Spatial Differentiation of the Water-Saving Industry in Guangzhou Based on a Development Heat Index

XIONG Yan; CHEN Yanshan; QIU Songxi; LIU Zhenmin; HE Jiaxiang; WANG Yuxin

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Spatial Differentiation of the Water-Saving Industry in Guangzhou Based on a Development Heat Index

更新时间：2026-10-13

- Spatial Differentiation of the Water-Saving Industry in Guangzhou Based on a Development Heat Index
- PEARL RIVER Pages: 1-11(2026)
- 作者机构：
  
  1.广州市南部水网流域事务中心，广东广州 510635
  2.广东省水利水电科学研究院水资源与水生态环境工程研究所，广东广州 510635
  3.广东省节水技术创新中心，广东广州 510635
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：20 August 2026，
  
  Revised：2026-09-20，
  
  Accepted：23 September 2026，
  
  Online First：13 October 2026，
- 稿件说明：
移动端阅览
熊艳，陈燕珊，邱颂曦等.基于热度指数的广州市节水产业空间分异研究［J］.人民珠江，DOI：10.3969/j.issn.1001-9235.XXXX.XX.001.

XIONG Yan,CHEN Yanshan,QIU Songxi,et al.Spatial Differentiation of the Water-Saving Industry in Guangzhou Based on a Development Heat Index[J].PEARL RIVER,
熊艳，陈燕珊，邱颂曦等.基于热度指数的广州市节水产业空间分异研究［J］.人民珠江，DOI：10.3969/j.issn.1001-9235.XXXX.XX.001. DOI：

XIONG Yan,CHEN Yanshan,QIU Songxi,et al.Spatial Differentiation of the Water-Saving Industry in Guangzhou Based on a Development Heat Index[J].PEARL RIVER, DOI：10.3969/j.issn.1001-9235...001.

摘要

聚焦广义节水产业，以广州市11个行政区为单元，紧扣“需求-供给-成效”全链条逻辑，构建涵盖需求基础、产业活力、节水成效的节水产业发展热度指数体系，采用熵值法、Spearman秩相关和Moran’s I等方法开展量化分析并划分差异化功能区。结果表明，2024年广州市节水产业空间非均衡性显著，总体呈现“东南产业高低凸显、北部涉农区托底、老城需求旺盛但产业薄弱”的分异格局；综合热度指数（含农业）呈显著正向空间集聚（Moran's I为0.570，

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038452&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038469&type=

13.54666710

2.96333337

），农业节水是驱动空间分异格局中最具区分度的维度；各维度指数耦合协同偏弱，需求基础指数与节水成效指数（含农业）呈显著负相关（

</mo><mi>p</mi><mo>=</mo><mn mathvariant="normal">0.011</mn></math>

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038503&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038480&type=

29.12533188

3.04800010

），Bootstrap检验确认稳健。据此将11区划分为均衡发展区、转型提升区、农业节水产业培育区、发展滞后区4类功能区，并提出分区发展对策。

Abstract

Focusing on the water-saving industry in a broad sense

this study takes the 11 administrative districts of Guangzhou as units of analysis. Following the full-chain logic of "demand–supply–effectiveness

" it constructs a Water-Saving Industry Development Heat Index system covering three dimensions: demand foundation

industrial vitality

and water-saving effectiveness. The demand foundation dimension includes per capita GDP

urbanization rate

and the share of the secondary industry; the industrial vitality dimension covers the number of water-saving enterprises

output value

revenue

and R

D expenditure; and the water-saving effectiveness dimension includes comprehensive water use per capita

water consumption per 10

000 yuan of GDP

industrial added value per unit of water consump

tion

leakage rate of the urban water supply network

reclaimed water utilization rate

effective utilization coefficient of farmland irrigation water

and the share of area covered by the comprehensive reform of agricultural water pricing. Data are drawn mainly from the Guangzhou Statistical Yearbook (2025)

the Guangzhou Water Resources Report (2025)

project-based enterprise surveys

and district-level self-assessments for water-saving society construction. Quantitative analysis and differentiated functional zoning are conducted using the entropy method

Spearman rank correlation

and Moran's I. To test the robustness of the index results

Monte Carlo perturbation (with ±20% uniform disturbances applied to the baseline weights) and bootstrap resampling are further employed. The results indicate that in 2024

the spatial imbalance of Guangzhou's water-saving industry was pronounced

showing an overall pattern of "prominent industrial highlands in the southeast

agriculture-related districts in the north providing bottom-line support

and strong demand but weak industry in the old urban cores." The comprehensive heat index (including agricultural water-saving indicators) exhibited significant positive spatial clustering (Moran's I 0.570

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038453&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038470&type=

13.54666710

2.96333337

). After removing agricultural indicators

Moran's I dropped to 0.126(

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038504&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038481&type=

13.54666710

2.96333337

)

confirming that the observed spatial clustering was mainly attributable to agricultural water-saving effects. The coupling coordination among dimensional indices was generally weak

and the demand foundation index was significantly negatively correlated with the water-saving effectiveness index that included agricultural water-saving indicators(

</mo><mi>p</mi><mo>=</mo><mn mathvariant="normal">0.011</mn></math>

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038454&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038471&type=

28.36333466

2.96333337

); this result was confirmed by the bootstrap test (95% CI [-0.972

-0.268

]

). This negative association reflects a structural mismatch: highly urbanized districts such as Yuexiu and Huangpu have little agricultural land and thus score low on agricultural water-saving indicators

whereas agricultural districts such as Conghua and Zengcheng achieve high water-saving effectiveness despite weak demand foundations. Meanwhile

the positive trend between demand foundation and industrial vitality did not pass the bootstrap robustness check

suggesting that the linkage between market demand and i

ndustry formation (

</mo><mi>p</mi><mo>=</mo><mn mathvariant="normal">0.089</mn></math>

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038505&type=

https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120038482&type=

26.83933067

2.96333337

)remains statistically inconclusive at the current stage. Accordingly

the 11 districts are divided into four functional zones: the balanced development zone (Panyu

Tianhe

Haizhu)

the transformation and upgrading zone (Huangpu)

the agricultural water-saving industry cultivation zone (Huadu

Conghua

Zengcheng

Baiyun)

and the lagging development zone (Yuexiu

Nansha

Liwan)

with corresponding zonal development strategies proposed. For the balanced development zone

consolidating multi-dimensional synergies and incubating knowledge-intensive water-saving services are recommended. For the transformation and upgrading zone

upgrading high-end water-saving equipment manufacturing and strengthening pipe-network retrofitting is suggested. For the agricultural water-saving industry cultivation zone

integrating agricultural water-saving projects with local industrial chains and expanding precision subsidy mechanisms are advised. For the lagging development zone

introducing industrial carriers

activating the retrofit market through urban renewal

and leveraging green finance tools such as Guangdong's "water-saving loan" program are proposed. Limitations of this study include reliance on 2024 cross-sectional data and the small sample size of 11 districts

which constrain causal inference and long-term trend analysis. Future research could inco

rporate panel data and spatial convergence models to address these gaps.

关键词

Keywords

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