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Article

A Study on the Determination and Spatial Flow of Multi-Scale Watershed Water Resource Supply and Benefit Areas

by
Xinping Ma
1,2,
Jing Li
1,* and
Yuyang Yu
1
1
School of Geography and Tourism, Shaanxi Normal University, Xi’an 710126, China
2
School of Geography and Environment, Xianyang Normal University, Xianyang 712000, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(17), 2461; https://doi.org/10.3390/w16172461
Submission received: 22 July 2024 / Revised: 17 August 2024 / Accepted: 23 August 2024 / Published: 30 August 2024
(This article belongs to the Section Water Resources Management, Policy and Governance)
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Abstract

:
Based on the principle of water supply and demand flow and the natural flow of water, this paper analyzes the flow direction and discharge of water resources in the study area. In order to provide scientific and systematic implementation suggestions for regional water resource protection management and ecological compensation, a SWAT (Soil and Water Assessment Tool) model was constructed to quantify the water resource supply of the upper Hanjiang River basin at three spatial scales: pixel, sub-basin, and administrative unit. The water demand at the three spatial scales was calculated using the LUCC (Land Use and Land Coverage) and water consumption index. The supply and benefit zones under different spatial and temporal scales were obtained. Simultaneously, this study uncovered the spatiotemporal dynamics inherent in water resource supply and demand, alongside elucidating the spatial extent and flow attributes of water supply. The ecological compensation scheme of water resource supply–demand was preliminarily determined. The findings indicate an initial increase followed by a decrease in both the water supply and demand in the upper reaches of the Han River, accompanied by spatial disparities in the water supply distribution. The direction of the water supply generally flows from branch to main stream. The final ecological compensation scheme should be combined with natural conditions and economic development to determine a reasonable financial compensation system.

1. Introduction

Ecosystem services are the natural conditions and functions that people depend on for healthy ecosystems [1]. They include all the benefits we obtain directly or indirectly from these ecosystems [2]. After the vigorous development of the “Millennium Ecosystem Assessment”, the research of ecosystem services has begun a paradigm shift from natural science research to integrated natural science and social science research. Ecosystem services research more closely considers space–time heterogeneity than mobility and regional effects. Increasingly, there is a stronger focus on the pivotal role that ecosystem services play in enhancing human well-being [3,4]. Clarifying the demand space and demand structure of ecosystem services will help to elucidate the role of ecosystem services in promoting and constraining economic development, to determine the spatial allocation of environmental resources, and to provide theoretical support for ecosystem service payment and ecological compensation [5,6].
The production of products and services by ecosystems for human benefit constitutes the supply of ecosystem services, whereas the demand for such services arises from human consumption and the utilization of the products and services generated by these ecosystems. Collectively, they form the vibrant and interconnected process of ecosystem services, bridging natural ecosystems with human social systems [7]. Water resources provide a variety of ecosystem services for humans. The investigation into the equilibrium between the supply and demand of water supply services, as well as spatial flow, can offer a dependable scientific foundation for the enduring progress of river basins [8,9,10]. Some research cases on water supply services have been studied [11,12]. For instance, we can achieve a balance between the supply and demand of water supply services by constructing a model that incorporates both the services and their spatial flow. This model will help visualize and manage water distribution, ensuring efficient and effective water supply based on actual demand. Dengshuai, C. [13] conducted a quantitative assessment of the spatial and temporal patterns of water supply and demand at the sub-basin level. Additionally, they explored how different land use scenarios could impact the future balance of water supply and demand, as well as the spatial flow of water supply services. Hongjuan, G. [14] and her team employed the InVEST model to examine the spatial and temporal features of water supply services in the Wujiang River Basin between 1990 and 2010. The findings revealed that the water supply services in the basin first escalated and later declined. Moreover, the overall spatial pattern of water supply underwent more notable changes compared to the average spatial pattern.
From the perspective of ecosystem service flows, we can examine and understand how various services in ecosystems are transferred and transformed among different components. This viewpoint not only focuses on the generation of services but also emphasizes how they flow within the ecosystem, how they are utilized by various organisms and human activities, and ultimately how they affect the health and sustainability of the entire ecosystem. Jie, X. et al. [15] determined the regional scope of the Dongjiang River Basin benefiting from water supply services and simulated the flow and flow path of the system. Based on the estimation model of biomass ecosystem services, some scholars have conducted assessments on the changes in ecosystem services within the Lancang River Basin, highlighting the significance and importance of monitoring and evaluating such variations to ensure sustainability and ecological balance in the region. The results indicate that the regulation, support, and cultural services of the basin are experiencing an increase, whereas the supply services are gradually decreasing [16]. Based on the above studies, it can be found that most of the current studies on the flow of water ecological services are based on the supply and demand of water resources, while the quantification of water demand is a difficult problem. Many studies have adopted the InVEST model to analyze the flow of water resources in a basin, focusing on the calculation of water supply. The SWAT model can achieve the calculation of water supply on multiple scales and is more precise in spatial precision. In addition, this study also uses DEM to calculate the natural flow direction of hydrology, which provides validation data for water resources flow research.
As a vital component of ecosystem services, water resources offer a diverse range of products and services to humanity, underpinning the sustainable development of society. From the perspective of ecosystem service flow, an in-depth investigation and understanding of the transfer and transformation mechanisms of water resources among different ecosystem components hold immense significance for maintaining ecological balance and fostering sustainable development [17]. In recent years, the intensification of global climate change and human activities has exacerbated the contradiction between the supply and demand of water resources, making the study of water ecological service flow a focal point of academic attention. Utilizing various models and methods, including the InVEST model and the SWAT model, numerous scholars have conducted thorough analyses of water resource flow within basins, with special emphasis on calculating water supply and balancing supply and demand [18]. It is of paramount importance to scientifically evaluate the temporal and spatial dynamics of water resource service flow to gain a reasonable understanding of regional water resource security. By constructing a water resource service flow model, the balance of supply and demand, as well as the spatial distribution characteristics of water resources, can be quantitatively analyzed, providing a scientific foundation for water resource management. For instance, studies on the Yanhe River basin, Weihe River basin, and Beiluo River basin illustrate that the confluence between water resource supply and demand and its spatial distribution characteristics is crucial for the sustainable development of these basins [19]. Through quantitative analysis, the supply areas and benefit areas of water resources within the basin can be delineated, revealing the inherent laws of water resource flow. The study of water resource service flow holds great significance in bridging the gap between natural ecosystems and human society, scientifically assessing water resource security, guiding the rational allocation of water resources and ecological compensation, enhancing the theoretical research framework of ecosystem services, and promoting regional sustainable development. This study aims to further explore the temporal and spatial characteristics of water resource service flow, providing a scientific basis for the sustainable development and management of water resources within the basin by quantifying water demand and simulating water supply service flow paths. Additionally, the natural flow direction of hydrology is calculated based on DEM data, with the aim of comprehensively revealing the complex mechanisms of water resource service flow and offering theoretical support and practical guidance for water resource protection and rational utilization.
The Hanjiang River basin stands as a pivotal testing ground for China’s most rigorous water resources management system, underscoring its significance in shaping the country’s water governance policies. Furthermore, the upper reaches of the Hanjiang River serve as a critical water source for the South-to-North Water Diversion Project, highlighting its indispensable role in ensuring water supply for this national infrastructure initiative. In practice, the upper reaches of the Hanjiang River bear the dual responsibility of not only guaranteeing water supply for the South–North Water Transfer Project but also supporting the economic progress of Southwest China. Therefore, it is imperative to investigate ways for the inhabitants of the Hanjiang River basin to employ water resources more judiciously, thereby facilitating sustainable economic and societal advancement. Currently, water resource research in the Hanjiang River basin mainly includes the influencing factors of runoff change, the level of ecosystem services, and their interrelationships. The upstream basin of the Hanjiang River is a national key basin and ecological compensation area for water resources. Water supply is the most important part of the ecosystem service protection in the basin. To formulate more scientific and comprehensive policies for water resources management and ecological compensation within the basin, this paper employs the SWAT model to strike a balance between supply and demand. Additionally, it utilizes a spatial flow model to analyze water supply services in the upper reaches of the Hanjiang River. This is achieved by quantifying the supply and demand of water services specifically in the upper reaches of the Hanjiang River located in Shaanxi Province. This paper reveals the spatial and temporal correlation between water supply and demand at the Hydrologic Research Unit (HRU) scale. It determines the spatial scope and circulation patterns of watershed supply and benefit areas. Furthermore, it presents an ecological compensation scheme for water supply services among county administrative units, which is based on the self-sufficiency rate [20].

2. Materials and Methods

2.1. Study Area

The Hanjiang River originates in the Hanwangshan Mountain in Da’an town, Ningqiang County, Hanzhong city, southwestern Shaanxi Province. It is situated in 30°10′–34°20′ north latitude and 106°15′–114°20′ east longitude (Figure 1). The Hanjiang River flows from west to east, traversing the provinces of Shaanxi and Hubei, ultimately merging into the Yangtze River at Longwangmiao in Hankou, Hubei Province. The majestic main channel, stretching an impressive 1577 km, stands as the longest and most prominent tributary of the mighty Yangtze River. The area of the river basin is 15.9 × 104 km2, and it is the first river basin along the Yangtze River [21,22].
The upper reaches of the Hanjiang River, particularly those within Shaanxi Province, serve as the lifeblood for the Middle Route of the South-to-North Water Transfer Project. This region is bounded by the majestic Qinling Mountains in the north, the rugged Dabashan Mountains in the southwest, and the vast Jianghan Plains in the southeast, creating a landscape that slopes downward from the northwest to the southeast. The study area, shaped like a trumpet opening towards the southeast, experiences a north subtropical monsoon climate with ample rainfall.
During summer, the warm and moist air currents carried by the southeast monsoon are lifted by the lofty Qinling Mountains, resulting in a hot and rainy season. The annual average precipitation in this area hovers around 800 mm. In contrast, winters are cold and dry due to the influence of cold, high-pressure air from the northwest. However, the northern mountains provide a natural barrier, shielding the region from most of the cold air intrusion from the south. The climate remains generally temperate throughout the year, with an average annual temperature of approximately 15 °C and an extended frost-free period.
The soil types in this region exhibit remarkable diversity, including yellow-cinnamon soil, yellow soil, brown soil, and yellow-brown soil [23,24]. Natural vegetation thrives in this environment, boasting a rich variety of coniferous and broad-leaved mixed forests, deciduous broad-leaved forests, and evergreen broad-leaved forests.

2.2. Sources of Data

Soil data with a 100 m resolution were sourced from the World Soil Database (HWSD), which was gathered during Nanjing’s Second National Land Survey. The necessary parameters for the “USERSOIL” in the SWAT database can be determined either through the Soil-Plant-Air-Water (SPAW) software or by utilizing an empirical formula. Additionally, the LUCC (Land Use and Cover Change) data were obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences. DEM (Digital Elevation Model) data, boasting a spatial resolution of 30 m, were acquired from the International Scientific Data Service Platform. The Shaanxi Hydrology and Water Resources Bureau kindly provided runoff data from Ankang Station(Ankang hydrology and water resources survey center, Ankang, Shaanxi, China) spanning from 1970 to 2015. Meteorological data were downloaded from the China Meteorological Data Sharing Center (accessible at http://data.Cma.cn/ (10 March 2024)). As illustrated in Figure 2, the basin within the study area was segmented into 106 distinct sub-basins. The numbers in Figure 2 are watershed codes.

2.3. Data Input and Operation of the SWAT Model

This study used the ArcSWAT2012 version in the ArcGIS 10.3 environment. The SWAT model can be applied to basins of various scales and requires considerable input data [25]. However, the SWAT model defines the type and format of required input data, which can improve the accuracy of simulation results compared to other hydrological models [26]. The SWAT model was developed based on the environmental characteristics of the United States; so, when applied to the Han River basin, we made local adjustments to the parameters. The SWAT-CUP tool was used for automatic parameter calibration, the SUFI-2 algorithm was selected, and the parameter value range was set. The model was calibrated and verified according to the measured data to ensure that the model simulation results were consistent with the observed data [27].
The model necessitates data that comprise a spatial database and an attribute database [28]. The establishment of spatial databases requires land use data, soil data, and DEM (Figure 3). Figure 3 shows the required input spatial data for model construction. These spatial data were required for model construction, and all of them were preprocessed by projection transformation and format change. Utilizing ArcGIS, land use and soil maps were transformed into data sharing the same projection coordinate details and raster dimensions as the DEM, thereby standardizing the spatial resolution of the SWAT model operations to a unified 30 m.
The attribute database includes soil databases and meteorological databases. The land use data (grid) was reclassified against the land use data classification in the SWAT model and converted into a model-specified code. The parameters required for “USERSIOL” in the SWAT database can be calculated by a software (SPAW) or empirical formulas. The digital infrastructure model (DIM), featuring a spatial resolution of 30 m, was sourced from the International Science Data Service Platform. For each weather station, .TXT files were compiled, documenting daily precipitation, daily peaks and valleys in temperature, solar radiation levels, average wind speeds, and relative humidity. Utilizing its built-in weather generator (WXGEN), the SWAT model was employed to construct a comprehensive climate database, effectively filling in any missing data gaps. The statistical software pcpSTAT and dew02 provided by SWAT were used to identify the meteorological data and calculate the parameters required for the database [29].

2.4. Calibration and Verification and Uncertainty Assessment

After the model simulation runs, the model simulation result needs to be corrected and verified. In this study, we chose the Ankang hydrological station located at the outlet of the upper reaches of the Hanjiang River. To minimize errors, we adopted a one-month simulation step. To guarantee the precision and dependability of our simulation outcomes, it is imperative to establish a warm-up period, a correction phase, and a validation stage. Because, at the early stage of model operation, the initial values of many variables such as the soil moisture content are set to zero, it affects the simulation results. By setting the warm-up period, it can reasonably estimate the initial value of the model parameters to improve the simulation accuracy. The correction period is set to adjust and calibrate the model parameters to make the simulation results more consistent with the actual observed data. In this stage, we used the measured data to correct the model parameters to adjust the parameters to make the simulation results as close as possible to the actual observed data, thereby improving the model’s forecasting ability. In the verification period, the rated parameters are unchanged. The observed data in the verification period were used to test the prediction ability of the model. By comparing the simulation results with the actual observation data, we can evaluate the performance of the model and ensure that the model’s predictions are reliable and valid. Based on this, this study set 1996–1998 as the warm-up period, 1999–2010 as the correction period, and 2011–2015 as the verification period (Figure 4). The optimal values of the parameters were determined using the SUFI-2 algorithm [30], and then, the optimal values of the parameters were simulated and verified by manually tuning within the SWAT model. The results of parameter calibration are shown in Table 1. Three indicators were selected to evaluate the applicability of the SWAT model runoff simulation results in the upper reaches of the Hanjiang River: the relative error (RE), correlation coefficient (R2), and Nash–Sutcliffe efficiency coefficient (Ens). Related studies suggest that the simulation values of RE > 20%, R2 > 0.6, and Ens > 0.5 mean statistically significant results. Figure 4 shows that R2 and Ens are above the significance level. R2 is 0.79 and Ens is 0.79. Through this test, the model shows a good applicability in the upper reaches of the Hanjiang River, and the simulation results are credible. According to the initial uncertainty range provided in SWAT-CUP, 500 simulations were carried out for each region.

2.5. Water Demand Model

The water demand service within the basin underscores the need and utilization of water resources by individuals engaged in their daily lives and various production activities. Based on the water usage patterns observed in the upper reaches of the Hanjiang River, the water demand service model comprises primarily four categories, namely agricultural water, industrial water, domestic water, and ecological water. Water consumption data for each district and county within the river basin were sourced from water resources bulletins issued by Shaanxi Province, Ankang city, and Hanzhong city. The spatial location’s water demand is then computed according to the land-use type (Table 2).
W = Wa + Wb + Wc + Wd
where Wa is agricultural water, Wb is industrial water, Wc is residential water, and Wd is ecological water.
Drawing from the water distribution table for different land-use types, the water use statistics in the upper reaches of the Hanjiang River Basin were spatially discretized, aligning with the spatial patterns of land use. Furthermore, the water demand grid data were integrated with the specific geographical locations.

2.6. Self-Sufficiency Ratio of Ecosystem Services

To further analyze the production–demand relationship and flow balance type of regional ecosystem services, the threshold of regional ecosystem service flows needs to be defined. To evaluate the nature of ecosystem services, we calculated an index called the “self-sufficiency rate of regional ecosystem services”, which essentially represents the ratio between the supply and consumer demand of ecosystem services. Using this ratio, we can measure and analyze the flow trends of ecosystem services in different regions. In simpler terms, it involves comparing the supply and consumption situations of different plots to observe the direction and intensity of ecological services. The conceptual model is as follows:
Sij = Pij/Cij × 100%
where Sij is the self-sufficiency for a certain period for type j ecosystems in patch i, Pij is the production of type j ecosystem services in patch i, and Cij is the consumption of ecosystem services. According to the ecosystem service self-sufficiency rate, different types of flow balances can be categorized. Theoretically, when Sij > 100%, there is a net supply; 100% > Sij > 80%, basic self-sufficiency; 80% > Sij > 50%, semi-self-sufficiency; and 50% > Sij, net benefit. According to the balance type of the self-sufficiency rate, the supply area and benefit area for the flow of ecosystem services are determined.

3. Results

3.1. Spatial and Temporal Characteristics of Water Supply in the Upper Reaches of the Hanjiang River

Figure 5 shows the spatial and temporal distribution of the water supply in the basin of the study area. According to the simulation results, the maximum water supply per unit pixel is 1378.55 mm in space. Regarding spatial distribution, the southern region of the study area predominantly featured regions with a significant water supply, while regions with no water supply emerged in 2015. However, the area of high yield water also increased, which reflects the polarization of the spatial distribution of the water supply in the study area.
In the years 2000, 2005, 2010, and 2015, the upper reaches of the Hanjiang River recorded average water supplies of 608.13 × 108 m3, 675.98 × 108 m3, 699.509 × 108 m3, and 677.236 × 108 m3, respectively. When viewed from a spatial distribution standpoint, the variations in water supply become even more evident. Administrative counties with a high water production include Ziyang, Xixiang, Hanbin, Yang, and Ningshan. The changes in the amount of water produced in each district and county from 2000 to 2015 are also different. The production of water in Yu County, Chenggu, Yangxian, Foping, Liuba, and Taibai shows an increasing trend year after year, and the production of water in Hantai, Ziyang, Zhenba, Hanyin, and Shiquan all decrease. The concentration of water production in Ziyang indicates that the spatial distribution of water production is extremely uneven there; the lower degree of dispersion in water production in Taibai indicates that the spatial distribution of water production is very uniform there. Figure 6 shows that the production of water in each county during these four years is limited to very small areas. In terms of time, the extremely small areas of water production generally decrease in size by 2015, and Ziyang has the least space available for water production.
Based on the quantification of water production, the spatiotemporal dynamics of water supply in the upper reaches of the Han River in Shaanxi Province were comprehensively analyzed at various scales, including HRU, sub-basins, and county-level administrative units (Figure 7). At both the HRU and sub-basin scales, it was observed that the water supply in the upper Han River region experienced a gradual decline between 2000 and 2015. When viewed at the administrative unit scale, the water supply ranged from 49.7047 to 108.35 billion m3. In terms of the overall volume, the sub-basin scale exhibited the highest water supply, followed by the HRU scale, while the administrative unit scale had the lowest. Furthermore, the trend indicated an initial increase followed by a subsequent decrease.

3.2. Spatial Distribution of Water Supply and Service Demand in the Upper Reaches of the Hanjiang River

The quantitative assessment of water supply service demand in the upper reaches of the Hanjiang River basin relies on data pertaining to administrative divisions and land-use types within the basin. These upper reaches predominantly encompass the districts and counties of both Hanzhong and Ankang cities.
Between 2000 and 2015, the water demand in the upper reaches of the Hanjiang River Basin ranged from 8 to 1030.8 mm. Upon analyzing interannual variations, it was observed that water consumption in this region initially rose and then declined during the studied period. Additionally, the spatial pattern analysis revealed a consistent spatial distribution trend of water consumption across the studied years, with a higher water demand noticed in cities, towns, and their respective industrial districts (Figure 8).
We performed a spatiotemporal dynamic analysis on the water demand at different scales and obtained spatiotemporal variation maps of the water demand at the pixel, sub-basin, and administrative unit scales based on the pixel scale (Figure 9). From 2000 to 2015, the maximum water demand at the pixel scale gradually decreased; the maximum value at the sub-basin scale demonstrates temporal instability, exhibiting an initial increase followed by a decrease. Conversely, the water demand at the administrative unit scale displays a trend of decreasing initially and then increasing. Overall, the maximum water demand significantly increased by 2015.

3.3. Identification of the Water Supply Service Provision Zone and Benefit Zone in the Upper Reaches of the Hanjiang River

On the basis of the accounting of ecosystem service supply and consumption, the regional ecosystem service self-sufficiency ratio and the net surplus (supply minus water demand) were used to measure the flow tendency at the grid scale. According to the balance type of plaque flow, the supply area and benefit area of ecosystem service flow were divided. The difference between water supply and consumption can indicate flowability. Based on the balance of water resource supply and demand in the upper reaches of the Hanjiang River, the types of supply and benefit in this region were categorized (see Figure 10).
The administrative subdistrict statistics were determined by the self-sufficiency rate of water resources, which also governs the division of basin supply and benefit areas (Figure 10). Figure 10 illustrates that the supply area is primarily concentrated in the northern part of the basin, mainly in Taibai County, Liuba County, Ningshan County, and Foping County. The benefit areas are mainly urban units with better economies, such as Hantai District, Hanbin District, Nanzheng County, Ziyang County, and Hanyin County. In the upper reaches of the Hanjiang River, the flow direction of water supply is from the branches to the main stream, and these regions exhibit a relatively good economic development.
By analyzing the water supply and demand situation at different scales, Figure 11 was obtained. The figure reveals an imbalance in the water supply–demand situation at the pixel scale, yet, overall, this imbalance is spatially less dispersed, with most areas demonstrating a balance between water supply and demand. At the sub-basin scale, all are in a state of water supply–demand balance. Since 2010, there has been an overall decline in supply–demand levels. By 2015, the situation improved slightly, but the high value of supply–demand levels significantly decreased. At the scale of administrative units, a situation of water supply–demand balance is also observed, although the level of supply–demand is slightly lower compared to sub-basin scales. There was an overall spatial decline in 2010, but the situation improved in 2015.
The spatial–temporal rate of change in water supply, water demand, and supply– demand was analyzed, and Figure 12 was obtained. Figure 12 shows the variation degree of water supply, demand, and supply–demand in the study area at a 10-year time scale. Figure 12 indicates that the rate of change in the water supply is relatively high, and most regions show a trend of increasing supply in space. Areas with no significant increase accounted for 88.15%. The water demand in most areas also showed an increasing trend; only a few areas showed a decreasing trend, and the water demand did not increase significantly in the area, accounting for 99.8%. The change rate of supply–demand all showed an increasing trend, and most regions showed a very significant increase, with the area with a very significant increase accounting for 65.59%, and the areas with a significant and insignificant increase accounting for 33.81% and 0.6%, respectively. This indicates that the supply–demand of water resources will continue to remain in a clear equilibrium state in the future.
Based on the balance of water resource supply and demand, the region where the supply exceeds the demand is designated as the supply area, and the region where the supply is lower than the demand is set as the benefit area. In terms of space, Figure 13 shows the supply–benefit area at the scale of pixels, sub-basins, and administrative units. From the perspective of space, the supply area gradually increased in the three scales from 2000 to 2015, and the supply area in the pixel scale was relatively larger, while the supply area in the administrative unit scale was smaller.

3.4. Spatial Characteristics of Water Resource Supply and Service Flow in the Upper Reaches of the Hanjiang River

3.4.1. Flow Direction Analysis Based on the DEM

Expanding on the provided information, the analysis of water flow characteristics within the basin, as influenced by both elevation and supply, underscores the importance of understanding the spatial distribution of water resources. By utilizing the Digital Elevation Model (DEM), which provides elevation data for each individual pixel, researchers can effectively determine the direction of water flow across the landscape. This approach offers a precise method for analyzing water movement patterns and identifying key areas of water supply within the basin.
In the case of Ningshan County and Taibai County, both administrative units are recognized for their significant water resource supply within the basin. Through a detailed examination of the slope direction of each pixel in these two areas, it was revealed that the dominant flow directions were consistently south, southeast, east, and north. Notably, the preponderance of southbound pixels was particularly evident, with Taibai County showing 65% of pixels oriented in this direction, while Ningshan County also exhibited a high percentage of southbound pixels, accounting for 62% of the total (Figure 14). This finding highlights a clear trend in water flow directionality, emphasizing the southern trajectory as the primary path for water movement in these two counties.
Furthermore, this analysis underscores the importance of considering both elevation and supply when studying water flow within the basin. By incorporating DEM data, researchers can gain a more comprehensive understanding of how water resources are distributed and how they flow across the terrain. This knowledge is crucial for effective water management, conservation efforts, and mitigating the impacts of potential water scarcity or flooding events in the region. Additionally, it provides valuable insights for policymakers and planners in making informed decisions regarding sustainable water resource development and utilization strategies.
We counted the number of slope directions on all administrative units in the basin, and the flow direction of each administrative unit was represented by the polar coordinate diagram (Figure 15). The size of the sector in the diagram represents the size of the proportional number of pixels. Green means larger quantities, purple means smaller quantities. It is found that the quantity proportion in the south direction is the highest, and the overall flow direction is southward, followed by the east and southeast direction, and the north is the lowest.
This analysis involved counting the number of slope directions across all administrative units within the basin. The results were then visualized using polar coordinate diagrams, with each administrative unit’s flow direction being represented. The findings indicate that the southern direction dominates, accounting for the highest quantity proportion. This suggests that the overall flow direction within the basin is primarily towards the south. The east and southeast directions follow in prominence, while the north direction exhibits the lowest proportion. This distribution pattern provides valuable insights into the directional characteristics of slope flows across the administrative units in the basin.

3.4.2. Water Supply Direction Based on Supply–Demand

The flow of water resource supply services refers to the volume of water resources that originate from a supply area and have the potential to move or be utilized in different spatial locations. This concept of flow determination encompasses not just the overall quantity of water resources provided by the supply area, but also delves deeper into understanding the distribution and impact of these resources. Specifically, it clarifies which benefit areas are influenced by the water resource services offered by the supply area. Additionally, it quantifies the contribution made to each of these benefit areas, providing a comprehensive understanding of how water resources are allocated and utilized across different regions. This analysis is crucial for effective water resource management and ensuring the equitable distribution of water resources to meet the demands of various benefit areas.
Based on the self-sufficiency rate of water resources, the benefit area and supply area were analyzed for each of the four years. Regarding the spatiotemporal change, the benefit area changed spatially over the years. The surplus amount of water resources in each administrative unit was calculated using zonal statistics, and the direction of water supply flow was determined based on this surplus amount. The difference between the surpluses of the two regions indicates the flow amount. Using this metric, the flow path and spatial distribution chart of water supply service flow, based on the self-sufficiency rate, were obtained (Figure 16). Figure 16 illustrates that the flow direction of the water supply service consistently flows from the supply area to the benefit area. In general, the flow is from north to south, except in the southeast, where there are some areas of concentrated flow from south to north. The main supply areas are Taibai, Zhouzhi, Liuba, and Ningqiang. In addition, Liuba and Ningqiang are classified as supply or semi-supply areas. The main benefit areas are Hantai District and Nanzheng. In 2015, Hanyin, Hanbin District, and Ziyang became the benefit areas. In the graphs, the magnitude of the flow is represented by an arrow; specifically, the flow from the supply area to the semi-supply area is larger than the flow from the semi-benefit area to the benefit area.
Based on a thorough analysis of the self-sufficiency rate of water resources, a comprehensive examination of the spatiotemporal dynamics between benefit areas and supply areas was conducted over a four-year period. Utilizing advanced zonal statistics, the surplus amount of water resources in each administrative unit was precisely calculated, which subsequently determined the direction of the water supply flow. By analyzing the differences in surpluses between regions, the flow amount was determined, enabling the derivation of detailed flow paths and the spatial distribution charts of the water supply service flow based on the self-sufficiency rate. The findings uncovered a consistent flow direction from supply areas to benefit areas, with a primary flow from north to south, and notable exceptions in the southeast where the flow was concentrated from south to north. Key supply areas, including Taibai, Zhouzhi, Liuba, and Ningqiang, were identified, with Liuba and Ningqiang also being classified as semi-supply areas. The main benefit areas were found to be Hantai District and Nanzheng, while in 2015, Hanyin, Hanbin District, and Ziyang also emerged as benefit areas. The magnitude of flow was represented by arrows, indicating a significant flow from supply areas to semi-supply areas, which was greater than the flow from semi-benefit areas to benefit areas. Overall, this comprehensive analysis provides valuable insights and a deeper understanding of the spatiotemporal dynamics and distribution of water supply services.
According to the water supply and benefit area obtained from the previous work, the annual water compensation of benefit area was calculated. The primary benefit area in the upper reaches of the Han River is the Hantai District, the areas that contribute the most to the regional water supply are Liuba and Mianxian, and Chenggu is also the main supply area. According to the ecological compensation policy, the beneficiary area should pay the corresponding ecological compensation funds to the supply area. Therefore, it is recommended that the proportion of compensation funds should be calculated based on the ratio of the supply area to the benefit area. According to the calculation of water resources in the supply area and benefit area, the main benefit areas of water supply service in 2000 were Hantai, Nanzheng, Ningqiang, and Hanbin. Liuba, Mianxian, and Chenggu counties were the main supply areas. The main compensation areas were Liuba, Chenggu, Ningshan, Langao, and Mianshan.

4. Discussion

4.1. Challenges and Advantages

4.1.1. Temporal and Spatial Variations in Water Supply at the HRU Scale

The analysis involves studying the fluctuations in water supply patterns, including seasonal variations, annual trends, and spatial disparities across the HRU. Understanding these temporal and spatial variations is crucial for effective water resource management, as it allows for the identification of areas with high or low water availability, the anticipation of potential water scarcity or surplus periods, and the development of strategies to mitigate the impacts of these variations on water supply systems and ecosystems.
Based on the SWAT model, this paper uses factors such as soil, climate, and topography and simulates the amount of water produced at different time scales based on land-use changes. In the past, most of the studies used the sub-basin scale to determine the amount of water produced [23,24]. This study outputs the amount of water produced in the basin from the Hydrologic Research Unit (HRU) scale, offering a detailed quantification of water resources at this specific level. By conducting a quantitative study of the water supply and demand in the basin at the grid scale, it enables a comprehensive statistical analysis of water production within administrative units. This analysis provides a solid foundation for formulating flow directions, conducting thorough flow analysis, and devising effective ecological compensation schemes. It facilitates a deeper understanding of the basin’s hydrological dynamics, supporting informed decision-making processes related to water resource management, conservation, and sustainable development strategies.

4.1.2. Determining Flow Direction and Calculating Water Supply Based on the Self-Reliance Rate

Using the SWAT model, the spatial water production in the upper reaches of the Hanjiang River in Shaanxi Province was simulated to derive the spatial distribution of water demand in the basin, taking into account the LUCC and the water demand index. Based on the calculation of the self-sufficiency rate, the water supply benefit area and supply area were categorized into different periods. By conducting flow analysis, the direction of water supply in the upper reaches of the Hanjiang River was determined, and the flow was calculated. This provides a scientific foundation for the ecological compensation of water supply services in the area. Most of the water supply service spatial flow simulations are based on the flow process under natural confluence, without considering the direction and rate of the supply–demand flows [25]. This paper presents two sets of flow results derived from DEM and supply–demand considerations. While most studies on water supply flows focus solely on the direction of water flow, they often overlook man-made factors, such as artificial water collection and pipeline diversion. Water-rich basins such as the Hanjiang River often contain important economic development areas. The implementation of the South–North Water Transfer Project has heightened the ecological responsibility for water resources in the upper reaches of the Hanjiang River. As a result, man-made water collection is bound to alter the direction and flow of water supply within the basin. Therefore, man-made water demand activities should be fully considered. Therefore, this paper provides the supply- and demand-based water supply service flow, and this method hopefully will be adopted by other scholars and applied to other large river basins.

4.1.3. Factors Influencing the Spatial Flow of Water Supply in the Upper Reaches of the Hanjiang River and Insights for Water Resources Management

The SWAT model is a hydrological model that mainly simulates runoff and sediment in a watershed. However, how to apply it to the study of ecological service flow is one of the difficulties in the field of ecosystem services [26,27]. Based on the results of SWAT model, this study delineated the supply area and benefit area of water resources in the basin and studied the flow direction of water resources. Based on the self-sufficiency rate, this paper identified the supply and benefit areas and identified the spatial flow and flow direction according to the water resources self-sufficiency of each administrative unit. The results indicate that the water supply service flows from the supply area to the benefit area. Both the supply area and the semi-supply area are primarily distributed in counties at higher altitudes and are situated at the source of the tributaries of the river basin. The semi-benefit areas occupy a large area, mainly concentrated in densely populated cities, and in recent years, there has been a trend of semi-benefit area expansion. Generally, the flow of water supply is closely related to the population density, topographic environment, and water resource protection method. Based on the analysis of the upper reaches of the Hanjiang River, it can be concluded that the headwaters of tributaries play a crucial role in the environmental protection of water resources. Ecological compensation should prioritize these areas. At the same time, the extent of the semi-benefit areas should be limited. In the benefit areas, rational water use policies should be emphasized, and water pollution supervision should be strengthened.

4.1.4. Research on Water Supply Services Lays the Groundwork for the South-to-North Water Diversion Project

Enhancing the overall water supply capacity in the upper reaches of the Hanjiang River holds immense importance for the South–North Water Transfer Project. Currently, numerous studies are examining the ecological compensation mechanism of the water source area pertaining to China’s South–North Water Transfer Project [28]. Utilizing the benefit-sharing coefficient method, certain researchers have computed the net benefits accrued to industrial and agricultural units located in the water-receiving regions of the Middle and Eastern Route Projects of the South–North Water Transfer [29]. Additionally, they have formulated an optimal allocation model for water resources. This model prioritizes maximizing the net benefits derived from regional water usage and considers constraints such as water supply and demand balances, along with the flow limitations of water diversion canals [30]. There are also some researchers [31,32] who employed both the ecosystem service value method and the total cost method of ecological protection to determine the upper and lower boundaries of the ecological compensation standard for the water source area of the Middle Route Project in the South–North Water Transfer. They then calculated the average of these two limits to establish the ecological compensation standard for the water source area.
The application outcomes indicate that the ecological compensation standard is most effective in Hanzhong and Shiyan cities. Notably, Shennongjia and Dazhou have the highest and lowest ecological compensation standard values, respectively. By analyzing land use shifts in the water source area of the Middle Route Project of the South–North Water Transfer from 2002 to 2010, researchers [33] conducted a comprehensive evaluation of the ecosystem service value and its fluctuations in the region. They established an upper limit standard and allocation system for ecological compensation, attempting to set an ecological compensation payment criterion based on variations in ecological service functions and dynamic value.
Some researchers [34] analyzed the existing governmental ecological compensation mechanism in the water source area of the Middle Route Project of the South–North Water Transfer Project and proposed the water rights trading model, the right to develop circulation model, the ecological economic model, and the public goods market purchase model. These studies often incorporate economic factors, even from the perspective of ecosystem services, to calculate ecological compensation. By considering ecosystem services, a more approximate value equivalent method can be employed [35]. In our opinion, to establish a reasonable and sound ecological compensation mechanism, we should consider not only economic factors but also the geo-ecological process in detail. This paper summarizes effective water resources management strategies by studying the spatial flow characteristics of water supply services in the upper reaches of the Hanjiang River. It aims to enhance water supply and quality in the source area of the South–North Water Transfer Project, thereby contributing to the project’s success [36,37]. Furthermore, in addition to water supply, water quality services, and water conservation functions, carbon sequestration and biodiversity services in the region should also be considered more comprehensively [38,39,40,41]. Enhancing the water supply service capacity in the upper reaches of the Hanjiang River is fundamental to ensure the smooth operation of the South–North Water Transfer Project. Good ecological environmental conditions are a prerequisite. Only by ensuring long-term water supply and ecological environmental quality can the South–North Water Transfer Project achieve sustainable development.

4.2. Uncertainty and Limitations

The upper reaches of the Hanjiang River, situated in the upstream water supply zone of China’s South–North Water Transfer Project play a pivotal role in providing essential ecosystem services, such as water supply, purification, and conservation. These services have profound impacts not only on the immediate environment but also on the middle and lower reaches of the Yangtze River, as well as the beneficiary regions of the South–North Water Transfer Project. The health and sustainability of the upper reaches directly influence the overall water security and ecological balance of these interconnected systems.
This paper considered the water resource supply and demand within the basin as a static flow, analyzing the internal dynamics and balances. However, to fully comprehend the complexities of water management and its implications for regional and national water security, future research must broaden its scope. It is imperative to expand the focus to encompass water supply flows across basins, considering the interconnectedness of water systems and the potential impacts of upstream activities on downstream regions [42,43]. This holistic approach will enable a more comprehensive understanding of water resource dynamics and facilitate the development of sustainable water management strategies that account for the intricate interdependencies between basins.

5. Conclusions

Based on the previously determined water supply and benefit areas, an annual water compensation calculation for the benefit areas was conducted. The primary benefit area in the upper reaches of the Han River was identified as Hantai District, with Liuba and Mianxian being the key contributors to the regional water supply, along with Chenggu as another main supply area. In accordance with the ecological compensation policy, it is stipulated that the beneficiary areas should remunerate the supply areas with corresponding ecological compensation funds. Consequently, it is recommended that the proportion of compensation funds should be determined by the ratio of the supply area to the benefit area. Following the calculation of water resources in both supply and benefit areas, the main benefit areas for water supply services in 2000 were identified as Hantai, Nanzheng, Ningqiang, and Hanbin, while Liuba, Mianxian, and Chenggu counties were recognized as the primary supply areas. The main compensation areas were determined to be Liuba, Chenggu, Ningshan, Langao, and Mianshan. This analysis provides a comprehensive understanding of the distribution of water supply services and the associated ecological compensation requirements.
By calculating the water supply–demand in the upper reaches of the Hanjiang River and combining these results with the self-sufficiency rate, the supply area and benefit area of water supply service were determined. Furthermore, the spatial flow characteristics of the water supply service were obtained, revealing that the main supply areas were Taibai County, Zhouzhi County, Liuba County, and Ningqiang County, which are classified as supply areas or semi-supply areas in the basin. The benefit areas include Hantai and Nanzheng counties. In recent years, Hanyin, Hanbin, and Ziyang counties have also become benefit areas. The flow from the supply area to the semi-supply area increases, whereas the flow from the semi-benefit area to the benefit area decreases.
Based on the spatial flow characteristics of water supply services, we summarized scientific strategies aimed at protecting water resources in the upper reaches of the Hanjiang River. The areas with higher altitudes and the headwaters of the tributaries of the Hanjiang River should be taken as the priority areas to protect, and the extent of the semi-benefit areas should be reduced as much as possible. The benefit areas should focus on implementing reasonable water use policies and strengthening water pollution supervision. The water resources protection strategy based on the spatial flow of water supply services can improve the overall water supply capacity of the upper reaches of the Hanjiang River. This research is dedicated to guaranteeing a sustained water supply in the upper reaches of the Hanjiang River, thereby ensuring the sustainable progress of the South–North Water Transfer Project.

Author Contributions

Conceptualization, J.L.; methodology, X.M.; software, X.M.; validation, X.M. and Y.Y.; formal analysis, J.L. and X.M.; investigation, X.M. and Y.Y.; identifying resources, J.L.; data curation, Y.Y.; writing the original draft, X.M.; writing, reviewing and editing, X.M.; visualization, X.M.; supervision, J.L.; project administration, J.L.; funding acquisition, J.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 42371297, 2024, and Shaanxi Provincial Sports Bureau Routine Project, grant number 20240673. The APC was funded by Jing Li, the National Natural Science Foundation of China, grant number 42371297.

Data Availability Statement

Restrictions apply to the availability of these data. Data was obtained from [third party] and are available [from the authors] with the permission of [third party].

Acknowledgments

We thank Jinbin Zhang, staff member of Shanxi Provincial Water Conservancy Department of China, for his generous sharing of hydrological data for this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location of the research area.
Figure 1. Location of the research area.
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Figure 2. Distribution map of meteorological stations.
Figure 2. Distribution map of meteorological stations.
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Figure 3. Sub-basin division and spatial data. (a shows the scope of the study basin and the spatial distribution of DEM. b shows the spatial distribution of LUCC in the basin of the study area. There are 6 types of land use in the basin. c shows the soil type map of the study area.)
Figure 3. Sub-basin division and spatial data. (a shows the scope of the study basin and the spatial distribution of DEM. b shows the spatial distribution of LUCC in the basin of the study area. There are 6 types of land use in the basin. c shows the soil type map of the study area.)
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Figure 4. Comparison of monthly runoff simulations and observations in terms of the periodic rate and validation period. (top) Rate periodic measured and simulated values; (bottom) The measured and simulated values in the validation period.
Figure 4. Comparison of monthly runoff simulations and observations in terms of the periodic rate and validation period. (top) Rate periodic measured and simulated values; (bottom) The measured and simulated values in the validation period.
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Figure 5. Spatial and temporal distribution of the water supply in the upper reaches of the Hanjiang River. (a) Spatial distribution of water supply in the study area in 2000; (b) Spatial distribution of water supply in the study area in 2005; (c) Spatial distribution of water supply in the study area in 2010; (d) Spatial distribution of water supply in the study area in 2015.
Figure 5. Spatial and temporal distribution of the water supply in the upper reaches of the Hanjiang River. (a) Spatial distribution of water supply in the study area in 2000; (b) Spatial distribution of water supply in the study area in 2005; (c) Spatial distribution of water supply in the study area in 2010; (d) Spatial distribution of water supply in the study area in 2015.
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Figure 6. Spatial and temporal change characteristics of water production in the administrative regions in 2000, 2005, 2010, and 2015. (a) Total water production; (b) Spatial dispersion of water production in each county; (c) Variation range of water yield in each county.
Figure 6. Spatial and temporal change characteristics of water production in the administrative regions in 2000, 2005, 2010, and 2015. (a) Total water production; (b) Spatial dispersion of water production in each county; (c) Variation range of water yield in each county.
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Figure 7. Changes in water supply over time and across different locations, considering various scales, reveal significant temporal and spatial variations.
Figure 7. Changes in water supply over time and across different locations, considering various scales, reveal significant temporal and spatial variations.
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Figure 8. The spatiotemporal distribution of the water demand in the upper reaches of the Hanjiang River.
Figure 8. The spatiotemporal distribution of the water demand in the upper reaches of the Hanjiang River.
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Figure 9. Temporal and spatial variation in the water demand at different scales.
Figure 9. Temporal and spatial variation in the water demand at different scales.
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Figure 10. Spatial distribution of water resource self-sufficiency rate in the upper reaches of the Hanjiang River.
Figure 10. Spatial distribution of water resource self-sufficiency rate in the upper reaches of the Hanjiang River.
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Figure 11. The spatial and temporal distribution of the water supply and demand at the pixel, sub-basin, and administrative unit scales.
Figure 11. The spatial and temporal distribution of the water supply and demand at the pixel, sub-basin, and administrative unit scales.
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Figure 12. Spatiotemporal variation rate of the water supply in the upper Hanjiang River basin.
Figure 12. Spatiotemporal variation rate of the water supply in the upper Hanjiang River basin.
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Figure 13. Temporal and spatial changes in supply–benefit areas in the upper reaches of the Hanjiang River in Shaanxi Province at different scales.
Figure 13. Temporal and spatial changes in supply–benefit areas in the upper reaches of the Hanjiang River in Shaanxi Province at different scales.
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Figure 14. Flow statistics based on the DEM.
Figure 14. Flow statistics based on the DEM.
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Figure 15. Direction of water flow in the administrative units.
Figure 15. Direction of water flow in the administrative units.
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Figure 16. Paths and spatial distribution of the flow of the water supply services based on the self-sufficiency rate.
Figure 16. Paths and spatial distribution of the flow of the water supply services based on the self-sufficiency rate.
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Table 1. Results of the parameter calibration.
Table 1. Results of the parameter calibration.
Serial NumberParameter NameDefinitionLower LimitUpper LimitCalibration Value
1r__CN2.mgtRunoff curve−0.20.2−0.08
2v__ALPHA_BF.gwBase flow regression coefficient0.01.00.7
3v__GW_DELAY.gwGroundwater delay coefficient30450240
4v__GWQMN.gwThreshold of water level generated by basic flow0.02.01.0
5v__CH_N2.rteManning coefficient of main channel0.00.30.19
6v__CH_K2.rteEffective hydraulic conductivity of main channel035002000
7SURLAGSurface runoff hysteresis coefficient−0.80.80.5
8LAT_TTIMERunning time of interflow in soil01005
Table 2. Water use distribution table for land-use types.
Table 2. Water use distribution table for land-use types.
Land Use TypesCorresponding Water Use Classification
Cultivated landWater to irrigate paddy fields and other agricultural areas
WoodlandWater to irrigate orchards and other types of trees
GrasslandWater to irrigate grasslands, shrubs, etc.
WaterFishery cultivation
Land used for buildingWater for domestic use and industrial production in urban and rural areas
Unused landUnallocated
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Ma, X.; Li, J.; Yu, Y. A Study on the Determination and Spatial Flow of Multi-Scale Watershed Water Resource Supply and Benefit Areas. Water 2024, 16, 2461. https://doi.org/10.3390/w16172461

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Ma X, Li J, Yu Y. A Study on the Determination and Spatial Flow of Multi-Scale Watershed Water Resource Supply and Benefit Areas. Water. 2024; 16(17):2461. https://doi.org/10.3390/w16172461

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Ma, Xinping, Jing Li, and Yuyang Yu. 2024. "A Study on the Determination and Spatial Flow of Multi-Scale Watershed Water Resource Supply and Benefit Areas" Water 16, no. 17: 2461. https://doi.org/10.3390/w16172461

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