Diagnosis of Performance and Obstacles of Integrated Management of Three-Water in Chaohu Lake Basin

Abstract

The integration of water resources, water environment, and water ecology (hereinafter “three-water”) is essential not only for addressing the current water crisis but also for achieving sustainable development. Chaohu Lake is an important water resource and ecological barrier in the middle and lower reaches of the Yangtze River, undertaking such functions as agricultural irrigation, urban water supply, and flood control and storage. Studying the performance of “three-water” in the Chaohu Lake Basin will help to understand the pollution mechanism and governance dilemma in the lake basin. It also provides practical experience and policy references for the ecological protection and high-quality development of the Yangtze River Basin. We used the DPSIR-TOPSIS model to analyze the performance of the river–lake system in the Chaohu Lake Basin and employed an obstacle model to identify factors influencing “three-water.” The results indicated that overall governance and performance of the “three-water” in the Chaohu Lake Basin exhibited an upward trend from 2011 to 2022. Specifically, the obstacle degree of driving force decreased by 19.6%, suggesting that economic development enhanced governance efforts. Conversely, the obstacle degree of pressure increased by 34.4%, indicating continued environmental stress. The obstacle degree of state fluctuated, showing a decrease of 13.2% followed by an increase of 3.8%, demonstrating variability in the effectiveness of water resource, environmental, and ecological management. Additionally, the obstacle degree of impact declined by 12.8%, implying the reduced efficacy of governmental measures in later stages. Response barriers decreased by 5.8%. Variations in the obstacle degree of response reflected differences in response capacities. Spatially, counties and districts at the origins of major rivers and their lake outlets showed lower performance levels in “three-water” management compared to other regions in the basin. Notably, Wuwei City and Feidong County exhibited better governance performance, while Feixi County and Chaohu City showed lower performance levels. Despite significant progress in water resource management, environmental improvement, and ecological restoration, further policy support and targeted countermeasures remain necessary. Counties and districts should pursue coordinated development, leverage the radiative influence of high-performing areas, deepen regional collaboration, and optimize, governance strategies to promote sustainable development.

1. Introduction

The Yangtze River, the third-largest river globally and the largest in Asia, has the world’s second-highest freshwater flow, and it is one of China’s most important strategic water sources. As China’s mother river, the Yangtze not only provides abundant water resources for coastal areas but also plays a pivotal role in the nation’s ecological security, economic development, and social stability [1]. Its watershed covers numerous vital agricultural and industrial regions and densely populated areas, serving as an essential important foundation for China’s sustained economic growth and coordinated regional development. Protecting the ecological environment of the Yangtze River and rationally utilizing its water resources are thus of profound strategic significance [2]. Rivers and lakes, as important carriers of water, biological, and environmental resources, constitute fundamental elements essential for human survival and development [3]. They not only closely relate to human production and livelihood but also critically maintain regional ecological functions, guarantee drinking-water safety, regulate climate, protect biodiversity, and promote sustainable economic and social development within basins. Hence, the rational protection and utilization of river and lake resources are crucial not only for the sustainable health of ecosystems but also for achieving coordinated socio-economic development [4].

Since the implementation of the Law of the People’s Republic of China on the Prevention and Control of Water Pollution in 1996, China’s water pollution control has primarily emphasized improving water environmental quality, particularly through standardized wastewater discharge [5]. However, in 2021, the “14th Five-Year Plan for Water Ecological Environment Protection in Key Basins” innovatively proposed the “three-water” protection framework, uniting water environment, water resources, and water ecology [6], emphasizing a comprehensive problem analysis from economic development and ecological protection perspectives to promote the holistic protection and restoration of water ecosystems [7]. In 2022, the report of the 20th Party Congress explicitly highlighted the integrated management of water resources, water environments, and water ecology, marking a new development stage in China’s water environmental protection from pollution treatment toward an integrated governance of these three dimensions—resources, environment, and ecology [8]. Water resources, water environments, and water ecology form a closely linked, interactive organic whole [9]. Coordinated development among these “three-water” entities is crucial to sustainable economic and social progress, as inadequacies in any one aspect could yield negative impacts, necessitating ongoing attention and protective measures [10]. Water environments, resources, and ecology remain central and interdependent components of water ecosystems. Water quantity and quality directly determine environmental quality; excessive water exploitation or severe pollution, causing reduced quantity or degraded quality, disrupts environmental balance, leading to river desiccation, lake shrinkage, declining water tables, and ecosystem degradation. Water environment, resources, and ecology form the core of water ecosystems [11] and are mutually interdependent. A favorable water environment enhances water resource value and supports ecosystem health; sufficient water resources stabilize the environment and ecosystem, dilute pollution, and yield ecological benefits; healthy ecosystems protect water sources and water security [12]. In view of contemporary water resource management and challenges, prior research has predominantly concentrated on water pollution management, such as eutrophication from agricultural nonpoint source phosphorus pollution [13], and the impact of varying watershed characteristics on river water quality [14], without comprehensively addressing integrated governance. We adopted a novel perspective focused on multi-party governance collaboration involving government, enterprises, and the public [15,16]. With the Chaohu Lake Basin as the case study, we analyzed the performance and obstacles of “three-water” governance in the Chaohu Lake Basin.

Here, we constructed a performance evaluation index system for “three-water” based on the DPSIR model, incorporating socio-economic, ecosystem service, and remote sensing indicators from diverse perspectives. The model integrates causal analysis and multi-indicator decision-making methods, is both systematic and objective, and is capable of comprehensively evaluating the issues related to the “three-water” governance in the context of complex environmental governance and providing decision-makers with a clear and reasonable basis for choosing options. Using the TOPSIS model, we assessed performance and, through the obstacle degree model, identified barriers to effective “three-water” governance in the Chaohu Lake Basin. We further analyzed impediments within the basin “three-water” management, aiming to promote more integrated, systematic, and sustainable water resource management practices, ensuring harmonious coexistence between water resource protection and utilization [17,18].

Thus, water resource management and protection require comprehensive consideration of three dimensions—resource development, environmental protection, and ecological restoration to ensure their harmonious coexistence and sustainable development. Achieving “three-water” [19] involves scientific planning, rational allocation, effective pollution prevention and control, and ecological restoration measures, thus ensuring water-resource security, improving environmental quality, and maintaining and restoring healthy ecosystems [20].

Neil et al. suggest that effective water resource management is a global imperative and integral to achieving Sustainable Development Goals, noting that such management often transcends multiple disciplines [21]. Because water closely connects with society and the environment, integrated approaches and enhanced stakeholder participation are essential. They raise questions regarding whether Integrated Water Resource Management (IWRM) maintains a long-term perspective and serves effectively as a cross-sectoral platform, also questioning its sustainability or dependence solely on limited actors and international donors. Addressing the challenges of IWRM demands sustained efforts rather than short-term solutions [22]. Tomasz et al. observed that current IWRM frameworks in countries like Poland suffer from non-transparent processes, inadequate social participation in decision making, insufficient public oversight, and failure to adequately address stakeholders’ needs for decentralized decision making. However, surveys indicate that residents and entrepreneurs demonstrate interest in water management, suggesting potential to harness this social capital, alongside educated labor, for improved future governance [23].

2. Study Area

Chaohu Lake, located in the center of Anhui Province, is one of the five major lakes in the Yangtze River Basin (Figure 1). It consists of 39 rivers flowing into the lake and one river (the Yuxi River) exiting the lake. Its hydrological system shows clear spatial asymmetry, primarily composed of the Hangbu River, Baishitian River, Pai River, Nanfang River, Jiongyang River, and Zhegao River, which originate in the western and northern mountainous regions. Among these, the Hangbu, Baishitian, and Nanfang rivers are the principal tributaries, and their combined watershed areas account for about 75% of the Chaohu Lake Basin. The water system of Chaohu Lake exhibits a typical three-direction convergence pattern, where waters from the south, west, and north flow into Chaohu Lake, eventually draining into the Yangtze River through the southeastward-flowing Yuxi River. This configuration creates a large-scale, typical “river-lake” composite ecosystem. Due to long-standing water pollution, the Chaohu Lake Basin was included in China’s national “Three Rivers and Three Lakes” key management areas as early as 1996.

The Chaohu Lake Basin covers an area of approximately 13,486 square kilometers, encompassing Hefei City and its surrounding eight counties and districts, with a total population of about 11.87 million, representing 19% of Anhui Province’s population. The basin extends to the Jianghuai Watershed in the north, the Yangtze River in the south, the Dabie Mountains in the west, and the Chu River Basin in the east. This watershed has a high level of economic development, accounting for more than one-fourth of Anhui Province’s GDP. It serves as a crucial commercial grain production and processing hub and plays an essential role in sustainable regional water resource utilization and ecological environmental improvement [24]. However, it is also a significant pollutant-carrying area, posing risks such as high concentrations of nitrogen, phosphorus, salt, and other pollutants, potentially leading to eutrophic outbreaks [25]. Therefore, accelerating the integrated management of the Chaohu Lake Basin’s “three-water” is urgent.

In recent years, the average annual precipitation in the Chaohu Lake basin has ranged roughly from 1120 to 1215 mm, with the flood season (May to August) accounting for more than 60% of the annual total, and there are significant interannual differences. The average annual runoff of surface water is 5.97 billion cubic meters, and the amount of water entering and leaving the lake is 3.49 billion cubic meters and 3 billion cubic meters, respectively. In 2015, in China’s assessment of water pollution prevention and control in key river basins, the percentage of assessed sections in the Chaohu Lake Basin that met the standard was only 50%. The water quality was assessed as poor V, with some areas showing heavy eutrophication and extreme eutrophication. The aquatic ecosystem of the Chaohu Lake Basin suffered serious damage early on. The deterioration of water quality and destruction of wetlands led to a decline in biodiversity. The disappearance of some treasured fish species and the decline of waterbirds in the lake have led to an imbalance in the lake’s ecosystem due to the loss of its regulatory mechanism. Frequent cyanobacterial outbreaks not only lead to a decline in dissolved oxygen and deterioration of water quality but also seriously threaten aquatic organisms and human health.

3. Methodology and Dataset

3.1. Principles of the DPSIR Model

The DPSIR model is an indicator-based framework for assessing environmental systems, elucidating causal relationships between environmental states and human activities. The model comprises five interconnected subsystems: driving forces (D), pressures (P), states (S), impacts (I), and responses (R) [26]; its specific structure is illustrated in Figure 2. By constructing an index system based on this model, we intuitively assessed governance effectiveness in the Chaohu Lake Basin and evaluated the watershed ecosystem’s support for human societal development. Previous studies have successfully employed the DPSIR model to evaluate ecological security in areas such as Hunan Province, the Yangtze River Delta urban agglomeration, and Wenshan Prefecture, confirming its effectiveness. It focuses on the key issues in the current governance of “three waters”, such as the insufficient integration of data from multiple sources and the imperfect governance performance evaluation system. A comprehensive evaluation framework integrating water resources, water environment, and water ecology was constructed based on the DPSIR modeling system. This system realized dynamic, quantitative, and spatialized diagnosis of governance performance through the introduction of socio-economic indicators, ecosystem service assessment data, and multi-source remote sensing information, bridging the gap between the lack of comprehensiveness and operationalization of governance performance in existing studies [27,28,29]. Thus, applying the DPSIR model to evaluate the governance efficiency of the “three-water” approach in the Chaohu Lake Basin was appropriate and feasible.

3.2. Building a System of Governance Evaluation Indicators

Following the principles of policy relevance, scientific rigor, and systematic integrity [30], we developed an evaluation index system to measure the governance performance of the “three-water” initiative in the Chaohu Lake Basin. Our system, informed by previous studies [31,32,33,34] and based on the DPSIR model’s theoretical framework, included three layers: a target layer, subsystems, and indicator layer (

Table 1. Performance evaluation indicator system for “three-water” governance in Chaohu Lake Basin.

Target Level	Subsystems	Indicator Stratum (Units)	Meaning and Nature of Indicators	Acronyms
Performance Evaluation Indicator System for “Three-Water” Governance in Chaohu Lake Basin	Drive	GDP (CNY trillion)	Economic development as a driver for “triple water integration” governance (+)	D1
		GDP per capita (CNY)	Economic development as a driver for “triple water integration” governance (+)	D2
		Specialized water construction revenues (CNY 10,000)	Economic development as a driver for “triple water integration” governance (+)	D3
		Per capita disposable income of urban residents (CNY)	Standard of living in the characterization area (+)	D4
		Per capita disposable income of rural residents (CNY)	Characterize the standard of living in the county (+)	D5
		Annual precipitation (mm)	Annual precipitation fluctuations directly affect water stress (+)	D6
	Pressure	Urbanization rate (%)	Pressure of population agglomeration on governance performance in “triple water integration” ($-$)	P1
		Total industrial water withdrawal (10,000 m3)	Resource intensity of economic development ($-$)	P2
		Urban population density (persons/km2)	Population pressure on “triple water integration” governance ($-$)	P3
		Per capita daily domestic water consumption (liters)	Water intensity per capita ($-$)	P4
		Total industrial wastewater discharge (10,000 tons)	Characterize the pollution pressure of economic development on the water environment ($-$)	P5
		Volume of sewage discharged (10,000 m3)	Characterize the pollution pressure of economic development on the water environment ($-$)	P6
		Water quality exceeded (total phosphorus, mg/L)	Characterize the pollution pressure of economic development on the water environment ($-$)	P7
		COD emissions (tons)	Characterize the pollution pressure of economic development on the water environment ($-$)	P8
		Ammonia nitrogen emissions (tons)	Characterize the pollution pressure of economic development on the water environment ($-$)	P9
	State	Gross output value of agriculture, forestry, and fisheries (CNY trillion)	Indirect characterization of improved water quality and optimization of industrial structure (+)	S1
		Total water resources (trillion m3)	Characterization of regional water resources (+)	S2
		Water resources per capita (m3/person)	Characterization of water allocations (+)	S3
		Total volume of water supplied by water supply projects (10,000 m3)	Characterization of regional water resources (+)	S4
		Green space ratio in built-up areas (%)	Indirect characterization of the water ecological status of the area (+)	S5
	Response	Share of investment in fixed assets in the water, environment, and utility management sector (%)	Characterization of government funding for “three-water” governance (+)	I1
		General public budget expenditure on energy conservation and environmental protection (CNY ten thousand)	Characterization of government funding for “three-water” governance (+)	I2
		General public budget expenditure on science and technology (CNY ten thousand)	Characterization of government funding for “three-water” governance (+)	I3
		Integrated production capacity of water supply (10,000 m3/day)	Capacity to characterize governance for “triple water integration” (+)	I4
		Investment in fixed assets for the construction of water supply facilities (CNY trillion)	Capacity to characterize governance for “triple water integration” (+)	I5
		Investment in fixed assets for the construction of drainage facilities (CNY trillion)	Capacity to characterize governance for “triple water integration” (+)	I6
		Investment in fixed assets for the construction of sewage treatment facilities (CNY trillion)	Characterization of government funding for “three-water” governance (+)	I7
		Daily capacity of sewage treatment plants (10,000 m3/day)	Capacity to characterize governance for “triple water integration” (+)	I8
	Influence	Quantity of water reused (10,000 m3)	Characterize the impact of “triple water integration” governance on the productive capacity, use and sustainability of water resources (+)	R1
		Total number of reservoirs (number)	Characterize the government’s response to urban “triple water integration” governance (+)	R2
		Irrigated arable land (thousands of hectares)	Characterization of water resources for land use in the region ($-$)	R3
		Sewage treatment rate (%)	Characterize the performance of “triple water integration” governance (+)	R4
		Number of water plants (number)	Characterize the government’s response to urban “triple water integration” governance (+)	R5

Note: (+) represents a positive indicator, the larger the value, the better the result; ($-$) represents a negative indicator, the smaller the value, the better the result.

). Through the closed-loop mechanism of systematic framework, dynamic coupling analysis, and scientific quantitative method, the model breaks through the traditional single-dimension evaluation and solves the problem of subjectivity, providing technical support for the synergistic promotion of water resources security, water environment management, and water ecology protection, and at the same time providing an accurate decision-making basis for the governance of complex water systems. The target layer represents the overall performance of the Chaohu Lake Basin in managing the integrated approach to water resources, environment, and ecology (“three-water”). The subsystems correspond directly to the five DPSIR model components. The indicator layer, comprising specific measurable indices, formed the foundation for assessment. After reviewing the relevant literature, selecting frequently utilized evaluation factors, and considering the availability of data, we finalized a 33-indicator evaluation system (Table 1). The primary data were obtained from each county’s Statistical Yearbook, Water Resources Bulletin, and City Building Statistics Yearbook, and raster data on precipitation, temperature, and net primary productivity (NPP) were integrated. Ecological indicators included vegetation cover calculated through NDVI, and biodiversity, water conservation, and soil conservation capacity were assessed in accordance with the Guidelines for the Delineation of Red Line for Ecological Protection.

Driving forces describe long-term societal or natural factors affecting “three-water” governance (water resources, water environment, water ecology) [35,36,37,38], such as climate change and economic growth. Pressures represent direct societal or natural disturbances, such as pollution emissions, population growth, and excessive water resource utilization, reflecting disturbance intensity [39,40,41]. States indicate the overall health of “three-water” governance, including water supply capacity, storage levels, and ecological conditions, which are combined into state indicators that reflect environmental quality [42,43]. Impacts assess changes and adjustments in the “three-water” system due to pressures, highlighting the system’s response to disturbances [44,45]. Responses involve adaptive actions and long-term strategies adopted by society to enhance “three-water” governance under pressure [46].

Drivers, pressures, and impacts are disturbance factors, classified into natural (e.g., climate change) and societal (e.g., economic development) sources. State indicators relate directly to water resource status (quantity and quality) and ecological health (e.g., biodiversity). Response indicators measure system resilience, improvement actions (e.g., pollution control, ecological restoration), and management strategies (e.g., policies, regulations, public participation). Specific evaluation criteria were established for each aspect to form a comprehensive indicator framework.

3.3. Entropy Weighted TOPSIS Modeling

The entropy-weighted TOPSIS model integrates the strengths of the entropy weight method and the TOPSIS technique by using information entropy to objectively determine the weights of each evaluation index. The greater the variation in an index, the higher its weight and its corresponding influence on decision making [47]. The TOPSIS method evaluates the distance between each assessment object and an “ideal solution,” ranking the objects based on their proximity to this ideal [48,49]. In our study, we determined the weights for each index using the entropy weighting method and subsequently applied the TOPSIS technique to calculate the performance indices for “three-water” governance among districts and counties in the Chaohu Lake Basin [50,51]. Compared to traditional TOPSIS, this entropy-weighted method yields more objective results. The equations are as follows:

Positive indicators:

$$x_{ij}^{+}={\displaystyle \frac{x_{ij}-min{x}_j}{max{x}_j-min{x}_j}},$$

(1)

Negative indicators:

$$x_{ij}^{-}={\displaystyle \frac{max{x}_j-x_{ij}}{max{x}_j-min{x}_j}},$$

(2)

The lower the entropy value, the richer the information of the indicator, indicating greater variability and thus higher weight:

$$e_j=-{\displaystyle \frac{1}{\mathit{ln}m}}{\sum }_{i=1}^m\left(f_{ij}\mathit{ln}{f}_{ij}\right),$$

(3)

Norm weights $w_j$:

$$w_j={\displaystyle \frac{1-e_j}{{\sum }_{j=1}^n\left(1-e_j\right)}},$$

(4)

Entropy weight $w_i$ construct a weighted normalized evaluation matrix ($Y$):

$$Y=X_{\left\{IJ\right\}}\times W\left(\begin{array}{ccc}{y}_{11}& \dots & y_{1n}\\ ⋮& \ddots & ⋮\\ y_{m1}& \dots & y_{mn}\end{array}\right)$$

(5)

The main steps of the TOPSIS method are as follows:

Water-Carrying Capacity Analysis Matrix:

$$Y={\left(y_{ij}\right)}_{m\times n}={\left[W_j\times X_{ij}\right]}_{m\times n},$$

(6)

Positive and negative ideal solution vectors $Y^{+}$ and $Y^{-}$:

$$Y^{+}=max\left(y_{1j},y_{2j},\dots ,y_{mj}\right) ,$$

(7)

$$Y^{-}=min\left(y_{1j},y_{2j},\dots ,y_{mj}\right),$$

(8)

European distance $D_i^{+}$ and $D_i^{-}$:

$$D_i^{+}=\sqrt{{{\sum }_{j=1}^n\left(Y_j^{+}-y_{ij}\right)}^2 },$$

(9)

$$D_i^{-}=\sqrt{{{\sum }_{j=1}^n\left(Y_j^{-}-y_{ij}\right)}^2 },$$

(10)

Proximity $C_i$:

$$C_i={\displaystyle \frac{D_i^{-}}{D_i^{+}+D_i^{-}}} ,$$

(11)

$C_i$ ∈ [0, 1]: The larger the value of $C_i$, the higher the WRCC score, and, thus, the stronger regional three-water support for human activities.

3.4. Barrier Degree Model

Ecological health is influenced by various factors. By applying the barrier degree model to our index system, we identified key obstacles affecting “three-water” governance in the Chaohu Lake Basin, thereby providing targeted policy guidance for sustainable development. The calculation is as follows:

$$D_{ij}=\left(1-x_{ij}^{+}\right)w_j ,$$

(12)

$$H_{ij}={\displaystyle \raisebox{1ex}{$D_{ij}$}\!\left/ \!\raisebox{-1ex}{${\sum }_{j=1}^n{D}_{ij}$}\right.},$$

(13)

where $x_{ij}^{+}$ is the normalized value; $w_j$ is the weight of each indicator; $\left(1-x_{ij}^{+}\right)$ is the deviation of each indicator; and $H_{ij}$ is the handicap.

3.5. Data Sources and Processing

The data that we used in our study were obtained from official statistical publications covering 33 indicators across demographic, economic, social, resource, and environmental domains, spanning the period from 2011 to 2022. Primary data sources included statistical yearbooks, water resource bulletins, and urban construction statistical yearbooks of respective counties. Additionally, raster datasets, such as precipitation, temperature, and net primary productivity (NPP), were integrated. Ecological indicators incorporated vegetation cover computed via NDVI, biodiversity assessments, and water and soil conservation capacities, evaluated according to the Guidelines for the Delineation of Ecological Protection Red Line. Data source links: China County Statistical Database (annual data version); Ministry of Housing and Urban-Rural Development, PRC; Ministry of Agriculture and Rural Affairs, PRC; Water Resource Bulletin of Anhui Province. The performance index for the management of the “three-water” approach in the Chaohu Lake Basin was represented as an average of district and county performance scores to ensure data representativeness and scientific accuracy. Compared with other studies, it is the first time that the DPSIR model was used to construct a performance evaluation system for the governance of the “three-water” by combining the indicators of water resources security, water environment management, and water ecological security. Assessment was conducted using the TOPSIS model, and analysis of barriers in the management of the Chaohu Lake watershed was conducted using the barrier degree model.

4. Results

4.1. Governance Performance

4.1.1. Characteristics of Temporal and Spatial Changes in Overall Governance Performance

According to Figure 3, in 2011, the economic development of counties and regions was relatively slow, governance capacity for the “three-water” was weak, so the pressure of water environment pollution was relatively severe. In 2011, the area of cyanobacterial bloom in the western lake area of Chaohu Lake remained high, and the area of bloom in the central and eastern lake areas also showed an increasing trend. Of the 19 sections of the 11 rivers around Lake Chaohu, 31.6% had water quality in the inferior five categories, indicating that the water quality was in a state of heavy pollution. Among these, the response indices of Feixi County and Shucheng County were relatively high, with composite indices of 0.308 and 0.298, respectively, indicating that these areas were more proactive in responding to environmental issues. By 2014, the governance capacity of He County and Feixi County regarding the “three-water” improved significantly compared to other counties and districts, with composite indices of 0.368 and 0.366. It may have originated in He County, which completed the treatment of 36 rural black-smelling water bodies through the establishment of a three-tier water treatment network for counties, towns, and villages, with the treatment rate exceeding 78.2%. As a county under the jurisdiction of Hefei city, Feixi County, relying on Hefei’s “westward and southward” strategy, has set up a platform for industrial development, laying a foundation for the introduction of advanced technology and management mode for water environment treatment. Other counties in the Chaohu Basin have also made progress in terms of policies, regulations, and management projects and have not lagged significantly behind He County and Feixi County. In 2017, the governance capacities of Henshan County, Feidong County, and Shucheng County further improved, with composite indices of 0.455, 0.362, and 0.3462, respectively, indicating that these districts responded more actively to environmental challenges. Additionally, the driving force indices of counties significantly increased, suggesting that economic development in these areas had shown substantial progress. By 2020, most counties and districts in the Chaohu Lake Basin exhibited notable improvements in subsystem indicators, and the governance performance of the “three-water” began yielding results. It is because the Regulations on the Prevention and Control of Water Pollution in the Chaohu Lake Basin were revised and implemented for the second time in 2019, which unified the norms of watershed management through legal means and promoted the counties and districts to strengthen the management of sewage discharge behavior. Nevertheless, Shucheng County, Feixi County, Wuwei City, and Baohe District continued to face certain challenges, requiring further improvement. By 2022, the “three-water” governance performance in the Chaohu Lake Basin achieved remarkable outcomes, with the overall governance performance index reaching 0.718. Environmental pressures in counties and districts decreased significantly, and the weight of impact factors increased notably, indicating that economic development proceeded alongside effective environmental protection. This is due to the fact that in 2021 the government initiated 136 comprehensive Chaohu Lake management projects with a total investment of CNY 8.81 billion, focusing on strengthening the construction of urban and rural sewage treatment facilities. It also completed over CNY 5 billion of investment in governance projects for key rivers such as the Nanfei River, the Fifteen Mile River, and the Pai River.

From the perspective of spatial distribution patterns, counties and districts located at the sources of major rivers and lake outlets, such as Baohe County, Feixi County, and Chaohu City, performed notably worse in the “three-water” governance system compared to other regions in the basin. This is due to the fact that most of the origins are in mountainous areas or water-shedding zones, with complex topography and fragile ecology, making cross-regional synergy and governance more difficult. There are historical problems such as eutrophication and sediment pollution in the outflow area, and the treatment requires systematic engineering support, which is difficult to be effective in the short term. The composite indices for these three locations in 2022 were 0.623, 0.604, and 0.596, respectively, which are lower than the overall governance performance index of the Chaohu Lake Basin. The state and response indices in some counties and districts remained relatively low, indicating differences in governance performance among regions. Thus, future coordination must be further strengthened to promote synergistic development in the Chaohu Lake Basin and achieve a more comprehensive balance between environmental and economic interests.

4.1.2. Spatial and Temporal Variation in Subsystem Governance Performance

Using the entropy weight method, we processed 62 indicators reflecting governance performance of the “three-water” in the Chaohu Lake Basin from 2011 to 2022. The evaluation index of each subsystem is shown in Figure 4. The driving force index steadily increased from 0.0428 in 2011 to 0.844 in 2022, indicating significantly enhanced capacity in the basin to promote the management of water resources, water environments, and water ecology. Concurrently, rapid economic development increased social participation. The stress index displayed a slight downward trend, signifying higher environmental pressure during the early stages of water management, likely due to resource consumption and pollution resulting from rapid urbanization and industrialization. However, as governance measures were gradually implemented, these pressures effectively decreased. The state index fluctuated notably, increasing from 0.209 in 2011 to 0.582 in 2022. This considerable fluctuation indicated the systematic improvement and optimization of water resources, water environments, and water ecology in the basin, with gradually emerging governance effectiveness. The impact index exhibited slight fluctuations between 2011 and 2015 but significantly rose after 2017, reaching 0.789 in 2022. This trend suggested increasingly positive impacts of governance measures on the ecological environment and socioeconomic conditions, especially in later years. The response index steadily increased from 0.249 in 2011 to 0.768 in 2021. This trend reflected enhanced responsiveness within the basin to issues related to water resources, water environments, and water ecology, supported by effective policy implementation and governance measures.

Overall, the Chaohu Lake Basin effectively alleviated environmental pressures, significantly improved the state of water resources, water environments, and water ecology, and achieved positive governance outcomes by strengthening driving forces and response measures from 2011 to 2022. This indicated that the implementation of integrated management strategies produced remarkable results and laid a solid foundation for future sustainable development.

Figure 5 and Figure 6 illustrate the changes in comprehensive evaluation indices and the five subsystems in counties and districts concerning governance performance of the “three-water” in the Chaohu Lake Basin from 2011 to 2022. During the 12th Five-Year Plan period, comprehensive evaluation indices of each county exhibited fluctuating upward trends, reflecting the gradual implementation and initial effectiveness of governance measures. During the 13th Five-Year Plan period, as “three-water” governance measures advanced further, the comprehensive evaluation index steadily increased, highlighting significant progress by counties and districts in water resource management and environmental protection.

With the continuous optimization of governance measures and strengthened policy support in 2021–2022, the comprehensive evaluation index improved further, reflecting ongoing progress and enhancement in the counties’ and districts’ governance performance in the “three-water.” Feixi County, Lujiang County, Shucheng County, Henshan County, He County, and Wuhui City exhibited higher pressure indices between 2011 and 2015, reaching 0.612, 0.595, 0.622, 0.558, 0.731, and 0.554, respectively, in 2015; these indices began gradually declining after 2016. This suggested that these counties and districts faced significant governance pressure in the early stages of the “three-water,” likely due to water consumption and pollution associated with rapid urbanization and industrialization. However, with the gradual implementation of governance measures, pressure on the water environment was effectively reduced, and water resource utilization efficiency markedly improved.

The driving force index for each county and district exhibited a steady upward trend from 2011 to 2022. For instance, the 2022 driving force indices for Wuwei City, Hanshan County, Heshan County, Shucheng County, and Chaohu City were all above 0.9. This substantial increase indicated significantly enhanced impetus for promoting the management of water resources, water environment, and water ecology, bolstered by improvements in policy support, technological innovation, and social participation, laying a solid foundation for integrated “three-water” management. The state indices of Chaohu City, Feidong County, Feixi County, Shucheng County, Hexian County, and Wuwei City fluctuated upward, suggesting the systematic repair and optimization of water resources, water environment, and water ecology, as well as initial demonstrations of effective governance.

The impact index of each county continued to rise between 2011 and 2022, with Hanshan County, Shucheng County, Lujiang County, and Feidong County reaching values above 0.7 by 2022. This increase reflected considerable improvements in regional responsiveness to issues involving water resources, water environment, and water ecology, with the enhanced relevance and implementation of governance measures, policy execution, and social participation.

The response indices of Baohe District, Feixi County, Lujiang County, and Wuwei City rose consistently between 2011 and 2022, reaching 0.619, 0.642, 0.776, and 0.677, respectively, in 2022. These values reflected notably improved responsiveness in addressing issues of water resources, water environment, and water ecology within the Chaohu Lake Basin, highlighting increasingly targeted and effectively implemented governance measures, enhanced policy implementation, and improved social participation. However, the response indices for Chaohu City, Shucheng County, Hanshan County, and He County significantly declined during the 13th Five-Year Plan period before recovering to 12th Five-Year Plan levels by 2022. This pattern indicated that the governments of these counties should continue increasing financial support to address water consumption and pollution stemming from industrialization and urbanization, thereby improving water resource utilization efficiency.

4.2. Diagnosis of Governance Performance Barriers

4.2.1. Diagnosis of Factors Impeding Governance Performance

According to Figure 7, the driving force obstacle degree for the Chaohu Lake Basin was 24.5% in 2011, subsequently decreasing annually to 4.9% by 2022. This trend indicated a significant reduction in the barrier effect of driving forces on governance performance, highlighting positive impacts from economic development and policy promotion. The stress barrier degree was 10.7% in 2011 but increased notably after 2017, reaching 45.1% by 2022. This persistent rise underscored environmental pressure as an increasingly significant barrier to governance effectiveness, warranting ongoing attention. The state barrier degree was 20.5% in 2011, subsequently showing a fluctuating downward and upward pattern and ultimately reaching 24.3% in 2022. This oscillation indicated a non-linear governance trajectory, suggesting temporary improvements followed by renewed obstacles that prevented sustained progress. The impact barrier percentage was about 24.4% in 2011, increasing to 25.7% in 2014, declining to 20.5% in 2020, and significantly dropping to 11.6% in 2022. Overall, the decreasing trend of impact factors throughout the study period highlighted persistent environmental pressures faced by the “three-water” governance efforts. The response barrier percentage gradually declined from about 19.9% in 2011 to 14.1% in 2022, suggesting reduced government investment in “three-water” governance performance, implying a need for the sustained or increased future allocation of financial and human resources.

Collectively, drivers and impacts diminished over the study period, while stress and state factors increased. The response factor also exhibited a general downward trend, suggesting gradually weakening systemic or environmental responses to drivers and impacts during the study period, alongside increasingly prominent stress factors.

4.2.2. Factor Analysis of Governance Performance Barriers

Using the obstacle degree model to evaluate the governance performance of the Chaohu Lake Basin’s “three-water” between 2011 and 2022, we processed 33 indicators to determine obstacle levels in each subsystem (Figure 7 and Figure 8). The obstacle degree exhibited distinct trends across subsystems during the study period.

The driving force obstacle degree displayed a downward trend in most regions, with significant declines observed particularly in 2022. For instance, in Shucheng County, the obstacle degree decreased markedly from 31.6% in 2011 to 0.1% in 2022; similarly, in Baohe District, it decreased from 31.63% to 6.2%. These declines suggested that rapid economic growth and improved per capita economic indicators substantially enhanced governance driving forces, although variations in policy support and social participation were evident.

Conversely, pressure obstacle degrees increased consistently across most counties, except in Chaohu City, especially, notably, in 2022. For example, in Hexian County, the pressure obstacle degree rose sharply from 10.2% in 2011 to 50.3% in 2022, and, in Wufei City, it rose from 5.1% to 60.8%. These increases indicated intensifying environmental pressures, likely attributable to resource consumption, pollution stemming from urbanization and industrialization, and growing populations.

The state obstacle degree varied distinctly by region. In Lujiang County, it initially decreased from 24.1% in 2011 to 19.9% in 2017 but rebounded to 33.3% by 2022. Conversely, in Wuwei City, the obstacle degree increased marginally from 23.5% to 23.8% between 2011 and 2017 but subsequently decreased significantly to 13% in 2022. These variations suggested fluctuations in water resources, water environment, and water ecology conditions over different periods, reflecting regional disparities in governance effectiveness.

The impact obstacle degree generally declined across most counties and districts, particularly in 2022. Significant reductions were observed in Feixi County—from 25.5% in 2011 to 16.3% in 2022—and in Feidong County—from 24.8% to 11.4% over the same period. These decreases indicated diminishing positive impacts of governance measures on the ecological environment and socioeconomic conditions in the later stages, suggesting a potential need for further governmental optimization of management strategies.

The response obstacle degree varied among counties and districts. For example, in Shucheng County, it increased from 4.4% in 2011 to 12.8% in 2022, whereas, in Baohe District, it decreased significantly from 18.7% to 6.5%. These differences highlighted varying regional responsiveness to challenges associated with water resources, water environment, and water ecology—indicating strengthened responsiveness in certain districts while weakening in others.

Collectively, the charts and tables illustrated clear trends and shifts in the governance performance of the “three-water” initiative in the Chaohu Lake Basin from 2011 to 2022. After long-term tracking and analysis, we distinctly observed substantial progress as well as ongoing challenges concerning water resource utilization, environmental protection, and ecological restoration across individual counties. Although certain counties and districts achieved remarkable outcomes, further strengthening policy support and responsiveness remains necessary to effectively address escalating environmental pressures. The continued optimization of comprehensive governance measures and deepening of cooperative strategies among multiple stakeholders are recommended to sustainably manage and improve water resources, water environments, and water ecology within the basin.

5. Policy Recommendations

5.1. Facing Up to Regional Differences and Promoting Synergistic Development

In its 2015 Action Plan for the Prevention and Control of Water Pollution, China clearly put forward the requirement of “integrating water resources, water environment and water ecology”. There are significant differences among counties in the governance of the Chaohu Lake Basin (Figure 3), and differentiated strategies are needed to promote coordinated regional development. The government should promote cross-regional cooperation in water governance through collaboration on policy making, technology development, experience sharing, and regular discussions on governance challenges and opportunities to achieve efficient regional governance. For example, the 2020 Law on the Protection of the Yangtze River proposes to “establish a basin coordination mechanism” and “strengthen cross-regional ecological compensation”. On one hand, communication and cooperation among counties should be strengthened, making full use of each county’s characteristics and advantages to form a favorable pattern of staggered and complementary development. On the other hand, attention must be paid to counties such as Hexian County, Feixian County, Chaohu City, etc., where the level of governance is below the watershed average. Focus should be placed on controlling sewage and industrial wastewater discharges, improving assistance mechanisms, increasing policy and resource support, and continuously expanding investment in water conservancy construction. Specialized investments should be directed to help these areas achieve balanced development and narrow the regional gap.

5.2. Give Full Play to the Radiation Effect of High-Level Counties and Districts and Deepen Regional Linkages

In 2019, the second revision of the “Chaohu Lake Basin Water Pollution Prevention and Control Regulations” clarified that the Chaohu Lake Basin implements a hierarchical protection system, which requires collaborative management by counties and districts and stipulates specific measures such as “ecological compensation mechanism” and “sewage rights trading”. Based on the problems with the comprehensive evaluation of governance performance in the regions (Figure 5 and Figure 6), efforts should be made to maximize the demonstration and radiation effect of high-level counties in the governance of “three-water.” This includes promoting the interaction and coordination of governance activities among counties to drive surrounding areas toward leapfrog development. Local governments and social organizations can utilize digital platforms to efficiently disseminate information, share data and experiences, and easily access and learn from best practices. Like Hefei City, the “14th Five-Year Plan” ecological environmental protection plan put forward the “digital Chaohu” construction, industrial pollution deep treatment, agricultural pollution prevention, the control of surface pollution, and other tasks. Counties and districts with more advanced economic development can provide financial support, strengthen regional water environment planning, export water supply and drainage technology, and cultivate water management talent. By doing so, they can foster cooperation and exchange, and disseminate mature management experience. This will in turn promote industrial upgrading and economic development in counties and districts with lower levels of “three-water” management, allowing them to integrate and share resources and complement one another’s strengths.

On one hand, economic and scientific-technological achievements should be spatially diffused, the potential for scientific and technological innovation should be unleashed, fixed asset investment in “three-water” governance should be increased, and new momentum should be injected into governance efforts. On the other hand, the transfer and structural optimization of crude industries should be actively promoted, the efficiency of water resource allocation should be improved, and the coordinated development of the regional economy and ecology should be advanced.

5.3. Focus on Obstacle Factors and Optimize Governance Strategies

Based on the degree of obstacles in the governance performance subsystem in each region (Figure 8), close attention should be paid to key obstacle factors in the governance of the Chaohu Lake Basin, especially emissions of the “three wastes,” water consumption, and other prominent issues. In the short term, the high-quality development of governance can be promoted by increasing financial investment in fixed assets for constructing water supply and drainage facilities, improving the comprehensive production capacity of water supply, expanding public budget expenditures on energy conservation, environmental protection, and science and technology, increasing the number of wastewater treatment plants to raise the wastewater treatment rate, and increasing green space coverage. At the same time, optimizing the industrial structure and promoting GDP growth should also be prioritized.

In the long term, it is necessary to continue promoting the dual-cycle development strategy, deepen market-oriented reforms, and unlock the growth potential of domestic demand to provide sustained momentum for the governance of the “three-water.” Additionally, all counties and districts should focus on their major individual obstacles, implement precise countermeasures, and address deficiencies, forming a new pattern of joint promotion and shared progress in governance of the “three-water” in the Chaohu Lake Basin.

5.4. Explore the Regional “Three-Water” Governance Model

Global water scarcity and environmental pressures are increasing. Each river basin should, according to its own resource conditions and ecological characteristics, explore and establish a “three-water” governance model suitable for its region, such as the ecological compensation mechanism for the Taihu Lake basin and the “digital hydrology” system for the Pearl River basin. Cities with a high level of governance can leverage modern information technology to build intelligent water resource management systems, enabling the real-time monitoring and smart scheduling of water resources. For example, big data analysis can be used to forecast water demand, optimize supply strategies, improve utilization efficiency, and reduce waste. Emphasis should be placed on protecting water ecology, promoting rainwater management and water quality improvement, implementing “source management,” reducing pollutant discharge, and safeguarding the ecological health of water bodies.

At the same time, regional water-sharing mechanisms should be explored to promote cross-regional scheduling and efficient utilization, thus mitigating the risk of water shortages. For cities with lower levels of governance, priority should be given to improving infrastructure, such as water supply systems, sewage treatment plants, and drainage networks. Infrastructure development should be advanced through government investment and public–private partnerships to enhance water resource deployment and treatment capacity. Industrial and agricultural pollution must be strictly controlled through rigorous sewage discharge standards, and green agricultural development should be promoted. Public awareness campaigns should be strengthened to promote water conservation and environmental protection, along with education on water resource preservation. Finally, the rational allocation and protection of water sources should be ensured to achieve high-level integrated management. International experiences draw on global watershed governance models such as the International Commission for the Protection of the Rhine (ICPR), the Chesapeake Bay Program in the United States, and Lake Biwa governance in Japan.

6. Conclusions

Based on the DPSIR framework, we integrated the TOPSIS evaluation method and the barrier analysis and constructed a performance evaluation system covering 33 indicators for the “three-water integration” governance of the Chaohu Lake Basin. This study not only realizes a systematic portrayal of the performance from 2011 to 2022 but also analyzes the inner mechanism of the complex governance system. The main conclusions are as follows:

(1)

Realize the theoretical leap from “single water environment management” to “systematic synergistic performance assessment”. This paper breaks through the limitations of previous single-pollutant control or single-sector assessment, incorporates ecosystem pressure, state and response into a unified analytical framework based on the DPSIR-TOPSIS model, and for the first time carries out a study of the spatio-temporal evolution of performance under the “three-water” scenario. This study found that watershed governance performance is generally good, but there are significant spatial imbalances. In particular, the “upstream–downstream” and “urban–rural interface” regions are typically characterized by a disconnect between responsibility and response, revealing structural tensions between the current performance appraisal mechanism within administrative boundaries and the overall governance of the watershed.

(2)

The coupled evolution mechanism of “five major subsystems” in the governance of the “three-water” is revealed. This study takes the subsystem as the profile, reflecting the dynamic transformation logic of the watershed development–governance relationship—from “pressure-driven” to “responsive checks and balances” and from “elemental platter” to “systemic synergy”. High-performing regions rely on the two-way feedback mechanism of “data-driven + institutional regulation” to form a closed loop of governance, while low-performing regions reveal deeper dilemmas, such as lagging technology application and weak policy transmission capacity, which provide a mechanism to guide the bridging of regional governance gaps in the future.

(3)

Construct the obstacle diagnosis logic of “problem orientation—factor tracing—path optimization”. The barrier degree analysis not only identifies key constraints such as industrial wastewater, water intensity, and sewage treatment, but it further explains the hidden structural dilemmas behind these factors, such as lagging behind in the upgrading of traditional industries, the slow promotion of residents’ awareness of water conservation, and insufficient capacity for infrastructure operation and maintenance. Based on this, it is necessary to form a synergistic governance strategy with “policy guidance–technical support–social mobilization” as the core and promote the governance of water resources, water environment, and water ecology from “engineering-driven” governance to a “people–technology system”. This is a multi-dimensional co-governance transformation.

(4)

Promote the construction of a long-term mechanism to move from “short-term performance” to “governance modernization”. The “three-water” of the Chaohu Lake Basin is not only concerned about the improvement of short-term governance performance but also committed to the construction of a long-term mechanism. Comparing the policy texts of the three Five-Year Plans, it is found that the policy objective of “three-water” has gradually moved from “pollution control” to “ecological restoration” and “systemic balance”. This reflects a fundamental change in the concept of watershed management. For example, in 2022, the “Chaohu Lake Basin Water Pollution Prevention and Control Regulations” were revised to include the “ecological flow guarantee” clause for the first time, marking a shift in the concept of governance from “anthropocentric” to “ecocentric”. At the same time, the main body of governance has evolved from “single government supply” to “multiple governance”, and the synergistic roles of the public and enterprises have become more and more prominent, gradually forming a new paradigm of “technology empowerment–institutional leadership–social participation”. The new paradigm of modern watershed governance is gradually formed by “technology-enabled, system-led social participation”. The social governance tools represented by the “environmental protection points” and other institutional innovations mark a new stage in China’s watershed governance of “building and sharing”.