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Socio-Hydrological Approach for Water Resource Management and Human Well-Being in Pinglin District, Taiwan

Graduate Institute of Bioresources, National Pingtung University of Science and Technology, Pingtung 912, Taiwan
Institute for Global Environmental Strategies, Hayama 240-0115, Kanagawa, Japan
College of Humanities and Social Sciences, National Pingtung University of Science and Technology, Pingtung 912, Taiwan
Authors to whom correspondence should be addressed.
Water 2023, 15(18), 3302;
Submission received: 18 August 2023 / Revised: 11 September 2023 / Accepted: 16 September 2023 / Published: 19 September 2023


Despite being a limited resource, pollution, poor management, and other drivers like climate change make available water unsuitable and insufficient for human consumption and ecosystem maintenance. Therefore, a transdisciplinary approach is needed for managing this precious resource. The overall aim of this paper is to address water inequalities and improve human well-being using an integrated approach of key informant interviews, hydrological modeling, and the payment of ecosystem services (PES) scheme in Pinglin District, Taiwan. This site is an upstream area of Feicui Reservoir, which protects the downstream tap water supply. Key informant interviews were conducted to identify the gaps in and challenges to water resource management. This was followed by a scenario-based hydrological simulation using a Water Evaluation and Planning (WEAP) tool to project future water quality by the year 2050 (using biochemical oxygen demand and total coliform content as key indicator parameters) and to trace the factors responsible for water pollution. Survey analysis of key informant interviews depicts that this area is facing several challenges, such as lack of water infrastructure, agricultural subsidy, construction restrictions, etc., which cumulatively cause water scarcity in the upstream regions. On the other hand, hydrological simulation results show that population decline and climate change under an RCP 8.5 scenario will have an enormous negative impact on water quality. The concentrations of BOD and E. coli in river water will expand by 110.1% and 117.3%, respectively, by 2050 compared to 2018. Finally, the results of the study suggest that the PES scheme can play a positive role in enabling integrated water resource management. For example construction of a small-scale wastewater treatment plant in the upstream area will reduce the total E. coli concentration by up to 90%. While the initial cost of construction will be taken care of by the government, the operation and management cost of this infrastructure will be covered by people living downstream, who need to pay only $0.10 per year per person. The obtained results should be vital for both the stakeholders and decision-makers in this region.

1. Introduction

Meeting demands for freshwater while providing a sustainable equilibrium between human activity and ecological imperatives is a major challenge [1]. Population growth and climate change are altering both the spatial and temporal patterns of water distribution, increasing competition for increasingly scarce water resources [2]. In addition, poor governance and lack of water treatment infrastructure are causing deterioration of the water environment [3]. In many Asian countries, 80% of untreated wastewater is discharged directly into water bodies, leading to the deterioration and reduction of natural resources [4,5]. Approximately 5 billion people worldwide inhabit regions where freshwater consumption surpasses double its replenishment rate [6]. It is easy for water pollution to occur (whether from a point source or a non-point source). Water pollution is a challenge to water resource management. Therefore, it is necessary to improve water quality through water resource management.
To accomplish effective water resource management, multiple methods and tools have been utilized to evaluate the processes governing the evolution of water resources (including both quality and quantity) at any particular location. However, there are many physiological, socioeconomic, and institutional linkages in the global water system. Addressing water pollution cannot be solved by traditional water management strategies alone. Integrated approaches and institutional change (i.e., horizontal and vertical integration) are needed. Examples include sustainable management [7,8], ecosystem services [9,10], payment for ecosystem services (PES) [11], and policy governance [12,13,14]. Using an integrated approach of field survey, laboratory analysis, statistical analysis [15], and hydrological simulations [16,17] for the hydrological research and the expected result is helpful for both the scientific communities and policy-makers.
Ecosystem services involve the ongoing interactions of various structural elements, including the water cycle, gas regulation, climate regulation, energy transfer, and nutrient cycling [18]. These interactions produce a range of benefits that are both directly and indirectly appropriated by humans, thereby creating specific ecosystem services like regulating, cultural, and provisioning services. Examples of key ecosystem services include habitat management, microclimatic regulation, disturbance management, hydrological regulation, sediment erosion management, pedogenesis, nutrient circulation, natural pest management, climate change adaptation, freshwater production, biodiversity conservation, and leisure activities [19,20]. PES involves the provision of compensation for the provision of environmental services. This entails the allocation of resources with the explicit purpose of enhancing the preservation and upkeep of environmental services, encompassing endeavors like reforestation, mitigation of soil erosion, and the adoption of conservation methodologies, among various other measures as outlined in reference [21]. Within the framework of hydrographic basins, the concept of payment for environmental services (PES) involves the establishment of mechanisms designed to provide compensation to users for the purpose of upholding or modifying land use practices that may influence the amount and characteristics of water resources.
Pinglin District, located at the headwaters of Taipei’s Feicui Reservoir, was designated as a protected water resource area after the construction of Feicui Reservoir in 1987. Due to its location within the reservoir’s catchment area, Pinglin and its three surrounding towns are subject to restrictions on new building and industrial development [22]. However, the water quality of the Feicui Reservoir still exhibits signs of eutrophication, primarily due to factors such as residential activities, tourism, agricultural runoffs, and ineffective soil and water conservation [23]. In response to these circumstances, the government is actively constructing wastewater treatment systems to handle domestic sewage [23]. Simultaneously, for agricultural areas, low-impact development is being adopted to mitigate non-point source pollution caused by agricultural activities [24,25]. To address the need of urban populations for clean drinking water, the Taiwan government designated the area as a water resource protection zone, strictly limiting the construction of new residential or commercial developments within the protected area. As a result, the economic and social development of Pinglin has been adversely affected [26].
This new zoning control is good for the environment, but it is quite unfair to the locals. It sacrifices the rights and interests of local residents for the sake of economic development, causing the socioeconomic gap between the rich and the underprivileged in urban and rural areas to widen. Kelly-Reif and Wing specifically noted the underappreciated dimension of environmental injustice that exists due to the current exploitation of urban-rural lands [27]. According to a Interview research results, there is a huge gap between the understanding of local governance institutions and what the locals need. To address such an issue, PES was introduced as a proposed policy approach tool to connect the government and local stakeholders [28].
In a wider context, Integrated Water Resource Management (IWRM) can be viewed as a category of nature-based solutions. As a well-established framework for planning, Integrated Water Resource Management (IWRM) could serve as a promising starting point to steer the effective execution of nature-based solutions across various sub-sectors [29]. The effectiveness of Integrated Water Resource Management (IWRM) hinges on achieving equilibrium between the well-being of ecosystems and human necessities [30]. Ecosystem management for both goals depends on understanding how ecosystems affect societal well-being; effective integration of scientific information and ecosystem services address this integration [31]. In Europe, the work of ecosystem services shows that the multifunctionality of water systems can help to reduce the impacts of extreme weather conditions [32].
With the aforementioned background and knowledge gap, the overarching aim of this study is to propose an integrated approach to address the challenges pertaining to water resource management and human well-being in the Pinglin area. More precisely, it aims to address the following three specific objectives: (1) identify the key issues leading to water inequalities in the local context; (2) run a scenario-based hydrological simulation to predict future water quality and to identify drivers and pressures governing the evolution of the water system; (3) propose localized IWRM by focusing on the implementation of PES.

2. Case Study Area

Pinglin District (PD) (Figure 1) is the upstream catchment area of the Feicui Reservoir in Taipei. It is located northeast of Taiwan. Surrounded by mountains, the center is flat and the height of the ranges from 250 m to 1200 m above sea level. Pinglin District has a subtropical monsoon climate, with an average annual temperature of approximately 75 °F (21.1 °C), an average summer temperature of approximately 80 °F (25.6 °C), and an average winter temperature of approximately 60 °F (15.9 °C). The average relative humidity for the year stands at 85.8%, while the average annual precipitation in Pinglin is approximately 3500 mm. The rainfall is the heaviest from June to October every year. Attributed to the southward movement of the continental cold air mass, the months from October to January experience the highest frequency of rainy days. In 1984, the Taipei Water Management Office of the Water Resources Agency was established to manage water quality and quantity within the upper Xindian River watershed, all aimed at safeguarding the rights of local people and their water needs, and to protect the water source as a whole.
This study undertakes an empirical exploration of Taiwan’s Pinglin region, located in the upstream vicinity of the Feicui Reservoir. This pivotal water resource has historically fulfilled a dual role: supporting crop irrigation in the mountainous areas to generate income for the local population and serving as a clean drinking water source for the urban population downstream (around 5 million people). The rapid economic growth and intensified urbanization over the past few decades raise the following challenges, and hence ensuring the safety and quality of the water for urban residents became a paramount concern:
1. Water resource management and protection. The competition for water resources between agricultural and urban uses raises questions about equitable allocation and effective management. Preserving the water quality of the Feicui Reservoir is pivotal, not only for urban drinking water but also for sustaining the agricultural economy. Balancing these competing demands is essential for achieving long-term water resource sustainability.
2. Agriculture development and ecological conservation. While agriculture plays a crucial economic role, it can also contribute to non-point source pollution and habitat disruption. Striking a balance between agricultural expansion and protecting the ecological integrity of the region presents a complex challenge.
3. Socioeconomic equilibrium. Measures to uphold water quality standards can influence local socioeconomic development, unveiling a subtle synergy between environmental preservation and economic prosperity.
4. Policy and governance challenges. Achieving sustainable development intricacies demands a cohesive policy framework reconciling diverse needs: agriculture, urbanization, and environmental preservation.
In response to these challenges, the government established a dedicated water management agency known as the Taipei Water Management Office under the jurisdiction of the Water Resources Agency (WRA). This agency assumes a pivotal role in orchestrating multifaceted responsibilities, including urban planning, the equitable distribution of incentives for water source conservation, pollution mitigation, and overseeing development within the watershed region. This intricate interplay starkly illuminates the delicate nexus between developmental pursuits and the imperatives of sustainability [26].

3. Methodology

Payments for ecosystem services (PES) schemes are purportedly innovative institutional frameworks designed to compensate producers of positive externalities. The core idea of PES is that land users, who tend to have little or no motivation to protect ‘nature’ on their land, are incentivized by direct economic benefits from beneficiaries of ecosystem services and can be motivated to embrace ecologically sustainable land use practices in order to safeguard the ‘nature’ present on their property, thereby contributing to ecosystem conservation and/or restoration efforts [32]. The literature indicates that Pinglin, as a water source provider, is facing a water resource crisis. For example, it faces water shortages caused by climate change or excessive concentrations of pollutants in rivers. Thus, conditional allocation through institutions can narrow the gap between institutions and social systems and lead to the most efficient allocation of scarce conservation resources [33]. The schematic representation of the methodology employed in this study is presented in Figure 2.

3.1. Key Informant Interview

Our research site is located in Pinglin District, Taiwan. From 22 January to 24 January 2022, we conducted key insider interviews with 35 local stakeholders to explore their perspectives on government practices of/policies on water resource management and their concerns in relation to the study area. Mainly tea farmers, village leaders, and paddy farmers between the ages of 25 and 70 (<30) were selected through a random sampling methodology and interviewed (Figure 3). They were asked how they are adapting to these direct and indirect drivers responsible for issues related to water insecurity. The questions were oriented towards natural resources, the distribution of state-controlled water resources, and the advantages and disadvantages of local ecosystem services. The coupled infrastructure systems approach (CIS), which is a systematic approach for collecting quantitative and qualitative data to represent governance institutions and design proxy indicators, was used. It emphasizes, whether its subject is hard or soft infrastructure, that production or maintenance requires investment and opportunity costs [34]. The CIS framework provides a breakdown of governance institutions into five distinct components [34], namely: hard human-made infrastructure (HHMI), which encompasses conventional infrastructure like bridges and roads; soft human-made infrastructure (SHMI), which includes local agricultural subsidies and the maintenance of the surrounding landscape; natural infrastructure (NI), which refers to naturally occurring features that hold significance for society, such as wetlands [35], and to the maintenance of the environmental landscape around the river; human infrastructure (HI) and social infrastructure (SI), which represent public welfare activities and educational visits by local people, respectively. Interview research has also shown that there are gaps between people’s expectations of government implementation and the direction of government’s actual investment, posing challenges [36].
Moreover, using the key results from the key informant interviews, we did a scenario-based hydrological simulation to further quantify the present condition and forecast future trends in water quality. The basic idea behind this exercise is to propose different plausible management schemes for water resource managers, in addition to maintaining the equity of the Ministry of Urban and Rural Environment.

3.2. Hydrological Model

3.2.1. Model Set-Up

The Water Evaluation and Planning tool (WEAP) operates on the fundamental principle of water balance accounting, ensuring that total inflows are equivalent to total net outflows and accounting for any changes in storage. This tool facilitates comprehensive assessments of specific water systems, representing primary supply and demand nodes and their interconnections both numerically and graphically. Furthermore, WEAP serves as a spatial reference for critical basin attributes, encompassing river and groundwater systems, demand locations, wastewater treatment facilities, watersheds, and administrative–political boundaries. Its user-friendly design ensures accessibility for local stakeholders, promoting ease of replication. Notably, the WEAP model’s capabilities extend to generating diverse scenario constructions, enabling policymakers and decision-makers to address pivotal “what if” inquiries. In this study, the entire research area was subdivided into smaller catchments based on topographical, hydrological, confluence, and climatic characteristics. Several hydrological modules, including the rainfall-runoff method (simplified coefficient method), irrigation demand only (simplified coefficient method), and rainfall-runoff (soil moisture method), are available in WEAP for simulating various aspects of the water cycle such as transpiration, infiltration, and runoff. Although the soil moisture method is a better method to evaluate the hydrological module, it is very data-intensive and needs values for various parameters from different soil layers. However, Pinglin District being a data-scarce region, the rainfall-runoff method (simplified coefficient method) is used for this study due to data availability [36].
The Streeter–Phelps model within WEAP was employed to estimate pollution concentrations in water bodies. This model simulates the oxygen balance of a river through two governing processes: oxygen consumption resulting from the decomposition of organic matter and reaeration resulting from oxygen deficiency. The removal of Biochemical Oxygen Demand (BOD) from water is determined by water temperature, settling rate, and water depth, as indicated in Equations (1) and (2):
B O D f i n a l = B O D i n i t e x p k r B O D U
B O D f i n a l = B O D i n i t e x p k r B O D U
BOD, or Biochemical Oxygen Demand, quantifies the amount of dissolved oxygen consumed by microorganisms as they break down organic substances in aquatic environments. A higher BOD value serves as an indicator of increased organic material concentration within the water, which, in turn, signifies a heightened pollution level. In this context, we define various parameters as follows:
  • BODinit: the initial concentration of BOD (Biochemical Oxygen Demand) at the uppermost part of the watercourse, measured in milligrams per liter (mg/L).
  • BODfinal: the BOD concentration at the downstream end of the watercourse, also expressed in milligrams per liter (mg/L).
  • t: the water temperature, measured in degrees Celsius.
  • H: the water depth in meters (m).
  • L: the length of the watercourse in meters (m).
  • U: the water velocity within the watercourse.
  • Vs: the settling velocity in meters per second (m/s).
  • kr, kd, and ka: the rate constants for total removal, decomposition, and aeration, respectively, measured in reciprocal time units (1/time).
  • kd20: the decomposition rate at a reference temperature of 20 degrees Celsius (°C).

3.2.2. Data Requirement for Model Set-Up

For projecting the future water quality of the Xindian River, specifically for the year 2050, scenario analysis is employed to assess various potential water management strategies. The primary datasets essential for modeling encompass domestic wastewater discharge, river water quality data collected at different monitoring stations, population figures, rainfall patterns, temperature records, river cross-section data, river length measurements, river flow rates, and land use/land cover information, among others. A comprehensive list of these datasets and their respective sources is provided in Table 1. Biochemical Oxygen Demand (BOD) and total coliforms data, collected at three distinct points along the Xindian River, constitute the key water quality parameters used in the modeling process. These datasets have been analyzed by the Water Resources Board following the standard water quality analysis methods established by the Environmental Protection Administration, Executive Yuan, R.O.C. (Taiwan). These parameters were chosen due to their regular availability for the simulation phase, making them the most viable options for the study. The selection of sampling sites was based on factors such as accessibility to water samples, cost-effectiveness, and the ability to observe the impact of urbanization at approximately equidistant locations within the river’s watershed. For hydrological modeling, we considered the upstream and downstream areas within the Xindian River watershed that experienced interbasin transfers. The modeling option also accounted for the transport of pollutants from catchments through rainfall-runoff mechanisms. On non-rainy days, pollutants accumulate on catchment surfaces and are subsequently carried into water bodies through surface runoff during the next rainy episode. For future precipitation data, we used two different global climate models (GCMs) (CESM1-CAM5 and MIROC5), along with outputs from representative concentration pathways (RCPs) 2.6, 4.5, and 8.5, after performing downscaling and bias correction. The quantile-based bias correction technique was used to reduce the biases in the precipitation frequency and intensity in this study [37]. After scaling and correcting deviations, we assessed the mean change in mean monthly precipitation for RCP 4.5 and RCP 8.5 to assess climate change for water quality. The study area was partitioned into three distinct demand zones, but our primary focus was solely on the upstream region to assess how population decline and the consequent discharge of domestic wastewater affect the current state of river water quality. The upstream area holds particular significance, as it is designated as a water quality protection zone. To estimate the future population in this area, we relied on the population projections provided by the National Development Council for the Republic of China (Taiwan). In the absence of precise data regarding the total volume of domestic wastewater, we assumed an average daily per capita domestic wastewater quantity of 130 L for this study. Additionally, we generated detailed land cover maps using ArcGIS version 10.7.
The simulated water quality results were compared with Grades A and B (i.e., Grade 1 public water), meaning that only water that is disinfected can be supplied to the public water supply. This stipulation is the surface water quality standard required by the Taipei Water Source Reserve. The established threshold values for BOD and total coliforms are as follows. For category A, BOD should be less than 1 mg/L, and total coliforms should be less than 50 mg/L. For category B, the corresponding limits are BOD less than 2 mg/L and total coliforms less than 5000 CFU/100 mL. The entirety of our simulation process was structured into three distinct phases: (a) initial model set-up and data input, (b) subsequent calibration and rigorous validation, and (c) the forward-looking simulation phase, which entailed scenario analysis. A summary of the dataset used for hydrological simulation for this study is presented in Table 1.

4. Results

4.1. Identification of Gaps in and Challenges for Water Resource Management

The policymakers need to consider the range of challenges and opportunities that climate change may pose and make decisions under high levels of uncertainty to achieve resilient cities [44]. Here, we review Taiwan’s Pinglin District, which is tasked with protecting the freshwater resources and water quality of the greater Taipei region’s 5 million people from destruction and pollution. The researchers compiled the interview data of 35 key informants and painted a picture in the form of three identified gaps between government practices and local stakeholder’s perceptions (in Figure 4). With the interview results, it was found that the local people are very concerned about water shortage (whether it is regarding their livelihood or agriculture), limited infrastructure development to cater to water quality improvement, and they sincerely hope that the government can provide improvement measures. The degree of social fit is biased towards the needs of urbanites but is less than that of local stakeholders.
Water of varying qualities is required by many industries and in different quantities by different users in a watershed. Allocating this water among various stakeholders involves integrated water resource management [29]. The basic concepts and principles of IWRM, such as economic efficiency, social justice, and ecological sustainability, are known and accepted [45,46]. However, future population growth or climate change will put pressure on water management. The question of how to adapt to the pressure of threats to the management of water resources is a significant challenge for local authorities.

4.2. Forecasting Future Hydrological Simulation Variables

Hydrological simulation modeling considers three key factors: land use, climate change, and population decline. The projected values of all parameters were computed for the target year of 2050, and the outcomes are illustrated in Figure 5. In Figure 5a, the findings regarding land use change are presented, demonstrating minimal alterations in the vegetation and building categories, a result of the government’s policies and decrees that strictly control local land use methods. The purpose of these controls is to maintain the safety of downstream water quality. Figure 5b shows the simulated comparison of monthly average rainfall between simulated values under different scenarios in 2050 and observed values in 2018. Two different GCM and two RCP models are used to compare the observed data and downscaled future projected data. We noticed subtle variations in monthly precipitation levels. Figure 5c shows population projection results for the study area based on the national guide [47]. The results show that the population in 2050 declines by 30% compared with 2018 levels. In this study, we consider the above influencing factors and examine whether they affect the water quality of the river.

4.3. Evaluating and Simulating Model Performance

Before a WEAP model can predict future scenarios, it must be calibrated and validated with test data. The entire WEAP module is mainly focused on the water quality component. In this study, model evaluation was performed using information on BOD. Model validation for BOD is shown in the bar graphs of Figure 6. The simulated BOD has a strong correlation with the correlation coefficient (R2) = 0.93 and the average error is approximately 5%. After completing validation with significant statistical values, we performed simulations for future water quality.
The future prediction of river water quality and discharge was simulated, taking into account three primary drivers of change: population decline, land use/land cover change, and climate change. These drivers were combined to create various scenarios in order to address “what if” scenarios: (a) population decline only; (b) population decline and climate change; (c) population decline and extreme climate change. These scenarios were developed to explore the potential impacts of different combinations of these drivers on the river’s water quality and discharge.
The results obtained from the hydrological model were compared with the national guidelines (as shown in Figure 7) for category B stream quality, which corresponds to drinking water standards where BOD should be less than 2 mg/L and total E. coli should be less than 50 CFU/100 mL, as specified by the Environmental Protection Administration, Executive Yuan (ROC). Examining Figure 7a, it is evident that the BOD concentrations under different scenarios ranged from 0.82 to 1.35 mg/L, indicating that the water quality remains good in accordance with the desirable water quality guidelines throughout the river section. However, when looking at the simulated results for total coliform (Figure 7b), the values ranged from 788 to 4852 CFU/100 mL under different scenarios. Unfortunately, none of the scenarios comply with the desirable values. The situation worsens, especially when considering the scenario with extreme climate change and land use/land cover changes, as the concentration of total coliform increases significantly.

4.4. Scenario with WWTP under PES Scheme

PES schemes provide payments to managers of land or other natural resources in exchange for the provision of definite ecosystem services (or actions expected to provide those services). Payments are made by the beneficiaries of the services concerned, such as individuals, communities, companies, or governments acting on the behalf of various parties [48]. PES is a novel scheme to make those who provide ecosystem services pay for them, just like any commercial service. Examples include climate regulation, water quality regulation, and the provision of wildlife habitats. It focuses on the ‘beneficiary pays principle’ principle rather than the ‘polluter pays principle’ [49]. The idea behind the compensation package highlighted in this article is to extrapolate the payment costs through the downstream beneficiary population. To protect the water quality of Beishi Creek, the PES calculation includes water quality requirements to improve the watershed environment as well as the operational management of the wastewater field. First, we know from scenario simulation analysis that future climate change will cause drastic changes in river water quality. Therefore, it is imperative to build small wastewater treatment plants and hence we have considered building other scenarios with the incorporation of WWTP.
Figure 8 shows that 90% of E. coli can be removed in a future scenario with WWTP. The cost of wastewater treatment generally depends on the type of treatment technology, its efficiency, and the discharge options used. Another factor is the size of the population served [50]. Considering both factors, we have estimated the cost of WWTP using a literature review. It can treat 500 MLD of water and the result shows that it will cost 1,079,654 USD [51]. Then, we have added the cost of pipelines to bring the domestic wastewater to the WWTP. The result shows that the cost of laying pipelines in the study area is approximately 20,000 USD per household, and a small wastewater plant in Pinglin will cost approximately 40,780 USD in total [51]. For this study, we have assumed that the initial cost for installing this infrastructure will be taken care of by the local government. However, the actual cost of operating the wastewater plant is approximately 25,501 USD, and approximately 2.1 million people use this treated water in the downstream area. Hence, sharing this operation amount per head, each person only needs to pay 0.1 USD each year. After consultation with people downstream, most of the beneficiaries were supportive of this idea for the long-term operation of small wastewater treatment plants and the promotion of the sustainability of water resources.

5. Conclusions and the Direction for Future Studies

Field visits and key informant interviews indicate that local management institutions in this region are not meeting local needs, and other governance methods are needed to improve social adaptability. A scenario-based hydrological simulation for water quality components shows the average concentrations of BOD and total coliforms within river water will increase by 110.1% and 117.3% by 2050, respectively, when compared to 2020. This observation underscores the dynamic nature of the region and the significant influences stemming from population growth and future climate changes, and highlights that climate uncertainty must be incorporated into water resource management policy planning. In addition, management decisions must consider interdependent resources in upstream and downstream parts of the watershed. Utilizing payment for ecosystem services (PES) in the planning process aids in the development of more effective strategies for creating ecosystem services and enhancing human well-being. The implementation of payments for ecosystem services in the allocation of water resources is intricately intertwined with the pursuit of sustainable development. When implementing payment for ecosystem services (PES), it is crucial to emphasize effective accountability and equitable distribution of benefits. These practices play a pivotal role in bolstering public willingness to engage in ecological conservation efforts [52] Based on the hydrological simulation analysis in the scenario with infrastructure, a plan for joint management of water quality between people and local governments in the upstream and downstream regions is proposed. It is found that, by paying 0.1 USD per person per year in the downstream area, the operation of small wastewater plants in the upstream area can be maintained, which can effectively maintain water safety in the face of rapid environmental changes in the future.
However, the results have some limitations, which we expect will force academics and practitioners to reconsider. (1) The government’s development policy for the region, and the question of how to balance the supply of urban and rural public infrastructure in a more ‘efficient’ and ‘fair’ manner for advanced coordinated urban and rural growth, while working to narrow the gap over time. (2) Sustainable water allocation frameworks should be considered. However, payment for ecosystem services is an alternative policy tool. Examining the public’s willingness to financially contribute to the water quantity and quality of the basin remains a necessary undertaking. Additionally, it is essential to gauge the level of support from participants involved in ecological protection of water resources (beneficiaries) for the PES criteria of the basin through open negotiations..

6. Potential Areas of Future Research

Simulating the Development of Urban-Rural Disparity.
Urban bias theory (UBT) in development economics states that there are challenges endemic to the large urban–rural disparities in the process of industrialization and urbanization [52]. Governmental responses to economic and developmental challenges have led to the implementation of various policies and social problems and have typically favored cities over rural areas [52,53]. This has resulted in increased consumption between urban and rural populations and income and wealth inequality, which are especially manifested by large income gaps [54], judging from the population structure of Pinglin. This situation suggests that the area is facing population decline, possibly due to the lack of jobs in the area, leading to a brain drain and loss of young people. Furthermore, according to the literature, state investment in regional construction is primarily aimed at maintaining water and soil protection, not at building structures that will contribute to regional economic development [55]. The coordinated development of towns and countries depends heavily on political decisions and infrastructure development [56,57]. Moreover, the impact of improved infrastructure on the relative level of regional economic development was confirmed by [57]. For example, the proactive efforts to advance infrastructure projects encompassing roads, water supply, electricity, and various other categories in recent years have made a substantial contribution to bridging the economic development gap between urban and rural areas in the United States.
Hence, there is a recommendation for both central and local governments to enhance the equilibrium in providing public infrastructure to urban and rural regions, with the aim of synchronizing urban and rural development and progressively diminishing the disparities. One key aspect is to accentuate the government’s role in allocating public funds. Governments need to avoid excessive disparities between urban and rural areas that create social conflict and hinder sustainable development. Another strategy involves giving precedence to investments in upstream infrastructure resources and provisioning. These resources are urgently needed, especially for essential public infrastructure resources like water supply systems and small wastewater treatment plants. Only by coordinating synergies between public infrastructure can a proper balance or coordinated development of towns and countries be achieved.
Sustainable Water Resources Allocation Framework
The objective of payment for ecosystem services (PES) is to attain a mutually beneficial outcome through collaboration between upstream and downstream basins [53]. After all, water is a public good. Therefore, the allocation of water resources should be based on social justice. Social justice focuses on the proper allocation of water resources in society. Equity has received little attention in the allocation of limited water resources, as the standard of equity is typically different for different people [58].
Through future scenario analysis, it has been confirmed that by 2050, the water quality in upstream areas will develop a serious pollution problem. Building a small sewage treatment plant means that maintaining good water quality becomes easier. The downstream area should pay for the addition and maintenance of small sewage treatment plants upstream in the basin. Upstream of the catchment, enhanced water management can meet downstream water demand. Suitable payments have the potential to incentivize watershed providers of ecosystem services to transition from outdated production methods and lifestyles [59]. Consequently, during the implementation of water resource ecosystem services, it is imperative to comprehensively incorporate the objectives of social development and ecological preservation, all while focusing on the restoration of the watershed’s ecosystem. This approach should also help mitigate the adverse impacts on upstream areas, which may experience detrimental development trends due to heightened downstream water supply demands [59].

Author Contributions

Conceptualization, T.-J.J., P.K., H.C. and O.S.; methodology, P.K. and H.C.; software, T.-J.J. and P.K.; validation, T.-J.J. and P.K.; formal analysis, T.-J.J. and P.K.; investigation, T.-J.J. and P.K.; resources, T.-J.J. and P.K.; data curation, T.-J.J. and P.K.; writing—original draft preparation, T.-J.J. and P.K.; writing—review and editing, T.-J.J., P.K., H.C. and O.S.; visualization, T.-J.J. and P.K.; supervision, T.-J.J. and P.K.; project administration, T.-J.J. and P.K.; funding acquisition, T.-J.J. and H.C. All authors have read and agreed to the published version of the manuscript.


This research is sponsored by the funding of Belmont ABRESO “Abandonment and Rebound—Societal views on landscape and land-use change and their impacts on water and soils” MOST 110-2116-M-002 -022 -MY3 and JST Belmont Forum Grant Number JPMJBF2102.

Data Availability Statement

All data used here is mentioned within the article. Otherwise, publicly available datasets were analyzed in this study and can be found here: [, accessed on 17 August 2023].


First authors would like to express heartfelt gratitude to the internship programme from Institute for Global Environmental Strategies, Japan, which provided favorable environment and facilities for his short stay to conduct this research work. Also, all authors would like to sincerely thank all the anonymous reviewers for their valuable time and providing constructive comments for improving the quality of this manuscript by many folds.

Conflicts of Interest

Authors declare no conflict of interest.


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Figure 1. Study area.
Figure 1. Study area.
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Figure 2. Methodology flowchart for the study.
Figure 2. Methodology flowchart for the study.
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Figure 3. Key informant interviews.
Figure 3. Key informant interviews.
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Figure 4. Identified gap in and challenges for water resource management source using results from key informant interviews.
Figure 4. Identified gap in and challenges for water resource management source using results from key informant interviews.
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Figure 5. Estimated future value for different factors: (a) land-use analysis; (b) monthly rainfall data, considered in the hydrological simulation; (c) population of the study area.
Figure 5. Estimated future value for different factors: (a) land-use analysis; (b) monthly rainfall data, considered in the hydrological simulation; (c) population of the study area.
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Figure 6. The validation of the model output involved comparing the simulated values to the observed values of average Biochemical Oxygen Demand (BOD) at various locations for the year 2018.
Figure 6. The validation of the model output involved comparing the simulated values to the observed values of average Biochemical Oxygen Demand (BOD) at various locations for the year 2018.
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Figure 7. Results show simulated water quality parameters: (a) BOD; (b) total E. coli for future scenario without adaptation measures.
Figure 7. Results show simulated water quality parameters: (a) BOD; (b) total E. coli for future scenario without adaptation measures.
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Figure 8. Scenario with WWTP under PES scheme.
Figure 8. Scenario with WWTP under PES scheme.
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Table 1. List of data used in this study with their source.
Table 1. List of data used in this study with their source.
S. No.ParametersTime IntervalScaleSource
1Population2008YearlyCensus of Taiwan [38]
2011–2050YearlyUNDESA [39]
2Water Quality (BOD, Tot. Coli)2010–2020MonthlyTaipei Water Management [40]
3River Cross-Section, StreamFlow2010–2020QuarterlyWRA [40]
4Rainfall, Temperature1984–2018 (Past data) average gave a value for current condition for year 2020MonthlyTaipei Water Management [39]
2021–2070 (Future data) average gave a value for future condition for year 2050TCCIP [41]
5Land Use Land Cover Map2010 and 2020YearlyLANDSAT [42]
2050Land change modeler [43]
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Jiang, T.-J.; Kumar, P.; Chien, H.; Saito, O. Socio-Hydrological Approach for Water Resource Management and Human Well-Being in Pinglin District, Taiwan. Water 2023, 15, 3302.

AMA Style

Jiang T-J, Kumar P, Chien H, Saito O. Socio-Hydrological Approach for Water Resource Management and Human Well-Being in Pinglin District, Taiwan. Water. 2023; 15(18):3302.

Chicago/Turabian Style

Jiang, Tasi-Jung, Pankaj Kumar, Herlin Chien, and Osamu Saito. 2023. "Socio-Hydrological Approach for Water Resource Management and Human Well-Being in Pinglin District, Taiwan" Water 15, no. 18: 3302.

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