中国WEFE系统耦合协调演变及其约束机制——基于省域尺度与干旱半干旱区视角

doi:10.12118/j.issn.1000-6060.2026.001

Abstract

Abstract:

Synergistic development of the water-energy-food-ecosystem (WEFE) system is a critical issue in regional sustainable development, particularly in arid and semi-arid regions where systemic coordination is essential for resource and ecological security. Based on panel data from 30 Chinese provinces (autonomous regions and municipalities), excluding Xizang, Hong Kong, Macao, and Taiwan, from 2006 to 2022, a comprehensive provincial scale evaluation index system for the WEFE system was constructed. Methods entropy weight, coupling coordination, spatial autocorrelation, and grey relation were employed to systematically characterize and analyze the spatiotemporal evolution and spatial association patterns of WEFE system coordination in China, particularly the differential performance and dominant constraint mechanisms of arid and semi-arid regions at the provincial scale. We found that: (1) At the provincial scale, the overall development level of the WEFE system in China showed steady improvement, though with uneven subsystem development. The water resources subsystem consistently lagged, exhibiting a pronounced rigid constraint in arid and semi-arid regions. (2) The overall coupling coordination of the WEFE system evolved from near-disorder/recession to barely coordinated development. Spatially, it exhibited a gradient pattern in which the east led, the center was stable, and the west was catching up, though with regional disparities gradually narrowing. Arid and semi-arid regions transitioned from national clusters of low coordination to local growth poles with high coordination values. (3) Coupling coordination demonstrated stable positive spatial autocorrelation, with the coexistence of high-high and low-low agglomeration patterns. (4) Regarding constraint mechanisms, at the national level, food security formed the foundational support for WEFE system coordination. Specifically regarding subsystem constraints, arid and semi-arid regions were primarily constrained by water use and energy utilization efficiency, whereas humid and semihumid regions were more limited by production efficiency and ecological quality.

Key words: WEFE system, coupling coordination, spatial autocorrelation, grey relation, arid and semi-arid regions

GUO Jinzhong, LIU Yajie, LIU Xiaoling. Coupling coordination evolution and constraint mechanisms of the WEFE system in China: Based on the provincial scale and the perspective of arid and semi-arid regions[J].Arid Land Geography, 2026, 49(9): 1924-1939.

Figures/Tables 11

Tab. 1

Comprehensive evaluation index system of the WEFE system"

子系统层	准则层	评价指标	单位	熵权法比重	性质
水资源子系统	总量指标	人均水资源总量（W₁）	m³·人^-1	0.2500	正
		人均用水量（W₂）	m³·人^-1	0.0130	负
		产水模数（W₃）	m³·km^-2	0.3043	正
	结构指标	农业用水量占比（W₄）	%	0.0631	负
		工业用水量占比（W₅）	%	0.0243	负
		生活用水量占比（W₆）	%	0.0198	负
		生态用水量占比（W₇）	%	0.3100	正
	效益指标	万元GDP用水量（W₈）	m³·(10⁴元)^-1	0.0047	负
	效益指标	万元工业增加值用水量（W₉）	m³·(10⁴元)^-1	0.0110	负
能源子系统	总量指标	一次性能源生产总量（E₁）	10⁴ tce	0.3679	正
		发电量（E₂）	10⁸ kWh	0.1517	正
		人均能源生产量（E₃）	tce·人^-1	0.4356	正
		能源消耗总量（E₄）	10⁴ tce	0.0225	负
	效益指标	万元GDP能耗（E₅）	tce·(10⁴元)^-1	0.0120	负
	效益指标	万元GDP电耗（E₆）	kWh·(10⁴元)^-1	0.0103	负
粮食子系统	总量指标	人均粮食产量（F₁）	kg·人^-1	0.1552	正
		粮食总产值（F₂）	10⁴ t	0.1875	正
		农用机械总动力（F₃）	10⁴ kWh	0.1871	正
		粮食播种面积（F₄）	hm²	0.1413	正
	效益指标	城镇居民家庭恩格尔系数（F₅）	%	0.0333	负
		农村居民家庭恩格尔系数（F₆）	%	0.0335	负
		农产品生产价格指数（F₇）	点	0.0364	正
		单位面积产量（F₈）	kg·hm^-2	0.0570	正
		有效灌溉面积（F₉）	10³ hm²	0.1687	正
生态子系统	生态基础	森林覆盖率（E_c1）	%	0.1159	正
		城市绿地面积（E_c2）	10⁴ hm²	0.2110	正
		建成区绿化覆盖率（E_c3）	%	0.0258	正
	生态压力	SO₂排放量（E_c4）	10⁴ t	0.0291	负
		农用化肥施用折纯量（E_c5）	10⁴ t	0.0244	负
		治理废水项目完成投资（E_c6）	10⁴元	0.2792	正
		治理废气项目完成投资（E_c7）	10⁴元	0.2599	正
	生态效率	生活垃圾无害化处理率（E_c8）	%	0.0271	正
	生态效率	城镇生活污水处理率（E_c9）	%	0.0276	正

Tab. 1

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 2

Fig. 6

Fig. 7

Tab. 3

Grey relation of coupling coordination development between subsystems and the WEFE system"

子系统	北京市		天津市		河北省		山西省		辽宁省
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.578	4	0.697	4	0.780	4	0.650	3	0.655	4
能源	0.892	3	0.926	2	0.936	2	0.626	4	0.916	1
粮食	0.956	1	0.958	1	0.950	1	0.804	1	0.690	3
生态	0.954	2	0.922	3	0.789	3	0.732	2	0.876	2
子系统	吉林省		黑龙江省		上海市		浙江省		安徽省
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.663	4	0.752	2	0.883	3	0.760	2	0.818	1
能源	0.815	1	0.736	3	0.950	1	0.620	4	0.514	4
粮食	0.669	3	0.509	4	0.927	2	0.846	1	0.757	2
生态	0.705	2	0.786	1	0.582	4	0.698	3	0.615	3
子系统	福建省		江西省		河南省		湖北省		湖南省
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.676	3	0.581	3	0.705	4	0.723	1	0.696	2
能源	0.568	4	0.769	1	0.859	1	0.652	4	0.709	1
粮食	0.834	1	0.677	2	0.859	2	0.686	3	0.512	4
生态	0.779	2	0.519	4	0.803	3	0.722	2	0.585	3
子系统	广东省		海南省		重庆市		四川省		贵州省
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.581	3	0.628	3	0.856	1	0.865	1	0.736	1
能源	0.769	1	0.805	2	0.847	2	0.612	4	0.659	2
粮食	0.677	2	0.627	4	0.493	3	0.810	3	0.624	4
生态	0.519	4	0.892	1	0.440	4	0.862	2	0.625	3
子系统	陕西省		甘肃省		青海省		宁夏回族自治区		内蒙古自治区
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.918	2	0.777	1	0.756	1	0.826	2	0.828	2
能源	0.526	4	0.614	4	0.548	4	0.525	4	0.527	4
粮食	0.970	1	0.641	4	0.658	3	0.897	1	0.893	1
生态	0.819	3	0.666	2	0.720	2	0.761	3	0.777	3
子系统	江苏省		山东省		广西壮族自治区		云南省		新疆维吾尔自治区
子系统	关联度	排名	关联度	排名	关联度	排名	关联度	排名	关联度	排名
水资源	0.755	2	0.694	4	0.850	1	0.717	2	0.751	2
能源	0.628	4	0.756	3	0.571	4	0.579	4	0.642	4
粮食	0.872	1	0.915	1	0.800	2	0.794	1	0.807	1
生态	0.630	3	0.780	2	0.737	3	0.689	3	0.748	3

Tab. 3

Tab. 4

Grey relation of coupling coordination development between each indicator of the subsystem and the WEFE system"

类型	省（自治区、直辖市）	指标（灰色关联度）
类型	省（自治区、直辖市）	水资源	能源	粮食	生态
干旱半干旱区	青海省	W₄（0.9865）	E₆（0.9898）	F₈（0.8263）	E_c3（0.9980）
	黑龙江省	W₄（0.8964）	E₄（0.9653）	F₄（0.8964）	E_c1（0.9905）
	内蒙古自治区	W₂（0.9000）	E₆（0.9843）	F₈（0.8914）	E_c3（0.9419）
	四川省	W₂（0.9496）	E₂（0.9902）	F₉（0.9376）	E_c1（0.9473）
	山西省	W₂（0.9903）	E₄（0.9763）	F₄（0.8231）	E_c5（0.9649）
	宁夏回族自治区	W₅（0.9500）	E₆（0.9666）	F₉（0.8976）	E_c1（0.9936）
	新疆维吾尔自治区	W₅（0.8293）	E₆（0.9863）	F₈（0.9267）	E_c1（0.9959）
	陕西省	W₅（0.9736）	E₆（0.9730）	F₈（0.8503）	E_c1（0.9884）
	甘肃省	W₆（0.9462）	E₁（0.9830）	F₉（0.8182）	E_c3（0.9720）
	河南省	W₆（0.9855）	E₁（0.9631）	F₉（0.9148）	E_c1（0.9627）
	北京市	W₆（0.9851）	E₄（0.9938）	F₈（0.9159）	E_c9（0.9216）
	天津市	W₆（0.9880）	E₂（0.9515）	F₈（0.8932）	E_c8（0.9283）
	河北省	W₆（0.9971）	E₁（0.9755）	F₁（0.8727）	E_c4（0.9857）
	山东省	W₆（0.9792）	E₁（0.9632）	F₈（0.8967）	E_c3（0.9866）
	吉林省	W₉（0.9563）	E₄（0.9843）	F₉（0.9563）	E_c3（0.9974）
	辽宁省	W₉（0.8600）	E₁（0.9643）	F₉（0.8600）	E_c3（0.9855）
湿润半湿润区	安徽省	W₆（0.9740）	E₁（0.9758）	F₈（0.8850）	E_c3（0.9944）
	云南省	W₆（0.9796）	E₄（0.9758）	F₄（0.9489）	E_c1（0.9840）
	江西省	W₆（0.9601）	E₁（0.9843）	F₄（0.9645）	E_c1（0.9893）
	湖南省	W₆（0.9700）	E₄（0.9622）	F₈（0.9449）	E_c1（0.9799）
	广西壮族自治区	W₅（0.8343）	E₆（0.9784）	F₄（0.9190）	E_c1（0.9949）
	重庆市	W₂（0.9393）	E₁（0.9920）	F₉（0.9128）	E_c5（0.9768）
	贵州省	W₂（0.9017）	E₂（0.9883）	F₄（0.9168）	E_c5（0.9396）
	湖北省	W₂（0.9994）	E₂（0.9759）	F₄（0.9368）	E_c1（0.9366）
	海南省	W₄（0.9742）	E₆（0.9844）	F₈（0.8899）	E_c1（0.9958）
	浙江省	W₄（0.8173）	E₆（0.9617）	F₉（0.8223）	E_c1（0.9730）
	福建省	W₄（0.9809）	E₂（0.9935）	F₈（0.7890）	E_c1（0.9796）
	广东省	W₄（0.9369）	E₂（0.9814）	F₈（0.9151）	E_c3（0.9799）
	上海市	W₈（0.8785）	E₃（0.9624）	F₈（0.8093）	E_c3（0.9921）
	江苏省	W₈（0.8777）	E₂（0.9688）	F₈（0.8777）	E_c8（0.9297）

Tab. 4

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年份	全局莫兰指数	P	年份	全局莫兰指数	P
2006	0.397	0.006	2015	0.331	0.015
2007	0.390	0.006	2016	0.338	0.013
2008	0.403	0.005	2017	0.333	0.014
2009	0.412	0.004	2018	0.306	0.021
2010	0.447	0.002	2019	0.352	0.011
2011	0.411	0.004	2020	0.327	0.016
2012	0.422	0.003	2021	0.319	0.016
2013	0.347	0.011	2022	0.293	0.025
2014	0.335	0.014

Coupling coordination evolution and constraint mechanisms of the WEFE system in China: Based on the provincial scale and the perspective of arid and semi-arid regions

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