X₇）	元·人^-1	地区生产总值/区域人口总量	+
		万元GDP用水量（X₈）	m³·(10⁴元)^-1	年用水总量/地区生产总值	-
		经济密度（X₉）	元·hm^-2	地区生产总值/区域总面积	+
		人口密度（X₁₀）	人·hm^-2	区域人口总量/区域总面积	-
		城镇化率（X₁₁）	%	区域城镇人口总量/区域人口总量	+
		人均用水量（X₁₂）	m³·人^-1	统计数据	-
粮食生产韧性	风险抵御能力	耕地总面积（X₁₃）	hm²	统计数据	+
		有效灌溉面积（X₁₄）	hm²	统计数据	+
		农村第一产业从业人员数（X₁₅）	人	统计数据	+
		粮食类居民消费价格指数（X₁₆）	%	当期粮食价格/基期粮食价格	-
		单位面积粮食产量（X₁₇）	kg·hm^-2	粮食总产量/粮食播种面积	+
		人均粮食占有量（X₁₈）	kg·人^-1	粮食总产量/全省总人数	+
	复原调适能力	复种指数（X₁₉）	%	农作物播种面积/耕地面积	+
		农业气象观测业务站点数（X₂₀）	个	统计数据	+
		成灾率（X₂₁）	%	成灾面积/受灾面积×100	-
		农村用电量（X₂₂）	kWh	统计数据	+
		农药施用强度（X₂₃）	kg·hm^-2	农药施用量/农作物播种面积	-
		化肥施用强度（X₂₄）	kg·hm^-2	化肥施用量/农作物播种面积	-
		农膜施用强度（X₂₅）	kg·hm^-2	农膜使用量/农作物播种面积	-
	创新变革能力	机械化水平（X₂₆）	kWh·hm^-2	农业机械总动力/农作物播种面积	+
		单位播种面积农林牧渔服务业产值（X₂₇）	10⁴元·hm^-2	农林牧渔专业及辅助性活动产值/农作物播种面积	+
		财政支农力度（X₂₈）	%	农林水事务支出/政府公共财政支出	+
		农业科研人员数（X₂₉）	人	科研人员数×（农业总产值/生产总值）	+

Tab. 1

Tab. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Tab. 3

Fig. 8

References 27

[1]	中共中央, 国务院. 加快建设农业强国规划(2024-2035年)[EB/OL]. [2025-04-07]. https://www.gov.cn/zhengce/202504/content_7017469.htm.
	[Central Committee of the Communist Party of China, State Council. The plan for accelerating the building of a strong agricultural country(2024-2035)[EB/OL]. [2025-04-07]. https://www.gov.cn/zhengce/202504/content_7017469.htm.]
[2]	陆大道, 孙东琪. 黄河流域的综合治理与可持续发展[J]. 地理学报, 2019, 74(12): 2431-2436. doi: 10.11821/dlxb201912001
	[Lu Dadao, Sun Dongqi. Development and management tasks of the Yellow River Basin: A preliminary understanding and suggestion[J]. Acta Geographica Sinica, 2019, 74(12): 2431-2436.] doi: 10.11821/dlxb201912001
[3]	康绍忠. 藏粮于水藏水于技——发展高水效农业保障国家食物安全[J]. 中国水利, 2022(13): 1-5.
	[Kang Shaozhong. Storing grain in water and storing water in technology: Developing high water-efficiency agriculture to ensure national food security[J]. China Water Resources, 2022(13): 1-5.]
[4]	陈桂生, 彭俊杰. “水-能源-粮食”纽带视角下黄河流域数字经济的绿色作用机制研究[J]. 管理学刊, 2025, 38(1): 146-158.
	[Chen Guisheng, Peng Junjie. Green effect of digital economy from a water-energy-food nexus perspective in China’s Yellow River Basin[J]. Journal of Management, 2025, 38(1): 146-158.]
[5]	谢群, 卢泽花, 贠晓哲. 黄河流域水资源承载力与高质量发展的耦合协调及其驱动机制研究[J]. 中国农业资源与区划, 2025, 46(4): 91-102.
	[Xie Qun, Lu Zehua, Yun Xiaozhe. Research on coupling coordination and driving mechanism of water resource carrying capacity and high-quality development in the Yellow River Basin[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2025, 46(4): 91-102.]
[6]	唐家凯, 丁文广, 李玮丽, 等. 黄河流域水资源承载力评价及障碍因素研究[J]. 人民黄河, 2021, 43(7): 73-77.
	[Tang Jiakai, Ding Wenguang, Li Weili, et al. Study on evaluation of water resources carrying capacity and obstacle factors in the Yellow River Basin[J]. Yellow River, 2021, 43(7): 73-77.]
[7]	Yin Y Y, Tang Q H, Liu X C, et al. Water scarcity under various socio-economic pathways and its potential effects on food production in the Yellow River Basin[J]. Hydrology and Earth System Sciences, 2017, 21(2): 791-804. doi: 10.5194/hess-21-791-2017
[8]	王帅, 甘林针, 钟钰. 走向韧性治理: 新时代国家粮食安全治理的思维转换与路径选择[J]. 华南农业大学学报(社会科学版), 2025, 24(3): 1-16.
	[Wang Shuai, Gan Linzhen, Zhong Yu. Towards resilient governance: Thinking transformation and path selection of national food security governance in the new era[J]. Journal of South China Agricultural University (Social Science Edition), 2025, 24(3): 1-16.]
[9]	Food and Agriculture Organization of the United Nations (FAO). The state of food and agriculture 2021: Making agrifood aystems more resilient to shocks and stresses[R]. Rome: Food and Agriculture Organization of the United Nations, 2021.
[10]	Béné C. Resilience of local food systems and links to food security: A review of some important concepts in the context of COVID-19 and other shocks[J]. Food Security, 2020(12): 805-822.
[11]	程国强, 施嘉庚. 持续增强粮食安全保障能力: 党的十八大以来的政策逻辑与当前的着力点[J]. 南京农业大学学报(社会科学版), 2025, 25(4): 45-55.
	[Cheng Guoqiang, Shi Jiageng. Continuous enhancement of food security capacity: The policy logics since the 18^th national congress of the communist party of China and current focus[J]. Journal of Nanjing Agricultural University (Social Sciences Edition), 2025, 25(4): 45-55.]
[12]	陈有华, 卢欣雨, 张壮, 等. 农业生产社会-生态系统韧性:维度与度量[J]. 生态学报, 2025, 45(9): 4548-4560.
	[Chen Youhua, Lu Xinyu, Zhang Zhuang, et al. Resilience of agricultural production systems: Dimensions and measurements[J]. Acta Ecologica Sinica, 2025, 45(9): 4548-4560.]
[13]	董亚妮, 祁春节, 桂成. 粮食产业链韧性测度、区域差异及收敛性研究——以长江经济带108个地级市为例[J]. 干旱区资源与环境, 2025, 39(8): 41-54.
	[Dong Yani, Qi Chunjie, Gui Cheng. Resilience measurement, regional differences and convergence of food industry chain: Case study of 108 cities in the Yangtze River Economic Belt[J]. Journal of Arid Land Resources and Environment, 2025, 39(8): 41-54.]
[14]	李菲菲, 周霞, 周玉玺. 中国粮食生产韧性的时空特征及演化趋势研究[J]. 统计与决策, 2025, 41(4): 75-80.
	[Li Feifei, Zhou Xia, Zhou Yuxi. Study on the spatiotemporal characteristics and evolution trend of China’s grain production resilience[J]. Statistics & Decision, 2025, 41(4): 75-80.]
[15]	张永旺, 周欣欣. 气候变化视角下中国粮食生产韧性时空差异及影响因素研究——以粮食主产区为例[J]. 农业经济与管理, 2024(6): 63-76.
	[Zhang Yongwang, Zhou Xinxin. Spatial-temporal differences and influencing factors of grain production resilience in China from perspective of climate change: A case study of major grain producing areas[J]. Agricultural Economics and Management, 2024(6): 63-76.]
[16]	李云玲, 郭旭宁, 郭东阳, 等. 水资源承载能力评价方法研究及应用[J]. 地理科学进展, 2017, 36(3): 342-349. doi: 10.18306/dlkxjz.2017.03.010
	[Li Yunling, Guo Xuning, Guo Dongyang, et al. An evaluation method of water resources carrying capacity and application[J]. Progress in Geography, 2017, 36(3): 342-349.] doi: 10.18306/dlkxjz.2017.03.010
[17]	Cheng K, Fu Q, Meng J, et al. Analysis of the spatial variation and identification of factors affecting the water resources carrying capacity based on the cloud model[J]. Water Resources Management, 2018, 32(8): 2767-2781. doi: 10.1007/s11269-018-1957-x
[18]	张泽琳, 周霞, 周玉玺. 黄河下游水资源承载力与粮食生产韧性时空耦合及驱动因素[J]. 水土保持研究, 2024, 31(3): 412-420, 431.
	[Zhang Zelin, Zhou Xia, Zhou Yuxi. Spatiotemporal coupling and driving factors of water resources carrying capacity and grain production resilience in the lower reaches of the Yellow River[J]. Research of Soil and Water Conservation, 2024, 31(3): 412-420, 431.]
[19]	热孜娅·阿曼, 方创琳, 赵瑞东. 新疆水资源承载力评价与时空演变特征分析[J]. 长江流域资源与环境, 2020, 29(7): 1576-1585.
	[Aman Reziya, Fang Chuanglin, Zhao Ruidong. Research on the water resources carrying capacity and spatial-temporal characteristics in Xinjiang[J]. Resources and Environment in the Yangtze Basin, 2020, 29(7): 1576-1585.]
[20]	罗强, 黄大金. 水资源安全与粮食生产韧性耦合协调特征及驱动因素研究——基于中国粮食主产区的实证[J]. 中国农机化学报, 2025, 46(7): 310-318.
	[Luo Qiang, Huang Dajin. Coupling coordination and driving factors of water resources security and grain production resilience: An empirical analysis of China’s major grain-producing regions[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(7): 310-318.]
[21]	陈振, 郑锐, 李佩华, 等. 河南省农业科技创新效率评价与分析[J]. 河南农业大学学报, 2018, 52(3): 464-469.
	[Chen Zhen, Zheng Rui, Li Peihua, et al. Evaluation and analysis of agricultural science and technology innovation efficiency in Henan Province[J]. Journal of Henan Agricultural University, 2018, 52(3): 464-469.]
[22]	王淑佳, 孔伟, 任亮, 等. 国内耦合协调度模型的误区及修正[J]. 自然资源学报, 2021, 36(3): 793-810. doi: 10.31497/zrzyxb.20210319
	[Wang Shujia, Kong Wei, Ren Liang, et al. Research on misuses and modification of coupling coordination degree model in China[J]. Journal of Natural Resources, 2021, 36(3): 793-810.] doi: 10.31497/zrzyxb.20210319
[23]	李珂, 何静, 孟阳阳, 等. 黄河流域乡村旅游重点村空间分布及影响因素[J]. 干旱区地理, 2025, 48(1): 2031-2041.
	[Li Ke, He Jing, Meng Yangyang, et al. Spatial distribution and influencing factors of key rural tourism villages in the Yellow River Basin[J]. Arid Land Geography, 2025, 48(1): 2031-2041.]
[24]	Breiman L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32. doi: 10.1023/A:1010933404324
[25]	刘媛, 熊柴, 蔡继明. 农民工进城落户的意愿为什么不高?--基于可解释机器学习方法的分析[J]. 中国农村经济, 2025, 47(4): 20-41.
	[Liu Yuan, Xiong Chai, Cai Jiming. Why are rural migrant workers not willing to transfer Hukou to cities? An analysis based on interpretable machine learning methods[J]. Chinese Rural Economy, 2025, 47(4): 20-41.]
[26]	陈展图, 杨庆媛, 童小容. 轮作休耕推进农业供给侧结构性改革路径研究[J]. 农村经济, 2017(7): 20-25.
	[Chen Zhantu, Yang Qingyuan, Tong Xiaorong. Research on the path of structural reform of agricultural supply side by rotation and fallow[J]. Rural Economy, 2017(7): 20-25.]
[27]	中华人民共和国水利部. 中国水资源公报2022[R]. 北京: 中国水利水电出版社, 2023.
	[Ministry of Water Resources of the People’s Republic of China. China water resources bulletin 2022[R]. Beijing: China Water & Power Press, 2023.]

类型	等级	耦合协调度
失调衰退型	极度失调	0.0~0.1
	高度失调	0.1~0.2
	中度失调	0.2~0.3
	轻度失调	0.3~0.4
	濒临失调	0.4~0.5
协调发展型	勉强协调	0.5~0.6
	初级协调	0.6~0.7
	中级协调	0.7~0.8
	良好协调	0.8~0.9
	优质协调	0.9~1.0

模型类型	测试集R²	RMSE	MAE	交叉验证R²均值	交叉验证R²标准差
随机森林	0.9324	0.0228	0.0194	0.8934	0.0441
SVR	0.5672	0.0578	0.0500	0.4488	0.0732
LightGBM	0.8286	0.0364	0.0279	0.8163	0.0511

Spatiotemporal coupling, evolutionary trajectories, and driving factors of grain production resilience and water resources carrying capacity in the Yellow River Basin

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