Arid Zone Research Vol. 42 No. 7 Jul. 2025

Ecological Management Zoning in the Ili River Valley Based on Water Supply Service Supply-Demand Relationships

HU Jiran¹, YAO Juan¹, XIONG Changjiang²

¹School of Economics and Business, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
²College of Agricultural and Rural Development, Henan University of Economics and Law, Zhengzhou 450016, Henan, China

Abstract

Water supply services sustain the survival and development of human society and constitute a critical component for advancing ecological civilization and high-quality watershed development in China. Focusing on the Ili River Valley in Xinjiang, this study analyzes the equilibrium characteristics and matching status of water supply service supply-demand relationships from 2005 to 2020 using statistical yearbook data, remote sensing data, water supply service models, the water resources security index (FSI), and supply-demand matching analysis. The results indicate: (1) The FSI in the Ili River Valley exhibited a "rise-decline" fluctuation, with the supply-demand balance evolving through three stages: "general deficit—surplus—persistent deficit." Spatial differentiation was significant: five counties and cities (Yining City, Yining County, Huocheng County, Qapqal Xibe Autonomous County, and Xinyuan County) experienced persistent deficits, while three counties (Nilek County, Tekes County, and Zhaosu County) and Horgos City (in 2020) maintained surpluses, with a phase transition point occurring in 2010. (2) Three dominant supply-demand matching types emerged: "low supply—high demand," "low supply—low demand," and "high supply—low demand." The spatial distribution of matching types displayed east-middle-west gradient differentiation, with counties exhibiting the same matching pattern showing spatial agglomeration and industrial convergence, significantly driven by regional economic structure. Specifically, livestock areas with superior ecological fundamentals maintained high supply capacity, while arable land-intensive agricultural areas faced continuous high demand pressure. Based on these findings, we delineate three ecological management zones—conservation, regulation, and improvement—to promote sustainable watershed ecosystem management and efficient water resource utilization.

Keywords: water supply services; supply-demand relationship; ecological zoning; Ili River Valley

Water has become a global focus in the 21st century, with clean drinking water included in the United Nations 2030 Sustainable Development Goals. As a primary component of ecosystem services, water supply services play a pivotal role in ensuring watershed ecosystem stability and advancing ecological civilization construction in China's arid and semi-arid regions. Concurrently, climate change and human activities have intensified watershed ecological risks, causing groundwater depletion, soil erosion, biodiversity loss, and other environmental problems that weaken watershed ecosystem water supply capacity and impede coordinated development of social, economic, and ecological interests. The Ili River Valley, a transboundary inland river basin between China and Kazakhstan and a key ecological protection area in the Silk Road Economic Belt, holds strategic value for socioeconomic development and ecological construction under the Belt and Road Initiative. Its water resources are critical for flood control, runoff regulation, and drought prevention. As an important water collection area for northern and southern Xinjiang, its water conservation and purification functions constitute the resource and environmental foundation for the survival and development of all ethnic groups in the region, making the security of production, living, and ecological water use a primary task. However, expanding agricultural acreage and increasing irrigation water demand have encroached upon ecological and domestic water use, while inefficient water resource development has exacerbated structural shortages, creating severe supply-demand imbalances.

Comprehensive analysis of the supply-demand relationship of water supply services in the Ili River Valley is fundamental for coordinating contradictions between water resource development and utilization, optimizing water resource allocation, improving efficiency, and implementing effective watershed aquatic ecosystem management. Quantitative assessment and spatial mapping of ecosystem service supply-demand relationships represent a frontier research area. International scholars primarily employ methods such as land use estimation, ecological process simulation, spatial overlay, and expert judgment to assess supply-demand levels across global or regional scales. Recent domestic research has yielded substantial results, particularly regarding water supply services. Scholars have investigated supply-demand spatial-temporal matching characteristics and flow patterns in regions including the southwestern karst area, Xiaojiang Basin, Huangshui River Basin, Taihang Mountains, and Loess Plateau using multi-source data (remote sensing, meteorological observations, land use) and methods such as the RUSLE model, InVEST model, and supply-demand ratio models. Other studies have analyzed watershed water resource balance using system dynamics models and bilateral supply-demand regulation approaches. These studies demonstrate that water supply service supply-demand relationships are crucial for maintaining healthy water resource system cycles and estimating water shortage risks, with strong control and guidance over water resources. Adjusting water diversion and promoting water-saving concepts and technologies can comprehensively improve water resource allocation efficiency.

However, existing research exhibits several limitations: (1) Most studies focus on either supply or demand sides, lacking systematic investigation of both; (2) Physical model methods require high-precision data, making it difficult to identify supply-demand contradictions at different spatial scales; (3) Water supply service research often discusses multiple ecosystem services together, lacking specificity and making it challenging to precisely identify water supply service contradictions. Therefore, this study focuses on the Ili River Valley, employing multi-source data and integrated models to construct systems for actual water supply service provision and demand, providing a comprehensive assessment of supply-demand relationships. We examine spatial-temporal matching characteristics, differences across spatial scales, and optimization measures to provide theoretical support for ensuring water resource security and promoting high-quality watershed development.

1 Study Area Overview and Research Methods

1.1 Study Area Overview

The Ili River Valley (80°09′–84°56′E, 42°14′–44°50′N) is located in the western Tianshan Mountains (Figure 1), covering a watershed area of 5.64×10⁴ km². Influenced by its trumpet-shaped topography surrounded by mountains on three sides and open to the west, westerly moisture lifts to form regional precipitation ranging from 215–800 mm annually, with an average maximum temperature of 10.9 °C, creating Xinjiang's unique humid microclimate known as the "Western Region Oasis." Vertical geomorphological differentiation is significant: low mountain zones serve as spring-autumn pastures, mid-mountain zones feature spruce forests, and high mountain zones are summer pastures. The ecosystem preserves Quaternary glacial relict plants, with wild fruit forests concentrated in Gongliu and Xinyuan counties. Natural grasslands exceed 2,000×10⁴ hm², with over 2,000 seed plant species. The hydrological system centers on the Ili River, whose runoff originates from permanent glacier replenishment, with three major tributaries—the Tekes, Kunes, and Kashgar rivers—all originating from high-altitude mountains. Administratively, the valley encompasses Yining and Horgos cities and eight counties. Water supply services are dominated by surface water, exhibiting watershed coupling characteristics. The complete ecosystem structure maintains stability in the agricultural-pastoral-forestry production system, where corn, wheat, and rice cultivation makes the region an important grain production base in Xinjiang.

1.2 Data Sources

1.2.1 Remote Sensing Data

Meteorological data included daily atmospheric pressure, relative humidity, solar radiation, wind speed, sunshine hours, maximum temperature, and minimum temperature from the China Meteorological Data Sharing Network (http://data.cma.cn/). Using professional meteorological interpolation software ANUSPLIN, we generated daily-scale climate raster data with 1 km resolution to calculate potential evapotranspiration and annual precipitation. MODIS NDVI data were downloaded from the Geospatial Data Cloud (http://www.gscloud.cn/), with annual maximum values extracted using the maximum value composite method to synthesize yearly 1 km resolution data. The InVEST model calculated water yield based on photosynthetically active radiation and actual light use efficiency. Parameters including vegetation evapotranspiration coefficients, LAI coefficients, vegetation available water content, root depth, and maximum soil thickness were referenced from established studies. The formula is:

$$Y_{xj} = P_x - AET_{xj}$$

where $Y_{xj}$ is the annual water yield (mm) for land cover type $j$ in grid cell $x$; $P_x$ is the annual precipitation (mm) for grid cell $x$; and $AET_{xj}$ is the annual actual evapotranspiration (mm) for land cover type $j$ in grid cell $x$.

1.2.2 Statistical Yearbook Data

Population, industrial water use (primary, secondary, and tertiary industries), and domestic water consumption data were obtained from the Xinjiang Statistical Yearbook, Ili Kazakh Autonomous Prefecture Statistical Yearbook, Xinjiang Statistical Bulletin, and Xinjiang Water Resources Bulletin (2005–2020). Horgos City statistics were not included in yearbooks, so only its 2020 water resources security index was calculated.

1.3 Methods

1.3.1 Quantification of Water Supply Service Provision and Demand

Water supply service provision was quantified using the InVEST model's water yield module based on water balance principles, calculating runoff for each grid cell by subtracting actual evapotranspiration from precipitation. Parameters related to land cover, climate, terrain, and soil were incorporated. Water supply service demand quantification followed methods by Ou Weixin et al. for the Taihu Basin, encompassing water consumption for human production and living activities, excluding vegetation absorption and river infiltration. Ecological water use, representing the smallest proportion, was omitted. The demand model included four categories: primary industry water use, secondary industry water use, tertiary industry water use, and residential domestic water use.

1.3.2 Water Resources Security Index Model

The water resources security index (FSI) characterizes the supply-demand balance of water supply services in the Ili River Valley by applying a common logarithm to the supply-demand ratio, enhancing spatial visibility and comparability of supply-demand contradictions. Following established research, the calculation formula is:

$$FSI_i = \lg\left(\frac{S_i}{D_i}\right)$$

where $i$ represents counties/cities in the valley; $S_i$ is the water supply service provision quantity; and $D_i$ is the demand quantity. When $FSI > 0$, water supply services are in surplus; when $FSI < 0$, shortage occurs; and when $FSI = 0$, supply and demand are balanced. Building on Chen Dengshuai et al.'s classification, we divide the supply-demand ratio threshold into five levels to more clearly quantify balance conditions (Table 1).

[TABLE:1]

1.3.3 Ecosystem Services Supply-Demand Matching Model

We applied the score standardization method to explore spatial differentiation characteristics of supply-demand relationships. Based on standardized results, we divided the data into quadrants for matching analysis. The x-axis represents standardized supply quantity, and the y-axis represents standardized demand quantity, forming four quadrants: Quadrant I—high supply, high demand; Quadrant II—low supply, high demand; Quadrant III—low supply, low demand; and Quadrant IV—high supply, low demand. The formulas are:

$$\bar{x} = \frac{1}{n}\sum_{i=1}^{n}x_i$$

$$s = \sqrt{\frac{\sum_{i=1}^{n}(x_i - \bar{x})^2}{n}}$$

where $x$ is the standardized supply or demand quantity; $x_i$ is the value for county/city $i$; $\bar{x}$ is the watershed average; $s$ is the watershed standard deviation; and $n$ is the number of evaluated counties/cities.

2 Results

2.1 Temporal and Spatial Characteristics of Water Supply Service Supply-Demand Balance

2.1.1 Temporal Characteristics

From 2005 to 2020, the water resources security index in the Ili River Valley showed a "rise then fall" trend, reaching its lowest value in 2020. When $FSI < 0$, water resources are in short supply (deficit state). From a stage perspective, the valley's supply-demand balance exhibited a persistent deficit state transitioning to higher deficit levels, evolving along the path: general deficit—general surplus—general deficit. This indicates that under the dual pressures of insufficient supply and increasing demand, water supply services in the Ili River Valley face overall shortage.

2.1.2 Spatial Characteristics

Spatially, the supply-demand balance relationships of five counties/cities—Yining City, Yining County, Huocheng County, Qapqal Xibe Autonomous County, and Xinyuan County—remained in persistent deficit. Nilek, Tekes, and Zhaosu counties and Horgos City (2020) maintained surplus states. Yining City's balance relationship experienced "high deficit—general deficit—high deficit" changes, with overall shortage intensifying in 2020. High population density (1,000 persons·km⁻²) creates substantial domestic water demand, while urban infrastructure development and road hardening reduce urban ecosystem water supply capacity. Yining County's balance shifted from "higher deficit—general deficit—higher deficit," while Huocheng County remained at "higher deficit" levels. Qapqal Xibe Autonomous County showed improvement from "higher deficit—general deficit." As major crop production areas, Yining and Qapqal counties have total sown areas of 8.498×10⁴ hm² and 9.18×10⁴ hm² respectively, ranking first and second in the valley, with substantial agricultural irrigation water demand. Located midstream of the Ili River, far from the three main tributary sources, these counties have relatively low water supply provision. Xinyuan County exhibited the most stable deficit state, with surplus only in 2010. Nilek, Tekes, and Zhaosu counties, situated upstream where water resources are abundant, maintained general surplus states ($0 < FSI < 1$), with some years showing higher surplus levels. Gongliu County's balance shifted from "general deficit" to surplus in 2010, joining the general surplus status.

[FIGURE:2]
[FIGURE:3]

2.2 Supply-Demand Matching Types in the Ili River Valley

The Ili River Valley exhibits three primary supply-demand matching types distributed across different quadrants: "low supply—high demand," "low supply—low demand," and "high supply—low demand." Counties show spatial heterogeneity and temporal variability in matching types, with east-west-middle spatial differentiation. Counties with identical matching types demonstrate spatial proximity effects and similar production structures. Grassland pastoral areas exhibit "high supply—low demand" patterns, while agricultural irrigation areas show "low supply—high demand" patterns. Specifically, Nilek County (2005, 2010, 2015), Zhaosu County, and Tekes County belong to the "high supply—low demand" type. From 2005 to 2020, Yining County, Qapqal Xibe Autonomous County, Huocheng County, and Xinyuan County were "low supply—high demand" types; Yining City and Gongliu County were "low supply—low demand" types; Yining City (2010) was "low supply—high demand"; and Nilek County (2020) was "high supply—high demand."

[FIGURE:4]

2.3 Ecological Management Zoning

Based on the spatial heterogeneity of water supply service supply-demand status and differences between supply and demand zones, we delineate three ecological management zones to achieve regional sustainable development goals: conservation, regulation, and improvement zones. This zoning is based on county-scale supply-demand matching types, combined with the Ili Prefecture Ecological Environmental Protection Master Plan (2018–2035) and local socioeconomic and natural geographic conditions.

2.3.1 Conservation Zone

The southwestern and eastern mountainous, forest, and grassland areas of the Ili River Valley—Zhaosu, Tekes, and Nilek counties—represent "high supply—low demand" conservation zones. As the source of the Ili River, these areas function as "water towers." According to the Xinjiang Uygur Autonomous Region Ecological Environment Status Bulletin, these three counties have rich flora and fauna resources, including national protected species such as snow leopards and ibex, with well-preserved grassland and forest ecosystems. The industrial structure is dominated by grassland animal husbandry and tourism. During summer snowmelt periods, large river runoff fully meets agricultural and tourism water demands. Water resource utilization efficiency is high while demand remains relatively low due to industrial characteristics. These counties should continue implementing returning farmland to forest policies, increase artificial forest planting, enforce strict grassland-livestock balance systems, implement rotational grazing and seasonal bans, restore grassland water conservation functions, and strengthen fire and pest control to maintain ecological balance.

2.3.2 Regulation Zone

The central and western agricultural irrigation areas—Yining County, Qapqal Xibe Autonomous County, Huocheng County, Xinyuan County, and Yining City—are "low supply—high demand" regulation zones. As the largest water consumption areas, these counties should prioritize efficient water supply service utilization. According to Xinjiang Water Resources Bulletin data, the four midstream counties receive only 30%–50% of upstream precipitation, with surface water resources accounting for just 20%–30% of upstream counties, while cultivated land comprises 40%–60% of area. High water-consumption agricultural models exacerbate demand pressure, creating significant supply-demand contradictions. Recommended measures include: land leveling to reduce slope, soil fertility improvement, water and soil conservation bioengineering, promotion of water-saving irrigation technologies (sprinkler, pipe irrigation), integrated water-fertilizer systems, and optimization of agricultural planting structure and scale to improve water resource-crop structure matching.

2.3.3 Improvement Zone

Gongliu County in central Ili River Valley is primarily a "low supply—low demand" improvement zone focused on enhancing ecosystem functions. It should utilize ecosystem self-recovery capacity, ensuring existing vegetation protection while implementing artificial grass planting, afforestation, and farmland shelterbelt construction to rapidly increase vegetation coverage. Water use structure should be strictly controlled, limiting irrigation area and adjusting water use ratios to protect ecological water use and improve vegetation survival rates.

3 Discussion

Water supply services constitute the most fundamental ecosystem service for maintaining human well-being. Coordinated supply-demand relationships are crucial for promoting positive interactions between natural and socioeconomic systems and achieving water ecological security and high-quality watershed development. Our results confirm supply-demand imbalances and mismatches in the Ili River Valley. The resulting flow characteristics demonstrate that water supply service generation and consumption are not static but directional processes. Significant differences exist in supply-demand balance and matching types among counties at different watershed locations. Nilek (2020), Zhaosu, and Tekes counties in the upstream southwestern and eastern mountain forest and grassland areas are "high supply—low demand" conservation zones functioning as water towers. These should implement measures to reduce ecological pressure and enhance water conservation capacity.

Spatial heterogeneity in water supply service supply-demand creates an uneven spatial distribution of water resources. Upstream "high supply—low demand" counties continuously transport water downstream to "low supply—high demand" areas through watershed hydrological cycles, forming a spatial pattern of supply and beneficiary zones. Future research should examine spatial flow characteristics, establish spatio-temporal connections between generation and consumption, map flow pathways, quantify flow volumes and velocities, and precisely identify supply and beneficiary zone boundaries. Furthermore, spatial heterogeneity-induced inequity in water resource distribution warrants deeper investigation. Using the total ecological value of water supply services as the reference standard for ecological compensation may create unrealistic compensation zones and amounts. Discussing watershed ecological compensation mechanisms from the perspective of water supply service flows could more objectively delineate compensation zones and scientifically calculate compensation standards.

4 Conclusion

Using water resources security index models and supply-demand matching models, this study characterized water supply service supply-demand relationships in the Ili River Valley from both balance and matching perspectives, and conducted ecological management zoning. The main conclusions are:

(1) From 2005 to 2020, the water resources security index showed an overall "rise then fall" trend, with supply-demand balance in deficit during 2005–2015 and in surplus during 2010. The evolution path was "general deficit—general surplus—general deficit." Yining City, Yining County, Huocheng County, Qapqal Xibe Autonomous County, and Xinyuan County remained in persistent deficit, while Nilek County, Tekes County, Zhaosu County, and Horgos City (2020) remained in persistent surplus.

(2) Water supply service supply-demand matching was dominated by three types: "low supply—high demand," "low supply—low demand," and "high supply—low demand." Matching types showed spatial heterogeneity and temporal variability, with east-middle-west spatial differentiation. Counties with identical matching types demonstrated spatial proximity effects and production structure similarity. Grassland pastoral areas primarily exhibited "high supply—low demand" patterns, while agricultural irrigation areas showed "low supply—high demand" patterns.

(3) Based on supply-demand quantities, balance, and matching relationships, we delineated three ecological management zones—conservation, regulation, and improvement—with differentiated ecological protection strategies proposed for each.

References

[1] United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development[R]. New York: United Nations, 2014: 1-41.

[2] Huang Zhihua, Zhao Jun, Xiao Hanyu, et al. Water service supply and demand situation and driving factors in Shiyang River Basin[J]. Journal of Soil and Water Conservation, 2021, 35(3): 228-235.

[3] Fu Bojie, Zhou Guoyi, Bai Yongfei, et al. The main terrestrial ecosystem services and ecological security in China[J]. Advances in Earth Science, 2009, 24(6): 571-576.

[4] Fu B J, Wang S, Su C H, et al. Linking ecosystem processes and ecosystem services[J]. Current Opinion in Environmental Sustainability, 2013, 5(1): 4-10.

[5] Chen Xiaohu. Analysis on the advantages of surface water resources in river basins and the potential for development and utilization[J]. Shaanxi Water Resources, 2020(11): 41-43.

[6] Li Ni. Research on the coordinated development of water resources utilization and environmental economy——comment on Research on the Coordinated Development Model of Water Resources and Environmental Economy and Its Application[J]. Yellow River, 2019, 41(7): 163.

[7] Yan Yuyan, Yang Liao, Wang Weisheng, et al. Analysis of spatial-temporal variation of landscape ecological risk and its terrain gradient in Ili valley[J]. Ecological Science, 2020, 39(4): 125-136.

[8] Wen Guangchao, Zhao Meijuan, Xie Hongbo, et al. Analysis of land vegetation cover evolution and driving forces in the western part of the Ili River Valley[J]. Arid Zone Research, 2021, 38(3): 843-854.

[9] Yang Liangjian, Cao Kaijun. Spatiotemporal pattern and driving mechanism of tourism ecological security in 85 counties and cities of Xinjiang[J]. Acta Ecologica Sinica, 2021, 41(23): 9239-9252.

[10] Yang Lei, Feng Qingyu, Chen Liding. Ecosystem services of soil and water conservation measures on the Loess Plateau[J]. Resources Science, 2020, 42(1): 87-95.

[11] Wolff S, Schulp C J E, Kastner T, et al. Quantifying spatial variation in ecosystem services demand: A global mapping approach[J]. Ecological Economics, 2017, 136: 14-29.

[12] Schroter M, Barton D N, Remme R P, et al. Accounting for capacity and flow of ecosystem services: A conceptual model and a case study for Telemark, Norway[J]. Ecological Indicators, 2014, 36: 539-551.

[13] Nedkov S, Burkhard B. Flood regulating ecosystem services: Mapping supply and demand, in the Etropole municipality, Bulgaria[J]. Ecological Indicators, 2012, 21: 67-79.

[14] Wu W, Tang H, Yang P, et al. Scenario based assessment of future food security[J]. Journal of Geographical Sciences, 2011, 21(1): 3-17.

[15] Burkhard B, Kroll F, Nedkov S, et al. Mapping ecosystem service supply, demand and budgets[J]. Ecological Indicators, 2012, 21(3): 17-29.

[16] Boithias L, Acuña V, Vergoñós L, et al. Assessment of the water supply: Demand ratios in a Mediterranean basin under different global change scenarios and mitigation alternatives[J]. Science of the Total Environment, 2014, 470: 567-577.

[17] Bagstad J K, Villa F, Batker D, et al. From theoretical to actual ecosystem services: Mapping beneficiaries and spatial flows in ecosystem service assessments[J]. Ecology and Society, 2014, 19(2): 64.

[18] Zhang Xinrong, Wang Xiaofeng, Cheng Changwu, et al. Ecosystem service flows in Karst area of China based on the relationship between supply and demand[J]. Acta Ecologica Sinica, 2021, 41(9): 3368-3380.

[19] Zhang Weixing, Wu Xiuqin, Yu Yang, et al. The changes of ecosystem services supply-demand and responses to rocky desertification in Xiaojiang Basin during 2005-2015[J]. Journal of Soil and Water Conservation, 2019, 33(5): 139-150.

[20] Zhan Tian, Yu Yang, Wu Xiuqin. Supply-demand spatial matching of ecosystem services in the Huangshui River Basin[J]. Acta Ecologica Sinica, 2021, 41(18): 7260-7272.

[21] Zhu Jianjia, Liu Jingtong, Liang Hongzhu, et al. Vertical gradients of water supply and demand in Taihang Mountains, China[J]. Chinese Journal of Applied Ecology, 2019, 30(2): 472-480.

[22] Huang Yun, Liu Jing, Zheng Bofu, et al. Characteristics and driving mechanisms of matching supply and demand of water supply services in the Yangtze River Economic Belt based on the perspective of service flow[J/OL]. Environmental Science, 1-20[2025-04-23]. https://doi.org/10.13227/j.hjkx.202406084.

[23] Ren Meng, Mao Dehua. Supply and demand analysis and service flow research of water production service in Lianshui River Basin[J]. Ecological Science, 2021, 40(2): 186-195.

[24] Yang Mingjie, Yang Guang, Gao Puzhang, et al. Analysis of the supply and demand of water resources for city in arid region based on SD model: A case of Karamay, Xinjiang[J]. Yangtze River, 2018, 49(5): 45-51, 73.

[25] Wang Zongzhi, Ye Ailing, Liu Kelin, et al. Modeling of bilateral joint regulation of basin-wide water resources supply and demand[J]. Journal of Hydraulic Engineering, 2021, 52(3): 265-276.

[26] Guan Dongjie, Sun Lingli, Jiang Laihan, et al. Dynamic change and evolutionary trend in the supply and demand relationship of water supply services in the Three Gorges Reservoir Area[J]. Journal of Chongqing Jiaotong University (Natural Science), 2023, 42(2): 75-85.

[27] Liu Xing, Wen Tianfu, Zen Xinmin, et al. Analysis and spatial differences of water supply and demand balance in Yuanhe River basin[J]. South North Water Transfers and Water Science & Technology, 2020, 18(5): 94-101.

[28] Zhang Jingling, Ji Xibing, Chen Xueliang, et al. Regional supply-demand balance and carrying capacity of water resources for Linze Oasis in the middle of Hexi Corridor[J]. Arid Land Geography, 2018, 41(1): 38-47.

[29] Shi Qianqian, Zhang Jingping, Li Jiayi. Random simulation for natural water supply time series in irrigation area[J]. Yellow River, 2018, 40(9): 148-152, 156.

[30] Ou Weixin, Liu Cui, Tao Yu. An analysis of spatio-temporal evolution of water supply and demand in Taihu Basin[J]. Resources and Environment in the Yangtze Basin, 2020, 29(3): 623-633.

[31] Wang Lucang, Gao Jing. Spatial coupling relationship between settlement and land and water resources based on irrigation scale—A case study of Zhangye City[J]. Journal of Natural Resources, 2014, 29(11): 1888-1901.

[32] Meng Jijun, Wang Jiangwei, Wang Ya, et al. A study of ecological water requirement and efficiency of water allocation based on oasis irrigation area scale: A case of middle reaches of Heihe River[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2018, 54(1): 171-180.

[33] Sharp R, Tallis H T, Ricketts T, et al. InVEST 3.2.0 User's Guide[M]. Stanford: The Natural Capital Project, 2015.

[34] Zhang L, Dawes W R, Walker G R. Response of mean annual evapotranspiration to vegetation changes at catchment scale[J]. Water Resources Research, 2001, 37(3): 701-708.

[35] Yan Li, Cao Guangchao, Kang Ligang, et al. Analysis of spatial-temporal changes in habitat quality and driving factors in Gonghe County using the InVEST model[J]. Arid Zone Research, 2024, 41(2): 314-325.

[36] He Hui, Yusufujiang Rusuli. Analysis of the relative role of vegetation cover changes and its influencing factors in Yili area from 2001 to 2015[J]. Journal of Central South University of Forestry & Technology, 2019, 39(10): 76-87.

[37] Huang Weizhao, Lan Shan, Zhang Yiwei, et al. Evaluation of farmers' perspective on the effectiveness of high standard farmland construction in the Ili River Basin[J]. Arid Zone Research, 2025, 42(4): 766-774.

[38] Wang Yida, Li Jing, Zhou Zixiang, et al. Simulation of water provision services flow in Wuding River Basin based on the SWAT model[J]. Journal of Shaanxi Normal University (Natural Science Edition), 2022, 50(4): 81-91.

[39] Li D, Wu S, Liu L, et al. Evaluating regional water security through a freshwater ecosystem service flow model: A case study in Beijing-Tianjin-Hebei region, China[J]. Ecological Indicators, 2017, 81(10): 159-170.

[40] Wang J, Zhai T L, Lin Y F, et al. Spatial imbalance and changes in supply and demand of ecosystem services in China[J]. Science of the Total Environment, 2019, 657: 781-791.

[41] Dong Xiaonan, Xie Miaomiao, Zhang Qinya, et al. Ecosystem services demand assessment regarding disaster vulnerability and supply-demand spatial matching[J]. Acta Ecologica Sinica, 2018, 38(18): 6422-6431.

[42] Zhang Cheng, Li Jing, Zhou Zixiang. Water resources security pattern of the Weihe River Basin based on spatial flow model of water supply service[J]. Scientia Geographica Sinica, 2021, 41(2): 350-359.

[43] Liu Chunfang, Wang Jiaxue, Xu Xiaoyu. Regional division and standard accounting of ecological compensation from the perspective of ecosystem service flow: A case study of Shiyang River Basin[J]. China Population, Resources and Environment, 2021, 31(8): 157-165.

[44] Yang Xia, An Dawei, Zhou Hongkui, et al. Daily variation of winter precipitation in Ili River Valley of Xinjiang from 2012 to 2017[J]. Journal of Glaciology and Geocryology, 2020, 42(2): 609-619.

[45] Guan Mengyuan, Zhang Qiang, Wang Baoliang, et al. Spatio-temporal evolution and flow of water provision service balance in Jinghe River Basin[J]. Journal of Resources and Ecology, 2022, 13(5): 881-892.

Ecological Management Zoning in the Ili River Valley Based on Supply and Demand of Water Supply Services

HU Jiran¹, YAO Juan¹, XIONG Changjiang²

¹School of Economics and Business, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
²College of Agricultural and Rural Development, Henan University of Economics and Law, Zhengzhou 450016, Henan, China