{"paper_id":"0fb2dece-74ac-42b5-aade-4cdc9ced9075","body_text":"Integrating Ecological Importance and Risk for Restoration Zoning and Ecological Water Demand in the Shiyang River Basin | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Integrating Ecological Importance and Risk for Restoration Zoning and Ecological Water Demand in the Shiyang River Basin Yue Liu, Xuebin Zhang, Ziyang Wang, Haoyuan Feng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6657423/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Effective ecological protection and restoration in arid inland river basins requires a holistic perspective of territorial spatial planning that balances conservation and rehabilitation in a dynamic and integrated manner. This necessitates a dual focus: safeguarding key ecological functional zones to maintain the continuity of ecological processes and the spatial connectivity of natural elements, while also implementing targeted, typology-based interventions to enhance self-organizing capacities of degraded ecosystems. Such strategies aim to stabilize ecological foundations and ensure the sustained delivery of ecosystem functions. Taking the Shiyang River Basin as a representative case, this study establishes a technical framework to delineate mountain, oasis, and desert ecosystems across the basin. Using multi-source data and quantitative approaches, we analyze the spatiotemporal evolution of ecological importance and ecological risk from 1990 to 2020. Based on these assessments, we delineate ecological protection and restoration zones and calculate ecological water demand to support precise and efficient management interventions. The results reveal that: (1) The spatial distribution of mountain, oasis, and desert systems in the Shiyang River Basin exhibits pronounced regional differentiation from southwest to northeast, with mountainous and desert systems dominating, while oasis areas remain relatively limited. (2) From 1990 to 2020, the index of ecosystem service importance increased significantly, rising from an average of 12.658 to 15.495. This growth followed a southwest-to-northeast gradient, indicating a spatial pattern of \"high in the southwest, low in the northeast.\" (3) Over the same period, ecological risk across the basin showed an overall upward trend, with the average risk index increasing from 3.844 to 3.904. The spatial pattern of risk grades followed an ascending order across mountain, oasis, and desert systems, with the oasis system experiencing the most pronounced rise in ecological risk. (4) In 2020, the total ecological water demand of the Shiyang River Basin reached 34.043 billion m³, with a spatial distribution pattern of “high in the south, low in the north”. The ecological core zones, restoration areas, and wilderness protection zones had the highest total ecological water demands, while the ecological reserve and buffer zones showed higher water demand per unit area. (5) Delineating ecological protection and restoration zones at the grid scale based on ecological importance and risk, alongside corresponding ecological water demand accounting, provides a robust foundation for refined and effective ecological governance in inland river basins. This approach holds significant implications for advancing ecological civilization and promoting sustainable development in arid regions. Earth and environmental sciences/Ecology Earth and environmental sciences/Ecology/Ecosystem ecology Earth and environmental sciences/Ecology/Ecosystem services Earth and environmental sciences/Ecology/Restoration ecology Mountain-Oasis-Desert System ecosystem service importance ecological risk ecological conservation and restoration ecological water demand Shiyang River Basin Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Introduction The balance and stability of ecosystems are fundamental to regional ecological security and the sustainable development of socio-economic systems [1] . Due to spatial heterogeneity in geographical patterns, ecosystems often perform distinct dominant functions across different regions, resulting in varying degrees of spatial differentiation in the importance of ecosystem services. A central challenge lies in identifying and prioritizing the conservation of critical natural elements and landscape configurations that underpin key ecological functions. Concurrently, rapid socio-economic development and accelerated urbanization have driven dramatic shifts in land-use patterns, intensifying anthropogenic pressures on natural environments [2] . These transformations have led to widespread ecological degradation and heightened environmental risks across territorial spaces. Effectively diagnosing the underlying causes and extent of ecosystem deterioration, and reconstructing damaged ecological structures and functional networks, has become a critical focus of regional conservation and governance strategies. In arid inland river basins—where ecosystems are inherently fragile, highly sensitive to disturbance, and costly to restore—precision and efficiency in coordinating the protection, development, utilization, and rehabilitation of territorial space are imperative. Anchored in the dual objectives of maintaining ecological functionality and mitigating environmental risks, this study advocates for a grid-based, spatially explicit approach to classify and zone ecological restoration and conservation priorities. By integrating assessments of ecosystem service importance with potential ecological risks, this framework enables targeted and grid-scale ecological interventions. Such a strategy is pivotal not only for enhancing human–environment conditions in arid and semi-arid regions but also for advancing high-quality development in inland river basins and modernizing territorial spatial governance systems. The Mountain–Oasis–Desert System (MODS) in arid inland river basins constitutes a distinctive ecogeographical unit characterized by pronounced spatial heterogeneity and functional complementarity, driven by hydrological cycles and fluxes of nutrients and energy. This system exhibits a highly complex internal structure and stark differentiation in ecological functions [3] . Under the dual pressures of global climate change and intensified anthropogenic disturbances, the ecological security of these basins faces mounting threats, including water scarcity, land degradation, and biodiversity loss—challenges that critically undermine the prospects for regional sustainability. Some research has been devoted to MODS and its surrounding ecological dynamics, encompassing studies on system coupling mechanisms [4] , land-use change and its impacts [5] , responses to climate variability [6] , landscape ecological patterns [7] , hydrological processes [8] , and ecosystem services [9] . However, existing efforts to delineate ecological conservation and restoration zones in these regions often adopt fragmented perspectives—focusing narrowly on geographic conditions, territorial spatial functions, ecological issues, or grid-scale classifications—thereby limiting a holistic understanding of regional differentiation, ecological service provisioning, and potential environmental degradation. This piecemeal approach falls short in guiding the design of integrated and adaptive restoration strategies. In light of the emerging spatial governance paradigm emphasizing element interlinkages, process coupling, and spatial coordination, there is a pressing need to construct an ecologically informed territorial spatial restoration framework rooted in systemic thinking. This study addresses this gap by synthesizing regional differentiation patterns of MODS, evaluating ecosystem service functions, and assessing latent ecological risks. By diagnosing structural deficiencies and functional imbalances within different subsystems, we develop a scientifically grounded, grid-based classification of ecological conservation and restoration zones. The resulting framework enables a spatially differentiated, precision-oriented restoration strategy tailored to the complex ecodynamics of inland river basins in arid regions. A growing body of scholarship has explored ecological conservation and restoration zoning across diverse regions, focusing primarily on three dimensions. First, zoning based on specific ecological elements—such as wetlands, green spaces, and farmlands—has been widely applied to identify and prioritize key ecological zones for protection and restoration [10] . Second, Ecological conservation and restoration zoning has been conducted across multiple spatial scales, including municipal jurisdictions [10] , provincial regions [11] , ecologically fragile zones [12] , national parks [13], , and grid-based units [14] . Third, researchers have adopted a range of analytical perspectives, including ecosystem service supply–demand relationships [15][16], ecological environmental quality [11] , ecosystem service valuation [17] , landscape ecological risk [18] , and the interplay between land use and ecological resilience [19] . For example, Ji et al. [20] delineated ecological management zones for the fragile alpine ecosystems of the Tibetan autonomous regions in Yunnan by coupling ecosystem service supply–demand dynamics with ecosystem resilience. Xu et al. [21] conducted ecological zoning for coastal megacities by integrating ecosystem restoration capacity—derived from ecological remote sensing indices—with land use patterns to assess ecological risk. Ecological importance captures the irreplaceable role of ecosystem functions, spatial structures, and key areas in safeguarding biodiversity and supporting the sustainable use of natural resources. In contrast, ecological risk reflects the probability of ecosystem degradation under adverse environmental pressures. The coupling of ecological importance and ecological risk represents a systems-level modeling of ecological capital stocks and anthropogenic disturbance flows. In arid inland river basins—where spatial heterogeneity is pronounced—zoning strategies that integrate ecological importance as a value-oriented driver and ecological risk as a constraint can support precise, adaptive management of ecological resources and socio-economic factors. This approach offers a robust framework for restoring ecosystem integrity and ensuring long-term ecological sustainability in these vulnerable landscapes. In arid inland river basins, vegetation ecological water demand refers to the volume of water required to sustain the structural stability and functional performance of the mountain–desert–oasis ecosystem. It represents the essential water consumption needed by these open systems to buffer adverse environmental disturbances and maintain a trajectory of positive ecological development [22][23] . A variety of methods have been developed to quantify ecological water demand in such regions, including the quota-based approach, estimations based on plant evapotranspiration, water balance models, biomass-based calculations, and remote sensing–driven methodologies. In this study, we adopt an enhanced Penman–Monteith equation to estimate vegetation ecological water demand. This method is widely recognized for its maturity and operational feasibility. By incorporating parameters such as vegetation coefficients, soil moisture limitation factors, and vegetation coverage, it enables more accurate simulations of plant transpiration and actual ecological water use, as well as precise characterization of the spatiotemporal distribution of regional water demand. To date, most research on ecological water demand in inland river basins has focused on descriptive analyses. For example, Hao et al. [24] applied the FAO-recommended method to investigate the spatial and temporal patterns of natural vegetation water demand, while Wei et al. [25] used an evapotranspiration-based approach in conjunction with land cover data to analyze water demand and its differentiation across vegetation types. However, integrative studies linking ecological water demand with water resource allocation and ecological restoration remain relatively scarce, underscoring a critical gap in current research. Inland river basins in arid regions, shaped by distinctive environmental constraints, face an increasingly acute conflict between socioeconomic development and ecological integrity—one that calls for immediate resolution under the imperatives of carbon neutrality. Situated at the intersection of the Tibetan Plateau, the Loess Plateau, and the Inner Mongolia Plateau, the Shiyang River Basin represents a strategically vital ecological barrier and a key oasis-based agricultural hub within China’s arid northwest. Yet, the region suffers from fragile environmental conditions, pronounced conflict between human development and natural systems, and spatial land-use structures that are poorly aligned with principles of sustainable growth [26] . In response, this study selects the Shiyang River Basin as a representative inland river system in arid China and constructs a technical framework for delineating the Mountain–Oasis–Desert System (MODS), grounded in high-resolution spatial data and integrative methodologies. This framework enables the identification of regional differentiation patterns and the diagnosis of structural deficiencies and process imbalances in ecological elements across distinct geographical units. Guided by ecological importance and constrained by ecological risk, this study delineates zones for ecological conservation and restoration based on the evaluation of ecosystem service importance and ecological risk at a 1 km × 1 km grid scale. It further explores ecological water allocation mechanisms for each zone according to vegetation water demand, and proposes differentiated management strategies tailored to specific conservation and restoration areas. This approach facilitates precision restoration, reduces restoration costs, and enhances ecological outcomes. It offers a novel framework grounded in an integrated and systems-oriented perspective for advancing ecological restoration in inland river basins of arid regions, thereby supporting the construction of ecological civilization and promoting sustainable development in these fragile environments. 2 Materials and Methods 2.1 Overview of the study area Situated on the northern foothills of the Qilian Mountains, west of the Wushaoling range, the Shiyang River Basin (36°29′N–39°27′N, 101°41′E–104°16′E) occupies the eastern segment of the Hexi Corridor in Gansu Province. The basin experiences a temperate continental arid climate, characterized by scarce precipitation, intense evaporation, and large diurnal temperature fluctuations, with a mean annual temperature of 6.4°C and an average annual rainfall of 260.0 mm. Administratively, the basin encompasses the entirety of Liangzhou District, Minqin County, Gulang County, Tianzhu Tibetan Autonomous County, Yongchang County, and Jinchuan District, as well as parts of Sunan Yugur Autonomous County—spanning seven county-level units across three prefecture-level cities (Fig. 1 ). Covering a total area of 42,473 km², the Shiyang River Basin represents a quintessential inland river basin in Northwest China’s arid zone. Due to its unique geographic setting and environmental conditions, the basin hosts a tripartite ecological structure of mountains, oases, and deserts arranged longitudinally from upstream to downstream. With a permanent population of approximately 1.9 million, it is among the most densely populated and heavily exploited inland river basins in China in terms of water and land resource utilization. Consequently, the region faces acute challenges in maintaining ecological security and achieving sustainable socio-economic development. 2.2 Data Sources and Processing The land use data for the Shiyang River Basin in 1990 and 2020 were derived through manual visual interpretation using a human–computer interactive approach, achieving an overall classification accuracy exceeding 88.95%. The land use classification system comprises six first-level and twenty-five second-level categories [27] . Road and settlement data were extracted from land use datasets, and distance metrics to roads and settlements were subsequently derived through spatial proximity analysis. To ensure consistency across datasets, all raster data were resampled to a spatial resolution of 1 km × 1 km, and all layers were reprojected to the WGS_1984_Albers coordinate system. Table 1 summarizes the main data in detail. Table 1 List of main data Data Type Spatial Resolution Data Source Land Use Data (1990/2020) 30 m Resource and Environment Science and Data Center (RESDC), Chinese Academy of Sciences ( http://www.resdc.cn ) Soil Erosion Types, Night-time Light Intensity, Mean Annual Precipitation, Mean Annual Temperature, Population Density, GDP per Unit Area 1 km Resource and Environment Science and Data Center (RESDC), Chinese Academy of Sciences Digital Elevation Model (DEM), Slope 30 m Geospatial Data Cloud ( http://www.gscloud.cn ) Normalized Difference Vegetation Index (NDVI) 1 km NASA MOD13A3 Dataset ( https://search.earthdata.nasa.gov/search ) Evapotranspiration Data 30 m National Earth System Science Data Center ( http://www.geodata.cn ) Wind Speed, Precipitation Records - China Meteorological Data Sharing Service ( http://data.cma.cn ) Snow Cover Information - National Tibetan Plateau/Third Pole Environment Data Center ( http://www.ncdc.ac.cn/portal/ ) 2.3 Research Methodology 2.3.1 Conceptual Framework This study aims to delineate ecological conservation and restoration zones in the Shiyang River Basin by integrating ecological importance as a value-oriented driver and ecological risk as a constraint. Furthermore, it explores ecological water allocation strategies within each zone based on vegetation water demand, thereby enabling precise and efficient restoration interventions. The research framework comprises the following components: (1) A technical classification system was established to delineate mountain, oasis, and desert ecosystems based on empirical data and regional characteristics. The mountain system, serving as the watershed’s critical water source area and a reservoir of mineral nutrients and genetic biodiversity, was identified using a spatial threshold-based approach. Regions with slope > 15° and elevation > 1500 m were initially classified as mountain zones. However, the fragmented nature of these patches conflicted with the expected continuity of geomorphic units. To address this, a spatial optimization was conducted using a 1.5 km buffer radius, determined through iterative analysis to maximize spatial aggregation. The oasis system, characterized by high productivity and biodiversity, and functioning as the core of human habitation and development, was extracted using a multi-dimensional feature-based method. Areas with vegetation cover exceeding 15% were identified and overlaid with water bodies and built-up land derived from land use data. To eliminate redundancy, isolated patches and areas overlapping with the mountain system were removed. The desert system, which serves as both the ecological background and the sensitive substrate in arid regions, was delineated through a spatial exclusion method, whereby all areas not classified as mountain or oasis ecosystems were defined as desert zones. (2) Based on the results of ecosystem service importance and ecological risk assessments, both attributes were classified into five ordinal levels—high, moderate-high, medium, moderate-low, and low—using the natural breaks (Jenks) method. (3) A zoning scheme was developed by integrating the ecological importance and risk classifications. Spatial overlay analysis was applied to delineate ecological conservation and restoration zones accordingly. (4) The vegetation water demand across the basin was estimated using a modified Penman–Monteith equation. These estimates were then used to inform the allocation of ecological water supplies across different conservation and restoration zones. Based on this, differentiated management strategies were proposed for each zone. The detailed conceptual framework is illustrated in Fig. 2 . 2.3.2 Assessment of Ecosystem Service Importance Drawing on previous studies [28][29] and the specific conditions of the Shiyang River Basin, this study evaluates the importance of ecosystem services using four key indicators: food provision, water retention, carbon sequestration, and wind break and sand fixation. The assessment is based on the index of Ecosystem Service Importance, with importance levels assigned values of 9 (high), 7 (moderate-high), 5 (medium), 3 (moderate-low), and 1 (low). Detailed calculation methods are presented in Table 2 . Table 2 Assessment methods of ecosystem services importance Calculation Factors Calculation formula Explanation of Variables Food provision \\(\\:{G}_{i}={G}_{sum}\\times\\:\\frac{{NDVI}_{i}}{{NDVI}_{sum}}\\) \\(\\:{G}_{i}\\:\\) denotes the production of grain, meat, dairy, and aquatic products in grid cell \\(\\:i\\) , and \\(\\:{G}_{sum}\\) represents the total output of these products across the Shiyang River Basin. \\(\\:{NDVI}_{i}\\) is the normalized difference vegetation index (NDVI) for grid \\(\\:i\\) , and \\(\\:{NDVI}_{sum}\\) is the cumulative NDVI across cropland, grassland, and water bodies within the basin. Water retention \\(\\:{W}_{xj}=\\left(1-\\frac{{AET}_{xj}}{{P}_{x}}\\right)\\times\\:{P}_{x}\\) \\(\\:{W}_{xj}\\) denotes the water yield (mm) of land cover type \\(\\:j\\) in grid cell \\(\\:x\\) . \\(\\:{AET}_{xj}\\) is the mean annual actual evapotranspiration (mm) for type \\(\\:j\\) in grid \\(\\:x\\) , and \\(\\:{P}_{x}\\) is the mean annual precipitation (mm) in grid \\(\\:x\\) . Carbon sequestration \\(\\:{S}_{cs}={C}_{above}+{C}_{below}+{C}_{soil}+{C}_{dead}\\) \\(\\:{S}_{cs}\\) represents the total carbon stock (t/hm²); \\(\\:{C}_{above}\\) and \\(\\:{C}_{below}\\) refer to aboveground and belowground biomass carbon (t/hm²), respectively; \\(\\:{C}_{soil}\\) is the soil organic carbon (t/hm²), and \\(\\:{C}_{dead}\\) denotes the carbon stored in dead organic matter (t/hm²). Wind break and sand fixation \\(\\:{F}_{S}={SL}_{p}-{SL}_{r}\\) \\(\\:{SL}_{p}=\\frac{2Z}{{sp}^{2}}\\times\\:{Q}_{p}\\times\\:{e}^{{-(z/sp)}^{2}}\\) \\(\\:{Q}_{p}=109.8\\times\\:(WF\\times\\:EF\\times\\:SCF\\times\\:{K}^{{\\prime\\:}})\\) \\(\\:sp=150.71\\times\\:{(WF\\times\\:EF\\times\\:SCF\\times\\:{K}^{{\\prime\\:}})}^{-0.3711}\\) \\(\\:{SL}_{r}=\\frac{2Z}{{sr}^{2}}\\times\\:{Q}_{r}\\times\\:{e}^{{-(z/sr)}^{2}}\\) \\(\\:{Q}_{r}=109.8\\times\\:(WF\\times\\:EF\\times\\:SCF\\times\\:{K}^{{\\prime\\:}}\\times\\:C)\\) \\(\\:sr=150.71\\times\\:{(WF\\times\\:EF\\times\\:SCF\\times\\:{K}^{{\\prime\\:}}\\times\\:C)}^{-0.3711}\\) \\(\\:{F}_{S}\\) denotes the provision of wind erosion mitigation services (kg/m²). \\(\\:{SL}_{p}\\) and \\(\\:{SL}_{r}\\) are the potential and actual wind erosion amounts (kg/m²), respectively. \\(\\:{Q}_{p}\\) and \\(\\:{Q}_{r}\\) represent the maximum sediment transport capacity (kg/m) under potential and actual wind forces. \\(\\:sp\\) and \\(\\:sr\\) are the actual and potential lengths of critical wind-exposed zones (m). \\(\\:Z\\) is the leeward distance (fixed at 50 m). \\(\\:WF\\) is a climatic factor (kg/m); \\(\\:EF\\) and \\(\\:SCF\\) are the soil erodibility and soil crusting factors, respectively; \\(\\:K{\\prime\\:}\\) and \\(\\:C\\) represent surface roughness and vegetation cover indices. Index of Ecosystem Service Importance \\(\\:{ESI}_{j}=\\sqrt[4]{\\prod\\:_{i=1}^{4}{ES}_{i}}\\) \\(\\:{ESI}_{j}\\) denotes the importance index of ecosystem services for spatial unit \\(\\:j\\) , while \\(\\:{ES}_{i}\\) is the categorical value assigned to the ecological importance of service type \\(\\:i\\) . 2.3.3 Construction of the Ecological Risk Assessment Index System The Shiyang River Basin is characterized by arid climatic conditions, marked spatiotemporal variability in annual precipitation, sparse surface vegetation, and soils highly susceptible to both wind and water erosion. Human activities such as deforestation, overgrazing, and intensive mineral resource extraction have further exacerbated ecological degradation, posing substantial threats to the basin's environmental integrity. Drawing on the theory of coupled social-ecological systems [30] , this study constructs an ecological risk assessment index system tailored to the Shiyang River Basin. The framework comprises 12 indicators spanning natural, social, and economic dimensions (Table 3 ). Based on regional characteristics and prior research, the natural breaks classification method was employed to stratify the ecological risk of each indicator into five levels—ranging from low to very high. Higher classification levels correspond to greater ecological sensitivity and fragility, indicating elevated levels of ecological risk. Table 3 Ecological security evaluation index system of Shiyang River Basin Index Layer Indicator Code Evaluation Factors Level 1 (Low) Level 2 (Moderate-low) Level 3 (Medium) Level 4 (Moderate-high) Level 5 (High) Natural Dimension N1 DEM(m) ≤ 1800 (1800, 2500] (2500, 3200] (3200, 4000] >4000 N2 Slope(°) ≤ 15 (15, 25] (5, 35] (35, 45] >45 N3 NDVI ≥ 0.60 [0.45, 0.60) [0.30, 0.45) [0.15, 0.30) <0.15 N4 Land cover Water, woodland Grassland Arable land Unused land Construction land N5 Types of soil erosion Slight water, Slight wind, Slight freeze–thaw Mild water, Mild wind, Mild freeze–thaw Moderate water, Moderate wind, Moderate freeze–thaw Intense wind, Very intense wind Severe wind N6 Average temperatures(℃) ≤ 2 (2, 4] (4, 6] (6, 8] >8 N7 Distance to water (m) ≤ 100 (100, 500] (500, 1000] (1000, 1500] >1500 N8 Annual precipitation (mm) ≥ 400 [300, 400) [200, 300) [100, 200) <100 Economic Dimension E1 GDP Density (10⁴ CNY/km²) ≤ 100 (100, 500] (500, 1000] (1000, 2000] >2000 E2 Night light index ≤ 300 (300, 1000] (1000, 2000] (2000, 4000] >4000 Social Dimension S1 Pop. Density (persons/km²) ≤ 100 (100, 500] (500, 1000] (1000, 2000] >2000 S2 Distance to the road (m) ≥ 1500 [1000, 1500) [500, 1000) [100, 500) <100 2.3.4 Ecological Risk Index Calculation Spatial Principal Component Analysis (SPCA), an advanced multivariate statistical method that incorporates spatial autocorrelation, is particularly suited for dimensionality reduction and feature extraction in geospatial datasets [31] . Unlike conventional PCA, SPCA facilitates the intuitive spatial extension of results, enhancing interpretability through geovisualization. In this study, the SPCA tool within ArcGIS was employed to extract statistically significant principal components—those with a cumulative variance contribution exceeding 90%. Each component was associated with a corresponding spatial loading map and quantified contribution ratio. The Ecological Risk Index (ERI) was then defined as a weighted composite of these principal components, with the variance contribution of each component serving as its respective weight. The resulting ERI values were classified into five ordinal risk levels using the natural breaks (Jenks) algorithm: ERI ≤ 1.0 (low), 1.0 < ERI ≤ 2.0 (moderately-low), 2.0 < ERI ≤ 3.0 (medium), 3.0 < ERI ≤ 4.0 (moderate-high), and ERI > 4.0 (high). The index is formalized as follows: $$\\:ERI=\\sum\\:_{j=1}^{m}{P}_{ij}{w}_{j}$$ In the equation, ERI denotes the Ecological Risk Index for the i -th assessment unit (grid cell); \\(\\:{P}_{ij}\\) represents the value of the j -th principal component in the i -th unit; and \\(\\:{w}_{j}\\) denotes the corresponding weight, determined by the variance contribution of the j -th component. 2.3.5 Ecological Conservation and Restoration Zoning Methodology The core implementation pathway of ecological conservation and restoration adheres to a dual strategy of functional maintenance and problem-oriented intervention. The function-oriented approach emphasizes the preservation of essential ecosystem attributes by systematically conserving ecologically strategic elements, biological communities, and regional landscape networks, thereby constructing a resilient ecological barrier against external disturbances. In parallel, the problem-oriented mechanism targets the precise identification and remediation of ecological degradation within territorial spaces, underpinned by a multidimensional ecological risk assessment framework that enables accurate evaluation of ecological damage across spatial elements [32] . Therefore, the essence of ecological conservation and restoration lies in accurately evaluating the importance of ecosystem service functions alongside their associated ecological risks. This involves delineating the spatial distribution of ecosystem service capacities, systematically identifying the mechanisms and spatial heterogeneity of ecosystem degradation, and integrating priority areas for conservation and restoration. Such an approach enables the delineation of scientifically grounded conservation zones and the formulation of a spatially differentiated ecological governance framework characterized by rational layout and targeted interventions [33] . Given the expansive area of the Shiyang River Basin, coupled with generally low ecological quality and high restoration costs and complexity, this study adopts a strategy guided by the principles of conservation prioritization, resource efficiency, and natural recovery. Based on 1 km × 1 km grid-scale assessments of ecosystem service importance and ecological risk levels (for the year 2020), spatial data were extracted and categorized into five classes—high (H), moderate-high (MH), medium(M), moderate-low (ML), and low (L). Through spatial overlay analysis, the Shiyang River Basin was partitioned into five ecological management zones: Wilderness Reserve Zone, Ecological Buffer Zone, Ecological Restoration Zone, Ecological Core Zone, and Ecological Set-aside Zone. Detailed classification criteria are presented in Table 4 . Table 4 Zoning standards of ecological protection and restoration Zone Types Ecological Importance–Risk Level Wilderness Reserve Zones L–H, ML–H, L–MH, ML–MH Ecological Buffer Zones M–L, M–ML, MH–M, H–M, M–M Ecological Restoration Zones M–MH, M–H, MH–MH, MH–H, H–MH, H–H Ecological Core Zones H–L, H–ML, MH–L, MH–ML Ecological Set-aside Zones L–L, L–ML, ML–L, ML–ML, L–M, ML–M 2.3.6 Modified Penman Equation The classical Penman equation is typically used to estimate potential evapotranspiration under ideal conditions—characterized by ample water and nutrient supply, and the absence of pests or diseases—thus reflecting the maximum water demand of vegetation [34] . The modified Penman approach extends this framework by incorporating vegetation coefficients and soil constraint factors to more accurately approximate actual plant water requirements [35] . Due to the lack of long-term, continuous in-situ observations in the study area, this research draws on prior empirical studies of forest and grassland vegetation in Northwest China [36] , alongside the Forest Ecosystem Service Function Assessment Manual [37] , to determine vegetation coefficients for cropland, forest, and grassland in the Shiyang River Basin for the year 2020. Informed by previous studies on soil critical moisture thresholds and wilting points [38][39] , the soil critical moisture content was set at 15%, and the wilting coefficient at 8%. Detailed computational procedures are presented in Table 5 . Table 5 Calculation method of vegetation water demand Calculation Factors Calculation formula Explanation of Variables Evapotranspiration \\(\\:{ET}_{0}=\\frac{0.408\\varDelta\\:（{R}_{n}-G）+r\\frac{900}{T+273}{u}_{2}（{e}_{s}-{e}_{a}）}{\\varDelta\\:+r（1+0.34{u}_{2}）}\\) \\(\\:{ET}_{0}\\) denotes the reference crop evapotranspiration (mm d⁻¹), \\(\\:\\varDelta\\:\\) represents the slope of the saturation vapor pressure curve (kPa °C⁻¹), and \\(\\:G\\) is the soil heat flux density (MJ m⁻² d⁻¹). The psychrometric constant is denoted by \\(\\:r\\) (kPa °C⁻¹), and \\(\\:{u}_{2}\\) refers to wind speed measured at a height of 2 meters (m s⁻¹). \\(\\:{e}_{s}\\) and \\(\\:{e}_{a}\\) represent the saturation vapor pressure and actual vapor pressure, respectively (both in kPa), while \\(\\:{R}_{n}\\) denotes the net radiation at the land surface (MJ m⁻² d⁻¹). Vegetation coefficient K CA =0.55 K CW =0.85 K CG =0.60 K CA . K CW and K CG represent the vegetation coefficients for cropland, forest land, and grassland, respectively. Soil moisture limitation factor \\(\\:{K}_{s}=\\left\\{\\begin{array}{c}1，\\theta\\:＞{\\theta\\:}_{c}\\\\\\:\\frac{\\theta\\:-{\\theta\\:}_{z}}{{\\theta\\:}_{c}-{\\theta\\:}_{z}}，{\\theta\\:}_{z}\\le\\:\\theta\\:\\le\\:\\\\\\:0，\\theta\\:＜{\\theta\\:}_{z}\\end{array}\\right.{\\theta\\:}_{c}\\) In the equation, θ denotes the soil moisture content; θ_c is the critical soil moisture threshold; and θ_z refers to the wilting point of the soil. Vegetation distribution area A PA =4472.31km 2 A PW =162.05km 2 K CG =896.69km 2 A PA , A PW and A PG correspond to the spatial distribution areas of cropland, forest land, and grassland, respectively. Vegetation ecological water demand \\(\\:ET={ET}_{0}\\times\\:{K}_{c}\\times\\:{K}_{s}\\times\\:{A}_{P}\\times\\:{10}^{-3}\\) \\(\\:ET\\) represents the ecological water demand of vegetation (m³), \\(\\:{ET}_{0}\\) is the reference crop evapotranspiration (mm), \\(\\:{K}_{c}\\) is the vegetation coefficient, \\(\\:{K}_{s}\\) is the soil moisture constraint coefficient, and \\(\\:{A}_{P}\\) denotes the vegetation-covered area (m²). 3 Results and Analysis 3.1 Delineation of the Mountain–Desert–Oasis Composite Ecosystem Based on an established classification framework for mountain–oasis–desert systems, the Shiyang River Basin was partitioned into three distinct sub-ecosystems: mountainous, oasis, and desert (Fig. 3 ), exhibiting pronounced spatial differentiation from southwest to northeast. The mountainous system comprises the largest proportion, accounting for 44.28% of the total basin area. Predominantly located in the Qilian Mountains in the southwest, this system is characterized by land use dominated by grasslands (45.83%), forested areas (16.63%), and croplands (17.31%). In contrast, the oasis system represents the smallest share, covering 16.79% of the basin. Concentrated in the central corridor region, it is primarily composed of croplands and urbanized land, accounting for 53.26% and 59.56% of the basin’s total cultivated and built-up areas, respectively. This region serves as the principal hub for human habitation and agricultural activity. The desert system spans 16,531.00 km², or 38.93% of the total area, and is primarily distributed across the northwestern transitional zone between the Tengger and Badain Jaran Deserts. Land use within this system is dominated by unused or barren land, which constitutes 82.17% of its area. Overall, the mountainous system features high vegetation cover and functions as a critical ecological service zone within the basin. The oasis system, with flat terrain and relatively abundant water resources, is a key area for agricultural production and urban–rural development. Meanwhile, the expansive and ecologically fragile desert system—characterized by gobi landscapes, exposed soils, and desert grasslands—acts as a vital refuge for characteristic flora and fauna of arid ecosystems and plays a crucial role in sustaining regional ecological balance and biodiversity. 3.2 Spatiotemporal Dynamics of Ecosystem Service Importance In this study, the importance of ecosystem services within the Shiyang River Basin was assessed using a composite index of the ecosystem service value. The results were classified into five ordinal levels—high, moderate-high, medium, moderate-low, and low—using the natural breaks (Jenks) method (Fig. 4). From 1990 to 2020, the ecosystem service importance index exhibited a steadily increasing trend, with the mean value rising from 12.658 to 15.495. Spatially, a distinct gradient emerged, characterized by moderate-high values in the southwest and moderate-low values in the northeast. Within mountain system, areas categorized as having high or moderate-high importance expanded substantially, increasing from 12.50% and 25.37% of the total mountainous area in 1990 to 36.66% and 28.04% in 2020, respectively. This shift reflects the transition from widespread ecosystem degradation due to intensive anthropogenic disturbances to large-scale ecological restoration initiatives. Notably, the implementation of reforestation and grassland restoration programs, along with the launch of the ecological civilization strategy and the establishment of Qilian Mountains National Park since 2012, have markedly enhanced regional ecosystem service functionality. In oasis system, zones of moderate-high and high importance showed a pronounced expansion—from 15.11% and 0.86% of the total oasis area in 1990 to 42.65% and 5.21% in 2020, respectively—while areas of moderate-low and medium importance concurrently declined. This indicates a substantial elevation in the ecological value of oasis regions, which now fulfill not only essential socio-economic roles but also increasingly vital ecological functions. These changes can be attributed to cropland development, the construction of ecological shelterbelts, and the promotion of water-efficient agro-pastoral practices. In contrast, desert system exhibited a modest expansion in areas of medium and moderate-high importance, alongside a contraction of zones with low and relatively low importance. These changes are closely linked to large-scale ecological engineering projects implemented during the study period, such as the Three-North Shelterbelt Program and sand stabilization initiatives. Overall, areas classified as having high or moderate-high ecosystem service importance remain limited, accounting for only 36.82% of the basin’s total area. These zones are primarily concentrated in the Qilian Mountains and oasis regions. In contrast, areas of low or moderate-low importance are mainly located in the northwestern part of the basin, adjacent to desert margins where wind erosion and arid conditions render the ecological environment fragile and the functional capacity of ecosystems relatively low. 3.3 Spatiotemporal Dynamics of Ecological Risk Based on the calculated Ecological Risk Index (ERI), this study evaluates the ecological risk patterns across the Shiyang River Basin, categorizing ERI values into five discrete levels—high, moderate-high, medium, moderate-low, and low—using the natural breaks (Jenks) classification method (Fig. 5). From 1990 to 2020, the spatial distribution of ecological risk exhibited pronounced differentiation, with risk intensifying progressively from the southwest to the northeast. Over the study period, the average ERI increased from 3.844 to 3.904, indicating an overall upward trend in ecological risk. Mountain system was predominantly characterized by low to medium risk levels, though their extent declined markedly—from 79.84–69.08% of the basin area. This contraction reflects the positive ecological impact of the Qilian Mountains conservation policies, which substantially enhanced vegetation cover, reinforced environmental regulation in mining zones, and curtailed land disturbance and pollution risks. In contrast, oasis system—primarily encompassing Jinchuan District, Liangzhou District, Yongchang County, Gulang County, and Minqin County—was dominated by medium to high risk levels. The average ERI within these regions rose from 4.330 to 4.386. Rapid urban expansion encroached upon large swaths of arable land, grassland, and unused land, leading to habitat fragmentation and loss. As a result, the area classified as medium risk shrank by 1,090.21 km², while high-risk zones expanded by 1,835.57 km². Desert system was predominantly under high ecological risk, although the average ERI decreased from 4.996 to 4.815. Notably, in Minqin County—situated between the Badain Jaran and Tengger Deserts—a suite of integrated restoration measures, including sand stabilization afforestation, riparian reforestation, ecological migration, farmland reversion, and habitat enclosure, led to significant environmental improvements around Qingtu Lake. Consequently, the area exposed to high ecological risk declined by 1,300.68 km². Collectively, the Shiyang River Basin is subject to persistently elevated ecological risk. Mountain, oasis, and desert systems exhibit a gradient of increasing risk, forming a spatial pattern that impedes wildlife migration, seed dispersal, nutrient cycling, and gene flow across the basin’s upper, middle, and lower reaches. This fragmented ecological landscape imposes substantial constraints on regional ecosystem stability and poses significant challenges to sustainable socio-environmental development. 3.4 Ecological Conservation and Restoration Zoning Results Based on the ecological conservation and restoration zoning framework proposed in this study, the Shiyang River Basin was delineated into five functional zones: Wilderness Reserve Zone, Ecological Buffer Zone, Ecological Restoration Zone, Ecological Core Zone, and Ecological Set-aside Zone (Fig. 6 ). The zoning results align closely with the region’s actual ecological protection and restoration needs. The Wilderness Reserve Zone encompasses the largest area, covering 18,795.17 km² or 43.75% of the total basin. Predominantly distributed across desert ecosystems, this zone is characterized by ecological sensitivity and fragility, with relatively high potential ecological risks. It constitutes a critical region for the conservation of characteristic arid-zone flora and fauna, the prevention of desertification, and the mitigation of ecosystem degradation. The Ecological Restoration Zone covers 4,387.28 km² (19.87% of the basin) and is primarily concentrated in oasis areas with high population density and intense economic activity. Restoration efforts in this zone aim to reconcile the demands of production with the imperatives of ecological protection. The Ecological Buffer Zone, also totaling 4,387.28 km² (10.21%), forms an important ecological shield, particularly within mountainous regions. It plays a crucial role in minimizing anthropogenic disturbances and desertification encroachment, acting as a natural barrier against windblown sand, pollutant dispersion, and biotic disruptions caused by human activity. The Ecological Core Zone spans 5,644.38 km² (13.14%) and is mainly located in mountainous areas with high vegetation cover and strong water conservation capacity. These zones are distant from densely inhabited regions and minimally disturbed by human activity, enabling them to maintain ecosystem stability and deliver essential ecological services critical to long-term regional sustainability and security. Finally, the Ecological Set-aside Zone accounts for 5,594.77 km² (13.02%), distributed primarily across mountainous and oasis landscapes. Characterized by relatively low ecological risk and limited ecosystem service capacity, these areas are designated for future spatial planning, including the advancement of ecological civilization, development of modern agriculture, and integrated urban–rural development initiatives. 3.5 Ecological Water Demand Characteristics Using the modified Penman equation, the total ecological water demand in the Shiyang River Basin in 2020 was estimated at 34.043 billion cubic meters. The spatial distribution of ecological water demand exhibited a pronounced south–north gradient, with higher demand in the southern regions (Fig. 7 ). The mountain system accounted for the largest share, totaling approximately 24.60 billion m³—72.25% of the basin-wide demand—driven by complex interactions among elevation, hydrological and climatic conditions, as well as ecological functions such as biodiversity conservation and soil stabilization. Within the mountain system, Ecological Core Zones, Ecological Buffer Zones, and Ecological Restoration Zones accounted for 51.40%, 30.62%, and 12.08% of the demand, respectively. Their per-unit-area ecological water demands were 1.71 million m³/km², 1.39 million m³/km², and 1.10 million m³/km², respectively, reflecting the higher vegetation cover and species richness in Ecological Core and Buffer Zones, where stable water supply is critical to ecosystem function. In contrast, the lower per-unit-area water demand in Ecological Restoration Zones is attributed to the relatively sparse distribution of water-intensive species or communities. The oasis system required 5.78 billion m³ of ecological water, constituting 16.97% of the basin’s total. The Ecological Restoration zones within the oasis system accounted for 75.30% of this demand, primarily due to higher evapotranspiration rates driven by vegetation type, surface temperature, and soil properties. The Ecological Set-aside and Buffer Zones in the oasis system exhibited higher per-unit-area water demands, closely associated with denser vegetation cover. Despite its extensive spatial extent, the desert system contributed only 3.67 billion m³, or 10.78% of total ecological water demand. Within this system, the Wilderness Reserve Zones consumed the most water, largely because desert vegetation—such as Haloxylon ammodendron, Tamarix spp., and Nitraria tangutorum—still necessitates minimal but consistent water input. Notably, the per-unit-area water demand in desert buffer areas was extremely high, reaching 14.40 million m³/km², largely due to large-scale artificial sand-fixation afforestation projects along the fringes of the Badain Jaran and Tengger deserts, especially in Jinchuan District and Yongchang County. Overall, ecological water demand across the Shiyang River Basin is primarily concentrated in the Ecological Core Zones, Ecological Restoration Zones, and Wilderness Reserve Zones. However, the highest per-unit-area demand is observed in the Ecological Set-aside Zones and Ecological Buffer Zones, underscoring the importance of vegetation structure and functional zoning in shaping regional water allocation. 4 Discussion 4.1 Analysis of Ecological Risk Drivers in the Shiyang River Basin To effectively manage potential ecological threats in the Shiyang River Basin, this study aims to identify the dominant stressors shaping regional ecological risk, thereby enabling targeted interventions. Spatial principal component analysis (PCA) reveals that the first six components collectively account for over 90% of the total variance, indicating their strong explanatory power in representing the basin’s ecological risk patterns (Fig. 8 ). These components show high loadings on six variables: mean annual precipitation, mean annual temperature, distance to roads, vegetation cover, land cover type, and soil erosion. Notably, precipitation and temperature dominate the first and second principal components, underscoring the central role of hydrothermal conditions as primary ecological risk determinants. As the principal form of moisture input, precipitation exerts a fundamental influence on ecosystem structure, function, and resilience—particularly pronounced in arid inland basins [40] . Spatial and temporal variations in its intensity and form critically affect ecological stability. Concurrently, rising mean annual temperatures intensify glacier melt and elevate potential evapotranspiration, thereby impacting vegetation growth, agricultural productivity, and water availability. Land cover type and vegetation cover reflect the ecosystem's response to climatic variability and anthropogenic disturbances. Areas characterized by high vegetation density—such as grasslands and forests—tend to exhibit enhanced soil and water conservation capabilities and greater ecological resilience, thereby facing comparatively lower risk. In contrast, croplands, built-up areas, and unused lands, with their inherently fragile soil structures, are more vulnerable to erosion processes. These risks are particularly acute in zones experiencing rapid land-use transformation, such as regions undergoing agricultural expansion, urbanization, or desertification. Soil erosion, a key indicator of ecological degradation, is tightly linked to topography, precipitation, vegetation dynamics, and land use. Steep terrains at higher elevations tend to experience more intense freeze-thaw and hydrodynamic erosion. Moreover, vegetation loss or land development exposes soil surfaces to heightened water and wind erosion. Road networks, as corridors of concentrated human activity, are associated with intensified land disturbance and vegetation destruction, ultimately undermining ecosystem stability. In sum, the ecological protection and restoration of the Shiyang River Basin must adopt an integrated approach that considers the interplay between natural geographical endowment, climatic stressors, vegetation dynamics, and the spatial extent of anthropogenic pressure. 4.2 Strategic Allocation of Ecological Water for Vegetation Restoration Revegetation serves as a vital linkage for sustaining the ecological balance of inland river basins in arid regions [41] . Based on the ecological protection and restoration zonation delineated in this study, a differentiated ecological water allocation strategy is proposed to promote vegetation recovery and improve the ecological integrity of the basin. The upstream mountainous Ecological Core Zones receive abundant precipitation sufficient to meet the water demands of its native vegetation, while simultaneously sustaining critical water retention functions for inland hydrological systems, thereby eliminating the need for additional ecological water supplementation. However, recent global warming has accelerated glacier melt, raising concerns about the increasing frequency of abnormal precipitation events and associated geohazards such as flash floods and debris flows, which pose significant risks to ecological stability. Adjacent to the Core Zone lies the Ecological Buffer Zones, which faces relatively poor hydrological conditions. Targeted interception and redirection of water can enhance ecological water supply, improving habitat quality and reducing resistance to species migration from the Ecological Core Zones. In the central oasis system, which suffers from severe water scarcity, large-scale ecological water supplementation is essential to support vegetation regrowth. Measures such as artificial rainfall enhancement and rainwater harvesting can be employed to augment usable runoff reaching the plains, thereby strengthening the oasis’s ecological buffer and barrier function between mountain and desert systems. As the socio-economic heart of the region, the oasis system should simultaneously prioritize water conservation. This includes advancing high-efficiency irrigation technologies and promoting the reuse of treated wastewater to significantly improve water-use efficiency. On this basis, an integrated water transfer strategy should be pursued, including the potential for inter-basin water diversion from sources such as the Yellow River or Datong River, to ensure adequate water supply for both the oasis Ecological Restoration Zones and downstream Ecological Wilderness Reserve Zones. In the Ecological Set-aside zones, water allocation should be guided by the principle of prioritizing supply to other critical zones. When surplus water is available, moderate urban and industrial development may be permitted; during periods of scarcity, the ecological character of these zones must be preserved. Rational allocation of ecological water resources is foundational to ensuring regional ecological security. Restoration planning in the Shiyang River Basin should adhere to the principles of “water-defined forest, grass, wetland, and farmland”—that is, the scale and intensity of restoration must be aligned with water availability. A coordinated strategy across the basin’s protection and restoration zonation is essential to advance integrated protection and systematic management of the mountain–oasis–desert continuum, ultimately optimizing the structure and functionality of the regional ecosystem. 4.3 Zonal Strategies for Ecological Conservation and Restoration Emerging research underscores that effective zonal ecological management can significantly optimize ecosystem service delivery [42] . Building upon the unique geographical context and ecological water demands of the Shiyang River Basin, this study proposes a set of differentiated, zone-specific ecological management strategies (Table 6 ), aiming to inform decision-making for ecological stewardship in arid inland river basins. In the mountain system, which primarily comprises Ecological Core Zones and Ecological Buffer Zones, strict protection measures are imperative. The Ecological Core Zones should prioritize ecological preservation, afforestation via natural regeneration, and the protection of wildlife habitats, with a complete prohibition on construction and human development activities. The Ecological Buffer Zones should promote eco-friendly tourism under a regulated, semi-open access model to ensure minimal disturbance to core ecological functions. In areas with steep slopes, soil and water conservation measures such as contour terraces and level trenches should be implemented to mitigate erosion. Although the Wilderness Reserve Zones constitute a relatively small proportion of the mountain system, they play a vital role in ecological connectivity. The Wilderness Reserve Zones should enforce restricted access policies and establish ecological corridors linking to the Ecological Core Zones to facilitate biological and material flows. The Ecological Restoration Zones should receive increased investment in ecological infrastructure and technologies to support artificial restoration and ecological water supplementation, thereby enhancing ecological carrying capacity. Given the sensitivity of mountain system, the Ecological Set-aside Zones within this system should function as flexible ecological buffers to address compounded environmental stressors such as climate change and biodiversity loss. The oasis system is predominantly characterized by agricultural and urban land cover, with the Ecological Restoration Zones, Wildness Reserve Zones, and Ecological Buffer Zones as the primary management units. These areas should be structured around a defensive greenbelt composed of shelterbelts at the oasis margins, integrated farmland windbreak networks, and targeted sand control measures at key desert–oasis transition points. Strategies include the establishment of new protective forests, vegetative green corridors, and windbreak barriers to form a comprehensive green ecological shield against encroaching desertification. Major ecological engineering efforts—such as combating land degradation, advancing the “Three North” Shelter Forest Program, implementing anti-desertification measures, expanding ecological public forests, wetland conservation and restoration, and reforestation of marginal farmland—should be intensified. Initiatives should focus on afforestation, fencing and enclosure for grassland recovery, and wetland conservation with an emphasis on exclusionary protection. Improvement of urban and rural human settlements must also be prioritized. Rational planning of green space—through rooftop greening, vertical landscaping, and green infrastructure—will increase vegetation cover and enhance the quality of urban and rural green areas. Building ecological buffer green spaces, peripheral greenbelts, and wilderness parks at the oasis fringe will further strengthen ecological resilience. Additionally, modernization of water-saving irrigation systems and promotion of green agriculture are essential for improving water-use efficiency. Technologies for water-conserving irrigation should be broadly adopted to reduce waste and improve agricultural productivity. The region’s solar and thermal resource advantages can be leveraged to develop high-value, locally adapted agroforestry industries, thereby supporting the establishment of a sustainable ecological economy. Although the Ecological Set-aside Zones in the oasis system occupy only 5.75 km², they hold strategic significance. During periods of agricultural instability induced by extreme climate events, these areas may be temporarily converted into production areas. In contexts where increasing demand for development land results in land-use conflicts, the Ecological Set-aside Zones could serve as green industrial or urban expansion areas under strict ecological constraints. The desert ecosystem, composed primarily of gobi, barren land, and degraded grassland, is inherently fragile and ecologically sensitive. Its dominant ecological functions include sand stabilization and the conservation of arid-zone biodiversity. As the principal Wilderness Reserve Zones of the Shiyang River Basin—with a vast area of 15,873.90 km²—desert ecological restoration faces substantial challenges. Restoration efforts should adhere to a “natural recovery as primary, artificial restoration as auxiliary” principle. Natural regeneration minimizes anthropogenic disturbance, promotes self-repair processes, and facilitates ecosystem resilience. For severely degraded areas, targeted restoration interventions are recommended. Water resources represent the primary limiting factor for desert ecosystem stability. Under the premise of safeguarding basin-wide ecological security, inter-basin water transfers, river channel restoration, and construction of ecological water infrastructure should be employed to ensure sustainable water use. These efforts aim to avoid overexploitation, enhance storage and distribution efficiency, and maintain the minimum ecological water threshold required for desert ecosystem recovery and vegetation regeneration. At the same time, the developments within the desert system must be scientifically delineated. Efforts should focus on fostering industries aligned with local ecological conditions, supporting the strategic relocation of industries from eastern China, and pursuing rational, regulated exploitation of mineral resources. Priority should be given to ecological restoration of mining sites and surrounding degraded grasslands. New models—such as photovoltaics for desert control and solar-powered economic development—should be actively explored to integrate ecological protection with socioeconomic advancement. Table 6 Integrated results of ecosystem importance-risk-ecological water demand in the Shiyang River Basin and restoration guidelines Zone Type Area(km 2 ) Primary Distribution Dominant Ecological Function Ecological Risk Total Ecological Water Demand (10⁸ m³) Water Demand per Unit Area (10⁴ m³/km²) Strategic guidelines for ecological conservation and restoration Wildness Reserve Zones 18795.17 (43.75%) Desert and mountain systems Wind erosion control and sand stabilization Ecologically fragile and sensitive; prone to desertification 54.70 29.10 Primarily natural regeneration Ecological Buffer Zones 4387.28 (10.21%) Transitional areas between mountain-desert and oasis-desert systems Soil and water conservation Dual stress from anthropogenic disturbance and desertification; risk of erosion 77.56 176.79 Assisted natural regeneration Ecological Restoration Zones 8536.60 (19.87%) Oasis system Food provisioning High intensity of human disturbance 79.13 92.69 Active ecological reconstruction Ecological Core Zones 5644.38 (13.14%) Mountain system Water retention and carbon sequestration Strongly impacted by climate change 126.42 223.97 Conservation-focused protection Ecological Set-aside Zones 5594.77 (13.02%) Mountain, oasis, and desert systems Flexible development Low risk; subject to dynamic ecological change 2.63 4.70 Context-specific adaptive management 5 Conclusions (1) The Shiyang River Basin exhibits pronounced spatial differentiation along a southwest–northeast gradient, encompassing three distinct ecological systems: mountains, oases, and deserts. The mountain system, primarily located in the Qilian Mountains in the southwest, covers the largest area and features high vegetation coverage. The oasis system, though spatially limited, constitutes a critical zone for urban–rural development and agricultural production. In contrast, the desert system, extending across the northwestern part of the basin, spans 16,531.01 km² and is dominated by gobi terrain, barren land, and desert grasslands. (2) From 1990 to 2020, the Ecosystem Service Importance Index (ESI) in the Shiyang River Basin exhibited a rising trend, with the mean value increasing from 12.658 to 15.495. Spatially, ESII followed a “southwest-high, northeast-low” distribution pattern. Regions categorized as having high or moderately high ecosystem service importance accounted for only 36.82% of the total basin area. The mountain- system contained the largest proportion of these high-importance zones. Both mountain and oasis systems saw significant expansions in high and moderate-high importance areas, while the desert system remained predominantly classified as low-importance. Nevertheless, both low and moderate-low importance areas within the desert system showed a tendency to shrink over time (3) Over the same period (1990–2020), the overall ecological risk in the basin remained elevated, with the average Ecological Risk Index (ERI) rising slightly from 3.844 to 3.904. A spatial gradient was observed in ecological risk levels, increasing from mountains to oases to deserts. Specifically, the mountain system was characterized by low to medium ecological risk, while the oasis system experienced medium to high risk levels. The desert system consistently exhibited the highest ecological risk across the basin. (4) Based on the joint assessment of ecosystem service importance and ecological risk, the basin was zoned into five distinct ecological management areas: Core Ecological Zones, Ecological Buffer Zones, Ecological Restoration Zones, Wilderness Reserve Zones, and Ecological Set-aside Zones. The Ecological Core and Buffer Zones are mainly concentrated in mountain system; the Ecological Restoration Zones are primarily located within the oasis system; the Wilderness Reserve Zones are situated in the desert system; and the Ecological Set-aside Zones are relatively limited in extent and spatially fragmented. (5) In 2020, the total ecological water demand across the Shiyang River Basin was estimated at 34.043 billion m³. Spatially, ecological water demand exhibited a “high-south, low-north” distribution pattern. Vegetation-related ecological water demand was concentrated in the Ecological Core Zones, Restoration Zones, and Wilderness Reserve Zones. However, per-unit-area vegetation water demand peaked within the Ecological Set-aside and Buffer Zones, highlighting their ecological sensitivity and water dependency. Declarations Author Contribution L.Y.: Writing – review & editing, Writing – original draft. Z.X.B.: Project administration, Methodology, Funding acquisition. W.Z.Y.: Resources and Software. F.H.Y.: Data curation. Data Availability The datasets used and analysed during the current study available from the corresponding author on reasonable request. References Liang, M., et al. Unifying spatial scaling laws of biodiversity and ecosystem stability. Science, 387 , eadl2373. https://doi.org/10.1126/science.adl2373 (2025). Guan, X., Wei, H., Lu, S., Dai, Q., & Su, H. Assessment on the urbanization strategy in China: Achievements, challenges and reflections. Habitat International , 71 , 97–109. https://doi.org/10.1016/j.habitatint.2017.11.009 (2018). Wang, Z. Y., Shi, P. J., Li, X. H. , Liu, Y.& Shi, J. Response mechanism and promotion path of habitat quality to land use change in Hexi Corridor area. Environ. Sci. 45 , 6910–6921. https://doi.org/10.13227/j.hjkx.202312250 (2024). Lin, H. L., Xiao, J. Y.& Hou, F. J. Coupling patterns of the meta-ecosystem of mountain, desert and oasis and its emdollars analysis in the Hexi Corridor, Gansu, China. Acta Ecol. Sin. 24 , 965–971 (2004). Zhang, P. Y., et al. Carbon source/sink effect of land use change from the perspective of composite ecosystem: Progress and review. Acta Ecol. Sin. 45 , 1–16. https://doi.org/10.20103/j.stxb.202402230384 (2025). Wang, H., et al. Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability. Sci. Total Environ. 697 , 133978. https://doi.org/10.1016/j.scitotenv.2019.133978 (2019). Liu, X. L.& Ren, J. Z. Landscape heterogeneity analysis of the mountain–oasis–desert compound ecosystem in the Hexi Corridor. J. Gansu Agric. Univ. 38 , 290–295, 319. (2003). Ren, J. Z.& Hou, F. J. System coupling of mountains–oases–deserts is a key measure for water resource protection in the Qilian Mountains. Acta Pratacult. Sin. 27 , 4–7. (2010). Yao, L. T., et al. Ecosystem service tradeoffs and synergies effects of land use change in Mountain–Oasis–Desert complex system: A case study of Zhangye City. Acta Ecol. Sin. 42 , 8138–8151. (2022). Wang, H. L., Gao, Y. N., Wang, Z. Y., Sha, W., Wu, J S. Urban ecological management division based on ecosystem services: A case study of Shenzhen City. Acta Ecol. Sin. 40 , 8504–8515. (2020). Zhao, N., Wang, B., Wang, Z.H. & Zhang, Y. Spatio-temporal evolution and driving mechanism of ecological environment quality in Inner Mongolia based on RSEI. Environ. Sci. 2024 , 5303. https://doi.org/10.13227/j.hjkx.202405303 (2024). Yang, F.F. & He, H. Ecological environment assessment and ecological zoning construction in the Ili River valley based on EVI-ESV. J. Environ. Ecol. Sci. 33 , 655–664. https://doi.org/10.16258/j.cnki.1674-5906.2024.04.016 (2024). Zhu, J., Li, Z., Yang, J., Wang, Y., Liu, X. & Chen, H. Ecological space management and control zoning of Giant Panda National Park from the perspective of ecosystem services and land use. Sci. Rep. 14 , 19951. https://doi.org/10.1038/s41598-024-65344-2 (2024). Wang, S., Zhang, Q., Wang, Z.F., Liu, Y. & Li, H. GIS-based ecological risk assessment and ecological zoning in the Three Gorges Reservoir area. Acta Ecol. Sin. 42 , 4654–4664. (2022). Xu, Y., Zhao, X., Huang, P., Wang, J. & Liu, C. A new framework for multi-level territorial spatial zoning management: integrating ecosystem services supply-demand balance and land use structure. J. Clean. Prod. 441 , 141053. https://doi.org/10.1016/j.jclepro.2024.141053 (2024). Zhu, Y.H., Hou, Z.D., Xu, C.X. & Li, J. Ecological risk identification and management based on ecosystem service supply and demand relationship in the Bailongjiang River Watershed of Gansu Province. Sci. Geogr. Sin. 43 , 423–433. https://doi.org/10.13249/j.cnki.sgs.2023.03.005 (2023). Hu, Y., Gong, J., Li, X., Song, L., Zhang, Z., Zhang, S., Zhang, W., Dong, J., & Dong, X. Ecological security assessment and ecological management zoning based on ecosystem services in the West Liao River Basin. Ecol. Eng. 192 , 106973. https://doi.org/10.1016/j.ecoleng.2023.106973 (2023). Wang, J., Wang, J. & Zhang, J. Optimization of landscape ecological risk assessment method and ecological management zoning considering resilience. J. Environ. Manag. 376 , 124586. https://doi.org/10.1016/j.jenvman.2025.124586 (2025). Li, C.L., Zhao, C.W., Fan, H., An, F. J., &Zeng, H. Y. Spatiotemporal evolution of land use and ecological resilience and construction of ecological zoning in Guiyang City. Environ. Sci. 2025 , 9357. https://doi.org/10.13227/j.hjkx.202409357 (2025). Ji, Z., Zou, S., Zhang, W., Song, F., Yuan, T., & Xu, B. Optimizing zoning for ecological management in alpine region by combining ecosystem service supply and demand with ecosystem resilience. J. Environ. Manag. 365 , 121508. https://doi.org/10.1016/j.jenvman.2024.121508 (2024). Xu, C., Li, B., Kong, F., & He, T. Spatial-temporal variation, driving mechanism and management zoning of ecological resilience based on RSEI in a coastal metropolitan area. Ecol. Indic. 158 , 111447. https://doi.org/10.1016/j.ecolind.2023.111447 (2024). Zhao, W.Z., Chang, X.L.& He, Z.B. Study on ecological water requirement of desert oasis vegetation in Ejina. Sci. China 2006 , 559–566. (2006). Deng, M.J., Huang, Q., Chang, J.X., &Huang, Z. S. Research and practice of large-scale ecological scheduling. J. Hydraul. Eng. 51 , 757–773. https://doi.org/10.13243/j.cnki.slxb.20200326 (2020). Hao, B., Su, X.L. & Ma, X.Y. Study on ecological water requirement of natural vegetation in Minqin County, Gansu Province. J. Northwest A&F Univ. (Nat. Sci. Ed.) 38 , 158–164. https://doi.org/10.13207/j.cnki.jnwafu.2010.02.002 (2010). Wei, L.M., Zheng, X., Guo, J.J., Zhou, Y. Y., &Yue, D. X. Spatial and temporal distribution of vegetation water consumption in Shule River Basin based on improved Penman formula method. Arid Zone Res. 37 , 1416–1426. https://doi.org/10.13866/j.azr.2020.06.06 (2020). Chen, Y.C., Zhang, Y., Zhang, X.C., & Zhang Y. Constructing a territorial spatial governance system for China’s integrated management of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts. J. Nat. Resour. 40 , 1174–1193. (2025). Xu, X.L., et al. Remote sensing monitoring dataset of multi-period land use and land cover in China [Data set]. Res. Cent. for Remote Sens. & GIS , http://www.resdc.cn/ (2018). hi, J., Shi, P.J., Li, X.H., Wang. Z. Y., &Xu A. K. Spatio-temporal variation and multi-scale influencing factors of ecosystem services in Shiyang River Basin. Prog. Geogr. 43 , 276–289 (2024). Zhang, X.B., Li, X.H., Wang, Z.Y. et al. A study on matching supply and demand of ecosystem services in the Hexi region of China based on multi-source data. Sci. Rep. 14 , 1332. https://doi.org/10.1038/s41598-024-51805-1 (2024). Tai, X., Xiao, W. & Tang, Y. A quantitative assessment of vulnerability using social-economic-natural compound ecosystem framework in coal mining cities. J. Clean. Prod. 258 , 120969. https://doi.org/10.1016/j.jclepro.2020.120969 (2020). Zhao, R., Zhan, L. P., Yao, M. X., &Yang, L. C. A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5. Sustain. Cities Soc. 56 , 102106. https://doi.org/10.1016/j.scs.2020.102106 (2020). Zhu, Z.Y., et al. Research on the provincial normalised monitoring of natural resources for territorial spatial supervision: a case study of Guangdong province. J. Nat. Resour. 40 , 600–617. (2025). Wang, C.X., Liu, Y.X., Yu, C. Y., & Liu, X. Q.. Research progress on the arrangement of territorial ecological restoration. Prog. Geogr. 40 , 1925–1941 (2021). Hu, G.L. & Zhao, W.Z. Review of calculation methods for vegetation ecological water demand in arid and semi-arid regions. Acta Ecol. Sin. 28 , 6282–6291. (2008). Hu, J.H., Ding, J.L., Zhang, Z.P., Wang, J. &Liu, J. M. Estimation of ecological water demand of vegetation in Turpan-Hami region over the past 30 years. Acta Ecol. Sin. 44 , 8699–8715. https://doi.org/10.20103/j.stxb.202403150537 (2024). Zhu, Y.K., Qin, S.G., Zhang, Y.Q., Zhang, J. T., Shao, Y. Y., &Gao. Y. Dynamics of vegetation phenology and its response to meteorological factors in the Mu Us Sandy Land. J. Beijing For. Univ. 40 , 98–106. https://doi.org/10.13332/j.1000-1522.20180020 (2018). Li, R.Q., et al. Manual for forestry ecosystem services function evaluation . (Beijing Forestry University, 2014). Hao, X., Zhao, Z., Fan, X., Zhang, J., & Zhang, S. Evaluation method of ecological water demand threshold of natural vegetation in arid-region inland river basin based on satellite data. Ecological Indicators , 146 , 109811. https://doi.org/10.1016/j.ecolind.2022.109811 (2023). Zhao, W.Z., Chang, X.L., He, Z.B., &Zhang Z. H. Study on ecological water requirement of desert oasis vegetation in Ejina. Sci. China Ser. D 36 , 559–566. (2006). Xia, H., Yuan, S. & Prishchepov, A.V. Spatial-temporal heterogeneity of ecosystem service interactions and their social-ecological drivers: implications for spatial planning and management. Resour. Conserv. Recycl. 189 , 106767. https://doi.org/10.1016/j.resconrec.2022.106767 (2023). Qu, S., Wang, L., Lin, A., Zhu, H., & Yuan, M. What drives the vegetation restoration in Yangtze River Basin, China: climate change or anthropogenic factors? Ecol. Indic. 90 , 438–450. https://doi.org/10.1016/j.ecolind.2018.03.029 (2018). Chen D, Duan Y, Jiang P, et al. Spatial zoning to enhance ecosystem service co-benefits for sustainable land-use management in the Yangtze River economic Belt, China[J]. Ecological Indicators, 2024, 159: 111753. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 18 Jun, 2025 Reviews received at journal 17 Jun, 2025 Reviewers agreed at journal 11 Jun, 2025 Reviews received at journal 11 Jun, 2025 Reviewers agreed at journal 11 Jun, 2025 Reviewers invited by journal 11 Jun, 2025 Editor assigned by journal 11 Jun, 2025 Editor invited by journal 29 May, 2025 Submission checks completed at journal 27 May, 2025 First submitted to journal 13 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6657423\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Article\",\"associatedPublications\":[],\"authors\":[{\"id\":470567194,\"identity\":\"6cf7e1ff-7956-48d5-8f28-3f7418c74e04\",\"order_by\":0,\"name\":\"Yue Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Northwest Normal University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yue\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":470567195,\"identity\":\"c7a0c6d5-94dd-41cb-81d4-c5df7931ce62\",\"order_by\":1,\"name\":\"Xuebin Zhang\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACNv7+Bwc+8EjwyDMzH3yQUFFDWAufxBnGgzNkbOQM29uSDR6cOUZYixxDDvNhHps0Y4YzZ9QkH7YwE+EwhrMHDvPkHE5snJHDVpHYwMbA396dgF8Lc1/CwTlnDie2S+Qeu5G4Q4ZB4szZDQRsOWBw4G0PyJa8tBuJZ9gYDCRyCWlJMDjA++9wYsONHLOCxDZmYrTkGBzk4QF734yBOC0SxxIOzuCBBLJEwpljPAT9It/ffPgDLCo//qiokeNv78WvBQPwkKZ8FIyCUTAKRgFWAADg1VDT82scUAAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Northwest Normal University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Xuebin\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":470567196,\"identity\":\"28667309-b4d9-4569-baa5-e08b91d3824d\",\"order_by\":2,\"name\":\"Ziyang Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Northwest Normal University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ziyang\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":470567197,\"identity\":\"6b73fafe-1286-47d1-8621-c32cdb7dbd1f\",\"order_by\":3,\"name\":\"Haoyuan Feng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Northwest Normal University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Haoyuan\",\"middleName\":\"\",\"lastName\":\"Feng\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-13 16:23:18\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6657423/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6657423/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1038/s41598-025-14203-9\",\"type\":\"published\",\"date\":\"2025-08-07T15:57:03+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":84696594,\"identity\":\"c9026e72-1f83-4a84-ad83-af2ebbffeee4\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:40:20\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":4640584,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eOverview map of the study area\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/b552ba2e77f74a4a60ac19b8.jpg\"},{\"id\":84698471,\"identity\":\"fd0920b6-8351-43bc-a78b-ee83e68349a5\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 11:04:20\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":351848,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eResearch framework\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/43740509e819e7aaf7c3b169.jpg\"},{\"id\":84697116,\"identity\":\"38e3c292-28ab-4999-a969-f6e169a8cc15\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:48:20\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1302623,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe results of mountain, oasis and desert ecosystems and the spatial distribution of land use in each ecosystem in 2020\\u003c/p\\u003e\\n\\u003cp\\u003e(MS, Mountain System; OS, Oasis System; DS, Desert System)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/57896ee449878475214f3c8d.jpg\"},{\"id\":84696596,\"identity\":\"c0fc7b97-0ace-40ff-aeae-efa17059973a\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:40:20\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1235491,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEvaluation results of ecosystem service function importance\\u003c/p\\u003e\\n\\u003cp\\u003e(MS, Mountain System; OS, Oasis System; DS, Desert System)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/5fe3b57e8d3354641367fc32.jpg\"},{\"id\":84698064,\"identity\":\"7965a0eb-0ea9-483d-a414-631966677231\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:56:20\",\"extension\":\"jpg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":985005,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eEvaluation results of ecological risk assessment\\u003c/p\\u003e\\n\\u003cp\\u003e(MS, Mountain System; OS, Oasis System; DS, Desert System)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image5.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/10098c71b771c7c4409ed6d5.jpg\"},{\"id\":84697122,\"identity\":\"dece41ba-06f0-4886-a329-6aa79e9693e8\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:48:20\",\"extension\":\"jpg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":638947,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRegional distribution of ecological protection and restoration in the Shiyang River Basin\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image6.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/b3e673bea1901858203a86f1.jpg\"},{\"id\":84698065,\"identity\":\"5ad54be1-fe41-4d66-a151-9e3697ea26ee\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:56:20\",\"extension\":\"jpg\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":227302,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCalculation results of vegetation ecological water demand in Shiyang River Basin\\u003c/p\\u003e\\n\\u003cp\\u003e(MS, Mountain System; OS, Oasis System; DS, Desert System)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image7.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/e4f2bd67ffb01d46d6ab906d.jpg\"},{\"id\":84697117,\"identity\":\"fecf9fdc-95f3-4621-8105-c5c05fd5aa33\",\"added_by\":\"auto\",\"created_at\":\"2025-06-16 10:48:20\",\"extension\":\"png\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":526155,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePrincipal component load thermogram\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image8.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/b92ad7ec7d0f90dd6193559a.png\"},{\"id\":88814249,\"identity\":\"22ef2743-a647-4ca4-9923-af80234e8c08\",\"added_by\":\"auto\",\"created_at\":\"2025-08-11 16:09:04\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":11294426,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6657423/v1/5b6d7ab2-2697-4f97-907d-66523a541efd.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Integrating Ecological Importance and Risk for Restoration Zoning and Ecological Water Demand in the Shiyang River Basin\",\"fulltext\":[{\"header\":\"1 Introduction\",\"content\":\"\\u003cp\\u003eThe balance and stability of ecosystems are fundamental to regional ecological security and the sustainable development of socio-economic systems\\u003csup\\u003e[1]\\u003c/sup\\u003e. Due to spatial heterogeneity in geographical patterns, ecosystems often perform distinct dominant functions across different regions, resulting in varying degrees of spatial differentiation in the importance of ecosystem services. A central challenge lies in identifying and prioritizing the conservation of critical natural elements and landscape configurations that underpin key ecological functions. Concurrently, rapid socio-economic development and accelerated urbanization have driven dramatic shifts in land-use patterns, intensifying anthropogenic pressures on natural environments\\u003csup\\u003e[2]\\u003c/sup\\u003e. These transformations have led to widespread ecological degradation and heightened environmental risks across territorial spaces. Effectively diagnosing the underlying causes and extent of ecosystem deterioration, and reconstructing damaged ecological structures and functional networks, has become a critical focus of regional conservation and governance strategies. In arid inland river basins\\u0026mdash;where ecosystems are inherently fragile, highly sensitive to disturbance, and costly to restore\\u0026mdash;precision and efficiency in coordinating the protection, development, utilization, and rehabilitation of territorial space are imperative. Anchored in the dual objectives of maintaining ecological functionality and mitigating environmental risks, this study advocates for a grid-based, spatially explicit approach to classify and zone ecological restoration and conservation priorities. By integrating assessments of ecosystem service importance with potential ecological risks, this framework enables targeted and grid-scale ecological interventions. Such a strategy is pivotal not only for enhancing human\\u0026ndash;environment conditions in arid and semi-arid regions but also for advancing high-quality development in inland river basins and modernizing territorial spatial governance systems.\\u003c/p\\u003e \\u003cp\\u003eThe Mountain\\u0026ndash;Oasis\\u0026ndash;Desert System (MODS) in arid inland river basins constitutes a distinctive ecogeographical unit characterized by pronounced spatial heterogeneity and functional complementarity, driven by hydrological cycles and fluxes of nutrients and energy. This system exhibits a highly complex internal structure and stark differentiation in ecological functions\\u003csup\\u003e[3]\\u003c/sup\\u003e. Under the dual pressures of global climate change and intensified anthropogenic disturbances, the ecological security of these basins faces mounting threats, including water scarcity, land degradation, and biodiversity loss\\u0026mdash;challenges that critically undermine the prospects for regional sustainability. Some research has been devoted to MODS and its surrounding ecological dynamics, encompassing studies on system coupling mechanisms\\u003csup\\u003e[4]\\u003c/sup\\u003e, land-use change and its impacts\\u003csup\\u003e[5]\\u003c/sup\\u003e, responses to climate variability\\u003csup\\u003e[6]\\u003c/sup\\u003e, landscape ecological patterns\\u003csup\\u003e[7]\\u003c/sup\\u003e, hydrological processes\\u003csup\\u003e[8]\\u003c/sup\\u003e, and ecosystem services\\u003csup\\u003e[9]\\u003c/sup\\u003e. However, existing efforts to delineate ecological conservation and restoration zones in these regions often adopt fragmented perspectives\\u0026mdash;focusing narrowly on geographic conditions, territorial spatial functions, ecological issues, or grid-scale classifications\\u0026mdash;thereby limiting a holistic understanding of regional differentiation, ecological service provisioning, and potential environmental degradation. This piecemeal approach falls short in guiding the design of integrated and adaptive restoration strategies. In light of the emerging spatial governance paradigm emphasizing element interlinkages, process coupling, and spatial coordination, there is a pressing need to construct an ecologically informed territorial spatial restoration framework rooted in systemic thinking. This study addresses this gap by synthesizing regional differentiation patterns of MODS, evaluating ecosystem service functions, and assessing latent ecological risks. By diagnosing structural deficiencies and functional imbalances within different subsystems, we develop a scientifically grounded, grid-based classification of ecological conservation and restoration zones. The resulting framework enables a spatially differentiated, precision-oriented restoration strategy tailored to the complex ecodynamics of inland river basins in arid regions.\\u003c/p\\u003e \\u003cp\\u003eA growing body of scholarship has explored ecological conservation and restoration zoning across diverse regions, focusing primarily on three dimensions. First, zoning based on specific ecological elements\\u0026mdash;such as wetlands, green spaces, and farmlands\\u0026mdash;has been widely applied to identify and prioritize key ecological zones for protection and restoration\\u003csup\\u003e[10]\\u003c/sup\\u003e. Second, Ecological conservation and restoration zoning has been conducted across multiple spatial scales, including municipal jurisdictions\\u003csup\\u003e[10]\\u003c/sup\\u003e, provincial regions\\u003csup\\u003e[11]\\u003c/sup\\u003e, ecologically fragile zones\\u003csup\\u003e[12]\\u003c/sup\\u003e, national parks\\u003csup\\u003e[13],\\u003c/sup\\u003e, and grid-based units\\u003csup\\u003e[14]\\u003c/sup\\u003e. Third, researchers have adopted a range of analytical perspectives, including ecosystem service supply\\u0026ndash;demand relationships\\u003csup\\u003e[15][16],\\u003c/sup\\u003e ecological environmental quality\\u003csup\\u003e[11]\\u003c/sup\\u003e, ecosystem service valuation\\u003csup\\u003e[17]\\u003c/sup\\u003e, landscape ecological risk\\u003csup\\u003e[18]\\u003c/sup\\u003e, and the interplay between land use and ecological resilience\\u003csup\\u003e[19]\\u003c/sup\\u003e. For example, Ji et al.\\u003csup\\u003e[20]\\u003c/sup\\u003e delineated ecological management zones for the fragile alpine ecosystems of the Tibetan autonomous regions in Yunnan by coupling ecosystem service supply\\u0026ndash;demand dynamics with ecosystem resilience. Xu et al.\\u003csup\\u003e[21]\\u003c/sup\\u003e conducted ecological zoning for coastal megacities by integrating ecosystem restoration capacity\\u0026mdash;derived from ecological remote sensing indices\\u0026mdash;with land use patterns to assess ecological risk. Ecological importance captures the irreplaceable role of ecosystem functions, spatial structures, and key areas in safeguarding biodiversity and supporting the sustainable use of natural resources. In contrast, ecological risk reflects the probability of ecosystem degradation under adverse environmental pressures. The coupling of ecological importance and ecological risk represents a systems-level modeling of ecological capital stocks and anthropogenic disturbance flows. In arid inland river basins\\u0026mdash;where spatial heterogeneity is pronounced\\u0026mdash;zoning strategies that integrate ecological importance as a value-oriented driver and ecological risk as a constraint can support precise, adaptive management of ecological resources and socio-economic factors. This approach offers a robust framework for restoring ecosystem integrity and ensuring long-term ecological sustainability in these vulnerable landscapes.\\u003c/p\\u003e \\u003cp\\u003eIn arid inland river basins, vegetation ecological water demand refers to the volume of water required to sustain the structural stability and functional performance of the mountain\\u0026ndash;desert\\u0026ndash;oasis ecosystem. It represents the essential water consumption needed by these open systems to buffer adverse environmental disturbances and maintain a trajectory of positive ecological development\\u003csup\\u003e[22][23]\\u003c/sup\\u003e. A variety of methods have been developed to quantify ecological water demand in such regions, including the quota-based approach, estimations based on plant evapotranspiration, water balance models, biomass-based calculations, and remote sensing\\u0026ndash;driven methodologies. In this study, we adopt an enhanced Penman\\u0026ndash;Monteith equation to estimate vegetation ecological water demand. This method is widely recognized for its maturity and operational feasibility. By incorporating parameters such as vegetation coefficients, soil moisture limitation factors, and vegetation coverage, it enables more accurate simulations of plant transpiration and actual ecological water use, as well as precise characterization of the spatiotemporal distribution of regional water demand. To date, most research on ecological water demand in inland river basins has focused on descriptive analyses. For example, Hao et al.\\u003csup\\u003e[24]\\u003c/sup\\u003e applied the FAO-recommended method to investigate the spatial and temporal patterns of natural vegetation water demand, while Wei et al.\\u003csup\\u003e[25]\\u003c/sup\\u003e used an evapotranspiration-based approach in conjunction with land cover data to analyze water demand and its differentiation across vegetation types. However, integrative studies linking ecological water demand with water resource allocation and ecological restoration remain relatively scarce, underscoring a critical gap in current research.\\u003c/p\\u003e \\u003cp\\u003eInland river basins in arid regions, shaped by distinctive environmental constraints, face an increasingly acute conflict between socioeconomic development and ecological integrity\\u0026mdash;one that calls for immediate resolution under the imperatives of carbon neutrality. Situated at the intersection of the Tibetan Plateau, the Loess Plateau, and the Inner Mongolia Plateau, the Shiyang River Basin represents a strategically vital ecological barrier and a key oasis-based agricultural hub within China\\u0026rsquo;s arid northwest. Yet, the region suffers from fragile environmental conditions, pronounced conflict between human development and natural systems, and spatial land-use structures that are poorly aligned with principles of sustainable growth\\u003csup\\u003e[26]\\u003c/sup\\u003e. In response, this study selects the Shiyang River Basin as a representative inland river system in arid China and constructs a technical framework for delineating the Mountain\\u0026ndash;Oasis\\u0026ndash;Desert System (MODS), grounded in high-resolution spatial data and integrative methodologies. This framework enables the identification of regional differentiation patterns and the diagnosis of structural deficiencies and process imbalances in ecological elements across distinct geographical units. Guided by ecological importance and constrained by ecological risk, this study delineates zones for ecological conservation and restoration based on the evaluation of ecosystem service importance and ecological risk at a 1 km \\u0026times; 1 km grid scale. It further explores ecological water allocation mechanisms for each zone according to vegetation water demand, and proposes differentiated management strategies tailored to specific conservation and restoration areas. This approach facilitates precision restoration, reduces restoration costs, and enhances ecological outcomes. It offers a novel framework grounded in an integrated and systems-oriented perspective for advancing ecological restoration in inland river basins of arid regions, thereby supporting the construction of ecological civilization and promoting sustainable development in these fragile environments.\\u003c/p\\u003e\"},{\"header\":\"2 Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Overview of the study area\\u003c/h2\\u003e \\u003cp\\u003eSituated on the northern foothills of the Qilian Mountains, west of the Wushaoling range, the Shiyang River Basin (36\\u0026deg;29\\u0026prime;N\\u0026ndash;39\\u0026deg;27\\u0026prime;N, 101\\u0026deg;41\\u0026prime;E\\u0026ndash;104\\u0026deg;16\\u0026prime;E) occupies the eastern segment of the Hexi Corridor in Gansu Province. The basin experiences a temperate continental arid climate, characterized by scarce precipitation, intense evaporation, and large diurnal temperature fluctuations, with a mean annual temperature of 6.4\\u0026deg;C and an average annual rainfall of 260.0 mm. Administratively, the basin encompasses the entirety of Liangzhou District, Minqin County, Gulang County, Tianzhu Tibetan Autonomous County, Yongchang County, and Jinchuan District, as well as parts of Sunan Yugur Autonomous County\\u0026mdash;spanning seven county-level units across three prefecture-level cities (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Covering a total area of 42,473 km\\u0026sup2;, the Shiyang River Basin represents a quintessential inland river basin in Northwest China\\u0026rsquo;s arid zone. Due to its unique geographic setting and environmental conditions, the basin hosts a tripartite ecological structure of mountains, oases, and deserts arranged longitudinally from upstream to downstream. With a permanent population of approximately 1.9\\u0026nbsp;million, it is among the most densely populated and heavily exploited inland river basins in China in terms of water and land resource utilization. Consequently, the region faces acute challenges in maintaining ecological security and achieving sustainable socio-economic development.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Data Sources and Processing\\u003c/h2\\u003e \\u003cp\\u003eThe land use data for the Shiyang River Basin in 1990 and 2020 were derived through manual visual interpretation using a human\\u0026ndash;computer interactive approach, achieving an overall classification accuracy exceeding 88.95%. The land use classification system comprises six first-level and twenty-five second-level categories\\u003csup\\u003e[27]\\u003c/sup\\u003e. Road and settlement data were extracted from land use datasets, and distance metrics to roads and settlements were subsequently derived through spatial proximity analysis. To ensure consistency across datasets, all raster data were resampled to a spatial resolution of 1 km \\u0026times; 1 km, and all layers were reprojected to the WGS_1984_Albers coordinate system. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e summarizes the main data in detail.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eList of main data\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eData Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSpatial Resolution\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eData Source\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLand Use Data (1990/2020)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e30 m\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eResource and Environment Science and Data Center (RESDC), Chinese Academy of Sciences (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.resdc.cn\\u003c/span\\u003e\\u003cspan address=\\\"http://www.resdc.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSoil Erosion Types, Night-time Light Intensity, Mean Annual Precipitation, Mean Annual Temperature, Population Density, GDP per Unit Area\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 km\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eResource and Environment Science and Data Center (RESDC), Chinese Academy of Sciences\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDigital Elevation Model (DEM), Slope\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e30 m\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eGeospatial Data Cloud (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.gscloud.cn\\u003c/span\\u003e\\u003cspan address=\\\"http://www.gscloud.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNormalized Difference Vegetation Index (NDVI)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 km\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNASA MOD13A3 Dataset (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://search.earthdata.nasa.gov/search\\u003c/span\\u003e\\u003cspan address=\\\"https://search.earthdata.nasa.gov/search\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEvapotranspiration Data\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e30 m\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNational Earth System Science Data Center (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.geodata.cn\\u003c/span\\u003e\\u003cspan address=\\\"http://www.geodata.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWind Speed, Precipitation Records\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eChina Meteorological Data Sharing Service (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://data.cma.cn\\u003c/span\\u003e\\u003cspan address=\\\"http://data.cma.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSnow Cover Information\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNational Tibetan Plateau/Third Pole Environment Data Center (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.ncdc.ac.cn/portal/\\u003c/span\\u003e\\u003cspan address=\\\"http://www.ncdc.ac.cn/portal/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Research Methodology\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.1 Conceptual Framework\\u003c/h2\\u003e \\u003cp\\u003eThis study aims to delineate ecological conservation and restoration zones in the Shiyang River Basin by integrating ecological importance as a value-oriented driver and ecological risk as a constraint. Furthermore, it explores ecological water allocation strategies within each zone based on vegetation water demand, thereby enabling precise and efficient restoration interventions. The research framework comprises the following components: (1) A technical classification system was established to delineate mountain, oasis, and desert ecosystems based on empirical data and regional characteristics. The mountain system, serving as the watershed\\u0026rsquo;s critical water source area and a reservoir of mineral nutrients and genetic biodiversity, was identified using a spatial threshold-based approach. Regions with slope\\u0026thinsp;\\u0026gt;\\u0026thinsp;15\\u0026deg; and elevation\\u0026thinsp;\\u0026gt;\\u0026thinsp;1500 m were initially classified as mountain zones. However, the fragmented nature of these patches conflicted with the expected continuity of geomorphic units. To address this, a spatial optimization was conducted using a 1.5 km buffer radius, determined through iterative analysis to maximize spatial aggregation. The oasis system, characterized by high productivity and biodiversity, and functioning as the core of human habitation and development, was extracted using a multi-dimensional feature-based method. Areas with vegetation cover exceeding 15% were identified and overlaid with water bodies and built-up land derived from land use data. To eliminate redundancy, isolated patches and areas overlapping with the mountain system were removed. The desert system, which serves as both the ecological background and the sensitive substrate in arid regions, was delineated through a spatial exclusion method, whereby all areas not classified as mountain or oasis ecosystems were defined as desert zones. (2) Based on the results of ecosystem service importance and ecological risk assessments, both attributes were classified into five ordinal levels\\u0026mdash;high, moderate-high, medium, moderate-low, and low\\u0026mdash;using the natural breaks (Jenks) method. (3) A zoning scheme was developed by integrating the ecological importance and risk classifications. Spatial overlay analysis was applied to delineate ecological conservation and restoration zones accordingly. (4) The vegetation water demand across the basin was estimated using a modified Penman\\u0026ndash;Monteith equation. These estimates were then used to inform the allocation of ecological water supplies across different conservation and restoration zones. Based on this, differentiated management strategies were proposed for each zone. The detailed conceptual framework is illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.2 Assessment of Ecosystem Service Importance\\u003c/h2\\u003e \\u003cp\\u003eDrawing on previous studies\\u003csup\\u003e[28][29]\\u003c/sup\\u003e and the specific conditions of the Shiyang River Basin, this study evaluates the importance of ecosystem services using four key indicators: food provision, water retention, carbon sequestration, and wind break and sand fixation. The assessment is based on the index of Ecosystem Service Importance, with importance levels assigned values of 9 (high), 7 (moderate-high), 5 (medium), 3 (moderate-low), and 1 (low). Detailed calculation methods are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssessment methods of ecosystem services importance\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCalculation Factors\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCalculation formula\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eExplanation of Variables\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFood provision\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{G}_{i}={G}_{sum}\\\\times\\\\:\\\\frac{{NDVI}_{i}}{{NDVI}_{sum}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{G}_{i}\\\\:\\\\)\\u003c/span\\u003e\\u003c/span\\u003edenotes the production of grain, meat, dairy, and aquatic products in grid cell \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:i\\\\)\\u003c/span\\u003e\\u003c/span\\u003e, and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{G}_{sum}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represents the total output of these products across the Shiyang River Basin. \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{NDVI}_{i}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the normalized difference vegetation index (NDVI) for grid \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:i\\\\)\\u003c/span\\u003e\\u003c/span\\u003e, and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{NDVI}_{sum}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the cumulative NDVI across cropland, grassland, and water bodies within the basin.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWater retention\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{W}_{xj}=\\\\left(1-\\\\frac{{AET}_{xj}}{{P}_{x}}\\\\right)\\\\times\\\\:{P}_{x}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{W}_{xj}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the water yield (mm) of land cover type \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:j\\\\)\\u003c/span\\u003e\\u003c/span\\u003e in grid cell \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:x\\\\)\\u003c/span\\u003e\\u003c/span\\u003e. \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{AET}_{xj}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the mean annual actual evapotranspiration (mm) for type \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:j\\\\)\\u003c/span\\u003e\\u003c/span\\u003e in grid \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:x\\\\)\\u003c/span\\u003e\\u003c/span\\u003e, and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{P}_{x}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the mean annual precipitation (mm) in grid \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:x\\\\)\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCarbon sequestration\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{S}_{cs}={C}_{above}+{C}_{below}+{C}_{soil}+{C}_{dead}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{S}_{cs}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represents the total carbon stock (t/hm\\u0026sup2;); \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{C}_{above}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{C}_{below}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e refer to aboveground and belowground biomass carbon (t/hm\\u0026sup2;), respectively; \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{C}_{soil}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the soil organic carbon (t/hm\\u0026sup2;), and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{C}_{dead}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the carbon stored in dead organic matter (t/hm\\u0026sup2;).\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWind break and sand fixation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{F}_{S}={SL}_{p}-{SL}_{r}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{SL}_{p}=\\\\frac{2Z}{{sp}^{2}}\\\\times\\\\:{Q}_{p}\\\\times\\\\:{e}^{{-(z/sp)}^{2}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{Q}_{p}=109.8\\\\times\\\\:(WF\\\\times\\\\:EF\\\\times\\\\:SCF\\\\times\\\\:{K}^{{\\\\prime\\\\:}})\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:sp=150.71\\\\times\\\\:{(WF\\\\times\\\\:EF\\\\times\\\\:SCF\\\\times\\\\:{K}^{{\\\\prime\\\\:}})}^{-0.3711}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{SL}_{r}=\\\\frac{2Z}{{sr}^{2}}\\\\times\\\\:{Q}_{r}\\\\times\\\\:{e}^{{-(z/sr)}^{2}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{Q}_{r}=109.8\\\\times\\\\:(WF\\\\times\\\\:EF\\\\times\\\\:SCF\\\\times\\\\:{K}^{{\\\\prime\\\\:}}\\\\times\\\\:C)\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:sr=150.71\\\\times\\\\:{(WF\\\\times\\\\:EF\\\\times\\\\:SCF\\\\times\\\\:{K}^{{\\\\prime\\\\:}}\\\\times\\\\:C)}^{-0.3711}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{F}_{S}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the provision of wind erosion mitigation services (kg/m\\u0026sup2;). \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{SL}_{p}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{SL}_{r}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e are the potential and actual wind erosion amounts (kg/m\\u0026sup2;), respectively. \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{Q}_{p}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{Q}_{r}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represent the maximum sediment transport capacity (kg/m) under potential and actual wind forces. \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:sp\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:sr\\\\)\\u003c/span\\u003e\\u003c/span\\u003e are the actual and potential lengths of critical wind-exposed zones (m). \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:Z\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the leeward distance (fixed at 50 m). \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:WF\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is a climatic factor (kg/m); \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:EF\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:SCF\\\\)\\u003c/span\\u003e\\u003c/span\\u003e are the soil erodibility and soil crusting factors, respectively; \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:K{\\\\prime\\\\:}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:C\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represent surface roughness and vegetation cover indices.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndex of Ecosystem Service Importance\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ESI}_{j}=\\\\sqrt[4]{\\\\prod\\\\:_{i=1}^{4}{ES}_{i}}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ESI}_{j}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the importance index of ecosystem services for spatial unit \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:j\\\\)\\u003c/span\\u003e\\u003c/span\\u003e, while \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ES}_{i}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the categorical value assigned to the ecological importance of service type \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:i\\\\)\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.3 Construction of the Ecological Risk Assessment Index System\\u003c/h2\\u003e \\u003cp\\u003eThe Shiyang River Basin is characterized by arid climatic conditions, marked spatiotemporal variability in annual precipitation, sparse surface vegetation, and soils highly susceptible to both wind and water erosion. Human activities such as deforestation, overgrazing, and intensive mineral resource extraction have further exacerbated ecological degradation, posing substantial threats to the basin's environmental integrity. Drawing on the theory of coupled social-ecological systems\\u003csup\\u003e[30]\\u003c/sup\\u003e, this study constructs an ecological risk assessment index system tailored to the Shiyang River Basin. The framework comprises 12 indicators spanning natural, social, and economic dimensions (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Based on regional characteristics and prior research, the natural breaks classification method was employed to stratify the ecological risk of each indicator into five levels\\u0026mdash;ranging from low to very high. Higher classification levels correspond to greater ecological sensitivity and fragility, indicating elevated levels of ecological risk.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eEcological security evaluation index system of Shiyang River Basin\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndex Layer\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eIndicator Code\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eEvaluation Factors\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eLevel 1 (Low)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLevel 2 (Moderate-low)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eLevel 3 (Medium)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eLevel 4 (Moderate-high)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eLevel 5 (High)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"7\\\" rowspan=\\\"8\\\"\\u003e \\u003cp\\u003eNatural Dimension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDEM(m)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;1800\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(1800, 2500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(2500, 3200]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(3200, 4000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;4000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eSlope(\\u0026deg;)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(15, 25]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(5, 35]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(35, 45]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;45\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNDVI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;0.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e[0.45, 0.60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e[0.30, 0.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e[0.15, 0.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026lt;0.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLand cover\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eWater, woodland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eGrassland\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eArable land\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eUnused land\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eConstruction land\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eTypes of soil erosion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eSlight water, Slight wind, Slight freeze\\u0026ndash;thaw\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eMild water, Mild wind, Mild freeze\\u0026ndash;thaw\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eModerate water, Moderate wind, Moderate freeze\\u0026ndash;thaw\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eIntense wind, Very intense wind\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eSevere wind\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAverage temperatures(℃)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(2, 4]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(4, 6]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(6, 8]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;8\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDistance to water (m)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(100, 500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(500, 1000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(1000, 1500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;1500\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAnnual precipitation (mm)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;400\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e[300, 400)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e[200, 300)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e[100, 200)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026lt;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eEconomic Dimension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eE1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eGDP Density\\u003c/p\\u003e \\u003cp\\u003e(10⁴ CNY/km\\u0026sup2;)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(100, 500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(500, 1000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(1000, 2000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;2000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eE2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNight light index\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;300\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(300, 1000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(1000, 2000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(2000, 4000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;4000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSocial Dimension\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eS1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePop. Density\\u003c/p\\u003e \\u003cp\\u003e(persons/km\\u0026sup2;)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e(100, 500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e(500, 1000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e(1000, 2000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026gt;2000\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eS2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDistance to the road (m)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;1500\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e[1000, 1500)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e[500, 1000)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e[100, 500)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u0026lt;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.4 Ecological Risk Index Calculation\\u003c/h2\\u003e \\u003cp\\u003eSpatial Principal Component Analysis (SPCA), an advanced multivariate statistical method that incorporates spatial autocorrelation, is particularly suited for dimensionality reduction and feature extraction in geospatial datasets\\u003csup\\u003e[31]\\u003c/sup\\u003e. Unlike conventional PCA, SPCA facilitates the intuitive spatial extension of results, enhancing interpretability through geovisualization. In this study, the SPCA tool within ArcGIS was employed to extract statistically significant principal components\\u0026mdash;those with a cumulative variance contribution exceeding 90%. Each component was associated with a corresponding spatial loading map and quantified contribution ratio. The Ecological Risk Index (ERI) was then defined as a weighted composite of these principal components, with the variance contribution of each component serving as its respective weight. The resulting ERI values were classified into five ordinal risk levels using the natural breaks (Jenks) algorithm: ERI\\u0026thinsp;\\u0026le;\\u0026thinsp;1.0 (low), 1.0\\u0026thinsp;\\u0026lt;\\u0026thinsp;ERI\\u0026thinsp;\\u0026le;\\u0026thinsp;2.0 (moderately-low), 2.0\\u0026thinsp;\\u0026lt;\\u0026thinsp;ERI\\u0026thinsp;\\u0026le;\\u0026thinsp;3.0 (medium), 3.0\\u0026thinsp;\\u0026lt;\\u0026thinsp;ERI\\u0026thinsp;\\u0026le;\\u0026thinsp;4.0 (moderate-high), and ERI\\u0026thinsp;\\u0026gt;\\u0026thinsp;4.0 (high). The index is formalized as follows:\\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$\\\\:ERI=\\\\sum\\\\:_{j=1}^{m}{P}_{ij}{w}_{j}$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eIn the equation, ERI denotes the Ecological Risk Index for the \\u003cem\\u003ei\\u003c/em\\u003e-th assessment unit (grid cell); \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{P}_{ij}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represents the value of the \\u003cem\\u003ej\\u003c/em\\u003e-th principal component in the \\u003cem\\u003ei\\u003c/em\\u003e-th unit; and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{w}_{j}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the corresponding weight, determined by the variance contribution of the \\u003cem\\u003ej\\u003c/em\\u003e-th component.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.5 Ecological Conservation and Restoration Zoning Methodology\\u003c/h2\\u003e \\u003cp\\u003eThe core implementation pathway of ecological conservation and restoration adheres to a dual strategy of functional maintenance and problem-oriented intervention. The function-oriented approach emphasizes the preservation of essential ecosystem attributes by systematically conserving ecologically strategic elements, biological communities, and regional landscape networks, thereby constructing a resilient ecological barrier against external disturbances. In parallel, the problem-oriented mechanism targets the precise identification and remediation of ecological degradation within territorial spaces, underpinned by a multidimensional ecological risk assessment framework that enables accurate evaluation of ecological damage across spatial elements\\u003csup\\u003e[32]\\u003c/sup\\u003e. Therefore, the essence of ecological conservation and restoration lies in accurately evaluating the importance of ecosystem service functions alongside their associated ecological risks. This involves delineating the spatial distribution of ecosystem service capacities, systematically identifying the mechanisms and spatial heterogeneity of ecosystem degradation, and integrating priority areas for conservation and restoration. Such an approach enables the delineation of scientifically grounded conservation zones and the formulation of a spatially differentiated ecological governance framework characterized by rational layout and targeted interventions\\u003csup\\u003e[33]\\u003c/sup\\u003e. Given the expansive area of the Shiyang River Basin, coupled with generally low ecological quality and high restoration costs and complexity, this study adopts a strategy guided by the principles of conservation prioritization, resource efficiency, and natural recovery. Based on 1 km \\u0026times; 1 km grid-scale assessments of ecosystem service importance and ecological risk levels (for the year 2020), spatial data were extracted and categorized into five classes\\u0026mdash;high (H), moderate-high (MH), medium(M), moderate-low (ML), and low (L). Through spatial overlay analysis, the Shiyang River Basin was partitioned into five ecological management zones: Wilderness Reserve Zone, Ecological Buffer Zone, Ecological Restoration Zone, Ecological Core Zone, and Ecological Set-aside Zone. Detailed classification criteria are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eZoning standards of ecological protection and restoration\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"2\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eZone Types\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eEcological Importance\\u0026ndash;Risk Level\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWilderness Reserve Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eL\\u0026ndash;H, ML\\u0026ndash;H, L\\u0026ndash;MH, ML\\u0026ndash;MH\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Buffer Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u0026ndash;L, M\\u0026ndash;ML, MH\\u0026ndash;M, H\\u0026ndash;M, M\\u0026ndash;M\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Restoration Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eM\\u0026ndash;MH, M\\u0026ndash;H, MH\\u0026ndash;MH, MH\\u0026ndash;H, H\\u0026ndash;MH, H\\u0026ndash;H\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Core Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eH\\u0026ndash;L, H\\u0026ndash;ML, MH\\u0026ndash;L, MH\\u0026ndash;ML\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Set-aside Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eL\\u0026ndash;L, L\\u0026ndash;ML, ML\\u0026ndash;L, ML\\u0026ndash;ML, L\\u0026ndash;M, ML\\u0026ndash;M\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.3.6 Modified Penman Equation\\u003c/h2\\u003e \\u003cp\\u003eThe classical Penman equation is typically used to estimate potential evapotranspiration under ideal conditions\\u0026mdash;characterized by ample water and nutrient supply, and the absence of pests or diseases\\u0026mdash;thus reflecting the maximum water demand of vegetation\\u003csup\\u003e[34]\\u003c/sup\\u003e. The modified Penman approach extends this framework by incorporating vegetation coefficients and soil constraint factors to more accurately approximate actual plant water requirements\\u003csup\\u003e[35]\\u003c/sup\\u003e. Due to the lack of long-term, continuous in-situ observations in the study area, this research draws on prior empirical studies of forest and grassland vegetation in Northwest China\\u003csup\\u003e[36]\\u003c/sup\\u003e, alongside the Forest Ecosystem Service Function Assessment Manual\\u003csup\\u003e[37]\\u003c/sup\\u003e, to determine vegetation coefficients for cropland, forest, and grassland in the Shiyang River Basin for the year 2020. Informed by previous studies on soil critical moisture thresholds and wilting points\\u003csup\\u003e[38][39]\\u003c/sup\\u003e, the soil critical moisture content was set at 15%, and the wilting coefficient at 8%. Detailed computational procedures are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCalculation method of vegetation water demand\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCalculation Factors\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCalculation formula\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eExplanation of Variables\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEvapotranspiration\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ET}_{0}=\\\\frac{0.408\\\\varDelta\\\\:（{R}_{n}-G）+r\\\\frac{900}{T+273}{u}_{2}（{e}_{s}-{e}_{a}）}{\\\\varDelta\\\\:+r（1+0.34{u}_{2}）}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ET}_{0}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the reference crop evapotranspiration (mm d⁻\\u0026sup1;), \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:\\\\varDelta\\\\:\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represents the slope of the saturation vapor pressure curve (kPa \\u0026deg;C⁻\\u0026sup1;), and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:G\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the soil heat flux density (MJ m⁻\\u0026sup2; d⁻\\u0026sup1;). The psychrometric constant is denoted by \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:r\\\\)\\u003c/span\\u003e\\u003c/span\\u003e (kPa \\u0026deg;C⁻\\u0026sup1;), and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{u}_{2}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e refers to wind speed measured at a height of 2 meters (m s⁻\\u0026sup1;). \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{e}_{s}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{e}_{a}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represent the saturation vapor pressure and actual vapor pressure, respectively (both in kPa), while \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{R}_{n}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the net radiation at the land surface (MJ m⁻\\u0026sup2; d⁻\\u0026sup1;).\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVegetation coefficient\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eK\\u003csub\\u003eCA\\u003c/sub\\u003e=0.55\\u003c/p\\u003e \\u003cp\\u003eK\\u003csub\\u003eCW\\u003c/sub\\u003e=0.85\\u003c/p\\u003e \\u003cp\\u003eK\\u003csub\\u003eCG\\u003c/sub\\u003e=0.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eK\\u003csub\\u003eCA\\u003c/sub\\u003e. K\\u003csub\\u003eCW\\u003c/sub\\u003e and K\\u003csub\\u003eCG\\u003c/sub\\u003e represent the vegetation coefficients for cropland, forest land, and grassland, respectively.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSoil moisture limitation factor\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{K}_{s}=\\\\left\\\\{\\\\begin{array}{c}1，\\\\theta\\\\:＞{\\\\theta\\\\:}_{c}\\\\\\\\\\\\:\\\\frac{\\\\theta\\\\:-{\\\\theta\\\\:}_{z}}{{\\\\theta\\\\:}_{c}-{\\\\theta\\\\:}_{z}}，{\\\\theta\\\\:}_{z}\\\\le\\\\:\\\\theta\\\\:\\\\le\\\\:\\\\\\\\\\\\:0，\\\\theta\\\\:＜{\\\\theta\\\\:}_{z}\\\\end{array}\\\\right.{\\\\theta\\\\:}_{c}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eIn the equation, θ denotes the soil moisture content; θ_c is the critical soil moisture threshold; and θ_z refers to the wilting point of the soil.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVegetation distribution area\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eA\\u003csub\\u003ePA\\u003c/sub\\u003e=4472.31km\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eA\\u003csub\\u003ePW\\u003c/sub\\u003e=162.05km\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eK\\u003csub\\u003eCG\\u003c/sub\\u003e=896.69km\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eA\\u003csub\\u003ePA\\u003c/sub\\u003e, A\\u003csub\\u003ePW\\u003c/sub\\u003e and A\\u003csub\\u003ePG\\u003c/sub\\u003e correspond to the spatial distribution areas of cropland, forest land, and grassland, respectively.\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVegetation ecological water demand\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:ET={ET}_{0}\\\\times\\\\:{K}_{c}\\\\times\\\\:{K}_{s}\\\\times\\\\:{A}_{P}\\\\times\\\\:{10}^{-3}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:ET\\\\)\\u003c/span\\u003e\\u003c/span\\u003e represents the ecological water demand of vegetation (m\\u0026sup3;), \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{ET}_{0}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the reference crop evapotranspiration (mm), \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{K}_{c}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the vegetation coefficient, \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{K}_{s}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e is the soil moisture constraint coefficient, and \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\:{A}_{P}\\\\)\\u003c/span\\u003e\\u003c/span\\u003e denotes the vegetation-covered area (m\\u0026sup2;).\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"3 Results and Analysis\",\"content\":\"\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Delineation of the Mountain\\u0026ndash;Desert\\u0026ndash;Oasis Composite Ecosystem\\u003c/h2\\u003e \\u003cp\\u003eBased on an established classification framework for mountain\\u0026ndash;oasis\\u0026ndash;desert systems, the Shiyang River Basin was partitioned into three distinct sub-ecosystems: mountainous, oasis, and desert (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e), exhibiting pronounced spatial differentiation from southwest to northeast. The mountainous system comprises the largest proportion, accounting for 44.28% of the total basin area. Predominantly located in the Qilian Mountains in the southwest, this system is characterized by land use dominated by grasslands (45.83%), forested areas (16.63%), and croplands (17.31%). In contrast, the oasis system represents the smallest share, covering 16.79% of the basin. Concentrated in the central corridor region, it is primarily composed of croplands and urbanized land, accounting for 53.26% and 59.56% of the basin\\u0026rsquo;s total cultivated and built-up areas, respectively. This region serves as the principal hub for human habitation and agricultural activity. The desert system spans 16,531.00 km\\u0026sup2;, or 38.93% of the total area, and is primarily distributed across the northwestern transitional zone between the Tengger and Badain Jaran Deserts. Land use within this system is dominated by unused or barren land, which constitutes 82.17% of its area. Overall, the mountainous system features high vegetation cover and functions as a critical ecological service zone within the basin. The oasis system, with flat terrain and relatively abundant water resources, is a key area for agricultural production and urban\\u0026ndash;rural development. Meanwhile, the expansive and ecologically fragile desert system\\u0026mdash;characterized by gobi landscapes, exposed soils, and desert grasslands\\u0026mdash;acts as a vital refuge for characteristic flora and fauna of arid ecosystems and plays a crucial role in sustaining regional ecological balance and biodiversity.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Spatiotemporal Dynamics of Ecosystem Service Importance\\u003c/h2\\u003e \\u003cp\\u003eIn this study, the importance of ecosystem services within the Shiyang River Basin was assessed using a composite index of the ecosystem service value. The results were classified into five ordinal levels\\u0026mdash;high, moderate-high, medium, moderate-low, and low\\u0026mdash;using the natural breaks (Jenks) method (Fig.\\u0026nbsp;4). From 1990 to 2020, the ecosystem service importance index exhibited a steadily increasing trend, with the mean value rising from 12.658 to 15.495. Spatially, a distinct gradient emerged, characterized by moderate-high values in the southwest and moderate-low values in the northeast. Within mountain system, areas categorized as having high or moderate-high importance expanded substantially, increasing from 12.50% and 25.37% of the total mountainous area in 1990 to 36.66% and 28.04% in 2020, respectively. This shift reflects the transition from widespread ecosystem degradation due to intensive anthropogenic disturbances to large-scale ecological restoration initiatives. Notably, the implementation of reforestation and grassland restoration programs, along with the launch of the ecological civilization strategy and the establishment of Qilian Mountains National Park since 2012, have markedly enhanced regional ecosystem service functionality. In oasis system, zones of moderate-high and high importance showed a pronounced expansion\\u0026mdash;from 15.11% and 0.86% of the total oasis area in 1990 to 42.65% and 5.21% in 2020, respectively\\u0026mdash;while areas of moderate-low and medium importance concurrently declined. This indicates a substantial elevation in the ecological value of oasis regions, which now fulfill not only essential socio-economic roles but also increasingly vital ecological functions. These changes can be attributed to cropland development, the construction of ecological shelterbelts, and the promotion of water-efficient agro-pastoral practices. In contrast, desert system exhibited a modest expansion in areas of medium and moderate-high importance, alongside a contraction of zones with low and relatively low importance. These changes are closely linked to large-scale ecological engineering projects implemented during the study period, such as the Three-North Shelterbelt Program and sand stabilization initiatives. Overall, areas classified as having high or moderate-high ecosystem service importance remain limited, accounting for only 36.82% of the basin\\u0026rsquo;s total area. These zones are primarily concentrated in the Qilian Mountains and oasis regions. In contrast, areas of low or moderate-low importance are mainly located in the northwestern part of the basin, adjacent to desert margins where wind erosion and arid conditions render the ecological environment fragile and the functional capacity of ecosystems relatively low.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Spatiotemporal Dynamics of Ecological Risk\\u003c/h2\\u003e \\u003cp\\u003eBased on the calculated Ecological Risk Index (ERI), this study evaluates the ecological risk patterns across the Shiyang River Basin, categorizing ERI values into five discrete levels\\u0026mdash;high, moderate-high, medium, moderate-low, and low\\u0026mdash;using the natural breaks (Jenks) classification method (Fig.\\u0026nbsp;5). From 1990 to 2020, the spatial distribution of ecological risk exhibited pronounced differentiation, with risk intensifying progressively from the southwest to the northeast. Over the study period, the average ERI increased from 3.844 to 3.904, indicating an overall upward trend in ecological risk. Mountain system was predominantly characterized by low to medium risk levels, though their extent declined markedly\\u0026mdash;from 79.84\\u0026ndash;69.08% of the basin area. This contraction reflects the positive ecological impact of the Qilian Mountains conservation policies, which substantially enhanced vegetation cover, reinforced environmental regulation in mining zones, and curtailed land disturbance and pollution risks. In contrast, oasis system\\u0026mdash;primarily encompassing Jinchuan District, Liangzhou District, Yongchang County, Gulang County, and Minqin County\\u0026mdash;was dominated by medium to high risk levels. The average ERI within these regions rose from 4.330 to 4.386. Rapid urban expansion encroached upon large swaths of arable land, grassland, and unused land, leading to habitat fragmentation and loss. As a result, the area classified as medium risk shrank by 1,090.21 km\\u0026sup2;, while high-risk zones expanded by 1,835.57 km\\u0026sup2;. Desert system was predominantly under high ecological risk, although the average ERI decreased from 4.996 to 4.815. Notably, in Minqin County\\u0026mdash;situated between the Badain Jaran and Tengger Deserts\\u0026mdash;a suite of integrated restoration measures, including sand stabilization afforestation, riparian reforestation, ecological migration, farmland reversion, and habitat enclosure, led to significant environmental improvements around Qingtu Lake. Consequently, the area exposed to high ecological risk declined by 1,300.68 km\\u0026sup2;. Collectively, the Shiyang River Basin is subject to persistently elevated ecological risk. Mountain, oasis, and desert systems exhibit a gradient of increasing risk, forming a spatial pattern that impedes wildlife migration, seed dispersal, nutrient cycling, and gene flow across the basin\\u0026rsquo;s upper, middle, and lower reaches. This fragmented ecological landscape imposes substantial constraints on regional ecosystem stability and poses significant challenges to sustainable socio-environmental development.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4 Ecological Conservation and Restoration Zoning Results\\u003c/h2\\u003e \\u003cp\\u003eBased on the ecological conservation and restoration zoning framework proposed in this study, the Shiyang River Basin was delineated into five functional zones: Wilderness Reserve Zone, Ecological Buffer Zone, Ecological Restoration Zone, Ecological Core Zone, and Ecological Set-aside Zone (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). The zoning results align closely with the region\\u0026rsquo;s actual ecological protection and restoration needs. The Wilderness Reserve Zone encompasses the largest area, covering 18,795.17 km\\u0026sup2; or 43.75% of the total basin. Predominantly distributed across desert ecosystems, this zone is characterized by ecological sensitivity and fragility, with relatively high potential ecological risks. It constitutes a critical region for the conservation of characteristic arid-zone flora and fauna, the prevention of desertification, and the mitigation of ecosystem degradation. The Ecological Restoration Zone covers 4,387.28 km\\u0026sup2; (19.87% of the basin) and is primarily concentrated in oasis areas with high population density and intense economic activity. Restoration efforts in this zone aim to reconcile the demands of production with the imperatives of ecological protection. The Ecological Buffer Zone, also totaling 4,387.28 km\\u0026sup2; (10.21%), forms an important ecological shield, particularly within mountainous regions. It plays a crucial role in minimizing anthropogenic disturbances and desertification encroachment, acting as a natural barrier against windblown sand, pollutant dispersion, and biotic disruptions caused by human activity. The Ecological Core Zone spans 5,644.38 km\\u0026sup2; (13.14%) and is mainly located in mountainous areas with high vegetation cover and strong water conservation capacity. These zones are distant from densely inhabited regions and minimally disturbed by human activity, enabling them to maintain ecosystem stability and deliver essential ecological services critical to long-term regional sustainability and security. Finally, the Ecological Set-aside Zone accounts for 5,594.77 km\\u0026sup2; (13.02%), distributed primarily across mountainous and oasis landscapes. Characterized by relatively low ecological risk and limited ecosystem service capacity, these areas are designated for future spatial planning, including the advancement of ecological civilization, development of modern agriculture, and integrated urban\\u0026ndash;rural development initiatives.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.5 Ecological Water Demand Characteristics\\u003c/h2\\u003e \\u003cp\\u003eUsing the modified Penman equation, the total ecological water demand in the Shiyang River Basin in 2020 was estimated at 34.043\\u0026nbsp;billion cubic meters. The spatial distribution of ecological water demand exhibited a pronounced south\\u0026ndash;north gradient, with higher demand in the southern regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e). The mountain system accounted for the largest share, totaling approximately 24.60\\u0026nbsp;billion m\\u0026sup3;\\u0026mdash;72.25% of the basin-wide demand\\u0026mdash;driven by complex interactions among elevation, hydrological and climatic conditions, as well as ecological functions such as biodiversity conservation and soil stabilization. Within the mountain system, Ecological Core Zones, Ecological Buffer Zones, and Ecological Restoration Zones accounted for 51.40%, 30.62%, and 12.08% of the demand, respectively. Their per-unit-area ecological water demands were 1.71\\u0026nbsp;million m\\u0026sup3;/km\\u0026sup2;, 1.39\\u0026nbsp;million m\\u0026sup3;/km\\u0026sup2;, and 1.10\\u0026nbsp;million m\\u0026sup3;/km\\u0026sup2;, respectively, reflecting the higher vegetation cover and species richness in Ecological Core and Buffer Zones, where stable water supply is critical to ecosystem function. In contrast, the lower per-unit-area water demand in Ecological Restoration Zones is attributed to the relatively sparse distribution of water-intensive species or communities. The oasis system required 5.78\\u0026nbsp;billion m\\u0026sup3; of ecological water, constituting 16.97% of the basin\\u0026rsquo;s total. The Ecological Restoration zones within the oasis system accounted for 75.30% of this demand, primarily due to higher evapotranspiration rates driven by vegetation type, surface temperature, and soil properties. The Ecological Set-aside and Buffer Zones in the oasis system exhibited higher per-unit-area water demands, closely associated with denser vegetation cover. Despite its extensive spatial extent, the desert system contributed only 3.67\\u0026nbsp;billion m\\u0026sup3;, or 10.78% of total ecological water demand. Within this system, the Wilderness Reserve Zones consumed the most water, largely because desert vegetation\\u0026mdash;such as Haloxylon ammodendron, Tamarix spp., and Nitraria tangutorum\\u0026mdash;still necessitates minimal but consistent water input. Notably, the per-unit-area water demand in desert buffer areas was extremely high, reaching 14.40\\u0026nbsp;million m\\u0026sup3;/km\\u0026sup2;, largely due to large-scale artificial sand-fixation afforestation projects along the fringes of the Badain Jaran and Tengger deserts, especially in Jinchuan District and Yongchang County. Overall, ecological water demand across the Shiyang River Basin is primarily concentrated in the Ecological Core Zones, Ecological Restoration Zones, and Wilderness Reserve Zones. However, the highest per-unit-area demand is observed in the Ecological Set-aside Zones and Ecological Buffer Zones, underscoring the importance of vegetation structure and functional zoning in shaping regional water allocation.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4 Discussion\",\"content\":\"\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.1 Analysis of Ecological Risk Drivers in the Shiyang River Basin\\u003c/h2\\u003e \\u003cp\\u003eTo effectively manage potential ecological threats in the Shiyang River Basin, this study aims to identify the dominant stressors shaping regional ecological risk, thereby enabling targeted interventions. Spatial principal component analysis (PCA) reveals that the first six components collectively account for over 90% of the total variance, indicating their strong explanatory power in representing the basin\\u0026rsquo;s ecological risk patterns (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). These components show high loadings on six variables: mean annual precipitation, mean annual temperature, distance to roads, vegetation cover, land cover type, and soil erosion. Notably, precipitation and temperature dominate the first and second principal components, underscoring the central role of hydrothermal conditions as primary ecological risk determinants. As the principal form of moisture input, precipitation exerts a fundamental influence on ecosystem structure, function, and resilience\\u0026mdash;particularly pronounced in arid inland basins\\u003csup\\u003e[40]\\u003c/sup\\u003e. Spatial and temporal variations in its intensity and form critically affect ecological stability. Concurrently, rising mean annual temperatures intensify glacier melt and elevate potential evapotranspiration, thereby impacting vegetation growth, agricultural productivity, and water availability. Land cover type and vegetation cover reflect the ecosystem's response to climatic variability and anthropogenic disturbances. Areas characterized by high vegetation density\\u0026mdash;such as grasslands and forests\\u0026mdash;tend to exhibit enhanced soil and water conservation capabilities and greater ecological resilience, thereby facing comparatively lower risk. In contrast, croplands, built-up areas, and unused lands, with their inherently fragile soil structures, are more vulnerable to erosion processes. These risks are particularly acute in zones experiencing rapid land-use transformation, such as regions undergoing agricultural expansion, urbanization, or desertification. Soil erosion, a key indicator of ecological degradation, is tightly linked to topography, precipitation, vegetation dynamics, and land use. Steep terrains at higher elevations tend to experience more intense freeze-thaw and hydrodynamic erosion. Moreover, vegetation loss or land development exposes soil surfaces to heightened water and wind erosion. Road networks, as corridors of concentrated human activity, are associated with intensified land disturbance and vegetation destruction, ultimately undermining ecosystem stability. In sum, the ecological protection and restoration of the Shiyang River Basin must adopt an integrated approach that considers the interplay between natural geographical endowment, climatic stressors, vegetation dynamics, and the spatial extent of anthropogenic pressure.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.2 Strategic Allocation of Ecological Water for Vegetation Restoration\\u003c/h2\\u003e \\u003cp\\u003eRevegetation serves as a vital linkage for sustaining the ecological balance of inland river basins in arid regions\\u003csup\\u003e[41]\\u003c/sup\\u003e. Based on the ecological protection and restoration zonation delineated in this study, a differentiated ecological water allocation strategy is proposed to promote vegetation recovery and improve the ecological integrity of the basin. The upstream mountainous Ecological Core Zones receive abundant precipitation sufficient to meet the water demands of its native vegetation, while simultaneously sustaining critical water retention functions for inland hydrological systems, thereby eliminating the need for additional ecological water supplementation. However, recent global warming has accelerated glacier melt, raising concerns about the increasing frequency of abnormal precipitation events and associated geohazards such as flash floods and debris flows, which pose significant risks to ecological stability. Adjacent to the Core Zone lies the Ecological Buffer Zones, which faces relatively poor hydrological conditions. Targeted interception and redirection of water can enhance ecological water supply, improving habitat quality and reducing resistance to species migration from the Ecological Core Zones. In the central oasis system, which suffers from severe water scarcity, large-scale ecological water supplementation is essential to support vegetation regrowth. Measures such as artificial rainfall enhancement and rainwater harvesting can be employed to augment usable runoff reaching the plains, thereby strengthening the oasis\\u0026rsquo;s ecological buffer and barrier function between mountain and desert systems. As the socio-economic heart of the region, the oasis system should simultaneously prioritize water conservation. This includes advancing high-efficiency irrigation technologies and promoting the reuse of treated wastewater to significantly improve water-use efficiency. On this basis, an integrated water transfer strategy should be pursued, including the potential for inter-basin water diversion from sources such as the Yellow River or Datong River, to ensure adequate water supply for both the oasis Ecological Restoration Zones and downstream Ecological Wilderness Reserve Zones. In the Ecological Set-aside zones, water allocation should be guided by the principle of prioritizing supply to other critical zones. When surplus water is available, moderate urban and industrial development may be permitted; during periods of scarcity, the ecological character of these zones must be preserved. Rational allocation of ecological water resources is foundational to ensuring regional ecological security. Restoration planning in the Shiyang River Basin should adhere to the principles of \\u0026ldquo;water-defined forest, grass, wetland, and farmland\\u0026rdquo;\\u0026mdash;that is, the scale and intensity of restoration must be aligned with water availability. A coordinated strategy across the basin\\u0026rsquo;s protection and restoration zonation is essential to advance integrated protection and systematic management of the mountain\\u0026ndash;oasis\\u0026ndash;desert continuum, ultimately optimizing the structure and functionality of the regional ecosystem.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e4.3 Zonal Strategies for Ecological Conservation and Restoration\\u003c/h2\\u003e \\u003cp\\u003eEmerging research underscores that effective zonal ecological management can significantly optimize ecosystem service delivery\\u003csup\\u003e[42]\\u003c/sup\\u003e. Building upon the unique geographical context and ecological water demands of the Shiyang River Basin, this study proposes a set of differentiated, zone-specific ecological management strategies (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e), aiming to inform decision-making for ecological stewardship in arid inland river basins. In the mountain system, which primarily comprises Ecological Core Zones and Ecological Buffer Zones, strict protection measures are imperative. The Ecological Core Zones should prioritize ecological preservation, afforestation via natural regeneration, and the protection of wildlife habitats, with a complete prohibition on construction and human development activities. The Ecological Buffer Zones should promote eco-friendly tourism under a regulated, semi-open access model to ensure minimal disturbance to core ecological functions. In areas with steep slopes, soil and water conservation measures such as contour terraces and level trenches should be implemented to mitigate erosion. Although the Wilderness Reserve Zones constitute a relatively small proportion of the mountain system, they play a vital role in ecological connectivity. The Wilderness Reserve Zones should enforce restricted access policies and establish ecological corridors linking to the Ecological Core Zones to facilitate biological and material flows. The Ecological Restoration Zones should receive increased investment in ecological infrastructure and technologies to support artificial restoration and ecological water supplementation, thereby enhancing ecological carrying capacity. Given the sensitivity of mountain system, the Ecological Set-aside Zones within this system should function as flexible ecological buffers to address compounded environmental stressors such as climate change and biodiversity loss.\\u003c/p\\u003e \\u003cp\\u003eThe oasis system is predominantly characterized by agricultural and urban land cover, with the Ecological Restoration Zones, Wildness Reserve Zones, and Ecological Buffer Zones as the primary management units. These areas should be structured around a defensive greenbelt composed of shelterbelts at the oasis margins, integrated farmland windbreak networks, and targeted sand control measures at key desert\\u0026ndash;oasis transition points. Strategies include the establishment of new protective forests, vegetative green corridors, and windbreak barriers to form a comprehensive green ecological shield against encroaching desertification. Major ecological engineering efforts\\u0026mdash;such as combating land degradation, advancing the \\u0026ldquo;Three North\\u0026rdquo; Shelter Forest Program, implementing anti-desertification measures, expanding ecological public forests, wetland conservation and restoration, and reforestation of marginal farmland\\u0026mdash;should be intensified. Initiatives should focus on afforestation, fencing and enclosure for grassland recovery, and wetland conservation with an emphasis on exclusionary protection. Improvement of urban and rural human settlements must also be prioritized. Rational planning of green space\\u0026mdash;through rooftop greening, vertical landscaping, and green infrastructure\\u0026mdash;will increase vegetation cover and enhance the quality of urban and rural green areas. Building ecological buffer green spaces, peripheral greenbelts, and wilderness parks at the oasis fringe will further strengthen ecological resilience. Additionally, modernization of water-saving irrigation systems and promotion of green agriculture are essential for improving water-use efficiency. Technologies for water-conserving irrigation should be broadly adopted to reduce waste and improve agricultural productivity. The region\\u0026rsquo;s solar and thermal resource advantages can be leveraged to develop high-value, locally adapted agroforestry industries, thereby supporting the establishment of a sustainable ecological economy. Although the Ecological Set-aside Zones in the oasis system occupy only 5.75 km\\u0026sup2;, they hold strategic significance. During periods of agricultural instability induced by extreme climate events, these areas may be temporarily converted into production areas. In contexts where increasing demand for development land results in land-use conflicts, the Ecological Set-aside Zones could serve as green industrial or urban expansion areas under strict ecological constraints.\\u003c/p\\u003e \\u003cp\\u003eThe desert ecosystem, composed primarily of gobi, barren land, and degraded grassland, is inherently fragile and ecologically sensitive. Its dominant ecological functions include sand stabilization and the conservation of arid-zone biodiversity. As the principal Wilderness Reserve Zones of the Shiyang River Basin\\u0026mdash;with a vast area of 15,873.90 km\\u0026sup2;\\u0026mdash;desert ecological restoration faces substantial challenges. Restoration efforts should adhere to a \\u0026ldquo;natural recovery as primary, artificial restoration as auxiliary\\u0026rdquo; principle. Natural regeneration minimizes anthropogenic disturbance, promotes self-repair processes, and facilitates ecosystem resilience. For severely degraded areas, targeted restoration interventions are recommended. Water resources represent the primary limiting factor for desert ecosystem stability. Under the premise of safeguarding basin-wide ecological security, inter-basin water transfers, river channel restoration, and construction of ecological water infrastructure should be employed to ensure sustainable water use. These efforts aim to avoid overexploitation, enhance storage and distribution efficiency, and maintain the minimum ecological water threshold required for desert ecosystem recovery and vegetation regeneration. At the same time, the developments within the desert system must be scientifically delineated. Efforts should focus on fostering industries aligned with local ecological conditions, supporting the strategic relocation of industries from eastern China, and pursuing rational, regulated exploitation of mineral resources. Priority should be given to ecological restoration of mining sites and surrounding degraded grasslands. New models\\u0026mdash;such as photovoltaics for desert control and solar-powered economic development\\u0026mdash;should be actively explored to integrate ecological protection with socioeconomic advancement.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eIntegrated results of ecosystem importance-risk-ecological water demand in the Shiyang River Basin and restoration guidelines\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"9\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eZone Type\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eArea(km\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePrimary Distribution\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDominant Ecological Function\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eEcological Risk\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eTotal Ecological Water Demand (10⁸ m\\u0026sup3;)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eWater Demand per Unit Area (10⁴ m\\u0026sup3;/km\\u0026sup2;)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eStrategic guidelines for ecological conservation and restoration\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWildness Reserve Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18795.17\\u003c/p\\u003e \\u003cp\\u003e(43.75%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eDesert and mountain systems\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eWind erosion control and sand stabilization\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eEcologically fragile and sensitive; prone to desertification\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e54.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003e29.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ePrimarily natural regeneration\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Buffer Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4387.28\\u003c/p\\u003e \\u003cp\\u003e(10.21%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eTransitional areas between mountain-desert and oasis-desert systems\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eSoil and water conservation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eDual stress from anthropogenic disturbance and desertification; risk of erosion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e77.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003e176.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eAssisted natural regeneration\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Restoration Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8536.60\\u003c/p\\u003e \\u003cp\\u003e(19.87%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eOasis system\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFood provisioning\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eHigh intensity of human disturbance\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e79.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003e92.69\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eActive ecological reconstruction\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Core Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5644.38\\u003c/p\\u003e \\u003cp\\u003e(13.14%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMountain system\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eWater retention and carbon sequestration\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eStrongly impacted by climate change\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e126.42\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003e223.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eConservation-focused protection\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEcological Set-aside Zones\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5594.77\\u003c/p\\u003e \\u003cp\\u003e(13.02%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMountain, oasis, and desert systems\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFlexible development\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLow risk; subject to dynamic ecological change\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.63\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003e4.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eContext-specific adaptive management\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"5 Conclusions\",\"content\":\"\\u003cp\\u003e(1) The Shiyang River Basin exhibits pronounced spatial differentiation along a southwest\\u0026ndash;northeast gradient, encompassing three distinct ecological systems: mountains, oases, and deserts. The mountain system, primarily located in the Qilian Mountains in the southwest, covers the largest area and features high vegetation coverage. The oasis system, though spatially limited, constitutes a critical zone for urban\\u0026ndash;rural development and agricultural production. In contrast, the desert system, extending across the northwestern part of the basin, spans 16,531.01 km\\u0026sup2; and is dominated by gobi terrain, barren land, and desert grasslands.\\u003c/p\\u003e \\u003cp\\u003e(2) From 1990 to 2020, the Ecosystem Service Importance Index (ESI) in the Shiyang River Basin exhibited a rising trend, with the mean value increasing from 12.658 to 15.495. Spatially, ESII followed a \\u0026ldquo;southwest-high, northeast-low\\u0026rdquo; distribution pattern. Regions categorized as having high or moderately high ecosystem service importance accounted for only 36.82% of the total basin area. The mountain- system contained the largest proportion of these high-importance zones. Both mountain and oasis systems saw significant expansions in high and moderate-high importance areas, while the desert system remained predominantly classified as low-importance. Nevertheless, both low and moderate-low importance areas within the desert system showed a tendency to shrink over time\\u003c/p\\u003e \\u003cp\\u003e(3) Over the same period (1990\\u0026ndash;2020), the overall ecological risk in the basin remained elevated, with the average Ecological Risk Index (ERI) rising slightly from 3.844 to 3.904. A spatial gradient was observed in ecological risk levels, increasing from mountains to oases to deserts. Specifically, the mountain system was characterized by low to medium ecological risk, while the oasis system experienced medium to high risk levels. The desert system consistently exhibited the highest ecological risk across the basin.\\u003c/p\\u003e \\u003cp\\u003e(4) Based on the joint assessment of ecosystem service importance and ecological risk, the basin was zoned into five distinct ecological management areas: Core Ecological Zones, Ecological Buffer Zones, Ecological Restoration Zones, Wilderness Reserve Zones, and Ecological Set-aside Zones. The Ecological Core and Buffer Zones are mainly concentrated in mountain system; the Ecological Restoration Zones are primarily located within the oasis system; the Wilderness Reserve Zones are situated in the desert system; and the Ecological Set-aside Zones are relatively limited in extent and spatially fragmented.\\u003c/p\\u003e \\u003cp\\u003e(5) In 2020, the total ecological water demand across the Shiyang River Basin was estimated at 34.043\\u0026nbsp;billion m\\u0026sup3;. Spatially, ecological water demand exhibited a \\u0026ldquo;high-south, low-north\\u0026rdquo; distribution pattern. Vegetation-related ecological water demand was concentrated in the Ecological Core Zones, Restoration Zones, and Wilderness Reserve Zones. However, per-unit-area vegetation water demand peaked within the Ecological Set-aside and Buffer Zones, highlighting their ecological sensitivity and water dependency.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eL.Y.: Writing \\u0026ndash; review \\u0026amp; editing, Writing \\u0026ndash; original draft. Z.X.B.: Project administration, Methodology, Funding acquisition. W.Z.Y.: Resources and Software. F.H.Y.: Data curation.\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe datasets used and analysed during the current study available from the corresponding author on reasonable request.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eLiang, M., \\u003cem\\u003eet al.\\u003c/em\\u003e Unifying spatial scaling laws of biodiversity and ecosystem stability. \\u003cem\\u003eScience,\\u003c/em\\u003e \\u003cstrong\\u003e387\\u003c/strong\\u003e, eadl2373. https://doi.org/10.1126/science.adl2373 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eGuan, X., Wei, H., Lu, S., Dai, Q., \\u0026amp; Su, H. Assessment on the urbanization strategy in China: Achievements, challenges and reflections. \\u003cem\\u003eHabitat International\\u003c/em\\u003e, \\u003cstrong\\u003e71\\u003c/strong\\u003e, 97\\u0026ndash;109. https://doi.org/10.1016/j.habitatint.2017.11.009 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, Z. Y., Shi, P. J., Li, X. H.\\u003cem\\u003e, Liu, Y.\\u0026amp; Shi, J.\\u003c/em\\u003e Response mechanism and promotion path of habitat quality to land use change in Hexi Corridor area. \\u003cem\\u003eEnviron. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e45\\u003c/strong\\u003e, 6910\\u0026ndash;6921. https://doi.org/10.13227/j.hjkx.202312250 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eLin, H. L., Xiao, J. Y.\\u0026amp; Hou, F. J. Coupling patterns of the meta-ecosystem of mountain, desert and oasis and its emdollars analysis in the Hexi Corridor, Gansu, China. Acta Ecol. Sin. \\u003cstrong\\u003e24\\u003c/strong\\u003e, 965\\u0026ndash;971 (2004).\\u003c/li\\u003e\\n\\u003cli\\u003eZhang, P. Y., \\u003cem\\u003eet al.\\u003c/em\\u003e Carbon source/sink effect of land use change from the perspective of composite ecosystem: Progress and review. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e45\\u003c/strong\\u003e, 1\\u0026ndash;16. https://doi.org/10.20103/j.stxb.202402230384 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, H., \\u003cem\\u003eet al.\\u003c/em\\u003e Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability. \\u003cem\\u003eSci. Total Environ.\\u003c/em\\u003e \\u003cstrong\\u003e697\\u003c/strong\\u003e, 133978. https://doi.org/10.1016/j.scitotenv.2019.133978 (2019).\\u003c/li\\u003e\\n\\u003cli\\u003eLiu, X. L.\\u0026amp; Ren, J. Z. Landscape heterogeneity analysis of the mountain\\u0026ndash;oasis\\u0026ndash;desert compound ecosystem in the Hexi Corridor. \\u003cem\\u003eJ. Gansu Agric. Univ.\\u003c/em\\u003e \\u003cstrong\\u003e38\\u003c/strong\\u003e, 290\\u0026ndash;295, 319. (2003).\\u003c/li\\u003e\\n\\u003cli\\u003eRen, J. Z.\\u0026amp; Hou, F. J. System coupling of mountains\\u0026ndash;oases\\u0026ndash;deserts is a key measure for water resource protection in the Qilian Mountains. \\u003cem\\u003eActa Pratacult. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e27\\u003c/strong\\u003e, 4\\u0026ndash;7. (2010).\\u003c/li\\u003e\\n\\u003cli\\u003eYao, L. T., \\u003cem\\u003eet al.\\u003c/em\\u003e Ecosystem service tradeoffs and synergies effects of land use change in Mountain\\u0026ndash;Oasis\\u0026ndash;Desert complex system: A case study of Zhangye City. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e42\\u003c/strong\\u003e, 8138\\u0026ndash;8151. (2022).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, H. L., Gao, Y. N., Wang, Z. Y., Sha, W., Wu, J S. Urban ecological management division based on ecosystem services: A case study of Shenzhen City. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e40\\u003c/strong\\u003e, 8504\\u0026ndash;8515. (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eZhao, N., Wang, B., Wang, Z.H. \\u0026amp; Zhang, Y. Spatio-temporal evolution and driving mechanism of ecological environment quality in Inner Mongolia based on RSEI. \\u003cem\\u003eEnviron. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e2024\\u003c/strong\\u003e, 5303. https://doi.org/10.13227/j.hjkx.202405303 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eYang, F.F. \\u0026amp; He, H. Ecological environment assessment and ecological zoning construction in the Ili River valley based on EVI-ESV. \\u003cem\\u003eJ. Environ. Ecol. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e33\\u003c/strong\\u003e, 655\\u0026ndash;664. https://doi.org/10.16258/j.cnki.1674-5906.2024.04.016 (2024). \\u003c/li\\u003e\\n\\u003cli\\u003eZhu, J., Li, Z., Yang, J., Wang, Y., Liu, X. \\u0026amp; Chen, H. Ecological space management and control zoning of Giant Panda National Park from the perspective of ecosystem services and land use. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e14\\u003c/strong\\u003e, 19951. https://doi.org/10.1038/s41598-024-65344-2 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, S., Zhang, Q., Wang, Z.F., Liu, Y. \\u0026amp; Li, H. GIS-based ecological risk assessment and ecological zoning in the Three Gorges Reservoir area. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e42\\u003c/strong\\u003e, 4654\\u0026ndash;4664. (2022).\\u003c/li\\u003e\\n\\u003cli\\u003eXu, Y., Zhao, X., Huang, P., Wang, J. \\u0026amp; Liu, C. A new framework for multi-level territorial spatial zoning management: integrating ecosystem services supply-demand balance and land use structure. \\u003cem\\u003eJ. Clean. Prod.\\u003c/em\\u003e \\u003cstrong\\u003e441\\u003c/strong\\u003e, 141053. https://doi.org/10.1016/j.jclepro.2024.141053 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eZhu, Y.H., Hou, Z.D., Xu, C.X. \\u0026amp; Li, J. Ecological risk identification and management based on ecosystem service supply and demand relationship in the Bailongjiang River Watershed of Gansu Province. \\u003cem\\u003eSci. Geogr. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e43\\u003c/strong\\u003e, 423\\u0026ndash;433. https://doi.org/10.13249/j.cnki.sgs.2023.03.005 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eHu, Y., Gong, J., Li, X., Song, L., Zhang, Z., Zhang, S., Zhang, W., Dong, J., \\u0026amp; Dong, X. Ecological security assessment and ecological management zoning based on ecosystem services in the West Liao River Basin. \\u003cem\\u003eEcol. Eng.\\u003c/em\\u003e \\u003cstrong\\u003e192\\u003c/strong\\u003e, 106973. https://doi.org/10.1016/j.ecoleng.2023.106973 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, J., Wang, J. \\u0026amp; Zhang, J. Optimization of landscape ecological risk assessment method and ecological management zoning considering resilience. \\u003cem\\u003eJ. Environ. Manag.\\u003c/em\\u003e \\u003cstrong\\u003e376\\u003c/strong\\u003e, 124586. https://doi.org/10.1016/j.jenvman.2025.124586 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eLi, C.L., Zhao, C.W., Fan, H., An, F. J., \\u0026amp;Zeng, H. Y. Spatiotemporal evolution of land use and ecological resilience and construction of ecological zoning in Guiyang City. \\u003cem\\u003eEnviron. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e2025\\u003c/strong\\u003e, 9357. https://doi.org/10.13227/j.hjkx.202409357 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eJi, Z., Zou, S., Zhang, W., Song, F., Yuan, T., \\u0026amp; Xu, B. Optimizing zoning for ecological management in alpine region by combining ecosystem service supply and demand with ecosystem resilience. \\u003cem\\u003eJ. Environ. Manag.\\u003c/em\\u003e \\u003cstrong\\u003e365\\u003c/strong\\u003e, 121508. https://doi.org/10.1016/j.jenvman.2024.121508 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eXu, C., Li, B., Kong, F., \\u0026amp; He, T. Spatial-temporal variation, driving mechanism and management zoning of ecological resilience based on RSEI in a coastal metropolitan area. \\u003cem\\u003eEcol. Indic.\\u003c/em\\u003e \\u003cstrong\\u003e158\\u003c/strong\\u003e, 111447. https://doi.org/10.1016/j.ecolind.2023.111447 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eZhao, W.Z., Chang, X.L.\\u0026amp; He, Z.B. Study on ecological water requirement of desert oasis vegetation in Ejina. \\u003cem\\u003eSci. China\\u003c/em\\u003e \\u003cstrong\\u003e2006\\u003c/strong\\u003e, 559\\u0026ndash;566. (2006).\\u003c/li\\u003e\\n\\u003cli\\u003eDeng, M.J., Huang, Q., Chang, J.X., \\u0026amp;Huang, Z. S. Research and practice of large-scale ecological scheduling. \\u003cem\\u003eJ. Hydraul. Eng.\\u003c/em\\u003e \\u003cstrong\\u003e51\\u003c/strong\\u003e, 757\\u0026ndash;773. https://doi.org/10.13243/j.cnki.slxb.20200326 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eHao, B., Su, X.L. \\u0026amp; Ma, X.Y. Study on ecological water requirement of natural vegetation in Minqin County, Gansu Province. \\u003cem\\u003eJ. Northwest A\\u0026amp;F Univ. (Nat. Sci. Ed.)\\u003c/em\\u003e \\u003cstrong\\u003e38\\u003c/strong\\u003e, 158\\u0026ndash;164. https://doi.org/10.13207/j.cnki.jnwafu.2010.02.002 (2010).\\u003c/li\\u003e\\n\\u003cli\\u003eWei, L.M., Zheng, X., Guo, J.J., Zhou, Y. Y., \\u0026amp;Yue, D. X. Spatial and temporal distribution of vegetation water consumption in Shule River Basin based on improved Penman formula method. \\u003cem\\u003eArid Zone Res.\\u003c/em\\u003e \\u003cstrong\\u003e37\\u003c/strong\\u003e, 1416\\u0026ndash;1426. https://doi.org/10.13866/j.azr.2020.06.06 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eChen, Y.C., Zhang, Y., Zhang, X.C., \\u0026amp; Zhang Y. Constructing a territorial spatial governance system for China\\u0026rsquo;s integrated management of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts. \\u003cem\\u003eJ. Nat. Resour.\\u003c/em\\u003e \\u003cstrong\\u003e40\\u003c/strong\\u003e, 1174\\u0026ndash;1193. (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eXu, X.L., et al. Remote sensing monitoring dataset of multi-period land use and land cover in China [Data set]. \\u003cem\\u003eRes. Cent. for Remote Sens. \\u0026amp; GIS\\u003c/em\\u003e, http://www.resdc.cn/ (2018).\\u003c/li\\u003e\\n\\u003cli\\u003ehi, J., Shi, P.J., Li, X.H., Wang. Z. Y., \\u0026amp;Xu A. K. Spatio-temporal variation and multi-scale influencing factors of ecosystem services in Shiyang River Basin. \\u003cem\\u003eProg. Geogr.\\u003c/em\\u003e \\u003cstrong\\u003e43\\u003c/strong\\u003e, 276\\u0026ndash;289 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eZhang, X.B., Li, X.H., Wang, Z.Y. et al. A study on matching supply and demand of ecosystem services in the Hexi region of China based on multi-source data. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e14\\u003c/strong\\u003e, 1332. https://doi.org/10.1038/s41598-024-51805-1 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eTai, X., Xiao, W. \\u0026amp; Tang, Y. A quantitative assessment of vulnerability using social-economic-natural compound ecosystem framework in coal mining cities. \\u003cem\\u003eJ. Clean. Prod.\\u003c/em\\u003e \\u003cstrong\\u003e258\\u003c/strong\\u003e, 120969. https://doi.org/10.1016/j.jclepro.2020.120969 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eZhao, R., Zhan, L. P., Yao, M. X., \\u0026amp;Yang, L. C. A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5. \\u003cem\\u003eSustain. Cities Soc.\\u003c/em\\u003e \\u003cstrong\\u003e56\\u003c/strong\\u003e, 102106. https://doi.org/10.1016/j.scs.2020.102106 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eZhu, Z.Y., et al. Research on the provincial normalised monitoring of natural resources for territorial spatial supervision: a case study of Guangdong province. \\u003cem\\u003eJ. Nat. Resour.\\u003c/em\\u003e \\u003cstrong\\u003e40\\u003c/strong\\u003e, 600\\u0026ndash;617. (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eWang, C.X., Liu, Y.X., Yu, C. Y., \\u0026amp; Liu, X. Q.. Research progress on the arrangement of territorial ecological restoration. \\u003cem\\u003eProg. Geogr.\\u003c/em\\u003e \\u003cstrong\\u003e40\\u003c/strong\\u003e, 1925\\u0026ndash;1941 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eHu, G.L. \\u0026amp; Zhao, W.Z. Review of calculation methods for vegetation ecological water demand in arid and semi-arid regions. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e28\\u003c/strong\\u003e, 6282\\u0026ndash;6291. (2008).\\u003c/li\\u003e\\n\\u003cli\\u003eHu, J.H., Ding, J.L., Zhang, Z.P., Wang, J. \\u0026amp;Liu, J. M. Estimation of ecological water demand of vegetation in Turpan-Hami region over the past 30 years. \\u003cem\\u003eActa Ecol. Sin.\\u003c/em\\u003e \\u003cstrong\\u003e44\\u003c/strong\\u003e, 8699\\u0026ndash;8715. https://doi.org/10.20103/j.stxb.202403150537 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eZhu, Y.K., Qin, S.G., Zhang, Y.Q., Zhang, J. T., Shao, Y. Y., \\u0026amp;Gao. Y. Dynamics of vegetation phenology and its response to meteorological factors in the Mu Us Sandy Land. \\u003cem\\u003eJ. Beijing For. Univ.\\u003c/em\\u003e \\u003cstrong\\u003e40\\u003c/strong\\u003e, 98\\u0026ndash;106. https://doi.org/10.13332/j.1000-1522.20180020 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eLi, R.Q., et al. \\u003cem\\u003eManual for forestry ecosystem services function evaluation\\u003c/em\\u003e. (Beijing Forestry University, 2014).\\u003c/li\\u003e\\n\\u003cli\\u003eHao, X., Zhao, Z., Fan, X., Zhang, J., \\u0026amp; Zhang, S. Evaluation method of ecological water demand threshold of natural vegetation in arid-region inland river basin based on satellite data. \\u003cem\\u003eEcological Indicators\\u003c/em\\u003e, \\u003cstrong\\u003e146\\u003c/strong\\u003e, 109811. https://doi.org/10.1016/j.ecolind.2022.109811 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eZhao, W.Z., Chang, X.L., He, Z.B., \\u0026amp;Zhang Z. H. Study on ecological water requirement of desert oasis vegetation in Ejina. \\u003cem\\u003eSci. China Ser. D\\u003c/em\\u003e \\u003cstrong\\u003e36\\u003c/strong\\u003e, 559\\u0026ndash;566. (2006).\\u003c/li\\u003e\\n\\u003cli\\u003eXia, H., Yuan, S. \\u0026amp; Prishchepov, A.V. Spatial-temporal heterogeneity of ecosystem service interactions and their social-ecological drivers: implications for spatial planning and management. \\u003cem\\u003eResour. Conserv. Recycl.\\u003c/em\\u003e \\u003cstrong\\u003e189\\u003c/strong\\u003e, 106767. https://doi.org/10.1016/j.resconrec.2022.106767 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eQu, S., Wang, L., Lin, A., Zhu, H., \\u0026amp; Yuan, M. What drives the vegetation restoration in Yangtze River Basin, China: climate change or anthropogenic factors? \\u003cem\\u003eEcol. Indic.\\u003c/em\\u003e \\u003cstrong\\u003e90\\u003c/strong\\u003e, 438\\u0026ndash;450. https://doi.org/10.1016/j.ecolind.2018.03.029 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eChen D, Duan Y, Jiang P, et al. Spatial zoning to enhance ecosystem service co-benefits for sustainable land-use management in the Yangtze River economic Belt, China[J]. Ecological Indicators, 2024, 159: 111753.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Mountain-Oasis-Desert System, ecosystem service importance, ecological risk, ecological conservation and restoration, ecological water demand, Shiyang River Basin\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6657423/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6657423/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eEffective ecological protection and restoration in arid inland river basins requires a holistic perspective of territorial spatial planning that balances conservation and rehabilitation in a dynamic and integrated manner. This necessitates a dual focus: safeguarding key ecological functional zones to maintain the continuity of ecological processes and the spatial connectivity of natural elements, while also implementing targeted, typology-based interventions to enhance self-organizing capacities of degraded ecosystems. Such strategies aim to stabilize ecological foundations and ensure the sustained delivery of ecosystem functions. Taking the Shiyang River Basin as a representative case, this study establishes a technical framework to delineate mountain, oasis, and desert ecosystems across the basin. Using multi-source data and quantitative approaches, we analyze the spatiotemporal evolution of ecological importance and ecological risk from 1990 to 2020. Based on these assessments, we delineate ecological protection and restoration zones and calculate ecological water demand to support precise and efficient management interventions. The results reveal that: (1) The spatial distribution of mountain, oasis, and desert systems in the Shiyang River Basin exhibits pronounced regional differentiation from southwest to northeast, with mountainous and desert systems dominating, while oasis areas remain relatively limited. (2) From 1990 to 2020, the index of ecosystem service importance increased significantly, rising from an average of 12.658 to 15.495. This growth followed a southwest-to-northeast gradient, indicating a spatial pattern of \\\"high in the southwest, low in the northeast.\\\" (3) Over the same period, ecological risk across the basin showed an overall upward trend, with the average risk index increasing from 3.844 to 3.904. The spatial pattern of risk grades followed an ascending order across mountain, oasis, and desert systems, with the oasis system experiencing the most pronounced rise in ecological risk. (4) In 2020, the total ecological water demand of the Shiyang River Basin reached 34.043\\u0026nbsp;billion m\\u0026sup3;, with a spatial distribution pattern of \\u0026ldquo;high in the south, low in the north\\u0026rdquo;. The ecological core zones, restoration areas, and wilderness protection zones had the highest total ecological water demands, while the ecological reserve and buffer zones showed higher water demand per unit area. (5) Delineating ecological protection and restoration zones at the grid scale based on ecological importance and risk, alongside corresponding ecological water demand accounting, provides a robust foundation for refined and effective ecological governance in inland river basins. This approach holds significant implications for advancing ecological civilization and promoting sustainable development in arid regions.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Integrating Ecological Importance and Risk for Restoration Zoning and Ecological Water Demand in the Shiyang River Basin\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-16 10:40:15\",\"doi\":\"10.21203/rs.3.rs-6657423/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-06-18T14:56:20+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-18T02:23:02+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"100721768919380954365415838792984612463\",\"date\":\"2025-06-12T03:31:44+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-11T12:33:51+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"18627053986906084010402033336050501797\",\"date\":\"2025-06-11T11:36:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-06-11T10:19:59+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-06-11T10:06:16+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-05-29T05:53:39+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-05-27T11:04:09+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Scientific Reports\",\"date\":\"2025-05-13T16:20:59+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"scientific-reports\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"scirep\",\"sideBox\":\"Learn more about [Scientific Reports](http://www.nature.com/srep/)\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Scientific Reports\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Scientific Reports\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"f1a8a671-1f2e-40e2-9aa4-f0dc6a3c9f2c\",\"owner\":[],\"postedDate\":\"June 16th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":49974620,\"name\":\"Earth and environmental sciences/Ecology\"},{\"id\":49974621,\"name\":\"Earth and environmental sciences/Ecology/Ecosystem ecology\"},{\"id\":49974622,\"name\":\"Earth and environmental sciences/Ecology/Ecosystem services\"},{\"id\":49974623,\"name\":\"Earth and environmental sciences/Ecology/Restoration ecology\"}],\"tags\":[],\"updatedAt\":\"2025-08-11T16:05:49+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6657423\",\"link\":\"https://doi.org/10.1038/s41598-025-14203-9\",\"journal\":{\"identity\":\"scientific-reports\",\"isVorOnly\":false,\"title\":\"Scientific Reports\"},\"publishedOn\":\"2025-08-07 15:57:03\",\"publishedOnDateReadable\":\"August 7th, 2025\"},\"versionCreatedAt\":\"2025-06-16 10:40:15\",\"video\":\"\",\"vorDoi\":\"10.1038/s41598-025-14203-9\",\"vorDoiUrl\":\"https://doi.org/10.1038/s41598-025-14203-9\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6657423\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6657423\",\"identity\":\"rs-6657423\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}