**1. Introduction**

Ecosystems provide basic and necessary services for human survival and social functioning, namely ecosystem services (ESs). ESs are the continuous provision of ecosystem goods and services by ecosystems and their ecological processes [1]. However, factors such as population growth, industrialization and urbanization have led to a rapid increase in the demand for ESs, and ecosystems are facing unprecedented pressure [2]. A comprehensive and reasonable quantitative assessment of ecosystem services value (ESV) is necessary to alleviate the contradiction between supply and demand of ESs, manage effectively and formulate relevant policies. Water resources are an essential part of ecosystems. Whereas, due to the existence of water pollution, waste of water resources and climate change, the water ecosystem is facing greater pressure than other types of ecosystems. Therefore, it is crucial to study the water ecosystem services value (WESV) and the various factors that affect WESV.

Monetization of ecosystem service value is the most recognized and practical form of ESV, and the calculation methods can be divided into two categories. One is to adopt the relevant methods of traditional ecological economics or environmental economics. Most of

**Citation:** Xiu, Y.; Wang, N.; Peng, F.; Wang, Q. Spatial–Temporal Variations of Water Ecosystem Services Value and Its Influencing Factors: A Case in Typical Regions of the Central Loess Plateau. *Sustainability* **2022**, *14*, 7169. https://doi.org/10.3390/su14127169

Academic Editors: Alban Kuriqi and Luis Garrote

Received: 9 May 2022 Accepted: 9 June 2022 Published: 11 June 2022

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these methods obtain the output of physical quantity based on statistical data or ecological model, and then they calculate the value of ecosystem services by combining the market value method, willingness survey method (CV) and revealed preference method. This kind of method has high requirements on data, parameters, model accuracy and method applicability, etc. Specific to the value of water resources ecosystem services, this kind of method is suitable for calculating the value of water resources with commodity attributes. The other is the equivalence factor method, which constructs the economic value equivalent per unit area of different ecosystems based on the division of ecosystem service functions and quantifies ESV in combination with the distribution of ecosystems. Compared with traditional methods, the equivalence factor method requires relatively fewer data, and the evaluation of ESVs is more comprehensive. Costanza et al. divided the global ESs into 17 species and calculated that the ESV of 16 biomes in the world was US\$33 trillion per year [3], and rivers or lakes were one of the 16 biomes. Meanwhile, another contribution of this study is to provide the equivalent table of services value per unit area of 17 ecosystems in each biome at the global scale, which provides a reference for future research. In 2003, the Millennium Ecosystem Assessment (MA) conducted by the United Nations classified global ESs into four primary categories, namely Provisioning Services, Regulating Services, Supporting Services, and Cultural Services [4]. At the regional scale, Xie et al. improved Costanza's research and obtained the equivalent factor of ecosystem service value suitable for China. Then, the ESV can be calculated combined with the area of each ecosystem. This study was accepted by a large number of Chinese scholars [5,6]. Whether it is a global scale or a regional scale, in the study of using the equivalent factor method to evaluate ecosystems, most of the rivers/lakes or waters are divided into one type of ecosystem for discussion. However, this method does not clarify the service value of groundwater, which is an important component of water resources. The most direct service value of groundwater is that it provides a part of water for production and domestic use, accounting for only 70% of the total global water use for agriculture, and 40% of agricultural water comes from groundwater [7]. Therefore, it is more comprehensive and accurate to combine the two methods to assess the WESV including surface water and groundwater.

It is not the ultimate goal of scholars to study the value of WESV; the more important goal is to study the relationship between WESV and the interaction of various factors. In order to deal with more severe water and environmental problems, exploring the influence of various factors on WESV has gradually become one of the research hotspots. Due to the social nature of water resources, social and economic factors have become one of the components that affect WESV. The characteristics of cities, populations, communities, and cultures [8] all have an impact on water resources and water ecology [9,10]. The urbanization level is a concentrated expression of the social and economic development degree, which profoundly affects the spatial distribution and potential functions of ecosystem services [11]. Many researchers have conducted related research in North China [12,13], Yangtze River Delta [14], Pearl River Delta [15], Southwest Mountainous [16,17] and Northwest arid regions of China [18,19]. WESV also has a significant response to changes in natural factors. Climate conditions [20–22], ecosystem types [23], and environmental quality [24] are the main influencing factors. Meanwhile, the coupling of many factors, such as nature, social economy and human activities, has a more realistic impact on WESV [25,26]. Many of the above studies have fully considered various factors and provided important references for explaining the changes caused by EVS or WESV. Unfortunately, the collinearity among some influencing factors and the nonstationarity in space have not attracted enough attention.

However, EVS exhibit spatial heterogeneity and spatial dependence with changes in geographic space due to differences in the socioeconomic development degree, natural resources, and geographic environment. Thus, incorporating geospatial aspects into the research scope is the key to addressing spatial heterogeneity. Geographically Weighted Regression (GWR) model is an effective tool for dealing with spatial heterogeneity, which is improved on the basis of ordinary least square [27]. The model incorporates the spatial location information as a coefficient into the regression equation and explores to eliminate the nonstationarity caused by spatial changes based on the fitted values of geographic element parameters [28]. The GWR model has been widely used in the fields of natural resources and ecological environment [29]. The water footprint has been extensively researched, including concepts, methods and applications, for better management of water resources and water ecology [30,31]. With the deterioration of ecological environment problems, it is necessary to analyze the evolution of ecological footprint and the spatial differences of influencing factors from the perspective of spatial heterogeneity [29]. In the related research on land use variation and ESV, the GWR model is used to solve the problem of spatial heterogeneity and compare with the OLS model [32]. In coastal counties of Mississippi and Alabama (U.S.), GWR was used in the estimation of the monetary value of distance to different waterfront types, in the extension to a traditional hedonic pricing method, and in analyzing the value of ecosystem services associated with waterfronts differed geospatially [33]. However, few researches utilize the GWR model to study WESV, which becomes the main content of this study.

In arid and semi-arid regions, water resources are very precious, which means that the ecological services provided by water resources play a vital role. Therefore, on the basis of accurately measuring the value of water resources ecosystem services, analyzing the impact of various factors on WESV is of great significance to effectively manage water resources and alleviate the contradiction between supply and demand of water resources ecosystem services.

Many studies have been conducted on the value of ecological services and their influencing factors. However, this study is more relevant. Specifically, the ecological service value of water resources is the object of this study. In addition, the scope of water resources is broader to include groundwater and surface water. This study serves the ecological compensation policy in China.

In this study, the typical area in the central Loess Plateau of China was taken as the research object, and the evaluation of water resources ecosystem service value and the analysis of the temporal and spatial changes of the influencing factors were carried out. The main works are as follows:


#### **2. Materials and Methods**

#### *2.1. Study Area*

The Loess Plateau (33◦43 –41◦160 N, 100◦54 –114◦33 E) covers an area of 640,000 km2 in the upper and middle reaches of China's Yellow River (Figure 1a) [34,35]. Most areas of the Loess Plateau belong to arid and semi-arid areas, with fragile environment, scarcity of water resources and serious soil erosion [36,37]. The study area of this paper is Yulin and Yan'an Cities (Figure 1b), with an area of about 79,957 km2, accounting for 12.49% of the area of the Loess Plateau. In terms of location, the study area is located in the middle of the Loess Plateau, which is a representative area in the middle of the Loess Plateau. From the perspective of administrative division, the study area belongs to the north of Shaanxi Province. The study area includes 25 county-level administrative units (Figure 1c). The study area with large topographic relief and hilly gully, is the core area for controlling soil and water loss in the Yellow River Basin. The annual average temperature of Yulin City in the north of the study area is about 10.5 ◦C, and the average annual precipitation is

about 400.00 mm. From north to south, the landform gradually transits from sandy land to gullies and hills [38,39]. It is an important energy and chemical base in China. Yan'an City in the south of the study area belongs to the hilly area of the Loess Plateau, which is high in the northwest and low in the southeast. The annual average temperature is about 7.70~10.60 ◦C, and the annual average precipitation is about 500.00 mm [40–42].

**Figure 1.** Location and administrative division of the study area: (**a**) Loess Plateau location; (**b**) study area location; (**c**) administrative division of the study area and DEM.
