Use of an Ecological Compensation Model in Water Resource Development: A Case Study from Shaanxi Province, China

Abstract

This study aims to analyze the current situation of water resource management in Shaanxi Province, study the basic principles of ecological compensation, evaluate the impact of water conservation projects on the ecological environment by establishing a model, and propose a sustainable water resource management model. Hanzhong City has certain typicality and representativeness within Shaanxi Province, and the problems it faces in water resource management and ecological environment may represent the entire province or similar regions. At the same time, Hanzhong City has rich data and research foundations. Therefore, by conducting a detailed analysis of the current water resource status in the Hanzhong City area of Shaanxi Province, the problems in current water resource management are revealed, and the basic principles of ecological compensation are intensely studied. The original ecological compensation plan in Shaanxi Province has been summarized. Guided by the concept of sustainable development, an ecological compensation model is established using algorithms, and the model is applied to sustainable water resource management. Establish a model for water conservation and water resource management through data collection, preprocessing, and cleaning, and apply it to practical cases in Hanzhong City. Through simulation and analysis of Hanzhong City, the new water resource management model effectively mitigates the adverse effects of water conservation projects on the ecological environment while improving water resource utilization efficiency. The changes in various environmental parameters indicate that the new plan has improved the ecological environment. Through the application of the model, the ecological compensation plan formulated has achieved sustainable protection of the ecological environment while promoting economic development. This study proposes a sustainable water resource management model through a comprehensive study of water resource management and ecological compensation in Shaanxi Province and verifies it in practical cases, demonstrating that the model has not only good applicability but also has significant effects in promoting economic growth and ecological environment protection.

1. Introduction

Environmental issues have gradually become a global concern with human society’s continuous development and industrialization acceleration. Among them, the deterioration of the ecological environment and water resource management challenges are increasingly attracting people’s attention. In this context, ecological compensation, as an essential means of coordinating economic development and ecological protection, is increasingly attracting the attention of scholars and decision-makers. Ecological compensation is an environmental management and protection strategy compensating for negative impacts on ecosystems caused by human activities or development projects through compensation measures [1,2]. Specifically, ecological compensation typically involves economic or resource compensation in exchange for protecting or restoring ecosystem health and function. For example, coal and natural gas development projects in Queensland, Australia, often impact the surrounding natural environment by destroying animal and plant habitats, causing water pollution and the destruction of land [3,4]. To mitigate these impacts, developers typically protect and restore the habitats of flora and fauna and manage water resources in the area to protect and restore the affected ecosystem. Ecological compensation involves the protection and restoration of ecosystems and the rational utilization of water resources. It is a critical practice to explore and coordinate the relationship between humans and nature from the perspective of sustainable development [5].

Water resource management, an essential component of ecological environment protection, has long received widespread worldwide attention. Water resources are the foundation for maintaining the health and stability of ecosystems and an essential element for socio-economic development. However, with the continuous intensification of global climate change and human activities, the problems of water resource scarcity and water quality deterioration are becoming increasingly severe, seriously affecting the sustainability of the ecological environment [6,7].

Research by institutions such as the International Union for Conservation of Nature (IUCN) has pointed out that many regions are experiencing water resource crises, especially those with underdeveloped economies and dense populations. The unreasonable utilization of water resources, disorderly discharge of pollutants, and extreme weather events caused by climate change further exacerbate the pressure on water resources. Governments and international organizations have taken several measures to address these issues, including formulating strict water resource management policies, implementing comprehensive water resource management plans, and promoting water-saving and sewage treatment technologies.

In China, water resource management, as an essential component of ecological civilization construction, also faces severe challenges. China has abundant water resources in total, but water resource management has become increasingly difficult due to its large population, low per capita water resource ownership, and uneven distribution of water resources, coupled with rapid economic development and accelerated urbanization. According to data from the Chinese Ministry of Water Resources, there is a widespread shortage of water resources in the northern region, while the southern region is facing difficulties in water pollution and deterioration of water quality.

The western region of China, especially Shaanxi Province, is known for its unique geographical environment and abundant natural resources. By 2025, it is estimated that the urbanization rate in Shaanxi Province will reach 65%, and the added value of manufacturing in Shaanxi Province will account for 23% of the regional GDP. With the rapid development of urbanization and industrialization, water resource management issues are gradually emerging [8].

Under the dual pressure of water scarcity and environmental pollution, Shaanxi Province urgently needs a scientific and reasonable water resource management model to balance the relationship between economic development and the ecological environment. Hanzhong City has a certain typicality and representativeness within Shaanxi Province. The problems faced by its water resource management and ecological environment represent the situation of the entire province or similar regions. At the same time, the geographical, demographic, and economic characteristics of Hanzhong City make the research more operational in the implementation process. Research teams can more easily obtain and manage necessary data, implement models and plans, and collect empirical data from them to validate the effectiveness of the models. Therefore, this study chooses Hanzhong City, Shaanxi Province, as the primary research area to deeply explore the application of ecological compensation in water resource management to provide strong support for the region’s sustainable development. The basic principles of ecological compensation serve as the starting point for research, providing guidance for understanding and applying ecological compensation mechanisms. By deeply analyzing the basic principles of ecological compensation, we can better grasp the complexity of ecosystems and the diversity of human activities affecting them. At the same time, as an ecologically fragile region, formulating and implementing compensation plans for the original ecological environment in Shaanxi Province has also become essential research objects. The study of compensation plans for the original ecological environment in Shaanxi Province can provide a reference for developing more effective compensation plans for the ecological environment.

Water resources are an essential component of the ecological environment, and their management involves the dual goals of socio-economic development and ecological balance. In analyzing the current situation of water resources in the surrounding areas of Shaanxi Province, research will focus on critical indicators such as distribution, utilization efficiency, and water quality to comprehensively understand the problems and challenges in water resource management. Meanwhile, with the continuous construction of water conservation projects, their impact on the ecological environment is becoming increasingly prominent. Water conservation projects may have adverse effects, such as damage to aquatic ecosystems and deterioration of water quality while improving the water resource supply [9]. Therefore, based on the impact of water conservation projects on the ecological environment, a basis for formulating corresponding ecological compensation plans will be provided. The concept of sustainable development, as the theoretical framework of research, will run through the entire research process. The algorithmic ecological compensation principle provides a method for designing and optimizing ecological compensation schemes from the perspective of sustainable development. The existing research on ecological compensation models provides a reference for research. Through in-depth analysis of these models, we can better understand their advantages, disadvantages, and scope of application. The application of sustainable water resource management models can provide scientific decision-making support for Shaanxi Province and experience and reference for other ecological regions.

The purpose of this study this study is to evaluate and enhance the management of water resources in Hanzhong City, Shaanxi Province, by conducting a comprehensive analysis of the existing challenges and proposing an improved ecological compensation strategy. We aim to uncover the underlying issues leading to water scarcity and environmental degradation and to assess the effectiveness of current ecological compensation plans. Through the application of a system dynamics model, we will simulate different water management approaches to optimize water resource allocation and utilization, thereby reducing pollution and ecological harm. The ultimate goal of this study is to foster a harmonious development that balances economic growth with environmental conservation, leading to sustainable regional development and an enhanced quality of life for local residents.

2. Application of Ecological Compensation

2.1. Basic Principles of Ecosystem Compensation

Eco-compensation is a mechanism for regulating the interests of relevant parties and promoting compensatory activities to stimulate ecological protection through institutional arrangements, mainly through economic means. Its core objective is the protection and sustainable use of ecosystem services. Although there have been several studies and practices on ecological compensation, there needs to be a more accepted definition. It can be understood as both broad and narrow [10]. Broad ecological compensation includes rewards for the benefits of ecosystem and natural resource protection and compensation for the losses caused by the destruction of ecosystems and natural resources. Narrow ecological compensation, on the other hand, focuses on charging those who cause environmental pollution. This mechanism provides helpful institutional support for ecological balance and sustainable development through economic incentives that lead all social parties to participate more actively in ecological protection.

As shown in Figure 1, the basic principles of ecological compensation include the principle of the destroyer paying, the principle of the user paying, the principle of the protector being compensated, and the principle of the beneficiary paying. Together, these principles form an organic framework that provides direction for the rational management of the ecological environment.

2.1.1. Destroyer Pays Principle

This principle stresses that in the process of ecosystem damage, the actors who directly or indirectly cause the damage should bear the corresponding financial responsibility. Whether it is the production activities of enterprises or the daily lives of individuals, as long as their behavior causes damage to the ecological environment, they should be responsible for repairing the damage and protecting the ecological environment. The establishment of the destroyer pays principle has prompted all sectors of society to treat their interactions with the environment more cautiously, effectively curbing the vicious circle of environmental destruction.

2.1.2. User Pays Principle

The user pays principle embodies the fact that in resource utilization, the users of the resources should bear the corresponding costs of maintaining the ecological environment. This principle is intended to encourage economic agents to be more careful in exploiting resources, thereby reducing the negative impact on the environment. While utilizing ecological resources, industrial enterprises and agricultural producers should bear the corresponding economic responsibility for the environmental impacts they cause. Through the user pays principle, the sustainable use of resources can be channeled towards the greening of the economy [11].

2.1.3. Protectors Gains Principle

The principle of protectors gains stresses that financial incentives should be given to individuals or organizations that contribute to protecting and restoring the ecological environment. In society, some people or organizations are committed to protecting the ecological environment and have invested a lot of time and resources. In order to encourage the positive behavior of these protectors, the principle of conservationist compensation stresses that they should be rewarded through specific economic means so as to promote the participation of more people in environmental protection actions.

2.1.4. Beneficiary Pays Principle

The beneficiary pays principle emphasizes that in environmental governance, the beneficiaries should pay for the ecosystem services they receive. This principle requires those individuals or organizations that benefit from the environment to compensate the ecosystem financially according to the extent of their benefit. For example, residents who enjoy clean air and beautiful scenery, as well as businesses that benefit from agricultural and industrial development, should pay for these environmental services to support the maintenance and restoration of the ecosystem. Equitable rights and interests between users and beneficiaries of the ecological environment are realized through the beneficiary pays principle.

The government and the market mechanism should cooperate to promote the construction of an ecological compensation system. The government plays a guiding and supervisory role in formulating policies and regulations. At the same time, the market mechanism can stimulate the enthusiasm of all parties and promote more efficient ecological and environmental governance using market regulation, such as the carbon market and environmental taxes. The formulation of this principle makes the environmental governance system more flexible and adaptable. It helps promote improving the ecological environment under the synergistic effect of the government and the market.

2.2. The Relationship between Water Resources and Ecological Environment Destruction

The development and utilization of water resources often directly or indirectly impact the surrounding ecological environment. The development of water resources may lead to the discharge of industrial wastewater, agricultural pesticides and fertilizers, urban sewage, and other pollutants, directly affecting the ecological health of water bodies. For example, excessive use of fertilizers and pesticides may lead to the eutrophication of water bodies, causing problems such as blue-green algae blooms and disrupting the balance of aquatic ecosystems. Large-scale water conservation projects such as reservoir construction and water diversion projects may alter the water volume and flow dynamics of water bodies, affecting the stability of aquatic habitats. This change may lead to the degradation of river ecosystems, affecting fish migration, wetland hydrological cycles, and so on. Overexploitation and irrational utilization of water resources may directly damage the structure and function of ecosystems. For example, the filling and degradation of wetlands can reduce the habitats of birds and other wildlife, affecting their population size and diversity.

In this context, ecological compensation has become one of the essential means to alleviate ecological damage in the process of water resource development. Through ecological compensation, economic or other compensation measures can be taken to balance and compensate for the adverse effects of water resource development on the ecological environment. For example, funding can support wetland restoration projects to restore wetland ecosystems damaged by water resource development. Alternatively, an ecological compensation fund can be established to protect and manage water conservation areas to compensate for the impact of water resource development on water source protection.

Therefore, the rational management of water resources and protecting the ecological environment are inseparable. Ecological compensation not only ensures the sustainable use of water resources but also promotes the restoration and protection of the ecological environment.

2.3. Shaanxi Province Ecological Compensation Programme

The original ecological compensation plan in Shaanxi Province has a positive effect as an important measure to address the increasingly severe ecological environment problems. Implementing the plan has a promoting effect on guiding economic entities to develop and utilize resources more cautiously, promoting green economic development, and promoting social equity. However, some things could still be improved in the plan’s practice, which may have certain constraints on the effectiveness of environmental governance.

Shaanxi Province’s ecological compensation program stresses that those actors who directly or indirectly cause damage to the ecological environment should be held financially responsible for the impacts they cause. By establishing a damage liability mechanism, Shaanxi Province encourages these destroyers to take the initiative to bear the costs of maintaining the ecological environment, prompting them to carry out all kinds of economic activities more prudently and to reduce their adverse impacts on the ecosystem. However, some enterprises and individuals have yet to assume their due economic responsibility in the face of environmental damage [12]. In the specific implementation process, some saboteurs have evaded the economic costs payable by evading regulation and violating the law, leading to deficiencies in the actual operation of the program. In addition, the program needs to fully address the long-term regulatory and governance challenges of persistent and potential environmental damage, resulting in a lack of timely and practical solutions to environmental problems.

In terms of protectors being compensated, through measures such as the establishment of an ecological reward fund and the promotion of ecological industries, Shaanxi Province has actively fostered an atmosphere that encourages the participation of protectors in ecological and environmental protection in order to promote the broad participation of all sectors of society in environmental governance initiatives, with the program’s initial aim being to encourage environmental protection organizations and individuals to play a more active role in ecological and environmental governance. However, some conservationists contributing to ecological and environmental protection have not received financial rewards due to the lack of clear compensation standards and mechanisms. This makes it possible for some environmental protection forces to face financial difficulties in their long-term ecological and environmental protection work, reducing their incentive to continue to invest in it and thus restricting the full implementation of the program.

The Shaanxi Province Original Ecological Compensation Program has achieved some initial results in promoting ecological and environmental governance, but it also faces a series of challenges and shortcomings. In practice, there is still room for improvement in terms of the mechanism for punishing environmental destroyers, the introduction of user fees, the active participation of beneficiaries, and compensation for protectors. Considerations of fairness and the combination of government guidance and market regulation need to be more in-depth and improved.

The conceptual framework of ecological compensation within this study is anchored on the principles of sustainable development, aiming to balance economic progress with ecological integrity. Our empirical simulation results, derived from the system dynamics model applied to Hanzhong City, provide a tangible demonstration of this framework’s practical application. The model effectively simulates the ecological compensation mechanisms, such as the protectors gains principle and the beneficiary pays principle, by quantifying the impacts of various water management strategies on the ecological environment. This not only validates the theoretical underpinnings of ecological compensation but also offers actionable insights into how these principles can be operationalized to enhance water resource management. The simulation outcomes showcase how targeted ecological compensation can mitigate the adverse effects of water conservation projects on the environment, thereby supporting the sustainable use of water resources and the concurrent protection and restoration of ecosystem health. This integration of theoretical framework and empirical findings underscores the study’s contribution to the field of ecological economics and water resource management.

3. Water Resources Management in Shaanxi Province

3.1. Water Resources Analysis

As an essential province in Northwest China, the status of water resources in Shaanxi Province plays a crucial role in achieving sustainable economic development and maintaining ecological balance.

Due to the diversity of geographical and climatic conditions within Shaanxi Province, there may be significant differences in water resource management strategies across different regions. As a part of Shaanxi Province, Hanzhong City’s geographical location and climate characteristics significantly impact water resource management. Hanzhong City is located in the central part of Shaanxi Province and is a typical mountainous basin terrain, greatly influenced by rivers such as the Wei and Han Rivers. This geographical feature poses unique challenges for Hanzhong City in balancing water resource supply and demand, water quality protection, and the balance between irrigation and ecological protection.

Under the overall framework of water resource management in Shaanxi Province, the water resource management policies and measures in Hanzhong City need to consider its local characteristics and specific needs. For example, Hanzhong City may need to pay special attention to the protection and management of local water sources and the potential drawbacks of water resource utilization caused by uneven precipitation. In addition, as an essential component of Shaanxi Province, the success of water resource management in Hanzhong City directly affects the sustainable use of water resources and the health of the ecological environment in the entire province.

Hanzhong City is located southwest of Shaanxi Province, adjacent to Baoji City, Xi’an City, Ankang City, Guangyuan City, Bazhong City, and Dazhou City in Sichuan Province. It is also adjacent to Longnan City in Gansu Province to the west. The city’s total area is 27,246 square kilometers, belonging to the inland East Asian monsoon climate zone. The climate is mild and humid, with an average annual temperature of about 14.5 °C. As of October 2022, Hanzhong City governs two districts and nine counties, with a total registered residence population of 3.7898 million. This geographical location and administrative division have given Hanzhong City significant geographical advantages, while the mild and humid conditions provide a suitable natural environment for its development.

Various factors, including climate change, land use change, economic development, etc., influence the water resource management in Hanzhong City. System dynamics models can comprehensively consider these influencing factors to simulate the dynamic changes of vital hydrological variables such as reservoir storage capacity and river flow. In the model, variables such as storage capacity, precipitation, and evapotranspiration of reservoirs in Hanzhong City were introduced and combined with decision variables of water resource management, such as scheduling strategies and water resource allocation. The evolution of the water resource system in the next few decades was simulated. This helps to evaluate the effectiveness of different water resource management strategies and provides a scientific basis for sustainable water resource utilization in Hanzhong City.

The unbalanced distribution of water resources in Shaanxi Province is a significant problem, with most of the water resources distributed mainly in the south and southeast. At the same time, the northern and north-western regions are relatively poor. This geographical difference has led to an imbalance in the supply of water resources, causing some areas to face water shortages for a long time. Especially in the northern arid areas, due to the lack of sufficient natural water sources, the rational use of water resources has become a bottleneck for local economic and social development [13]. Understanding the status of water resources is a prerequisite for their rational use. Therefore, four aspects are discussed: rainfall, surface water, groundwater, and total water resources.

3.1.1. Rainfall

As shown in Figure 2, the precipitation situation in Shaanxi Province in 2022 shows a series of changes. Overall, the average precipitation in Shaanxi Province is about 621.54 mm, which is equivalent to a total rainfall of 127,783.6 million m³. This is an increase of 5.2% compared with the multi-year average (1976–2020) but a slight decrease of 0.91% compared with 2019.

About basin precipitation, the average annual precipitation in the Yellow River basin increased by 8.7%, while the average precipitation in the Yangtze River basin increased by 1.5%. This indicates some differences in the distribution of water resources in different regions. Among the precipitation in each administrative division, Hancheng, Yulin, and Shangluo have less precipitation, with a decrease of 8.91%, 2.2%, and 3.87%, respectively. In contrast, the other ten cities (districts) had relatively more precipitation, with Yangling District having the most significant increase of 47.3% and Hanzhong having the smallest increase of 0.44% [14].

In addition, the precipitation changes in the basins and secondary areas show diversity. The decreases in the Jing River, Beiluo River, Longmen–Sanmenxia (straight), and Closed Stream areas were 11.52%, 2.16%, 1.98%, and 4.23%, respectively. In contrast, the precipitation of the Weihe River has a larger deviation of 29.93%, while the deviation of the Hanjiang River is the most minor, only 1.08%. These data provide an essential reference for scientific and reasonable water resource management and highlight the differences in the distribution of water resources across Shaanxi Province [15].

3.1.2. Surface Water

Shaanxi Province has a surface water resource of 34,705.8 million m³ with an annual runoff depth of 169.84 mm. However, the per capita surface water resource has declined by 2.7% compared to the multi-year average and 17.9% from 2019. This indicates that Shaanxi Province faces a significant decrease in surface water resources, triggering urgent attention to water resource management and protection.

Changes in surface water resources in watersheds also show differences, with surface water resources in the Yellow River Basin increasing by 4.2% and those in the Yangtze River Basin decreasing by 4.8%. This uneven distribution may have implications for local ecology and economy.

From Figure 3, in the changes in surface water resources in various cities (districts), six cities (districts), including Xi’an, Baoji, Xianyang, Yangling, Weinan, and Ankang, showed a trend of more surface water resources, with Yangling District having the highest deviation of 37.33%. Ankang has the slightest deviation of 7.47%. On the contrary, the surface water resources of the remaining seven cities (districts) decreased by different magnitudes compared with the average of the regular year, with Shangluo having the most significant decrease, amounting to 27.39%, and Xixian New District having the most minor decrease, amounting to 3.15% [16].

The surface water resources of the Jing River and Wei River were higher than the normal year average, with the Wei River having the highest increase of 18.117% and the Jing River having the lowest increase of 8.449%. However, the other seven districts showed different degrees of decrease than the usual year average, with the highest decrease of 26.63% in the Closed Stream District and the most minor decrease of 0.63% in the Yiluo River.

3.1.3. Groundwater

The groundwater resource situation in Shaanxi Province in 2022 showed some changes. In the plain area, the total amount of shallow groundwater resources was 5.853 billion m³, an increase of 431 million m³ compared to the previous year. Specifically, the increase in the Yellow River Basin amounted to 605 million m³, while the Yangtze River Basin declined by 174 million m³. In the hilly area, the total amount of groundwater resources was 11.165 billion m³, an increase of 405 million m³ compared to the previous year. Similarly, the increase in the Yellow River Basin amounted to 568 million m³, while the Yangtze River Basin saw a decline of 142 million m³, as shown in Figure 4.

Shaanxi province’s total groundwater resources are 16.138 billion m³, an increase of 13.42% over the multi-year average. Further subdivided, groundwater resources in the Yellow River basin increased by 5.24%, while the Yangtze River basin showed a more significant increase of 22.33%.

3.1.4. Total Water Resources

As shown in Figure 5, The total water resources of Shaanxi Province in 2022 will be 39.533 billion m³, including 34.706 billion m³ of surface water resources, 13.204 billion m³ of groundwater resources, and 10.144 billion m³ of overlapping statistics of groundwater and surface water. The total water resources declined by 13.77% compared with the previous year and 1.71% compared with the multi-year average. At the basin level, the total water resources of the Yellow River basin increased by 5.4%, while the total water resources of the Yangtze River basin decreased by about 3.15%.

Shaanxi Province water resources statistics show that the base data for 2022 includes precipitation, surface water, groundwater, and total water. Precipitation resources are the most abundant, groundwater resources are the most limited, and surface water resources are slightly smaller than total water. There is a fluctuating downward trend in all types of water resources between 2013 and 2022. Water supply and demand projections for the next ten years indicate that demand will exceed supply, signaling further water resource problems. The above data show the main features of the water resources situation in Shaanxi Province, highlighting the urgent challenges ahead and the need to take adequate measures to ensure the sustainable use of water resources.

3.2. Impacts of Water Projects on the Ecological Environment

The advancement of water conservation projects in Shaanxi Province has had far-reaching impacts on the local ecological environment, both in terms of positive ameliorative effects and involving a series of potential adverse effects. In terms of water resource management, irrigated agriculture, flood prevention, and disaster mitigation, water conservation projects have provided necessary support for the economic and social development of Shaanxi Province. However, at the same time, some projects have also caused some potential problems for the ecological environment of Shaanxi Province [17].

The construction of reservoirs has altered the natural flow state of local rivers, affecting sedimentation and material circulation in downstream waters. Reservoirs trap sediment in rivers, resulting in a lack of sediment recharge in downstream reaches and affecting the stability of the riverbed. This poses a potential threat to the riparian ecosystem and the biodiversity of the waters, which may lead to the destruction of the living environment of some aquatic plants and animals. The advancement of water conservation projects in Shaanxi Province may lead to the reduction of wetland areas and the destruction of wetland ecosystems. Wetlands are essential in maintaining ecological balance, purifying water bodies, and regulating water sources. However, constructing some water conservation projects may lead to the abandonment or reduction of wetlands, reducing their ecological service function to water bodies. This poses a potential threat to the species diversity and ecological stability of wetland ecosystems and affects the overall health of water ecosystems.

The natural environment and water conservation projects have particularly impacted aquatic organisms and water quality in Shaanxi Province. The construction of reservoirs and the implementation of water transfer projects have changed environmental factors such as temperature, flow rate, and water level of the waters, which have caused a particular impact on the living environment of aquatic organisms. Some specific fish and benthic organisms may be threatened, leading to the reduction of aquatic biodiversity. For water quality problems, on the one hand, the construction of reservoirs may lead to eutrophication of water bodies. Due to the interception of rivers, organic materials such as sediment cannot flow normally, and the eutrophic substances in the bottom sediment of reservoirs are gradually released, contributing to the eutrophication of water bodies. On the other hand, irrigated agriculture and urban drainage may introduce harmful substances such as pesticides and fertilizers, polluting the water body. This poses a potential threat to the ecological service function and water quality safety of water bodies.

4. Sustainable Development and Water Resources Management

4.1. Principles of Algorithm-Based Ecological Compensation

The principle of algorithm-based ecological compensation aims to achieve a quantitative assessment of ecosystem services through scientific modeling and calculation methods and determine the amount of ecological compensation accordingly [18]. The core of this principle is to establish an ecosystem compensation model to quantify and assess the loss of ecosystems by considering the value of ecosystem services, the degree of damage, and the restoration cost.

One of the commonly used algorithms in ecological compensation modeling is the Banzhaf index algorithm [19]. This algorithm is based on the cooperative game theory, which calculates each participant’s contribution to the cooperation and then determines the allocation proportion of each participant in obtaining compensation. Specifically, the Banzhaf Index algorithm considers participants as players in a cooperative game. It determines each player’s share of the cooperative process by calculating their influence on forming different cooperative alliances. This algorithm can objectively reflect each party’s influence when measuring different players’ contributions to ecological environment protection.

In addition, there are algorithms based on the ecological risk assessment model, which assesses the degree of damage to the ecological environment based on the vulnerability of the ecosystem and the degree of threat. The ecological risk assessment model considers factors such as the stability of the natural system, species diversity, and the resilience of the ecosystem, and it quantifies the damage to the ecological environment by establishing corresponding assessment indicators and weights. The algorithm reflects the necessity and reasonableness of ecological compensation more comprehensively based on considering the ecosystem’s multifaceted characteristics. The setting of its assessment indicators and weights must be adjusted according to the specific ecosystem characteristics and degree of damage. Generally speaking, expert consultation, field surveys, and other methods can be used to determine the relative importance of different indicators and establish weighting coefficients. At the same time, the specific quantification method of each indicator needs to be considered comprehensively to ensure the scientificity and accuracy of the assessment results [20].

4.2. Application of Modeling to Sustainable Water Resources Management

The modeling application in sustainable water resources management has essential theoretical and practical significance. Establishing scientific water resources management models can help better understand the distribution and utilization of water resources, predict future trends, and provide adequate references for decision-makers [21]. This section will explore different types of water resources management models and their applications in achieving sustainable water resources management.

Algorithm-based water resource management models play a key role in sustainable development. Models similar to the Banzhaf index algorithm allow for a scientifically sound assessment of water resource allocation. By considering the weights of each participant in the use of water resources, the model can help establish a fair and efficient water allocation mechanism.

The ecological compensation model, however, considers the impact of water conservation projects on the ecological environment, which can help assess the projects’ potential impact on the water ecosystem and propose corresponding ecological compensation programs. This realizes the coordinated development of water resources management and ecological and environmental protection and promotes sustainable water resource use.

In practice, water resource management in Shaanxi Province can draw on the hedonic pricing model [22]. The model estimates the economic benefits of different options by quantitatively assessing the impacts of different water resource use methods. The model considers the economic and social benefits of water resource management decisions by analyzing the impacts of water resource management on the real estate market in nearby areas.

The ecological risk assessment model (ERAM) is also an important tool in water resources management. It assesses the potential risks of water resources management to the ecosystem by taking into account factors such as the stability of natural systems, biodiversity, and ecosystem resilience. By identifying possible problems in advance, water managers can take appropriate measures to mitigate the adverse impacts of water management on the ecosystem and ensure sustainable water use.

In this paper, a system dynamics model was chosen to evaluate the multifaceted impact of water conservation projects on the ecological environment of Hanzhong City, providing scientific basis and decision support. Hydraulic engineering has a significant impact on the spatiotemporal allocation of water resources. The model simulates the scheduling and operation plans of reservoirs and dams, revealing the project’s dynamic changes in water resource allocation in different seasons and regions. By rational regulation of water resources within the watershed, the model effectively alleviates regional water resource shortages, ensures a balanced distribution of water resources, and reduces the uneven distribution of water resources.

Hydraulic engineering has changed rivers’ natural flow, affecting the health of downstream ecosystems. The model evaluates the trend of ecological flow by simulating the changes in river water flow under different engineering scheduling schemes, ensuring that necessary ecological flow is maintained during water resource scheduling. This provides a foundation for protecting the health of river ecosystems and avoiding the deterioration of downstream ecological environments.

The model comprehensively evaluates the long-term environmental impact of water conservation projects. Through long-term simulation, the model reveals the long-term effects of hydraulic engineering on the ecological environment, including its impact on land use, water resource sustainability, and ecosystem health. These results provide essential references for understanding the long-term ecological effects of engineering and improving water resource management, ensuring the sustainable development of the ecological environment.

5. Modeling of Water Resources and Water Management

5.1. Data Collection

As shown in Figure 6, data collection and processing are crucial steps in the process of water resources and water management modeling. In the practice of water resources management in Shaanxi Province, systematic and comprehensive data collection is needed to ensure the accuracy and scientificity of the model [23].

For establishing the water resources management model, the critical data include hydrological data, meteorological data, topographical data, and other aspects of information. Hydrological data collection covers hydrological stations in various areas of Shaanxi Province, including real-time observation data such as river level and flow. Meteorological data include temperature, precipitation, and other meteorological elements that can be obtained through meteorological stations. Topographic data include geographic information such as terrain elevation and slope, which can be obtained through remote sensing technology and digital elevation models. The acquisition of these data is the basis for model building and provides a reliable source of information for subsequent analyses.

During data collection, attention also needs to be paid to the spatial and temporal resolution of the data, which needs to be chosen to suit the specific purpose of the study and the scale of water resources management. For example, for water resources management in small catchments, high-resolution hydrological and meteorological data may be required to reflect local changes accurately. For large-scale water resources management, relatively low-resolution data can be used to reduce computational complexity.

Quality control of the collected data is required in the data collection phase. This includes data missing value processing, outlier detection, and data consistency verification. Among the commonly used methods are statistical methods and interpolation methods. For example, interpolation methods can be used to fill in missing values, and outlier detection methods can be used to exclude abnormal data to ensure that the data used in the model is accurate, complete, and credible.

5.2. Data Preprocessing and Cleaning

Data preprocessing and cleaning are vital steps in modeling water resources and water management. This stage ensures the quality and accuracy of the raw data, providing a reliable basis for model analysis and decision-making.

For data quality control, attention needs to be paid to handling outliers. Outliers may hurt the model and need to be detected and handled using appropriate statistical methods [24]. Commonly used outlier detection methods include the Z-score method based on mean and standard deviation, which is calculated as follows in Equation (1):

$$Z={\displaystyle \frac{\left(X-\mu \right)}{\sigma }}$$

(1)

In Equation (1), Z is the Z-score, X is the data value, μ is the mean value, and σ is the standard deviation of the data. By calculating the Z-score, it is possible to determine whether the data deviates too much from the mean and thus identify outliers. When using the Z-score method to detect outliers in data in water resource management models, it is possible to determine whether each data point deviates from the mean of the dataset by calculating its Z-value. Suppose the Z-value of an observation exceeds the set critical value (such as ±2 or ±3). In that case, it is considered that the data point may be an outlier, and further analysis or processing is needed. Using such standards helps to ensure the accuracy and reliability of data, avoiding the impact of abnormal data points on analysis results. When calculating the water resources data in Hanzhong City, the Z-score of the fixed observation value is 2.5, which means that the data point differs from the mean by 2.5 standard deviations. If the set outlier threshold is ±2, the data point will be marked as an outlier, and further analysis and processing are required. If the critical value is set to ±3, the data point will not be considered an outlier. Choosing an appropriate Z-value threshold standard helps balance the sensitivity and stability of outlier detection.

Standard methods include interpolation to treat missing values. The interpolation method estimates the missing values based on the information from the existing data, and the standard interpolation methods are linear interpolation, polynomial interpolation, Kriging interpolation, etc. [25]. Taking linear interpolation as an example, for the missing value between two known points (x₁,y₁) and (x₂,y₂), x₀ corresponding to y₀, linear interpolation can be calculated by Equation (2):

$$y_0=y_1+{\displaystyle \frac{\left(x_0-x_1\right)\left(y_2-y_1\right)}{\left(x_2-x_1\right)}}$$

(2)

This interpolation method is based on a linear relationship between two known points and provides a simple and effective way to estimate missing values. In addition, a de-duplication operation is required to treat duplicate values. Duplicate values may originate from data collection or system errors, and by removing duplicate values, redundant information in the model can be avoided. In practice, de-duplication can be achieved using the DISTINCT keyword in a database or using data processing functions in a programming language [26].

During data preprocessing, attention must also be paid to the normalization and standardization of the data. This is because models require input data to be compared and analyzed on the same scale. For normalization, the min–max normalization method can be used to scale the raw data to a range of 0~1, calculated as follows in Equation (2):

$$X_{normalisation}={\displaystyle \frac{X-X_{\min }}{X_{\max }-X_{\min }}}$$

(3)

In Equation (3), X_min and X_max are the data’s minimum and maximum values, respectively. Standardizations, calculated as described in the previous section, convert the data to a standard normal distribution with a mean of 0 and standardization of 1 by means of Z-score standardization.

Data consistency verification is also an essential part of data preprocessing; consistency verification can be carried out using logic checking, range checking, and other means to ensure the logical relationship and reasonableness of the data. For example, for water level and flow rate data, it is necessary to ensure that the water level is manageable in the case of zero flow rate to maintain reasonable consistency with the data.

5.3. Model Selection and Construction

The system dynamics model is a mathematical model that studies and analyzes the dynamic relationships and evolutionary processes among various factors within complex systems. The design of this model is based on a deep understanding of the system’s internal structure, interactions, and feedback mechanisms, using mathematical equations and simulation techniques to simulate the behavior and trends of the system. The system dynamics model involves variables (stocks) representing the accumulation or change in the system, such as water volume in a reservoir, population, or economic assets. The changes in these variables can be continuous (such as changes in water level) or discrete (such as changes in population). The model includes flows, which describe the rate of change or flow process between variables. For example, the inflow and outflow of water, the population’s birth rate, and the mortality rate can all be modeled as flows. The parameters in the model are fixed values or functions that affect the system’s behavior. These parameters can be flow coefficients, growth rates, consumption rates, etc. They define the essential characteristics and behavioral patterns of the model. One of the critical components is feedback loops, which describe the self-regulation mechanisms within the system. The feedback loop reflects the interdependence and mutual influence between variables, and through these loop systems, they can self-adjust and adapt to external changes. The system dynamics model also involves accumulations, which refer to the variables or resources accumulated in the system that accumulate or decrease over time, reflecting the historical trajectory and trends of the system’s dynamic changes.

The construction and analysis of models usually uses mathematical equations and simulation techniques. Simulating different initial conditions and parameter settings makes it possible to predict the behavior and evolution trend of the system in different situations. This ability makes system dynamics models not only a tool for describing phenomena but also a predictive and decision-support tool, helping to understand the essence of complex systems and develop effective management strategies and policies.

In the field of water and water resources management, system dynamics modeling is an effective tool for describing and simulating the dynamic relationships between elements in a water resources system and their trends over time. The theoretical foundations of system dynamics are derived from nonlinear dynamics and control theory and can be applied to the modeling of multivariate, time-lagged, and nonlinear systems. The following is a guide to selecting and building a system dynamics model for water resources management.

Modeling requires system identification, i.e., identifying the critical elements in the water resources management system and their interactions. Considering the effects of the hydrological cycle, meteorological changes, and human activities on water resources, the system’s state variables and decision variables can be defined. Taking S(t) to denote reservoir storage, P(t) to denote precipitation, ET(t) to denote evapotranspiration, and I(t) to denote impacts due to human activities, the system dynamics can be represented as Equation (4):

$${\displaystyle \frac{dS\left(t\right)}{dt}}=P\left(t\right)-ET\left(t\right)-I\left(t\right)$$

(4)

Equation (4) reflects the dynamics of reservoir storage, which is influenced by precipitation and evapotranspiration and disturbed by human activities. Parameters in the system dynamics equation, such as evapotranspiration coefficients and influence factors, must be estimated from historical data and field surveys. For example, ET can be estimated from meteorological station observations and parameters such as vegetation type. Anthropogenic impacts can be estimated from statistical data and factors such as population changes. The process of estimating parameters needs to consider the data’s uncertainty and is usually fitted using methods such as least squares.

Based on system identification and parameter estimation, a complete set of system dynamics equations is established to comprehensively reflect the complex dynamics of the water resources management system. For example, to consider the impact of water management decisions on water storage, the decision variable D(t) is introduced (see Equation (5)).

$${\displaystyle \frac{dS\left(t\right)}{dt}}=P\left(t\right)-ET\left(t\right)-I\left(t\right)+D\left(t\right)$$

(5)

Equations (4) and (5) are formulated based on the principles of system dynamics, which is a framework for understanding the behavior of complex systems over time. Equation (4) represents the dynamic behavior of reservoir storage, which is influenced by precipitation (P(t)), evapotranspiration (ET(t)), and anthropogenic impacts (I(t)). This equation is derived from the water balance principle, which states that the change in storage (ΔS(t)) is equal to the input from precipitation minus the output due to evapotranspiration and human activities. Mathematically, this is expressed as ΔS(t) = P(t) − ET(t) − I(t). Equation (5) introduces a decision variable, D(t), which represents the water management decisions that can be adjusted to optimize water resource allocation. This equation extends the basic water balance model by incorporating the impact of management strategies on reservoir storage, thus allowing for the simulation of different water resource management scenarios and their potential outcomes. The parameters within these equations are estimated using historical hydrological data and statistical analysis, ensuring that the model reflects the actual conditions of the water resources system in Hanzhong City.

The system dynamics model can more fully consider the impact of water management decisions on reservoir storage. Numerical solution methods are required for simulating the established system dynamics equations. Commonly used numerical methods include Euler’s method and the Lunger–Kutta method. These methods can progressively advance the system’s evolution at discrete time points and obtain the change process of each state variable in a continuous time period [27].

Validation of the model is an important part of ensuring its accuracy and reliability. The model is validated through comparison with measured data. In the case of the reservoir storage scenario, historical reservoir storage observations can be used to compare with the model simulation results, and the reasonableness of the model can be verified through error analysis and other methods.

The established system dynamics model can be used to simulate and predict water resource management. By adjusting the decision variables, different water resource management strategies can be simulated to predict the future trend of reservoir storage. For example, different reservoir scheduling schemes can be simulated by setting different decision variables D(t) to try different reservoir scheduling schemes. The strategy and plan for the operation and management of reservoirs and the utilization of water resources mainly involve operations such as water storage, discharge, and flood discharge during different time periods.

6. Model Applications

6.1. Regional Overview

Hanzhong is located in the southwestern part of Shaanxi Province, neighboring Baoji, Xi’an, and Ankang, as well as Guangyuan, Bazhong, and Dazhou in Sichuan Province. At the same time, it is also connected to Longnan in Gansu Province to the west. With a total area of 27,246 km², the city belongs to the inland East Asian monsoon climate zone, with a mild and humid climate and an average annual temperature of about 14.5 °C. As of October 2022, Hanzhong has two districts and nine counties, with a population of 3,789,800. This geographical location and administrative division give Hanzhong a significant location advantage, while the mild and humid conditions provide a suitable natural environment for its development [28].

Water resources management in Hanzhong is affected by many factors, including climate change, land use change, and economic development. These influencing factors can be considered comprehensively to simulate the dynamic changes of key hydrological variables such as reservoir storage and river flow through the system dynamics model. Variables such as reservoir storage, precipitation, and evapotranspiration in Hanzhong were introduced into the model and combined with decision-making variables of water resources management, such as scheduling strategy and water allocation. The evolution of the water resources system in the coming decades was simulated, which helps to evaluate the effectiveness of different water resources management strategies and provides a scientific basis for sustainable water resources use in Hanzhong.

Using models, it is possible to simulate the trend of reservoir storage in Hanzhong under different scenarios and further predict the possible future water resource situation. For example, considering climate change, the model can simulate the changes in rainfall and evapotranspiration rates to predict the fluctuation of reservoir water storage.

The simulation results can be verified by comparing the historical observation data and then adjusting and optimizing the model’s parameters to improve its accuracy and reliability. This process is a critical step in applying the model to ensure that the model reasonably reflects the actual situation.

6.2. Simulation Results

A system dynamics model was used to simulate the water resource situation in Hanzhong, obtaining a series of key simulation results. These insights into possible future water management challenges and the impacts of different decision-making scenarios were then used.

As shown in

Table 1. Reservoir storage simulation.

Year	Reservoir Storage (million m3)
2015	600
2020	550
2025	550
2030	520
2035	530
2040	500

, the model simulation results show that Hanzhong’s future reservoir water storage exhibits apparent seasonal and inter-annual variations. Considering the combined effects of climate change, human activities, and water resource management, the reservoir storage volume shows fluctuations in different periods, reflecting the dynamic changes in the water resource system. This provides an essential reference for the future development of rational reservoir scheduling and water resource management strategies.

Models consider the impacts of the hydrological cycle on water resources, including critical elements such as precipitation and evapotranspiration. The results indicate that future climate change may lead to changes in the distribution and intensity of precipitation, which will significantly impact the water resources system. By modeling different climate scenarios, it is possible to predict trends in the hydrological cycle, which can help formulate water resources management strategies to cope with climate change, as shown in

Table 2. Precipitation and evapotranspiration projections.

Year	Precipitation (mm)	Evapotranspiration Rate (mm/d)
2025	600	4.5
2030	580	4.8
2035	620	4.3
2040	550	5.0

Note: Self-created table.

.

The model simulation results also reflect the vulnerability of the water resources system in Hanzhong. By introducing different scenarios, the model assesses the stability and adaptability of the water resources system in the face of different pressures. For example, under increased levels of human activity or climate deterioration, the system dynamics model reveals the vulnerability of the water resources system and guides coping measures.

In

Table 3. Wetland area and aquatic ecosystem health index.

Year	Wetland Area (km2)	Water Ecosystem Health Index
2025	100	0.8
2030	95	0.7
2035	110	0.9
2040	98	0.75

Note: Self-created table.

, the model simulations’ results also relate to ecological environment trends. Ecological environment parameters such as wetland areas and the health status of aquatic ecosystems may change under different water management decisions. By simulating the changing trend of the ecological environment, it is possible to assess the impacts of different management strategies on the ecosystem and provide a basis for designing ecological compensation schemes.

The model simulates a comparison of water resource conditions under different decision-making scenarios by introducing decision-making variables for water resource management. These include adjusting reservoir storage, optimizing precipitation use, and evapotranspiration. Comparing the simulation results of different scenarios enables the assessment of their impacts on the water resources system and provides decision-makers with a scientific basis for choosing the water resources management strategy that best meets their practical needs.

6.3. Model-Based Ecosystem Compensation Program Development

Based on the system dynamics model’s prediction results for Hanzhong’s water resource situation, a series of ecological compensation programs are formulated. These programs aim to achieve a good relationship between economic development and ecological balance in water resource management. The following is the specific content of the ecological compensation program.

Based on the results of the model simulation, water stress can be effectively alleviated by optimizing water resource management decisions in the event of possible future water shortages. Therefore, an optimal water resource management plan is developed, including adjusting decisions on reservoir scheduling, precipitation use, and evapotranspiration control. The simulation of the system dynamics model can assess the changes in water resources under different management strategies and provide a scientific basis for decision-making.

Considering the impacts of water resources management on water ecosystems, it is recommended that a series of water ecosystem protection and restoration measures be implemented. The model simulation results show that factors that have a greater impact on water ecosystems, such as fluctuations in reservoir storage capacity and decreases in precipitation, can be identified. Based on these identification results, corresponding protection and restoration programs, including wetland protection and watershed ecological restoration, are formulated to promote the healthy development of water ecosystems.

In the model, it is taken into account that ecological compensation requires the introduction of economic instruments to optimize the use of resources. Therefore, a water resources tax system should be introduced to incentivize enterprises and residents to use water resources more rationally by taxing water resources. Through the simulation of the system dynamics model, the impact of the water resources tax system on the use of water resources can be assessed, and appropriate tax rates and adjustment strategies can be found. Aiming at the damage to the ecological environment caused by human activities, a compensation mechanism for ecological environment damage should be established. By adjusting the influence factors of human activities in the model, the changes in the ecological environment under different degrees of damage can be simulated. Then, the standards and mechanisms of damage compensation can be determined. This mechanism will help incentivize enterprises and individuals to pay more attention to protecting the ecological environment in their production and life and form an excellent environmental governance mechanism [29]. In order to encourage positive contributions to the ecological environment, an incentive policy based on eco-efficiency is proposed. By adjusting the eco-efficiency parameters in the model, the operation of the water resources system under different eco-efficiency can be simulated. Then, based on the simulation results, an incentive policy is designed to provide incentives to enterprises and individuals who have made significant contributions to ecological environment protection and to promote the improvement of the ecological environment.

Based on the model’s results, it is recommended that public participation and information transparency be strengthened in the formulation of ecological compensation programs. The model’s simulation can simulate the impacts of different decision-making options on public life and business operations, which will, in turn, lead to public understanding and support for the ecological compensation scheme. The mechanism of information transparency will also help establish a fair and equitable ecological system.

7. Ecological Situation under the New Program

7.1. Changes in Environmental Parameters

The ecological environment status under the new scheme is a further in-depth analysis of the model simulation results. It focuses on changes in various environmental parameters and aims to provide more detailed data support for the development of the ecological compensation scheme. By introducing data from actual observations and model simulations, a comprehensive understanding of the new scheme’s potential impact on Hanzhong’s ecological environment can be achieved.

Under the new program, the study focuses on changes in the area of wetlands, which, as an important ecosystem component, plays an important role in ecological balance. Based on the model simulation and actual observation data, the wetland area showed some fluctuating changes after the implementation of the new program, as shown in

Table 4. Comparison of wetland areas before and after the new program.

Year	Wetlands before Programme (km2)	Wetlands after Programme (km2)
2025	100	95
2030	95	100
2035	110	105
2040	98	92

Note: Self-created table.

.

Observing changes in wetland areas allows one to assess the new program’s impact on ecosystems and provides data support for subsequent ecosystem compensation programs. The ecosystem health index is a comprehensive indicator for evaluating the condition of water ecosystems, taking into account the effects of several ecological parameters. The changes in the water ecosystem health index under the new scheme were obtained through model simulation and actual observation data, as shown in

Table 5. Comparison of water ecosystem health indices before and after the new program.

Year	Health Index of Water Ecosystems before New Program	Health Index of Water Ecosystems after New Programme
2025	0.8	0.85
2030	0.7	0.88
2035	0.9	0.82
2040	0.75	0.79

Note: Self-created table.

.

Changes in the water ecosystem health index intuitively reflect the new program’s program and the ecological environment of water bodies and provide an important reference basis for developing the ecological compensation program.

Quality is an essential indicator of the health status of water bodies, and several parameters, such as dissolved oxygen, nitrogen, and phosphorus, were considered comprehensively. The evolution of water quality indicators under the new scheme was obtained through actual monitoring and model simulation, as shown in

Table 6. Comparison of water quality indicators before and after the new program.

Year	Water Quality Indicators before the New Program	Water Quality Indicators after New Program
2025	favorable	talented
2030	medium	talented
2035	favorable	favorable
2040	medium	favorable

Note: Self-created table.

.

Water biodiversity is an essential factor in assessing the health of watershed ecosystems. As shown in

Table 7. Comparison of aquatic biodiversity indices before and after the new program.

Year	Aquatic Biodiversity Indices before the New Program	Aquatic Biodiversity Indices after New Program
2025	0.85	0.90
2030	0.80	0.92
2035	0.88	0.87
2040	0.75	0.78

Note: Self-created table.

, the diversity under the new scenario was obtained through practical surveys and models through practical surveys and model simulation simulations.

Changes in aquatic biodiversity have important implications for ecosystem stability and resilience, and the enhancements under the new program provide a scientific basis for developing ecosystem compensation schemes.

7.2. Results and Discussion

The simulation of the system dynamics model under the new program revealed several changes in several aspects, such as wetland area, aquatic ecosystem health index, water quality indicators, and aquatic biodiversity. A comprehensive assessment of these changes can show that the new program will positively impact Hanzhong’s ecological environment. The fluctuation of wetland area indicates that the ecosystem has been protected and restored to a certain extent; the improvement of the water ecosystem health index reflects the improvement of the overall health of the ecosystem, and the upgrading of the water quality indicators shows that the quality of the water body has been improved. The increase of aquatic biodiversity further strengthens the stability of the ecosystem.

Wetlands are an essential part of the ecosystem and play an essential role in water purification and biodiversity maintenance. The fluctuating changes in the wetland area under the planning of the new program are directly related to ecosystem restoration and the sustainable use of water resources. The results show that the moderate fluctuation of the wetland area indicates that the new scheme protects the wetland ecosystem to a certain extent, which helps to improve the anti-disturbance ability of the ecosystem and promotes the ecological service function of the wetland. The water ecosystem health index integrates several ecological parameters, and its enhancement reflects the stability and health improvement of the whole water ecosystem. Compared with the original scheme, the increase in the water ecosystem health index indicates that the new water resources management scheme is more conducive to the balance of the ecosystem and the maintenance of biodiversity, a result that suggests that the new scheme has taken into account the need for economic development and ecological and environmental protection in water resources management.

Not only the health of aquatic systems but also water quality, which is one of the intuitive indicators reflecting the health of water bodies and has an essential impact on human life and industrial production, the improvement of water quality indicators under the influence of the new program has provided a reasonable basis for improving the quality of water used by residents and reducing water pollution. Implementing the new program has reduced the discharge of pollutants and promoted enhancing the self-purification capacity of water bodies so that the ecological environment of the watershed gradually tends to be in a good state. Aquatic biodiversity is one of the critical indicators of the health of waters and is crucial to maintaining ecological balance and the stability of the food chain. The increase in aquatic biodiversity indicates that the various organisms in the ecosystem are provided with better habitat and reproduction conditions. The model simulation results show that implementing the new program has provided the waters with a more suitable environment for survival and has contributed to the enrichment and prosperity of aquatic biodiversity.

Although the new scheme has achieved some positive results, the system dynamics model used in the study also has several shortcomings and limitations, which need to be taken seriously and improved in future research and practical applications. The system dynamics model relies on much historical data and accurate parameter settings. Due to the difficulty in obtaining data related to water resource management in Hanzhong City, as well as incomplete or inaccurate historical data, the prediction results of the model may have inevitable errors. In addition, the accuracy and timeliness of data directly affect the reliability and effectiveness of the model, especially in the face of extreme weather events or sudden environmental problems. The model needs to be able to make timely and accurate predictions and responses. Although various relevant data have been collected and utilized as much as possible during the model construction process, parameter uncertainty remains one of the main challenges that system dynamics models face. Many parameters used in the model, such as the growth rate of water resource demand, changes in rainfall, etc., have significant uncertainty, and the uncertainty of these parameters may lead to deviations in the prediction results, thereby affecting scientific and effective decision-making.

In simulating the process of water resource management, system dynamics models mainly consider explicit variables such as water quantity and quality. However, the complexity of ecosystems determines that far more factors affect water resource management. For example, changes in soil structure, succession of plant communities, and the impact of climate change on evaporation and precipitation patterns all significantly impact the utilization of water resources and the protection of the ecological environment. These complex environmental factors are difficult to fully reflect in the model, resulting in certain limitations when dealing with practical problems. Water resource management involves natural ecosystems and is profoundly influenced by socio-economic factors. For example, population growth, economic development, and land use changes will all significantly impact the demand and utilization of water resources. Although the system dynamics model considers these factors to a certain extent, its prediction of the dynamic changes in water resource demand for socio-economic development needs to be more comprehensive and accurate, which may lead to a disconnect between management strategies and actual demand.

Although specific achievements have been made in applying system dynamics models in Hanzhong City, the applicability and universality of the models are still worth exploring. The water resource management issues in Hanzhong City have specific local characteristics, and many parameters and variable settings in the model may not apply to other regions. The model’s effectiveness may be limited, especially in areas with water scarcity or insufficient rainfall, and further adjustment and optimization are needed.

8. Conclusions

Through the study of water resources management and ecosystem compensation in Shaanxi Province, this thesis explores the potential impacts of the new water resources management program on the ecosystem from the perspective of sustainable development. It provides a scientific basis for developing a reasonable ecosystem compensation program. Through the establishment and application of the model, a series of simulation results on water resources management, wetland area, water ecosystem health, water quality index, and water biodiversity are obtained. Implementing the new scheme positively impacts wetland protection, water quality improvement, and water ecosystem health. The fluctuating changes in wetland areas indicate that the ecosystem has been protected to a certain extent. The water The fluctuation of the wetland area shows that the ecosystem has been protected to a certain extent; the improvement of the water ecosystem health index reflects the improvement of the overall health of the ecosystem; the upgrading of the water quality index provides cleaner water for the ecosystem; and the increase of aquatic biodiversity further strengthens the stability of the ecosystem. However, the simulation results of the model are affected by several factors, including the accuracy of the data, the precision of the model, and the uncertainty of future development. When developing water resource management and ecosystem compensation programs, the simulation results should be treated with caution, taking into account various factors in the actual situation.

This study provides a research framework for water resource management and ecological compensation based on a system dynamics model. It provides an in-depth analysis of a specific case in Shaanxi Province. Implementing the new program provides important lessons for sustainable water resource management and the achievement of ecological balance. It also highlights the need to balance economic development and ecological protection when formulating management strategies and compensation programs.