水循环视角下黄河流域城市包容性绿色发展效率测度与分析

doi:10.12118/j.issn.1000-6060.2025.098

摘要/Abstract

摘要：

聚焦水循环视角测度的包容性绿色发展效率水平是判断黄河流域生态保护和高质量发展的重要依据。从包容性绿色发展内涵出发，结合流域内水资源短缺现实特征，创新性地将水循环纳入包容性绿色发展效率测度指标体系；采用超效率SBM模型构建并测度流域内77个城市2013—2022年的包容性绿色发展效率并对其时空演化特征进行分析；最后结合既有研究梳理包容性绿色发展效率影响因素的同时，采用时空地理加权回归模型分析其影响效应的时空演化特征。结果表明：（1）黄河流域包容性绿色发展效率总体上呈逐年上升趋势，且这种趋势在“黄河流域生态保护和高质量发展”国家重大战略提出后表现得更为明显。（2）流域内不同地区层面包容性绿色发展效率时空变化趋势呈现出明显差异。（3）流域内包容性绿色发展效率在空间分布上存在正空间自相关性，呈现出以省会等发达城市为核心的高效率值成片集聚分布特征，但这种自相关性呈逐渐减弱的趋势。（4）黄河流域包容性绿色发展效率的影响因素主要集中于城市发展、自然地理、制度环境和社会发展4个方面，且它们对包容性绿色发展效率影响效应的时空变化特征各不相同。

关键词: 水资源, 包容性绿色发展效率, 超效率SBM模型, GTWR模型, 黄河流域

Abstract:

The assessment of inclusive green development efficiency (IGDE) using a water cycle perspective is pivotal for the promotion of ecological sustainability and high-quality growth in the Yellow River Basin. This study addresses regional water scarcity challenges, incorporating indicators of the water cycle into an IGDE evaluation framework, relying on a super-efficiency slacks-based measure model to analyze IGDE's spatiotemporal evolution across 77 cities from 2013 to 2022. Methods of spatial autocorrelation and geographically temporally weighted regression were used to identify regional disparities and dynamic mechanisms of influence. Key findings include the following: (1) IGDE demonstrated a persistent upward trajectory, including accelerated growth, following the implementation of a national strategy for basin development, highlighting the role that policy interventions play. (2) Significant spatial heterogeneity emerged, revealing efficiency gaps between upper-basin and middle-lower basin regions. (3) High-efficiency clusters centered on economically advanced cities exhibited weakening spatial dependency over time. (4) Urbanization, natural resource endowments, institutional governance, and social innovation were identified as core drivers, and their impacts displayed distinct spatiotemporal variabilities. Theoretically, the research in this study advances sustainability science by integrating water cycle dynamics into green development metrics in a way that addresses limitations in conventional efficiency assessments. Methodologically, it establishes a novel spatiotemporal analytical framework that combines the measurement of efficiency, spatial econometrics, and regression modeling to decipher complex regional interactions. In a practical perspective, the findings provide actionable insight to optimize resource allocation, enhancing cross-regional governance and formulating adaptive policies tailored to basin-specific conditions. Bridging ecological objectives and socioeconomic inclusivity, this study offers empirical evidence that supports the coordinated management of water resources and green development in the Yellow River Basin.

Key words: water resources, inclusive green development efficiency, ultra-efficiency SBM model, GTWR model, Yellow River Basin

孟望生, 刘玮霖, 刘华桢. 水循环视角下黄河流域城市包容性绿色发展效率测度与分析[J]. 干旱区地理, 2025, 48(10): 1841-1854.

MENG Wangsheng, LIU Weilin, LIU Huazhen. Measurement and analysis of inclusive green development efficiency in the Yellow River Basin cities from the perspective of water cycle[J]. Arid Land Geography, 2025, 48(10): 1841-1854.

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区域	包含城市
上游	白银市、定西市、嘉峪关市、金昌市、酒泉市、兰州市、平凉市、庆阳市、天水市、武威市、西宁市、张掖市
中游	安康市、安阳市、巴彦淖尔市、包头市、宝鸡市、大同市、鄂尔多斯市、汉中市、鹤壁市、呼和浩特市、焦作市、晋城市、晋中市、开封市、临汾市、洛阳市、漯河市、吕梁市、南阳市、平顶山市、濮阳市、三门峡市、商洛市、商丘市、石嘴山市、朔州市、太原市、铜川市、渭南市、乌海市、乌兰察布市、吴忠市、西安市、咸阳市、忻州市、新乡市、信阳市、许昌市、延安市、阳泉市、银川市、榆林市、运城市、长治市、郑州市、中卫市、周口市、驻马店市、固原市、晋中市
下游	滨州市、德州市、东营市、菏泽市、济南市、济宁市、聊城市、临沂市、青岛市、日照市、泰安市、威海市、潍坊市、烟台市、枣庄市、淄博市

类别	指标	衡量方式
投入	资本	固定资产投资/10⁴元
	劳动	城镇从业人员数/10⁴人
	能源	全社会用电量/10 MWh
	水资源	城市供水总量/10⁴ m³
期望产出	经济产出	实际生产总值/10⁴元
	社会福利	社会福利指数（运用RAGA-PPC模型将每万人医疗床位、中小学师生比、养老保险覆盖率综合成社会福利指数）
	水资源重复利用	城市用水重复利用率/%
非期望产出（环境污染）	空气污染	空气污染指数（运用RAGA-PPC模型将空气质量体系指标群中各子指标值（PM_2.5、PM₁₀、SO₂、NO₂、CO、O₃）与CO₂值综合成空气污染指数）
非期望产出（环境污染）	水污染	污水排放量/10⁴ t
非期望产出（社会不公）	城乡居民收入差距	城镇居民可支配收入/农村居民可支配收入
非期望产出（社会不公）	失业	失业率/%

年份	全局莫兰指数	期望莫兰指数	莫兰指数标准差	Z统计量	P值
2013	0.235	-0.013	0.069	3.597	0.000
2014	0.241	-0.013	0.069	3.692	0.000
2015	0.274	-0.013	0.069	4.168	0.000
2016	0.254	-0.013	0.069	3.876	0.000
2017	0.188	-0.013	0.069	2.911	0.002
2018	0.147	-0.013	0.069	2.318	0.010
2019	0.115	-0.013	0.069	1.866	0.031
2020	0.157	-0.013	0.069	2.480	0.007
2021	0.229	-0.013	0.068	3.561	0.000
2022	0.075	-0.013	0.068	1.285	0.099

年份	总基尼系数	地区内基尼系数			贡献率/%
年份	总基尼系数	上游	中游	下游	地区内	地区间	超变密度
2013	0.125	0.173	0.117	0.043	46.304	37.644	16.052
2014	0.110	0.165	0.098	0.034	44.560	40.554	14.886
2015	0.103	0.165	0.089	0.037	43.891	39.996	16.113
2016	0.103	0.150	0.091	0.040	44.446	39.621	15.933
2017	0.105	0.146	0.098	0.039	46.183	37.323	16.494
2018	0.101	0.140	0.094	0.047	46.660	34.390	18.951
2019	0.092	0.133	0.091	0.027	48.739	30.303	20.958
2020	0.086	0.132	0.082	0.028	47.160	30.161	22.678
2021	0.077	0.132	0.070	0.029	45.988	31.097	22.914
2022	0.096	0.151	0.088	0.055	46.817	26.912	26.272

影响因子	样本量	最小值	最大值	均值	标准误差
城市空间形态紧凑度	770	1.00	1.97	1.23	0.01
城市多中心结构	770	0.00	0.84	0.32	0.01
城市化水平	770	0.15	1.00	0.47	0.01
降水量	770	69.90	1552.51	681.74	9.12
气温	770	4.21	21.92	12.71	0.13
风速	770	5.40	15.64	9.33	0.06
环境规制	770	3.00	139.00	49.01	0.69
政府财政支持	770	0.07	0.92	0.21	0.00
产业结构	770	0.23	2.19	0.82	0.01
对外开放度	770	0.00	0.73	0.11	0.01
技术进步	770	1.79	11.36	7.28	0.06