1. Introduction
Hangzhou Bay, located in the northeastern part of the Zhejiang Province of China, and being the second largest bay area of the country, serves as a core development area of the Yangtze River Delta. Over the years, due to rapid industrialization, the Hangzhou Bay Economic Zone in particular has been seen to be significantly contributing to the growth in economy, which accounts for about 68% of the total economic output of Zhejiang Province, mainly from 78% of the domestically listed high-tech companies (75% of which are China’s top 500 private enterprises). Consequent to these, the area has undergone accelerated urbanization and has witnessed challenges related to them. From amongst many of these challenges, pollution of the Hangzhou Bay waters resulting from a continuous increase in discharge of the domestic waste water and industrial effluents into the Bay due to insufficient wastewater treatment capacity has been a major concern; hence, this has intensified the pressure for water governance in the region [
1]. According to the Ecological Environment Condition Reports of Zhejiang Province for the recent years, the water quality in the nearshore waters of the Hangzhou Bay area has remained at Class IV, indicating a “poor” ecological environment state, persistently. In the new era, it is of strategic significance for our region to take measures to ensure water safety, ecological health, and a livable water environment.
Hangzhou Bay extends from the Cao’e River weir section between Ganpu Town in Haiyan County and Shangyu District in the west to the line connecting Yangzi Point and Zhenhai Point in the east, adjacent to the waters of Zhoushan and Beilun Port. It is bordered by Shaoxing City to the west, Ningbo City to the east, and Jiaxing City and Shanghai City to the north. The bay is a trumpet-shaped estuary where the Qiantang River and Cao’e River converge. The scope of this study includes Hangzhou City, Ningbo City, Shaoxing City, Jiaxing City, and the nearshore waters of the Hangzhou Bay area, extending from Shanghai in the north to Zhoushan in the south and to the mouth of the Qiantang River in the west, as shown in
Figure 1.
Environmental protection and pollution control have been common challenges faced by countries around the globe in the process of industrialization. Many Western countries encountered severe environmental problems and large-scale pollution incidents during their rapid industrialization in the late 19th century, such as the 1930 Meuse Valley event in Belgium, the 1943 Los Angeles photochemical pollution event in the United States, and the 1986 Rhine River pollution incident [
2,
3]. Rachel Carson’s book “Silent Spring” in 1962 highlighted the widespread pollution and ecological damage caused by overindustrialization, triggering a broader understanding of the conflicts between economic development and environmental protection. The concept of sustainable development was subsequently introduced in the 1972 report by the Club of Rome titled “Limits to Growth”. It emphasized the need for shared responsibility in managing the contradiction between environmental degradation and economic progress. Recognizing the importance of water environment governance, the Chinese government has implemented various measures to address the challenges in the Hangzhou Bay area. Initiatives such as the “Zhejiang Coastal Waters Pollution Prevention and Control Plan” and the “Hangzhou Bay Regional Pollution Comprehensive Treatment Plan” were introduced in 2013. Subsequently, the “Zhejiang Marine Environmental Pollution Special Treatment Work Plan” was implemented in 2016. In 2019, the “Hangzhou Bay Pollution Comprehensive Treatment Campaign Implementation Plan” was launched, aiming to address ecological and environmental issues and support the development of a world-class modern bay area in the Zhejiang Province [
4]. In 2022, the “Key Waters Comprehensive Treatment Campaign Action Plan” was introduced, focusing on Hangzhou Bay, coastal cities, and their management waters. The plan aims to control pollution sources, improve water quality in nearshore areas, protect estuarine habitats, and promote the high-level protection of the marine ecological environment, thereby facilitating the integrated development of the Yangtze River Delta region [
5]. Therefore, it is very important to analyze the performance of Hangzhou Bay water management and its influencing factors.
In this study, the performance evaluation of water environment governance is approached from the perspective of the DEA–Tobit model. It comprehensively considers multiple input–output variables to measure governance efficiency and takes into account various external factors such as socio-economic factors, industrial development, and population density. The aim is to determine the causal relationship between the water governance performance in the Hangzhou Bay area and these influencing factors in order to reflect the long-term impacts of water environment governance on socio-economic and resource development within the region. Our workflow is illustrated in
Figure 1. This study focuses on the assessment of water environmental governance performance in the Hangzhou Bay region. Firstly, we collected water environmental governance data such as the expenditure on agricultural, forestry, and water affairs and the sewage treatment rate from 2011 to 2021 in the region. Then, we utilized the Super-Efficiency data envelopment analysis (SE-DEA) model combined with the Tobit model to evaluate the performance of the region in water environmental governance. Finally, based on the research findings, we developed an innovative model for water environmental governance using the Triple Helix theory and proposed recommendations for optimizing water environmental governance.
The rest of this paper is organized in the following way.
Section 2 reviews the related literature.
Section 3 describes the data and methodology in detail.
Section 4 presents the results and discussion.
Section 5 provides the main conclusions.
2. Literature Review
The evaluation of water environmental governance performance, as an important tool in environmental management, originated from the United States with the passage of the Clean Water Act in 1972 [
6], which marked the beginning of efforts to protect and manage water bodies. This act established regulations for the management and limitation of water quality, making the evaluation of water environmental governance performance a necessary task. Subsequently, in 1990, the U.S. Environmental Protection Agency developed the Total Maximum Daily Load (TMDL) program, which was further supported by related rules published in 1992 [
7]. This program established water quality goals and assessed the improvement of water quality through monitoring, modeling, and analysis, thus becoming an important method for evaluating water environmental governance performance. During the same period, the European Union began formulating the Water Framework Directive, which stipulated comprehensive management and protection measures for water bodies [
8]. The directive required member states to classify and assess water bodies within their territories and set water quality objectives and deadlines, and became an important standard for evaluating water environmental governance performance. Since then, the evaluation of water environmental governance performance has been incorporated into systematic research, yielding substantial results over the past few decades.
The research on water environment governance performance includes the construction of indicator systems, evaluation of various subsystems of water environment governance, analysis of driving forces, and their applications. In terms of research methods for water environment performance assessment, many domestic and international scholars and research institutions, after understanding the theoretical mechanisms of the water environment’s impact on socio-economic dynamics, analyze water quality through real-time monitoring, mathematical modeling, and physical and chemical analysis to assess the governance performance of water environments. The research methods have evolved from index evaluation methods to the current data envelopment analysis [
9], analytic hierarchy process [
10], and artificial neural networks [
11], and the research scope has expanded from the performance evaluation of individual water treatment plants to regional and watershed water environment governance performance. Lassaux used the Life Cycle Analysis (LCA) method to calculate the effluent water quality of 100 sewage treatment plants and measure their governance performance using indicators such as treatment efficiency and lime consumption [
12]. Hernández et al. evaluated the sewage treatment efficiency of 338 sewage treatment plants in Spain using the data envelopment analysis (DEA) method, with energy expenditure, maintenance costs, labor costs as input variables, and the pollution treatment rate as the output variable. They found that most sewage treatment plants had a low governance efficiency, and subsequently analyzed the obstacles causing the low governance efficiency [
13]. Zaheer and Bai (2003) proposed a new artificial neural network based on the decision-making method for water quality management to control environmental pollution, which was used to assess the relative impact of various pollution sources on river water quality [
14]. Guo et al. used the SBM–Tobit method to construct an assessment model to calculate the green efficiency of water resources in 18 cities in Henan Province from 2011 to 2018, discussed the operational mechanisms of relevant influencing factors, and identified methods to improve the green efficiency of water resources [
15]. Alodah et al. simulated hydrological impacts of extreme events by generating random climate data to conduct research on water resource system risks and performance [
16]. Regarding the construction of model indicator systems, Pires et al. constructed 170 water management indicators from three dimensions—environment, economy, and society—to measure the sustainable development of water resource utilization [
17]. Rak et al. (2019) proposed a comprehensive risk assessment method for self-managed water supply systems that takes into account multiple factors such as frequency or probability, property loss, health impacts, and safety. They developed a four-parameter risk matrix that enables a comprehensive evaluation of the risk level in water supply systems. The method was validated through case studies and demonstrated good practicality in small- and medium-sized water supply systems [
18]. Urbanik et al. (2019) employed a multi-parameter risk matrix approach to assess pipeline failure risks in natural gas supply systems. This method comprehensively considers factors such as pipeline type, failure probability, and consequence effects. A risk matrix was developed to evaluate the risks, and the effectiveness of the method was validated through case studies [
19]. Li et al. (2016) established an evaluation index system for water security using five subsystems—water cycle security, water environmental security, water ecological security, water social security, and water economic security with 39 indicators—and used macroeconomic data from 2000 to 2012 to assess the water security status of China using a water security evaluation model [
20].
In terms of research on strategies for water environment pollution control, different countries have different governance models and strategies due to the relationship between water governance and sustainable socio-economic development. As environmental protection efforts started earlier in foreign countries compared to domestic ones, the governance models and strategies established by them have a greater reference value for water governance in China [
21,
22]. The US government initiated the protection and governance of the Mississippi River in the 1960s, maintaining a stable ecological environment in the surrounding river basin. The main focus was on establishing mechanisms for public participation, integrating ecological environmental protection with economic development, and rational resource allocation, progressing from point source management to non-point source management [
23]. Due to the rapid economic growth in Japan after World War II, the pressure on the water environment carrying capacity in the Lake Biwa region increased, leading to severe pollution and declining water quality [
24]. The Japanese government established a government-led and citizen-participatory protection mechanism for the Lake Biwa basin [
25]. The management shifted from extensive management to a combination of development and utilization with ecological protection. This is related to the background that many countries have proposed Integrated Water Resources Management (IWRM) since the 1990s [
26,
27]. IWRM presents a framework for comprehensive water resources management, constructing interactions among natural water resource systems, human activity systems, and water resource management systems. It emphasizes the interactions between water resource systems and human activities, and emphasizes the coordination between water resource utilization and ecological environmental protection [
28].
In summary, the existing literature on the evaluation of water environment governance performance has several limitations. Firstly, although there have been studies on the evaluation of water environment governance performance in different countries or regions, there is a lack of research focusing on the Hangzhou Bay area, resulting in insufficient findings. Secondly, the measurement methods used for evaluating water environment performance often involve subjective factors. For example, the determination of indicator weights using methods like the Delphi method and analytic hierarchy process (AHP) may not objectively reflect the facts. In light of these limitations, this study adopts the widely used objective evaluation method of data envelopment analysis (DEA) and extends the original model by incorporating the Super-Efficiency DEA (SE-DEA) method. It considers both positive and negative indicators and utilizes actual water environment data from the Hangzhou Bay area over the past decade to construct an evaluation system for water environment governance performance. The SE-DEA–Tobit model is employed to assess the effectiveness of regional water environment governance and identify potential external influencing factors during the governance process. This research aims to provide reference and recommendations for the scientific formulation of water environment protection plans and management policies. The findings can also serve as valuable insights for watershed governance in other countries and regions.
5. Discussion
(1) Collaborative governance among government, industry, academia, and research can enhance governance performance.
This study combines the actual situation of water environmental governance in Hangzhou Bay and analyzes the periodic fluctuations in governance performance through the DEA–Tobit model. It is found that relying solely on the government as the single governance entity is no longer sufficient to address governance pressures. Therefore, introducing collaborative efforts among government, industry, and the public can effectively enhance governance performance. On the one hand, the government should allocate reasonable financial budgets for water governance through “visible hands” and impose production constraints on highly polluting companies through corresponding laws and policies. On the other hand, as the key subject of water governance, the industry’s production activities directly affect water quality and governance effectiveness. So, the industry should upgrade outdated industries and reduce pollution in accordance with policies while improving water efficiency through the constantly improving water rights market. At the same time, the public should participate in governance through collaborative efforts among government, industry, academia, and research, which can significantly optimize governance effectiveness. As direct beneficiaries of water governance, the public can improve their sense of satisfaction and sense of acquisition.
(2) Strengthen sewage treatment and reduce emissions.
Efforts should be made to achieve a standardized governance of industrial point source pollution, increase environmental protection requirements, strictly control new sources of pollution, accelerate the ecological management of non-point sources (especially agricultural sources), control agricultural pollution, reduce the use of fertilizers and pesticides, promote organic and ecological agriculture, and accelerate the construction of various sizes of sewage treatment plants to comprehensively strengthen watershed sewage treatment. At the same time, multiple approaches should be used to treat existing pollution and increase the water environmental capacity. Continuing to implement cross-basin large-scale water diversion measures can promote the flow and exchange of water bodies in various lake areas, reduce inferior water sources from small- and medium-sized rivers entering the lake, and improve the water environment. The introduction of high-tech water environmental governance such as source pollution control systems, artificial aeration systems, and submerged plant purification systems can effectively improve the water quality of lakes in conjunction with traditional technologies such as ecological dredging and blue-green algae harvesting. New sewage treatment technologies such as biofilm reactors and MBR should be promoted to improve sewage treatment efficiency and quality. In addition, diversified sewage treatment technologies such as using wetlands, artificial infiltration, and groundwater replenishment can be utilized through natural processes, and strategies such as rainwater collection and separate discharge can be used to achieve rain and sewage separation and reduce pollutant emissions.
(3) Optimize industrial structure to achieve clean production.
From the government’s perspective, a comprehensive industrial adjustment plan should be formulated with clear goals and a roadmap for optimizing the industrial structure. This includes developing guidance principles for clean production, identifying priority areas for clean industrial development, and formulating corresponding policy support measures. The plan should consider national development needs, resource endowments, and environmental capacity, and rationally guide industrial development. At the same time, the government can provide financial and economic support to clean production enterprises through fiscal and tax policies. This includes reducing the tax burden of enterprises, providing subsidies for clean technology research and development, and establishing green credit funds.
For enterprises, existing industrial structures should be adjusted, and clean production should be promoted comprehensively to guide industries towards low pollution and low energy consumption. Outdated production capacity should be phased out, and high-tech reforms should be introduced to reduce pollution emissions in the production process. Water resource waste and losses caused by crude water supply methods should be reduced, which can improve production efficiency and reduce pollution treatment costs.
(4) Promote cost-sharing for water environmental governance and achieve water environmental governance transformation through multi-party collaboration.
To change the government’s single-handed management model, ecological protection, environmental governance, and monetary compensation should be balanced to provide a reasonable cost-sharing mechanism for water environmental governance. Responsibility and benefit-sharing should be emphasized, with enterprises bearing the costs of water resource use and pollution discharge while consumers support the long-term costs of water environmental governance. A sewage treatment cost-sharing mechanism should be implemented, and the government can establish a special sewage treatment fund to finance the construction, renovation, and maintenance of sewage treatment facilities. Funds can be raised through government appropriations, environmental taxes, sewage discharge fees, etc., to ensure the sustainable development of sewage treatment work. Companies and residents should be charged a certain sewage discharge fee based on their discharge volume and pollutant concentration, and differentiated charges should be implemented for different industries and residents. The fees collected should be used for the construction and operation management of sewage treatment facilities.
To encourage enterprises and residents to actively participate in sewage treatment and emission reduction work, the government can establish a reward and punishment system. Enterprises and residents that meet or exceed emission standards can be rewarded, such as by reducing sewage discharge fees, enjoying tax benefits, or obtaining environmental certification. Enterprises and residents that exceed emission standards or refuse to cooperate should be punished, including fines, production and business suspensions, and revocation of licenses. To ensure the effective implementation of the sewage treatment cost-sharing mechanism, the government should strengthen the supervision and enforcement of sewage discharge enterprises and residents. A monitoring system should be established to regularly sample and test sewage discharge and publicly disclose monitoring results. At the same time, law enforcement efforts should be strengthened to punish enterprises and individuals that violate emission standards and sewage treatment cost-sharing mechanisms, ensuring the effectiveness of the system.
6. Conclusions and Limitations
6.1. Conclusions
This article addresses the issue of water environmental governance in the context of rapid urbanization and industrialization in the Hangzhou Bay area. To measure governance performance, a SE-DEA model was established, and panel data from 2011 to 2021 were used to calculate the governance efficiency of the Hangzhou Bay region and the coastal cities of Hangzhou and Ningbo. Based on the actual development situation in the region, the reasons for changes in the water environmental governance performance of the Hangzhou Bay region, Hangzhou, and Ningbo were analyzed separately. Using the efficiency values obtained from the SE-DEA model as the dependent variable, a Tobit model was used to analyze the impact of external factors on governance efficiency and to infer causality for factors other than input–output in water environmental governance. This provides a starting point and breakthrough for comprehensively improving the governance efficiency of the Hangzhou Bay area’s water environment.
During the study period, the governance performance of the Hangzhou Bay region exhibited frequent fluctuations, with the water environmental governance performance often being ineffective from 2012 to 2019. This was mainly due to the rapid socio-economic development of the Hangzhou Bay region during this time, which increased the pressure on water environmental governance. At the same time, the extensive management methods used meant that water environmental governance efficiency remained consistently poor. However, from 2019 to 2021 the water environmental governance performance in the Hangzhou Bay region improved significantly, with the DEA efficiency value increasing from 0.97 to 1.17, shifting from an ineffective state to a super-efficient state. This reflects a significant improvement in governance effectiveness, with the area of severely polluted waters decreasing from 47.00% to 23.80%, and the water quality compliance rate increasing from 92.50% to 98.80%. From the perspective of urban water governance, the water environmental governance efficiency of Hangzhou and Ningbo cities exhibited a “W-shaped” trend, indicating poor governance from 2012 to 2019, but significant improvement in recent years.
Using the Tobit model to analyze the external factors influencing water environmental governance, it was found that hypothesis 1 was partially verified, with the main breakthrough point for improving the governance efficiency of the Hangzhou Bay region’s water environment being the urban water environmental governance level in Hangzhou city. Hypothesis 2 was also correct, as an increase in disposable income for urban residents leads to greater environmental awareness and public environmental protection efforts, which is favorable for water environmental governance. Simultaneously, an increase in disposable income can significantly increase fiscal revenue and investment in governance facilities and supervision. Hypothesis 3 was incorrect, as the number of patent authorizations was not significant, due to the contradiction in the transformation of scientific research results in the Hangzhou Bay region’s R&D activities, with many patent achievements failing to be successfully transformed into innovative investments in water environmental governance. Furthermore, the control variables revealed that the total population and the GDP of the secondary industry have significant impacts on the water governance performance of the Hangzhou Bay region. On the one hand, an increase in population leads to a higher population density, rapid urbanization, and industrialization, which increases the pressure on governance. On the other hand, the rapid development of the secondary industry leads to increased energy consumption and pollution emissions, exacerbating the deterioration of the water environmental ecology.
6.2. Limitations and Future Directions
The limitations of this study are primarily attributed to the relatively small sample size, as it only covers data from 2011 to 2021. Due to the dynamic nature of water environmental governance, a shorter time span may not fully reflect long-term trends and changes. Therefore, future research on water environmental governance in the Hangzhou Bay area could consider expanding the time range by including data from additional years to obtain more comprehensive and accurate analytical results. Furthermore, although this study focuses on water environmental governance in the Hangzhou Bay area, it lacks consideration of other potential influencing factors or variables. Future research can further broaden the scope of investigation by incorporating factors such as water resource utilization, economic development level, and government policies to obtain more comprehensive and holistic research conclusions.
Lastly, while this study provides initial insights into water environmental governance in the Hangzhou Bay area, there are still unresolved issues and challenges. For instance, questions remain regarding the balance between economic development and ecological/environmental protection, as well as the formulation of effective policies and management measures. Future research can delve deeper into these issues and propose specific solutions to promote the sustainable development of water environmental governance in the Hangzhou Bay area. In summary, by expanding the sample size, extending the time range, considering more influencing factors, and addressing practical challenges, future research can further enhance and advance the field of water environmental governance in the Hangzhou Bay area. This will provide policymakers and decision-makers with more targeted and feasible recommendations to achieve sustainable management and protection of the region’s water environment.